Gallium-68-labeled radiopharmaceuticals: a review

Abstract

This review delves into the realm of gallium-68 (⁶⁸Ga)-labeled radiopharmaceuticals. Over the last decade, ⁶⁸Ga-labeled radiopharmaceuticals have gained prominence and shown tremendous growth in both preclinical evaluation and clinical translation due to their accessibility, favourable physical properties, and simple chemistry. Despite the high positron emission energy of 836 keV, it has been extensively used in diagnostic imaging. The present review aims to elucidate the status of various potential and clinically relevant ⁶⁸Ga-labeled radiopharmaceuticals, as well as their preclinical and clinical stages. In this review article, we briefly discuss the physical characteristics, mode of production, suitable bifunctional chelators, and radiolabeling chemistry of ⁶⁸Ga. Various ⁶⁸Ga-labeled radiopharmaceuticals are discussed with respect to their biological targets, preclinical results, clinical results if available, and their current state of readiness for clinical translation and application in humans.

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Karan S. Tanwar (left) and Mukesh K. Pandey (right)

Karan Tanwar (left) is as an Assistant Professor and Scientific Officer at the Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), TMC, Navi-Mumbai, India. He completed his post-graduation in Nuclear Medicine from Panjab University and PGIMER in 2017 and passed his Radiological Safety Officer (RSO Nuclear Medicine) exam in the same year, conducted by the Atomic Energy Regulatory Board of India. From 2018 to 2022, he worked in the medical cyclotron and radiopharmacy facility at PGIMER. In 2021, he was awarded the UICC Technical Fellowship under Professor Mukesh K. Pandey at the Mayo Clinic, Rochester, USA. Mukesh K. Pandey (right) is a Professor of Radiology and Pharmacology and Director of Molecular Imaging and Radionuclide Therapy Research at the Mayo Clinic, Rochester, MN, USA. He received his PhD from the University of Delhi and postdoctoral training from the University of Massachusetts and Harvard Medical School, BWH, Boston. He has authored >91 publications and filed/issued several patents. Professor Pandey is also a Fellow of the Royal Society of Chemistry (FRSC) and a recipient of Mayo's prestigious “Presidential Discovery and Translation Award”. His research interests include the design, development, preclinical and clinical evaluation of novel radiotheranostics for oncology, cardiology, neuroscience, neurodevelopmental disorders, infections, and regenerative medicine.

1. Introduction

The diagnostic accuracy of various diseases, especially cancer, has progressed in the last decade due to advancements in molecular imaging using novel biomarker-based radiotracers. Molecular imaging aids in the functional quantification of molecular abnormalities at the sub-cellular level. Generally, a hybrid molecular imaging modality comprises positron emission tomography (PET) and computed tomography (CT), also known as PET/CT, or single photon emission computed tomography (SPECT) and CT, also referred to as SPECT/CT. Magnetic resonance imaging (MRI) is also used in combination with PET, known as PET/MRI, by combining the capabilities of PET and MRI to achieve better anatomical and molecular imaging outcomes. In contrast to conventional anatomical imaging, PET and SPECT imaging in combination with CT/MRI offers the added advantage of functional imaging with accurate anatomical localization. A potent boom in the field of molecular imaging was seeded with the introduction of the fluorine-18 (¹⁸F) radioisotope in 1937 via²⁰Ne(d,α)¹⁸F nuclear reaction at the Ernest O. Lawrence cyclotron laboratory.¹ Since then, ¹⁸F has been extensively explored in the field of health sciences for various clinical applications, most notably through ¹⁸F-labeled fluoro-2-deoxy glucose ([¹⁸F]FDG). However, despite its diverse medical applications, ¹⁸F has certain limitations, such as radio fluorination, which requires the use of organic solvents and high temperatures and therefore precludes its ability to directly radiolabel certain peptides or proteins sensitive to these conditions.² Moreover, its half-life of 120 min and lack of a suitable generator necessitate a nearby medical cyclotron facility for the rapid supply of ¹⁸F.

These limitations have resulted in a demand to explore alternative radioisotopes that are easy to produce, diverse and possess feasible aqueous medium chemistry, while maintaining good PET imaging characteristics.

⁶⁸Ga has emerged as a potent radionuclide with this versatility. In 1966, Gottschalk et al. introduced ⁶⁸Ga for the first time in the clinical space, investigating its role in studies of the central nervous system.³ However, the breakthrough in the clinical employment of ⁶⁸Ga appeared with the advent of the ⁶⁸Ge/⁶⁸Ga generator, which provides ⁶⁸Ga in the form of [⁶⁸Ga]GaCl₃ instead of [⁶⁸Ga]Ga-EDTA. This generator facilitates easy availability and cost-effective commercial access to ⁶⁸Ga, enabling simple labeling chemistry in an aqueous medium (suitable for small molecules, peptides, proteins, macromolecules, and nanoparticles).⁴ In addition, the development of various commercially available macrocyclic chelators and introduction of lutetium-177 (¹⁷⁷Lu) as a theranostic pair escalated the clinical utility of ⁶⁸Ga. In the past few years, several ⁶⁸Ga-labeled radiopharmaceuticals have been successfully employed in the field of oncology, cardiology, pulmonology, infection, and inflammation imaging. Also, various target-specific (receptors, enzymes, antigens, and small effector) and biological mechanism-specific (proliferation, apoptosis, hypoxia, glycolysis, and angiogenesis) ⁶⁸Ga-labeled radiopharmaceuticals have been explored. This radionuclide continues to play a potent role in the progression of nuclear medicine globally in clinics and research. The present review article focuses on ⁶⁸Ga-based radiopharmaceuticals explored at the preclinical and clinical stages in the last decade (up to 2023).

2. Physical characteristics and mode of gallium-68 production

In nature, gallium exists as ⁶⁹Ga and ⁷¹Ga with an abundance of 60.1% and 39.9%, respectively. However, the most useful radioactive isotopes of gallium in nuclear medicine are ⁶⁷Ga and ⁶⁸Ga. ⁶⁸Ga is a short-lived positron-emitting radionuclide, exhibiting suitable physical properties for PET imaging such as a short half-life of 67.7 min and an abundance of positron emission (89%) with a maximum energy of 1.92 MeV and a mean energy of 0.89 MeV. The 0.89 MeV positron energy offers a PET resolution of roughly 2.3 mm (bone) to 11.5 mm (lung) for living tissues. These values lie well within the system resolution of modern PET cameras (4–5 mm) as well as high-resolution PET systems (3 mm).⁵⁶⁸Ga decays to stable zinc-68 (⁶⁸Zn). Generally, a low activity ⁶⁸Ga tracer is administered in comparison to ¹⁸F-labeled tracers⁶ to produce comparable resolution images with a lower radiation absorbed dose to the patient. The two primary routes for the production of ⁶⁸Ga are through a ⁶⁸Ge/⁶⁸Ga generator⁷ or cyclotron bombardment of ⁶⁸Zn.

2.1. Production via⁶⁸Ge/⁶⁸Ga generator

In hospital radiopharmacies, ⁶⁸Ga is generally available via a ⁶⁸Ge/⁶⁸Ga generator. This generator was refined over several decades. The first-generation ⁶⁸Ge/⁶⁸Ga generator came into the picture in the early 1960s based on the liquid–liquid extraction technique.⁸ In the 1990s, the first commercial generator providing cationic ⁶⁸Ga(III) was introduced. To date, various commercial manufacturers provide ⁶⁸Ge/⁶⁸Ga generators with a long shelf-life of 1 year, highly stable column bed, and cationic chemical form of ⁶⁸Ga³⁺, permitting versatile and easy radiolabeling chemistry. The parent radionuclide ⁶⁸Ge (t_1/2 = 270.9 days) is loaded onto a column matrix (titanium oxide column, stannous oxide column, nanoceria–polyacrylonitrile or modified silica-based column), and using a suitable eluent (HCl, NaOH, sodium citrate or EDTA, depending on the type of sorbent), cationic ⁶⁸Ga is eluted.⁹ Depending on the column used, the eluate obtained may also contain trace quantities of metallic impurities such as stable Zn²⁺, Ti⁴⁺, Cu²⁺ and Fe³⁺.^10,11 Among these metal cations, Zn²⁺ and Fe³⁺ are well-known strong competitors to ⁶⁸Ga³⁺ given that they form more stable complexes. Generally, Zn²⁺ is present in very small quantities in the eluate due to the decay of ⁶⁸Ga.¹¹ However, a higher quantity of Zn²⁺ is found in generators where elutions are performed infrequently. The quantity and probability of these metallic impurities in the eluate increase with aging of the generator. Also, the amount of ⁶⁸Ge breakthrough increases with the number of elutions. Hence, the radiolabeling of ⁶⁸Ga is generally compromised due to the presence of these metallic impurities. Although the advent of the ⁶⁸Ge/⁶⁸Ga generator was instrumental in widening the availability of ⁶⁸Ga, particularly to sites without a nearby medical cyclotron, the demand for ⁶⁸Ga has increased exponentially over the last decade, and it has become challenging to meet the demand solely via generator production because of its shortcomings. These limitations include low activity yield of ⁶⁸Ga per elution (which cannot fulfill the needs of clinics with high patient loads), the necessary wait time between elutions, and ⁶⁸Ge breakthrough. Consequently, researchers have started revisiting the cyclotron production method for the bulk production of ⁶⁸Ga in a single run.

2.2. Production via medical cyclotron

Prior to the development of the ⁶⁸Ge/⁶⁸Ga generator, the primary method for producing ⁶⁸Ga was using solid targets of ⁸⁹Zn electroplated on a copper substrate in a cyclotron.¹² However, the solid target method demands a high capital cost, targetry expertise and suitable provision for the target unloading for its further processing. In addition, it also requires lengthy separation steps, making it unsuitable for short-lived radioisotopes such as ⁶⁸Ga.¹³ Hence, the cyclotron-based production of ⁶⁸Ga using a solid target has not been widely employed. However, due to the surge in the demand for ⁶⁸Ga in the field of molecular imaging, researchers have explored the possibility of producing ⁶⁸Ga using a liquid target as an alternative. Initially, Vogg et al. attempted to produce radiometals using a nitrate solution and showed the possibility of producing ⁸⁶Y and other isotopes utilising the existing cyclotron facility for ¹⁸F.¹⁴⁶⁸Ga production using the [⁶⁸Zn]ZnCl₂ liquid target was demonstrated by Jensen et al.¹⁵ After several improvements, Pandey et al. successfully developed a robust method for ⁶⁸Ga production in a liquid target and translated the liquid target-based production of ⁶⁸Ga into clinical practice.^13,16 In this method, enriched zinc nitrate diluted in nitric acid is employed as the target solution, which removes the time-consuming dissolution and simplifies the automated purification later adopted by several other researchers.^17–19 Thus, it has emerged as a convenient alternative to the ⁶⁸Ge/⁶⁸Ga generator.

3. Chemistry of gallium-68

Gallium is a group-13 element of p-block with an atomic mass of 69.723 and atomic number 31. It does not exist as a free element in nature; instead, it is found in compound form. As an element, it appears silvery blue. In an aqueous acidic solution, its only steady oxidation state is +3.^20,21 The other prevailing oxidation states (−5 to +2) of ⁶⁸Ga do not play any significant role in radiolabeling. ⁶⁸Ga³⁺ is a strong Lewis acid with a high charge density and a small ionic radius of 62 pm.²⁰ As the Ga³⁺ cation, its coordination number varies from 4–6, and it easily forms a complex with ligands containing oxygen, nitrogen, and sulfur as donor atoms.²¹ Due to hydrolysis, gallium exists as Ga(OH)²⁺ at pH about of 2.5, which transforms to Ga(OH)₂¹⁺ as the pH increases. In the pH range of 3 to 7, it tends to form insoluble hydroxides, i.e., Ga(OH)₃. Due to the amphoteric nature of gallium, these insoluble hydroxides become soluble at higher pH values to form gallate, i.e., Ga(OH)₄¹⁻. Hence, it is crucial to utilize weak ligands (citrate, acetate, oxalate, and HEPES) that can serve as buffers and weakly chelating ligands simultaneously to prevent the production of insoluble hydroxides during ⁶⁸Ga radiolabeling. However, due to human toxicity limitations, acetate buffers are preferred over HEPES.^21–23

4. Gallium-68 complexation with chelators

The ⁶⁸Ga atom, similar to other metals, cannot be directly incorporated into targeting biomolecules via covalent bonding, and hence requires a chelator. An ideal chelator has the properties of quick and stable coordinate complex formation, preferably at room temperature, short reaction time, moderate pH (4–8), and low chelator concentration. These properties allow the reliable routine manufacturing of radiopharmaceuticals. To facilitate radiopharmaceutical production, various cyclic and acyclic chelators have been explored for ⁶⁸Ga radiolabeling. Among them, 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA), a macrocyclic chelator, and N,N′-bis[2-hydroxy-5-(carboxyethyl)benzyl]ethylenediamine-N,N′-diacetic acid (HBED-CC), an acyclic chelator, have found success in the clinical translation of FDA-approved ⁶⁸Ga radiopharmaceuticals, i.e., [⁶⁸Ga]Ga-DOTATATE, [⁶⁸Ga]Ga-DOTATOC and [⁶⁸Ga]Ga-HBED-CC-PSMA. DOTA and HBED-CC are widely known for their ability to form stable complexes with Ga-68. However, several limitations exist, such as the fact that DOTA requires heating (80–100 °C) for proper chelation with ⁶⁸Ga and various geometric isomers can be generated during the synthesis of [⁶⁸Ga]Ga-HBED-CC-PSMA at room temperature.²⁴ Furthermore, they require purification to remove the impurities generated during their synthesis. Hence, in the search for ideal chelators that exhibit high thermodynamic stability during the formation of complexes with ⁶⁸Ga and kinetic inertness in vitro as well as in vivo, various chelators and their derivatives with easy radiolabeling and excellent pharmacokinetics have been developed. These chelators have been thoroughly discussed in many review articles.^25–27 Thus, due to the development of these chelators, various biomolecules have been successfully conjugated with them and radiolabeled with Ga-68, and successfully translated into humans (Fig. 1).

Fig. 1 Gallium-68-labeled tracers targeting various biological entities.

5. Applications of gallium-68-labeled radiopharmaceuticals

Due to its versatile chemistry, suitable physical characteristics for imaging, and easy availability, several radiopharmaceuticals have been developed using ⁶⁸Ga during the last two decades.

5.1. Gallium-68 radiopharmaceuticals for apoptosis imaging

Cell death is a fundamental biological process primarily regulated by apoptosis, which is an energy-dependent form of programmed cell death. Characterized by distinct biochemical alterations, apoptosis has been extensively targeted for molecular imaging using SPECT and PET tracers. A variety of radiolabeled probes has been developed to provide a non-invasive substitute for conventional biopsy methods by enabling the selective and repeatable detection of apoptotic cell death in vivo.²⁸

Recent advancements in the development of molecular imaging probes in PET have made it possible to image and quantify cells undergoing apoptosis. Various PET imaging probes targeting the cell membrane, cell membrane acidification, membrane asymmetry, caspase substrates or inhibitors have been explored for apoptosis imaging in different disease conditions. In 2011, Bauwens et al. demonstrated the binding of two ⁶⁸Ga-DOTA-maleimide-labeled annexin A5 analogues (Cys2- and Cys165-AnxA5) to apoptotic cells in a mouse model. PET/MRI images of both tracers demonstrated their high uptake in the liver and spleen of anti-Fas-treated mice but low uptake in the tumor. According to the authors, the reason for the high discrepancy in the uptake of both tracers between the apoptotic liver and apoptotic tumor is due to the death-induced heterogenicity in the tumor. Based on the results, these tracers cannot be used as tumor imaging agents in conventional PET imaging.²⁹ However, they may serve as potential apoptosis imaging agents in systemic organs, atherosclerosis, acute myocardial infarction, etc.

Vascular cell adhesion molecule-1 (VCAM-1) is a cell surface-expressed transmembrane glycoprotein of the immunoglobulin family. It is closely related to the development of various tumor diseases, i.e., breast cancer,³⁰ ovarian cancer,³¹ and renal cell carcinoma,³² leading to tumor metastasis. Several tumor tissues are known to be affected by its anti-apoptotic actions. Upregulation and downregulation of VCAM-1 expression in various cancer conditions give a better understanding of tumor growth and tumor cell destruction, respectively. Zhang et al. developed a novel ⁶⁸Ga-labeled radiopharmaceutical, [⁶⁸Ga]Ga-NOTA-VCAM-1_scvf, to study the expression of VCAM-1 in tumors. The radiolabeling yield and radiochemical purity (RCP) of [⁶⁸Ga]Ga-NOTA-VCAM-1_scvf were found to be 96.92% ± 2.02% and 96.97% ± 2.13%, with a molar activity of 10.17 ± 1.07 MBq per nmol. The serum stability test of [⁶⁸Ga]Ga-NOTA-VCAM-1_scvf revealed >90% RCP at 3.0 h. In vitro immunofluorescence staining performed in B16F10 and A375m cells showed high fluorescence intensity in VCAM-1 expressing B16F10 cells. Also, microPET/CT imaging showed its high uptake and retention in a B16F10 xenograft tumor. The variation in uptake was also seen with the effect of LY2409881, an IKKβ inhibitor, which can cause apoptosis of VCAM1 expressing cells, of the growth of B16F10 melanoma. The results suggest that [⁶⁸Ga]Ga-NOTA-VCAM-1_scvf can specifically bind to tumors with overexpression of VCAM-1 with good retention.³³

Apoptosis involves the expression of phosphatidylethanolamine (PE) on the cell membrane surface. PE is a promising biological target for apoptosis imaging. To target PE, duramycin has been investigated given that it demonstrates high affinity and specificity towards PE. It is a small cyclic polypeptide containing 19 amino acids. It has a low molecular weight with favourable characteristics such as stability against enzymatic hydrolysis and ease of conjugation and labeling. Considering these characteristics, the potential of duramycin has been explored for the in vivo imaging of cell death.³⁴ The effectiveness of [⁶⁸Ga]Ga-NODAGA-duramycin in identifying chemotherapy-induced organ damage in mice was examined by Rix et al. utilizing PET/CT. In the case of [⁶⁸Ga]Ga-NODAGA-duramycin, the radiochemical yield and RCP were both greater than 95%. The binding specificity of [⁶⁸Ga]Ga-NODAGA-duramycin towards damaged cells was demonstrated using an in vitro competitive binding assay. [⁶⁸Ga]Ga-NODAGA-duramycin uptake was assessed in different cell lines in the presence of unlabeled duramycin, which demonstrated a significant reduction in tracer uptake (p < 0.001), confirming its competitive specific binding. Additionally, the PET/CT images showed the uptake of [⁶⁸Ga]Ga-NODAGA-duramycin in the toxicity-induced organs, which was also confirmed by the immunohistochemistry and blood parameter analysis, thereby endorsing PE-mediated apoptosis imaging.³⁵

[⁶⁸Ga]Ga-NODAGA-4-(N-(S-glutathionylacetyl)amino)-phenylarsonous acid (GSAO), also known as [⁶⁸Ga]Ga-cell death indicator (CDI), is another tracer that has been assessed for cell death imaging. GSAO is a trivalent arsenic-based peptide, which enters dying cells via anionic transporters and forms a complex with heat shock 90 proteins (hsp90). A preclinical study performed by Shon et al. demonstrated the favourable pharmacokinetic, imaging characteristics, and radiation dosimetry of a novel tracer.³⁶ Further, to facilitate clinical translation, Shon et al. also conducted a first in human studies using [⁶⁸Ga]Ga-CDI for imaging tumor cell death. A total of 5 patients with squamous cell carcinoma (SSC) of the ovary, serous carcinoma of the ovary, SSC of the oesophagus, ductal breast carcinoma, and adenocarcinoma were investigated. All the patients showed no adverse side effects upon the intravenous administration of [⁶⁸Ga]Ga-CDI. PET imaging showed faster clearance of the tracer via the kidneys, where 39% ± 18% of the total radioactivity was excreted within 90 min post injection. In the remaining organs, the tracer demonstrated low-level physiological uptake and varying tumoral uptake depending on the histology of the tumor. Its uptake was observed in all cancer types, with the highest uptake observed in metastatic cutaneous SCC (SUV_max = 6.5), followed by SCC of the oesophagus (SUV_max = 5.7), adenocarcinoma (SUV_max = 4.4), ovarian carcinoma (SUV_max = 2.7) and the least in breast carcinoma (SUV_max = 2.4). The whole-body average effective dose delivered by the tracer was found to be even marginally lower than the dose delivered by [⁶⁸Ga]Ga-PSMA and [⁶⁸Ga]Ga-DOTA-TATE.³⁷ However, more clinical trials are needed to assess the potential of [⁶⁸Ga]Ga-CDI.

Neurodegenerative diseases such as Alzheimer's and Parkinson's disease result from programmed cell death, i.e., apoptosis of neurons. Generally, apoptosis follows extrinsic and intrinsic pathways, which eventually merge into a caspase cascade. Hence, caspase-3 has been identified as a suitable target for apoptosis imaging. Recently, various markers have been engineered to track the activity of caspase-3, which either binds to or is cleaved by active/cleaved caspase-3 (CC3). Ostapchenko et al. created a bifunctional (fluorescence and positron emission) brain-penetrating ⁶⁸Ga-labeled tracer molecule to accumulate in vivo in cells with increased activity of CC3. The design of the [⁶⁸Ga]Ga-TC3-OGDOTA tracer includes ⁶⁸Ga complexation of the DOTA chelator, which is conjugated to the CC3 cleavable DEVD (a peptide sequence) and fluorescent Oregon Green label. The in vitro cell culture study showed the accumulation of [⁶⁸Ga]Ga-TC3-OGDOTA in 88% of the cortical neuronal cells exhibiting an apoptotic nuclear morphology after treatment with camptothecin (CPT) toxicity compared to about 90–91% accumulation in apoptotic cells exposed to oxygen–glucose deprivation (OGD) and β-amyloid oligomer (AβO). In vivo PET revealed the accumulation of [⁶⁸Ga]Ga-TC3-OGDOTA in the brain of mouse models of stroke or Alzheimer's disease.³⁸

Recently, a preclinical study was conducted using the ⁶⁸Ga-labeled C2A domain of synaptotagmin-I ([⁶⁸Ga]Ga-C2Am) to determine the extent of cell death following treatment. The RCP for [⁶⁸Ga]Ga-C2Am radiolabeling in a single pot was >95%. In vivo imaging (at 2 h) performed 24 h after treatment revealed the uptake of [⁶⁸Ga]Ga-C2Am with the tumor to muscle ratio of 2.3 ± 0.4. The tracer showed the ability to evaluate the tumor response following treatment.³⁹

Among the mentioned tracers in Table 1, [⁶⁸Ga]Ga-CDI is the only tracer that has reached clinical trials. This tracer needs further evaluation regarding the optimization of imaging time post-treatment and detection of different forms of cell death.

Table 1 Gallium-68-labeled radiopharmaceuticals for apoptosis imaging

Tracer	Structure	Status	Ref.
[^68Ga]Ga-Annexin A5	Not available	Preclinical phase	Bauwens et al., 2011^29
[^68Ga]Ga-NOTA-VCAM-1scvf		Preclinical phase	Zhang et al., 2018^33
[^68Ga]Ga-NODAGA-Duramycin	Not available	Preclinical phase	Rix et al., 2020^35
[^68Ga]Ga-TC3-OGDOTA		Preclinical phase	Ostapchenko et al., 2019^38
[^68Ga]Ga-CDI		Clinical phase	Shon et al., 2022^36
[^68Ga]Ga-C2Am		Preclinical phase	Bulat et al., 2023^39

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5.2. Gallium-68 radiopharmaceuticals for somatostatin receptor imaging

Somatostatin receptors (SSTRs) are G-protein-coupled transmembrane receptors. These receptors were first studied in rat pituitary tumor cells by Schonbrunn and Tashjian in 1978.⁴⁰ Five subtypes of SSTRs were identified and named SSTR1 to 5.⁴¹ They are expressed in various normal human tissues, which include regions of the brain, spleen, adrenals, pituitary gland, pancreas, liver, gastrointestinal tract, kidneys and lungs, exhibiting different subtypes.⁴² The overexpression of SSTRs has been identified in various pathological cancer conditions, with a particularly higher incidence in neuroendocrine tumors (NETs).⁴³ NETs expressing variable density and subtypes of SSTRs include pituitary adenomas, pheochromocytomas, paragangliomas, lung carcinoids, small-cell lung cancers, Merkel cell carcinomas, medullary thyroid carcinomas and neuroblastomas.⁴⁴ It has been observed that in most cancer conditions, the SSTR2 subtype is majorly expressed even when other subtypes are also present.^45,46 With the successful radiolabeling of somatostatin analogues (SSAs), it has become possible to perform imaging, therapeutic treatment and quantification of somatostatin receptors expressing tumors. In the current scenario, SSTR imaging plays a pivotal role in the clinical management of NETs. Various diagnostic radiopharmaceuticals including [⁶⁸Ga]Ga-DOTA-NOC, [⁶⁸Ga]Ga-DOTA-TOC and [⁶⁸Ga]Ga-DOTA-TATE targeting different SSTR subtypes have been explored for the imaging of SSTR overexpression. The first clinical implication of [⁶⁸Ga]Ga-DOTA-TOC was reported in patients with meningiomas,⁴⁷ followed by its application in patients with NETs,⁴⁸ both in 2001. Since then, various clinical investigations have been performed utilising ⁶⁸Ga as the choice of positron-emitting radioisotope, DOTA as a chelator and tyrosine-3-octreotate (TATE)/1-Nal3-octreotide (NOC)/Phe1-Tyr3-octreotide (TOC) as an SSTR targeting vector. Among them, [⁶⁸Ga]Ga-DOTA-TATE/[⁶⁸Ga]Ga-DOTA-NOC has gained widespread acknowledgement due to its appropriate diagnosis, staging, restaging and response evaluation of NETs. Each [⁶⁸Ga]Ga-DOTA-TATE/TOC/NOC exhibits higher affinity towards the SSTR 2 subtype than the gamma emitter-labeled SSA [¹¹¹In]In-DTPA-octreotide^49,50 used for SPECT imaging. In addition, [⁶⁸Ga]Ga-DOTA-TATE/TOC/NOC offers the additional advantage of being a theranostic match to excellent therapeutic radiopharmaceuticals, i.e., [⁹⁰Y]Y-DOTA-TOC and [¹⁷⁷Lu]Lu-DOTA-TATE, for peptide receptor radionuclide therapy (PRRT).

These different tracers exhibit variable affinities towards the different SSTR subtypes, demonstrating different sensitivities toward lesion detection in various pathological conditions. Various comparative studies have been conducted to determine the diagnostic superiority of one tracer over another. One of the comparison studies conducted on 18 gastroenteropancreatic neuroendocrine tumor (GEP NET) patients showed the lesion detection supremacy of [⁶⁸Ga]Ga-DOTA-NOC over [⁶⁸Ga]Ga-DOTA-TATE.⁵¹ However, a similar study conducted on 20 NET patients presented an equivocal response of both tracers in detecting the number of lesions.⁵² Thus, researchers are still exploring ideal tracers exhibiting affinity towards all the subtypes of SSTRs.

To target tumors with heterogeneous somatostatin receptor expression, various pasireotide derivatives, [⁶⁸Ga]Ga-DOTA-PA1,⁵³ [⁶⁸Ga]Ga-DOTA-SOM230,⁵⁴ and [⁶⁸Ga]Ga-DOTA-ST8950,⁵⁵ have been developed and evaluated preclinically. Similar to octreotide, pasireotide is a somatostatin analogue; however, it targets several SST subtypes, including SST1, SST2, SST3, and SST5. In vitro cellular uptake, in vivo animal biodistribution and microPET imaging of [⁶⁸Ga]Ga-DOTA-PA1 has shown its potential for targeting multi-receptor (SSTR1, SSTR2, SSTR3, and SSTR5) expressing tumors.⁵³ Conversely, [⁶⁸Ga]Ga-DOTA-ST8950 has shown specificity towards tumors expressing SSTR2 and SSTR5.⁵⁵ These tracers possess the capacity to become useful clinical tracers targeting tumors with heterogeneous receptor expression. However, further evaluation is required to clinically translate ⁶⁸Ga-labeled pasireotide-based radiopharmaceuticals.

Liu et al. synthesized a precursor called benereotide as a potential targeting vector for SSTR positive tumors. It is a large 18-membered lactam and a novel SST analogue exhibiting higher affinities towards subtypes of SSTR and higher stability compared to octreotide. Using a DOTA derivative chelator, benereotide was conjugated, resulting in the highest radiolabeling yield of 60% (pH 3.5, incubated at 100 °C for 20 min). The RCP obtained was about 98%, and the tracer showed excellent stability in different buffers. The highest tracer uptake was noted in the liver and blood with values of 13.87% ± 0.05% ID per g and 4.91% ± 0.39% ID per g at 1.5 h, respectively. MicroPET imaging performed at 4 h resulted in excellent images of the tumor with a high tumor to background ratio.⁵⁶ However, no further study has been conducted to evaluate its clinical utility.

SSTR imaging helps to identify patients suitable for PRRT, providing more personalized care. A prominent characteristic of SSTR imaging and therapy is the internalization and tumor retention of the agonist tracers. Contrary to this, Ginj et al. introduced a paradigm shift in 2006 by stating that SSTR antagonists may exhibit a superior performance to the present agonists despite their lack of internalization.⁵⁷ Among the different investigated antagonists, JR11 (Cpa-c(dCys-Aph(Hor)-dAph(Cbm)-Lys-Thr-Cys)-dTyr-NH₂)) showed the highest affinity towards the SSTR subtype 2. Fani et al. evaluated the effect of metal chelation on the binding affinity of SST antagonists. Their findings indicated that the DOTA-JR11 precursor had a greater binding affinity (IC50 0.72 ± 0.12 nM) for SSTR2 than the radiolabeled [⁶⁸Ga]Ga-DOTA-JR11 (IC50 29 ± 2.7 nM). Interestingly, the binding affinity was restored once the chelator was changed to NODAGA from DOTA (IC50 values for NODAGA-JR11 and [⁶⁸Ga]Ga-NODAGA-JR11 were 4.1 ± 0.2 nM and 1.2 ± 0.2 nM, respectively). Compared with [⁶⁸Ga]Ga-DOTA-TATE, [⁶⁸Ga]Ga-DOTA-JR11 (also known as [⁶⁸Ga]Ga-OPS202 or [⁶⁸Ga]Ga-IPN01070) demonstrated a notably high tumor uptake (about 1.3-times higher), despite having a lower affinity for SSTR2. Similarly, [⁶⁸Ga]Ga-NODAGA-JR11 demonstrated higher tumor uptake (nearly 1.7 times) despite its lower affinity for SSTR2 than [⁶⁸Ga]Ga-DOTA-TATE.⁵⁸ Thus, this study revealed the encouraging prospective of antagonists for the imaging and therapy of SSTR expressing tumors.

To further unfold the potential of antagonist SST analogues, Fani et al. synthesized another promising SST antagonist peptide, p-Cl-Phe-cyclo(D-Cys-Tyr-D-4-amino-Phe(carbamoyl)-Lys-Thr-Cys)D-Tyr-NH₂, also known as LM3,⁵⁹ which selectively binds to SSTR 2. NODAGA conjugated LM3 complexed with ⁶⁸Ga achieved more than 95% RCP and a molar activity of 120 MBq per nmol with a labeling yield of >97%. Cell culture studies showed that ^natGa-NODAGA-LM3 selectively targeted SSTR2, with IC₅₀ values of >1000 nM for human SSTR1, SSTR3, SSTR4, and SSTR5 receptors and 1.3 ± 0.3 for SSTR2. In addition, it was observed that ^natGa-NODAGA-LM3 at a higher concentration (1000 nM) did not induce receptor internalization in human embryonic kidney (HEK)-SST2 cells. An animal biodistribution study performed on nude mice bearing HEK-sst2 xenografts showed the significant SSTR2 tumor uptake of [⁶⁸Ga]Ga-NODAGA-LM3 (37.27% ± 5.49% injected dose per gram (% ID per g) at 1 h). Also, [⁶⁸Ga]Ga-NODAGA-LM3 demonstrated 30% higher tumor uptake than [⁶⁸Ga]Ga-DOTA-LM3. Zhu et al. presented a case study using [⁶⁸Ga]Ga-DOTANOC and [⁶⁸Ga]Ga-NODAGA-LM3 in the case of pancreatic NET and extensive tumor thrombosis in the portal venous system. According to their observation, both tracers revealed similar patterns with high tumor affinity and tumor-to-background ratio.⁶⁰ Due to its promising results in preclinical studies, Zhang et al. performed a case study with [⁶⁸Ga]Ga-DOTA-LM3 in a patient with a [⁶⁸Ga]Ga-DOTATOC negative scan in high-grade liver metastases of a pancreatic neuroendocrine neoplasm.^61,62 After performing a diagnostic [⁶⁸Ga]Ga-DOTA-LM3 scan, intra-arterial [¹⁷⁷Lu]Lu-DOTA-LM3 therapy was successfully given to the patient. The patient was in complete remission after receiving three cycles of intra-arterial PRRT.⁶¹ Based on these assuring results, a preliminary clinical study was recently performed on patients with well-differentiated NETs. This study was conducted to evaluate the safety, biodistribution, dosimetry (phase I), and diagnostic efficacy (phase II) of [⁶⁸Ga]Ga-NODAGA-LM3 and [⁶⁸Ga]Ga-DOTA-LM3 in patients with well-differentiated NETs. PET/CT images revealed the significantly lower uptake of [⁶⁸Ga]Ga-DOTA-LM3 in comparison to [⁶⁸Ga]Ga-NODAGA-LM3 in the pituitary, parotids, liver, spleen, pancreas, adrenal, stomach, small intestine, and kidneys. The whole-body effective dose was 0.026 ± 0.003 mSv per MBq for [⁶⁸Ga]Ga-NODAGA-LM3 and 0.025 ± 0.002 mSv per MBq for [⁶⁸Ga]Ga-DOTA-LM3. Similar to the study by Fani et al., the radiolabeled antagonists showed long tumor retention despite their minimal internalization.

The structures of all the somatostatin receptor-targeting tracers are listed in Table 2.

Table 2 Gallium-68-labeled radiopharmaceuticals targeting different SSTR subtypes

Tracer	Target	Nature	Structure	IC50 for SSTR2	Status
[^68Ga]Ga-DOTA-NOC	SSTR2, SSTR3 and SSTR5	Agonist		1.9 ± 0.4 nM^50	Clinical Phase
[^68Ga]Ga-DOTA-TOC	SSTR2 and SSTR5	Agonist		2.5 ± 0.5 nM^49	Clinical phase
[^68Ga]Ga-DOTA-TATE	SSTR2	Agonist		0.2 ± 0.04 nM^49	Clinical phase
[^68Ga]Ga-DOTA-PA1	SSTR1, SSTR2, SSTR3 and SSTR5	Agonist		17.8 ± 3.2 nM (Kd value)^53	Pre-clinical phase
[^68Ga]Ga-DOTA-ST8950	SSTR2 and SSTR5	Agonist		0.32 nM^55	Pre-clinical phase
[^68Ga]Ga-DOTA-Benereotide	SSTR1, SSTR2, SSTR3 and SSTR5	Agonist		Not reported^56	Pre-clinical phase
[^68Ga]Ga-NODAGA-JR11	SSTR2	Antagonist		1.2 ± 0.2 nM^63	Clinical phase
[^68Ga]Ga-NODAGA-LM3	SSTR2	Antagonist		1.3 ± 0.3 nM^59	Clinical phase

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5.3. Gallium-68 radiopharmaceuticals for prostate cancer imaging

Prostate cancer is the second most common cancer in males.⁶⁴ Thus, various PET tracers targeting different biomarkers have been developed over the years to diagnose prostate cancer, but tracers targeting prostate specific membrane antigen (PSMA) have shown superiority over other diagnostic imaging biomarkers. Several PSMA-targeting PET tracers with high specificity and high positive detection rate in patients with low prostate specific antigen (PSA) values (<1 ng mL⁻¹) have been explored (Table 3).

Table 3 Gallium-68-labeled radiopharmaceuticals for PSMA targeting

Tracer	Structure	Status	Ref.
[^68Ga]Ga-PSMA-11		Clinical phase	Eder et al., 2012^79
[^68Ga]Ga-PSMA-617		Clinical phase	Benešova et al., 2015^73
[^68Ga]Ga-P16-093		Clinical phase	Zha et al., 2018^74
[^68Ga]Ga-NGUL		Clinical phase	Moon et al., 2018^80
[^68Ga]Ga-PSMA-I&T		Clinical phase	Weineisen et al., 2015^77
[^68Ga]Ga-NO3A-DM1-Lys-Urea-Glu		Pre-clinical phase	Kumar et al., 2016^78

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PSMA is a transmembrane glycoprotein having three subunits, an internal unit of 19 amino acids, a transmembrane unit of 24 amino acids and an external unit of 707 amino acids.⁶⁵ Being highly expressed on the surface of prostate cancer cells, PSMA has been considered the best-targeting antigen for imaging.⁶⁶

Afshar et al. used ⁶⁸Ga-labeled PSMA ligands in humans to perform PET imaging for the diagnosis of prostate cancer. This study showed that [⁶⁸Ga]Ga-HBED-CC-PSMA-11 can detect prostate cancer relapses by targeting the extracellular domain of PSMA.⁶⁷ Since then, many comparative studies have been conducted to evaluate its superiority over existing tracers for prostate cancer imaging.^68–72 [⁶⁸Ga]Ga-HBED-CC-PSMA-11 demonstrated a high detection rate at very low PSA levels in almost all the studies. As a result, [⁶⁸Ga]Ga-HBED-CC-PSMA-11, which received FDA approval in 2020, has emerged as the most popular tracer for prostate cancer imaging. HBED-CC exhibits several ideal characteristics as a chelator for ⁶⁸Ga complexation; however, it does not form a stable complex with therapeutic isotopes such as ¹⁷⁷Lu, ²²⁵Ac and ²¹³Bi, which are considered therapeutic pairs of ⁶⁸Ga. This led to the development of PSMA-617 with the same pharmacophore (Lys-u-Glu), in conjugation with a DOTA chelator for PSMA-targeted therapies.⁷³ The research on more effective PSMA-targeting agents is still very active, and recently many novel tracers have surfaced with better pharmacokinetics and greater affinity towards PSMA-expressing prostate cancer.

Zha et al. synthesized a novel PSMA-targeting tracer, i.e., [⁶⁸Ga]Ga-Glu-NH-CO-NH-Lys(Ahx)-linker-HBED-CC conjugated with O-(carboxymethyl)-L-tyrosine, also known as [⁶⁸Ga]Ga-P16-093.⁷⁴ Clinical studies have been conducted based on the promising preclinical results of [⁶⁸Ga]Ga-P16-093. Recently, a head-to-head comparison study of [⁶⁸Ga]Ga-P16-093 and [⁶⁸Ga]Ga-PSMA-617 was conducted to evaluate the superiority of diagnosing recurrent prostate cancer. This study revealed the significant accumulation of [⁶⁸Ga]Ga-P16-093 in tumoral sites in comparison to [⁶⁸Ga]Ga-PSMA-617 (SUV_max of 7.88 ± 5.26 vs. 6.01 ± 3.88, respectively). The authors also observed the high detection capability, less blood pool retention and lower bladder uptake of [⁶⁸Ga]Ga-P16-093.⁷⁵ This promising tracer is currently under phase 1 clinical trials.

[⁶⁸Ga]Ga-NOTA Glu-Urea-Lys (NGUL), another intriguing PSMA-targeting tracer, has been developed and evaluated in patients with metastatic prostate cancer. This tracer could detect all the primary as well as metastatic lesions identified with [⁶⁸Ga]Ga-PSMA-11 but with far less accumulation in normal organs and a quicker rate of urine clearance. In contrast to [⁶⁸Ga]Ga-PSMA-11, a relatively low tumor to background ratio was observed.⁷⁶

In 2015, Weineisen et al. introduced another PSMA inhibitor, PSMA I & T (DOTAGA-(I-y)fk(Sub-KuE)), where I & T refer to imaging and therapy, respectively. It was synthesized, radiolabeled with ⁶⁸Ga and evaluated preclinically. Its promising preclinical results led to its further use in humans as a proof of concept. The RCY and RCP obtained after the fully automated synthesis of [⁶⁸Ga]Ga-PSMA I & T were 67% ± 10% (non-decay corrected) and 98% ± 2%, respectively. It was found to be safe for human administration given that no adverse side effects showed up in the first patient. PET/CT images of a metastatic CRPC patient revealed significant tracer uptake in multiple abdominal lymph nodes, liver metastasis and bone lesions with an average lesion to background SUV_max ratio of 17.6, 20.7 and 35.2, respectively. The physiological tracer uptake was found in the salivary glands, kidneys, liver, spleen and proximal segments of the small intestine. PSMA I & T has emerged as a potential theranostic PSMA targeting inhibitor, which can be radiolabeled with ⁶⁸Ga as well as ¹⁷⁷Lu.⁷⁷

Exploring the theranostic application of PSMA targeting, a novel small molecule drug conjugate was radiolabeled with ⁶⁸Ga, [⁶⁸Ga]Ga-NO3A-DM1-Lys-Urea-Glu, for simultaneous imaging and therapy. It is composed of 3 units, as follows: (a) a PSMA binding motif (Lys-u-Glu), (b) a chemotherapy drug, maytansine (DM1), and (c) a chelator (NO3A) for complexation with ⁶⁸Ga. PET/CT images of small animals with a PSMA-positive PC3-PIP tumor showed the significant uptake (4.30% ± 0.20% ID per g at 1 h) of [⁶⁸Ga]Ga-NO3A-DM1-Lys-Urea-Glu.⁷⁸ The PSMA-targeted chemo theranostic concept has shown promising results; however, further optimization of the tracer is ongoing.

The newly developed PSMA-targeting tracers have emerged as potential competitors to the existing [⁶⁸Ga]Ga-PSMA-11. Among them, [⁶⁸Ga]Ga-P16-093 had shown superior tumor detection potential in comparison to the [⁶⁸Ga]Ga-PSMA-11, but [⁶⁸Ga]Ga-P16-093 has yet to be examined in different clinical scenarios of prostate cancer in a head-to-head comparison.

5.4. Gallium-68 radiopharmaceuticals for cancer-associated fibroblasts imaging

Generally, fibroblasts converted into cancer-associated fibroblasts (CAFs) promote cancer cell invasion, migration and growth, immunosuppression, metabolic programming, and angiogenesis.⁸¹ CAFs typically demonstrate high expression of fibroblast activation protein (FAP) on the surface of the cell membrane. FAP is a type II membrane-bound glycoprotein that is minimally expressed in normal tissues. Thus, the differential expression of FAP in tumors compared to normal tissues makes it a promising target for imaging and therapy. This has led to the development of several FAP inhibitor (FAPI)-based diagnostic and therapeutic radiopharmaceuticals (Table 4). The majority of FAP inhibitors are derived from UAMC1110.⁸² Among the various explored FAPIs, talabostat had encouraging preclinical results, but failed to induce a tumor response in most malignancies during phase II clinical trials.⁸³ Later, different quinolone-based FAPIs were determined preclinically to achieve high specific binding to FAP with rapid and complete internalization of the radiolabeled FAPI. Loktev et al. developed small inhibitor enzyme molecule-based radiotracers, i.e., FAPI-01 and FAPI-02, which successfully showed specific binding and complete internalization to human and murine FAP.⁸⁴ FAPI-01 was not studied further because of its enzymatic deiodination.

Table 4 Gallium-68-labeled radiopharmaceuticals targeting fibroblast activation protein (FAP)

[^68Ga]Ga-FAPI derivatives	Structure	Radiolabeling conditions	IC50	Status
[^68Ga]Ga-FAPI-2		Temperature: 95 °C	21 nM^86	Clinical phase
		Incubation: 10 min
[^68Ga]Ga-FAPI-4		Temperature: 95 °C	6.5 nM^86	Clinical phase
		Incubation: 10 min
[^68Ga]Ga-FAPI-21		Temperature: 95 °C	6.7 nM^84	Pre-clinical phase
		Incubation: 10 min
[^68Ga]Ga-FAPI-46		Temperature: 95 °C	2.06 ± 1.84 nM^92	Clinical phase
		Incubation: 10 min
[^68Ga]Ga-FAPI-55		Temperature: 95 °C	5.4 nM^84	Pre-clinical phase
		Incubation: 10 min
[^68Ga]Ga-FAPI-74		Room temperature	Not reported^99,100	Pre-clinical phase
		Incubation: 15 min
[^68Ga]Ga-FAP-2286		Temperature: 95 °C	3.4 ± 1.1 nM^95	Clinical phase
		pH: 4–4.5
		Incubation: 15 min
[^68Ga]Ga-2P(FAPI)2		Temperature: 100 °C	3.68 ± 1.82 nM^92	Clinical phase
		pH: 3.3–3.6
		Incubation: 15 min
[^68Ga]Ga-SA.FAPI		Temperature: 95 °C	1.4 ± 0.2 nM^101	Clinical phase
		Incubation: 15 min
[^68Ga]Ga-MHLL1		Temperature: 100 °C	212 nM^98	Pre-clinical phase
		Incubation: 5–7 min

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Conversely, FAPI-02 showed much better pharmacokinetics such as slow clearance, rapid internalization, and high tumor uptake in both tumor xenografts and epithelial carcinoma patients.⁸⁵ Hence, FAPI-02 was investigated further, and based on it many compounds were synthesized to optimize the tracer uptake and retention in tumor tissues.⁸⁶ Among the various FAP-targeting compounds, FAPI-02, FAPI-04, FAPI-21, FAPI-46, FAPI-55, FAPI-74, SA.FAPI and FAP-2286 have been radiolabeled with ⁶⁸Ga and further investigated in clinical applications.^84,87 Among the modified derivatives of FAPI-02, FAPI-04 showed the most promising results due to its prolonged tumor retention, allowing improved signal-noise ratios.^84,88,89 Besides FAPI-04, FAPI-46 and SA.FAPI have emerged as potential clinical tracers with even further improved tumor retention.^90,91 However, to realize their therapeutic application, further optimizations are in progress.

Recently, Zhao et al. synthesized a FAPI dimer radiolabeled with ⁶⁸Ga and performed a preclinical evaluation together with a pilot clinical study. The study revealed the better pharmacokinetics of [⁶⁸Ga]Ga-DOTA-2P(FAPI)₂ than the monomer [⁶⁸Ga]Ga-FAPI-46. This study showed the potential of the tracer for diagnostic imaging as well as targeted therapy of FAP-expressing tumors.⁹² A clinical study has been registered to assess the clinical utility of [⁶⁸Ga]Ga-DOTA-2P(FAPI)₂ in various cancer conditions (ClinicalTrials.gov NCT number: NCT04941872).

Further extending the applications of FAP inhibitors, Rosenkrans et al. evaluated [⁶⁸Ga]Ga-FAPI-46 preclinically in pulmonary fibrosis-induced mice. Significant tracer uptake was observed in the fibrosis-induced mice at 7 days (0.33% ± 0.09% IA per cc) and 14 days (1.01% ± 0.12% IA per cc). The biodistribution results were consistent with the histology.⁹³ Recently, a clinical study was carried out by Luo et al. in 20 patients of rheumatoid arthritis. In total, 244 affected joints were detected using [⁶⁸Ga]Ga-FAPI. Among the 244 detected joints, 20 affected joints were not even shown in the [¹⁸F]FDG PET/CT images (ClinicalTrials.gov NCT number: NCT04514614).⁹⁴ Thus, this study revealed the great diagnostic potential of [⁶⁸Ga]Ga-FAPI in detecting rheumatoid arthritis.

The pharmacokinetic profile of the majority of FAPIs shows their fast tumor clearance, which results in compromised therapeutic efficacy. Consequently, a novel cyclic peptide-based FAP-targeting tracer, FAP-2286, has been developed and radiolabeled with both ⁶⁸Ga and ¹⁷⁷Lu to address the low tumor retention of FAP inhibitor-based compounds. In vitro analysis and in vivo animal imaging of FAP-2286 have shown excellent results, favouring its clinical translation. The PET/CT images of a pilot human study performed in 11 patients revealed the theranostic potential of FAP-2286.⁹⁵ A phase 1/2 study in advanced solid tumors is under clinical trials (ClinicalTrials.gov NCT number: NCT04939610). Recently, an updated extensive review article was published, covering the existing literature on [⁶⁸Ga]Ga-FAPI and its future prospects.⁹⁶

Also, non-oncological applications of FAP imaging are also in demand, especially in cardiology. It has been identified that FAP is highly expressed in the early week after the onset of myocardial infarction (MI).⁹⁷ This makes FAP imaging of activated myofibroblasts in myocardial injury or MI possible. Therefore, a study of fibroblast activity after MI was performed using [⁶⁸Ga]Ga-FAPI-04,⁹⁷ and recently with the novel tracer [⁶⁸Ga]Ga-MHLL1.⁹⁸ Langer et al. synthesized a novel FAP-specific compound, i.e., MHLL1 radiolabeled with ⁶⁸Ga, and performed in vivo PET imaging in a mouse model together with an in vitro cellular study. The RCY and RCP obtained in the radiolabeled [⁶⁸Ga]Ga-MHLL1 were 74.4% ± 2.86%, and 71.2% ± 12.9%. The radiolabeled product was stable in phosphate buffered saline and human serum by >80% at 180 min. The in vitro analysis performed in transfected HT1080 cells expressing human FAP and murine FAP showed the specificity of [⁶⁸Ga]Ga-MHLL1 with an IC50 of 212 nM and 142 nM, respectively. In vivo serial PET imaging on day-2 and day-7 revealed tracer accumulation in the infarcted region of the heart. Ex vivo autoradiography and histology of the excised heart confirmed the accumulation of the tracer in the infarcted region at day-7 after MI. According to the authors, further evaluation and optimization of the tracer are needed.⁹⁸

To date, the US-FDA has not approved any FAPI compounds. However, recently, a company has submitted an IND application to the US-FDA for a phase II clinical trial of pancreatic adenocarcinoma patients with [⁶⁸Ga]Ga-FAPI-46 (ClinicalTrials.gov NCT number: NCT05262855). Besides [⁶⁸Ga]Ga-FAPI-04, [⁶⁸Ga]Ga-FAPI-46 is presently the most clinically tested FAPI derivative.

5.5. Gallium-68 radiopharmaceuticals for human epidermal growth factor receptor imaging

Human epidermal growth factor (HER) family receptors are classified as HER1, HER2, HER3, and HER4, also called ErbB1, ErbB2, ErbB3, and ErbB4, respectively.¹⁰² In a healthy individual, these receptors are minimally expressed on the cell surface of normal epithelial tissues. However, HER2 has been found to be overexpressed in several cancer conditions such as head and neck, lung, breast, colorectal, and urothelial cancer cells.¹⁰³ This makes HER2 a potential targeting moiety for the imaging and therapy of HER2-expressing tumors. Recent studies involving a monoclonal recombinant antibody, i.e., trastuzumab, have revealed encouraging responses in patients with HER2-positive breast cancer.¹⁰⁴ Hence, molecular imaging of breast ductal carcinoma with HER2-positive receptor expression has been performed by radiolabeling its antibodies with ⁶⁸Ga.^105–107 Clinical PET studies involving trastuzumab as a ligand have shown the effective imaging of HER2-positive lesions.^108,109 However, logistical problems were encountered due to the high molecular weight of trastuzumab, resulting in the prolonged biodistribution, slow tumor uptake, slow clearance of the tracer, and poor imaging. Thus, to overcome these shortcomings and enhance the target-to-non-target contrast, various modifications have been performed to radiolabel trastuzumab antibody fragments (F(ab′) and F(ab₂)), single chain variable fragments, nucleic acid aptamers, diabodies, nanobodies and minibodies.

In 2013, Beylergil et al. developed a fragment of trastuzumab, i.e., F(ab)₂, and labeled it with ⁶⁸Ga to image and quantitatively analyse HER2 expression in breast cancer patients. The authors observed the favourable pharmacokinetics and radiation dosimetry of [⁶⁸Ga]Ga-DOTA-F(ab)₂-trastuzumab. However, in many of the tumoral sites, minimal or no uptake of the tracer was observed. Thus, the authors inferred that the tracer is safe for human administration but requires evaluation in a better-defined group of patients, immunoreactivity and optimization in the mass of the antibody.

Ueda et al. developed a ⁶⁸Ga-labeled anti-HER2 single-chain Fv (scFv) fragment to evaluate the HER2 expression in a tumor model. Anti-HER2-scFv was conjugated to the p-isothiocyanatobenzyl derivative of deferoxamine (Df-p-SCN) chelator instead of DOTA because of its ability to form a complex at room temperature (important for heat-sensitive antibodies/antibody fragments). The RCY and RCP obtained were 86% and >98%, respectively. In vitro analysis performed using ⁶⁸Ga revealed the binding affinity of [⁶⁸Ga]Ga-Df-anti-HER2 scFv to be 9.94 ± 1.36 nM. The biodistribution study and PET imaging of [⁶⁸Ga]Ga-Df-anti-HER2 scFv showed its significant accumulation in HER2-positive xenografts.

The third generation of monoclonal antibodies, i.e., having two heavy chains with only a single variable domain (VHH, ∼15 kDa), are also known as nanobodies. A HER2 nanobody was first used clinically in 2014 (Phase I) to detect primary and metastatic HER2-expressing breast tumors.¹¹⁰ Based on its promising results, a phase I/phase II trial on breast cancer patients involving brain metastases is ongoing using [⁶⁸Ga]Ga-NOTA-Anti-HER2 VHH1.¹¹¹

The first clinically investigated affibody molecule labeled with ⁶⁸Ga was ABY-002. Breast cancer patients tolerated this molecule well and its pharmacokinetics showed rapid excretion from normal tissues.¹⁰⁵ A preclinical study of ⁶⁸Ga-labeled ABY-002 affibody was carried out by Tolmachev et al., demonstrating its specific binding to HER-2 expressing cells. In vivo imaging showed the specific targeting of SKOV-3 (a human epithelial ovarian cancer cell line derived from the ascitic fluid of a patient with ovarian adenocarcinoma) xenografts with high contrast. The tracer showed reasonable clearance from the blood, lungs, gastrointestinal, and muscle at 2 h post injection.¹¹² However, significant tracer accumulation was noted in the liver and kidneys. This led to the development of a re-engineered second-generation derivative, i.e., ABY-025. Initially, ABY-025 was radiolabeled with a SPECT radioisotope (¹¹¹In), but due to its limited ability to resolve small lesions and its low SPECT/CT resolution, ⁶⁸Ga was explored for PET imaging. A clinical study was performed to study the HER2 expression in 16 patients of known metastatic breast cancer by administering the ⁶⁸Ga-labeled ABY-025 affibody. This study revealed tracer uptake in all HER-2 positive lesions at 1 h, which further increased at 4 h. In contrast, the HER-2-negative lesions showed consistent minimal tracer uptake from 1 h to 4 h. This study also demonstrated the PET SUV correlation with biopsy HER-2 scores (r = 0.91, p < 0.001). In addition, the tracer helped in converting the disease status from HER-2 negative to HER-2 positive in 3 patients, and further the course of treatment changed.¹¹³ Another HER-2-targeting affibody, [⁶⁸Ga]Ga-NOTA-MAL-Cys-MZHER_2:342, was clinically tested in 2 patients. PET/CT images revealed the detection of HER-2-positive primary tumors with the SUV_max of 2.16 ± 0.27 and HER-2-negative primary tumor with the SUV_max of 0.32 ± 0.05.¹¹⁴ Miao et al. conducted a clinical study in 24 histopathologically confirmed breast cancer patients with [⁶⁸Ga]Ga-NOTA-MAL-MZHER2, which demonstrated the sensitivity and specificity of 91.7% and 84.6%, respectively, in differentiating HER-2-expressing breast cancer.¹¹⁵

The need for size optimization of HER2-specific targeting antibodies has led to the development of engineered scaffold proteins. The albumin binding domain (ABD) of streptococcal protein G has been used as a scaffold for developing HER2 targeting tracers. Various ABD-derived targeting proteins, commonly known as ADAPTs, i.e., ABD-derived affinity proteins (∼5 kDa), have been developed and utilized in molecular imaging. Among the ADAPTs, ADAPT6 was conjugated with a maleimido-derivative of DOTA, DOTA-C-(HE)3-ADAPT6, and radiolabeled with ⁶⁸Ga and used as a HER2-specific targeting novel tracer for imaging. The radiolabeling yield obtained was 98.3% ± 1.7%, with more than 95% RCP. In vivo PET imaging of a human tumor xenograft in mice using [⁶⁸Ga]Ga-DOTA-C-(HE)3-ADAPT6 showed significant tracer uptake in the tumor site with a high tumor to normal tissue ratio. This study unveiled the potential of small-sized engineered scaffold proteins for non-invasive PET imaging.¹¹⁶

Another member of the EGFR family, HER3, playing a potential role in targeted therapy resistance, has also been explored as a suitable target. A novel peptide, HER3P1, was synthesized and radiolabeled with ⁶⁸Ga to quantify the heterogeneous temporal and spatial expression of HER3. Larimer et al. synthesized this novel peptide by performing phage display selection and performed its in vitro characterization, developed a tumor model and performed in vivo PET imaging.¹¹⁷ The competitive cell binding assay revealed the high specificity of [⁶⁸Ga]Ga-NOTA-HER3P1 towards moderately HER3-expressing MDA-MB-453 cells compared to low HER3-expressing HCC-1954 cells. The RCP obtained was greater than 95% with a specific activity of 296 ± 25.9 MBq per mg of the labeled peptide. The PET imaging of 22RV1 (human prostate castration-resistant cancer cell line) tumor-bearing mice showed its uptake in the tumor with a tumor-to background ratio in the range of 1.59–3.32, together with its uptake in the kidneys and bladder, showing the standard excretion route. The quantification of HER3 expression performed by PET imaging of [⁶⁸Ga]Ga-NOTA-HER3P1 was highly correlated with the Western blotting quantification. The authors stated that this novel peptide has potential for visualising and quantifying HER3 expression, but increasing its tumor uptake still requires further optimization. [⁶⁸Ga]Ga-NODAGA-(HE)3-ZHER3 (an affibody tracer) and [⁶⁸Ga]Ga-DFO-seribantumab-F(ab′)2 have also been recently evaluated for targeting HER3 receptors.^118,119

Affibodies targeting HER-2 expression have shown superiority over full antibody and antibody fragments because of their reduced size and better pharmacokinetics. As a result, there are numerous active clinical trials involving affibodies.

5.6. Gallium-68 radiopharmaceuticals for gastrin releasing peptide receptor imaging

Gastrin-releasing peptide (GRP) is a regulatory peptide that acts on gastrin-releasing peptide receptors (GRPR) to regulate the physiological functions of the gastrointestinal system, central nervous system, epithelial cell proliferation, and many more. GRPR belongs to the mammalian bombesin (BBN) receptor family. Cancer conditions such as breast, prostate, gastrointestinal, and small cell lung cancer overexpress GRPR. Hence, considering GRPR as a potential target for imaging and therapy, several GRPR-specific radiolabeled peptides have been developed (Table 5).¹²⁰ Initially, BBN analogues with agonistic properties were developed and translated to the clinical space.^121–123 Unfortunately, they were not studied further due to their unwanted side effects and activation of GRPR. In addition, a study involving the head-to-head comparison of agonist and antagonist BBN analogues demonstrated the superiority of an antagonist analogue, prompting further research.¹²⁴

Table 5 Gallium-68 radiopharmaceuticals for gastrin-releasing peptide receptor targeting

Tracer	Structure	Status	Ref.
[^68Ga]Ga-RM1		Clinical phase	Mansi et al., 2009^125
[^68Ga]Ga-RM2		Clinical phase	Mansi et al., 2010^135
[^68Ga]Ga-AMBA		Pre-clinical phase	Mansi et al., 2009^125
[^68Ga]Ga-RM26		Clinical phase	Varasteh et al., 2013^136
[^68Ga]Ga-SB3		Clinical phase	Maina et al., 2015^130
[^68Ga]Ga-NeoBOMB1		Clinical phase	Nock et al., 2016^132
[^68Ga]Ga-MJ9		Clinical phase	Gourni et al., 2014^133

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Several GRPR antagonist-based radiolabeled analogues have been developed, characterized, and studied preclinically as well as clinically for different clinical conditions. The first GRPR antagonist studied was [⁶⁸Ga]Ga-RM1 (DOTA-Gly-4-aminobenzoyl-JMV594), which showed preclinical dominance over the GRPR agonist [⁶⁸Ga]Ga-AMBA (DOTA-Gly-4-aminobenzoyl-BBN(7–14)).¹²⁵ This led to the further development of antagonistic peptides, and in 2010, Mansi et al. developed the DOTA-conjugated bombesin antagonist analogue RM2 (DOTA-4-amino-1-carboxymethyl-piperidine-D-Phe-Gln-Trp-Ala-Val-Gly-His-Sta-Leu-NH2), also known as BAY86-7548, targeting GRPR-positive tumors. It emerged as a promising agent, which was evaluated clinically in healthy volunteers and GRPR-expressing prostate cancer patients. The tracer was found to be safe for human administration with an estimated whole body effective dose of 0.051 mSv per MBq, which is comparable but slightly higher than that of the routinely used ⁶⁸Ga labeled radiopharmaceuticals. In another study conducted on 14 prostate cancer patients, this tracer revealed the sensitivity, specificity and accuracy of 88%, 81% and 83%, respectively, in detecting primary prostate cancer.^126,127

In the case of another GRPR antagonist, JMV594 derivative RM26 (NOTA-PEG3-JMV594), several studies have demonstrated the specific uptake of [⁶⁸Ga]Ga-RM26 in GRPR-positive breast and prostate lesions, together with metastatic sites.^128,129 On comparing the PET/CT images of [⁶⁸Ga]Ga-RM26 with [⁶⁸Ga]Ga-BBN in 22 prostate cancer patients, Zhang et al. observed the superiority of [⁶⁸Ga]Ga-RM26 in detecting primary lesions as well as metastatic lesions over [⁶⁸Ga]Ga-BBN.¹²⁹ Recently, a phase 1 clinical trial of [⁶⁸Ga]Ga-NOTA-PEG2-RM26 has been registered to evaluate the diagnostic efficacy in GRPR-expressing prostate cancer patients (ClinicalTrials.gov NCT number: NCT06147362).

In 2015, a DOTA-conjugated GRPR antagonist, SB3 (DOTA-p-aminomethylaniline-diglycolic acid-DPhe-Gln-Trp-Ala-Val-Gly-His-Leu-NHEt), was radiolabeled with ⁶⁸Ga and clinically investigated for the first time in patients with advanced prostate cancer and breast cancer.¹³⁰ A phase 1 clinical study involving 10 prostate cancer patients was also carried out, which revealed that the sensitivity of this tracer in detecting GRPR-positive lesions is 88%.¹³¹ Further extending the theranostic application of SB3, it was also radiolabeled with ¹¹¹In (for SPECT) and ¹⁷⁷Lu (for therapy). However, the respective radioligands showed less affinity towards GRPR as well as low biological stability. As a consequence, the clinical applications of SB3 were limited. Later, the same group introduced another novel GRPR antagonist, i.e., NeoBOMB1, by replacing the C-terminal -His¹²-Leu¹³-NHEt of SB3 with -His¹²-NH-CH[CH₂-CH(CH₃)₂]₂. This modification was required to increase the theranostic potential of the GRPR antagonist. Nock et al. performed in vitro assays on human androgen-independent prostate adenocarcinoma PC-3 cells expressing GRPR receptors. Their study showed the high affinity of NeoBOMB1 and ^natGa-bound NeoBOMB1 towards GRPR receptors expressed on the cell membrane of PC3 cells. The authors also mentioned the low internalization of the tracer, exhibiting its antagonistic nature. An in vivo study was performed in PC3 xenograft–bearing mice, which showed the stability of [⁶⁸Ga]Ga-NeoBOMB1 in mice (>90% at 30 min post injection), and its biodistribution was observed in the PC3 xenograft and the pancreas, which is a GRPR-rich organ. Further translating into humans, four patients with prostate adenocarcinoma were administered [⁶⁸Ga]Ga-NeoBOMB1 and PET/CT scans were performed. The tracer was well tolerated by the patients and no side effects were observed. The scans showed high uptake of [⁶⁸Ga]Ga-NeoBOMB1 in primary and metastatic lesions, and also detected osseous (bone) and liver micrometastasis.¹³²

Another novel GRPR antagonist, MJ9, Pip-D-Phe-Gln-Trp-Ala-Val-Gly-His-Sta-Leu-NH2 (Pip, 4-amino-1-carboxymethyl-piperidine), has been developed and investigated. NODAGA- and NOTA-conjugated MJ9 were radiolabeled with ⁶⁸Ga, and greater than 98% labeling yield was obtained with a specific activity of 130 GBq per mol and 60 GBq per mol, respectively. The IC50 value obtained for ^natGa-NODAGA-MJ9 and ^natGa-NOTA-MJ9 was 2.1 ± 0.3 nmol L⁻¹ and 0.5 ± 0.1 nmol L⁻¹, respectively. The biodistribution study revealed the fast clearance of both ⁶⁸Ga-labeled tracers with high GRPR-positive tumor uptake at 2 h post injection (approximately 20% IA per g). Also, the GRPR-expressing organ, the pancreas, showed a high tracer uptake of nearly 40% IA per g at 2 h post injection. Small animal PET imaging showed the uptake of both ⁶⁸Ga-labeled tracers in the induced tumor at 1 h post injection, together with their significant uptake in the pancreas and intestine.¹³³ To assess the radiation dosimetry, which is particularly important for these compounds due to their non-target organ uptake, Gnesin et al. carried out a first-in-human study utilizing [⁶⁸Ga]Ga-NODAGA-MJ9 in 5 prostate adenocarcinoma patients. The pancreas, being an organ expressing the highest GRPR, received the maximum absorbed dose of 260 μGy per MBq, followed by the urinary bladder, small intestine, and kidneys (69.8, 38.8 and 34.8 μGy per MBq, respectively). The effective dose delivered to the patients assuming a 30 min voiding cycle was 17 μSv per MBq, which was found to be in a similar range to other ⁶⁸Ga-labeled analogues.¹³⁴

Generally, GRPR-targeting antagonist tracers have been used in small clinical investigations. Thus, the potential of these ⁶⁸Ga-labeled antagonist tracers needs to be evaluated in a large population study.

5.7. Gallium-68 radiopharmaceuticals for neurotensin receptor imaging

In 1973, Carraway et al. isolated a 13-amino acid neuropeptide, i.e., neurotensin, from bovine hypothalami.¹³⁷ It is commonly found in the central nervous system and gastrointestinal tract. There are three types of neurotensin receptors (NTRs), i.e., NTR1, NTR2 and NTR3, which help in performing functions such as neuromodulation, the digestion process, pancreatic and biliary secretion stimulation, and gastric acid secretion inhibition. Several studies have shown the involvement of NTR1 in tumor progression in various cancer conditions, including digestive cancers.^138–141 Also, NTR2 expression has been reported in prostatic cancer, chronic lymphocytic leukaemia^142,143 and glioma.¹⁴⁴

Alshoukr et al. synthesized two novel DOTA-conjugated neurotensin analogues and radiolabeled them with ⁶⁸Ga, [⁶⁸Ga]Ga-DOTA-NT-20.3 and [⁶⁸Ga]Ga-DOTA-LB119, to study NTR positive tumors. The in vitro assay on an NTR1-positive HT-29 cell line (human colon adenocarcinoma cells) revealed the IC50 of 14 ± 2 nM and 7.5 ± 0.7 nM for [⁶⁸Ga]Ga-DOTA-NT-20.3 and [⁶⁸Ga]Ga-DOTA-LB119, respectively. Based on the biodistribution and PET imaging of nude mice grafted with HT29 cells, [⁶⁸Ga]Ga-DOTA-NT-20.3 showed superiority over [⁶⁸Ga]Ga-DOTA-LB119 given that it also detected small tumors.¹⁴⁵ This preliminary study demonstrated the potential of [⁶⁸Ga]Ga-DOTA-NT-20.3 as an imaging agent for NTR-positive tumors. Based on the promising results of [⁶⁸Ga]Ga-DOTA-NT-20.3, the same group conducted another preclinical study to discriminate human pancreatic ductal adenocarcinoma (PDAC) from pancreatitis. Preclinical PET imaging, biodistribution, blocking and histology examination in an animal model showed the ability of this tracer to discriminate human PDAC from pancreatitis.¹⁴⁶ Maschauer et al. developed different neurotensin peptide derivatives based on the sequence NLys-Lys-Pro-Tyr-Tle-Leu, radiolabeled with ¹⁸F and ⁶⁸Ga for PET imaging. In vitro and in vivo results demonstrated the receptor affinity for NTR1 (19–110 nM) and their high tumor uptake in HT29-tumor bearing mice, respectively. Among the different ⁶⁸Ga-labeled peptides, [⁶⁸Ga]Ga-8 (NT derivative with a metabolically stable peptide sequence of NLys⁸-Lys⁹-Pro¹⁰-Tyr¹¹-Tle¹²-Leu¹³) showed promising results for further evaluation.¹⁴⁷ Recently, another preclinical study was carried out by Wu et al. to explore [⁶⁸Ga]Ga-DOTA-NT-20.3 in PSMA-negative prostate cancer. It was successfully synthesized with an RCY and RCP of 88.07% ± 1.26% and 99%, respectively. The in vitro analysis demonstrated the affinity of [⁶⁸Ga]Ga-DOTA-NT-20.3 towards NTR1 (IC50 7.59 ± 0.41 nM). The in vivo biodistribution and imaging of [⁶⁸Ga]Ga-DOTA-NT-20.3 revealed its significant tumor uptake (4.95% ± 0.67% ID per g at 1 h) and high contrast images.¹⁴⁸

Bodin et al. devised, synthesized, and preclinically assessed [⁶⁸Ga]Ga-JMV 7488, a new neurotensin analogue that targets NTR2. The results showed the utility of [⁶⁸Ga]Ga-JMV 7488 in targeting NTR2-expressing cancer conditions, particularly in breast cancer with low FDG avidity, prostate cancer with negative PSMA expression and colorectal cancer.¹⁴⁹

All the tracers that target NTR expression are in preclinical stage and revealed only mild to moderate uptake. Therefore, the search for suitable NTR targeting tracers for clinical application is still ongoing.

5.8. Gallium-68 radiopharmaceuticals for chemokine receptor imaging

Among the family of chemokine receptors, the CXCR4 receptor has been identified as a potential G-coupled transmembrane receptor for the imaging and therapy of various solid tumors. Under normal conditions, this receptor is generally expressed by various cells during development and thereafter.¹⁵⁰ Its overexpression has been observed in various cancer conditions such as breast, colon, lung, multiple myeloma, melanoma, and pancreatic cancer.^150–156 Metastatic progression involves the interaction of CXCR4 and its chemotactic ligand CXCL12 (stromal cell-derived factor-1, SDF-1α). This leads to the activation of signal transduction cascades, which ultimately result in cancer cell proliferation, migration, and survival.^157,158 To image the overexpression of CXCR4 receptors, various SPECT and PET tracers have been investigated.^159–163 Considering the favourable physical and chemical characteristics of ⁶⁸Ga, researchers have developed ⁶⁸Ga-labeled CXCR4-binding peptides (Table 6).¹⁶⁴ Gourni et al. studied the novel [⁶⁸Ga]Ga-CPCR4.2 and demonstrated its 50% radiochemical yield with more than 95% RCP. The in vitro study showed its high affinity towards CXCR4 receptors and IC50 of 4.99 ± 0.72 nM and 177 nM for ^natGa-CPCR4.2 and CPCR4.2 against CXCR4-expressing Jurkat cell lines, respectively. PET images revealed its very high tumor uptake within a time frame of 120 min, together with a high background in excretory organs, i.e., liver, kidneys, and urinary bladder, which was rapidly reduced with time.¹⁶⁵ Another preclinical study was conducted based on a novel ⁶⁸Ga-labeled CXCR4-binding cyclic peptide, i.e., [⁶⁸Ga]Ga-DOTA-4-FBn-TN14003. The RCY and RCP obtained were 72.5% ± 4.9% and >99.5%, respectively. [⁶⁸Ga]Ga-DOTA-4-FBn-TN14003 was found to be highly stable for 4 h in PBS. A cellular study using Jurkat cell lines revealed the binding affinity of [⁶⁸Ga]Ga-DOTA-4-FBn-TN14003 and 4-FBn-TN14003 with IC50 values of 1.99 ± 0.31 nM and 4.07 ± 1.00 nM, respectively. The cell binding affinity assay demonstrated the high affinity of [⁶⁸Ga]Ga-DOTA-4-FBn-TN14003 and 4-FBn-TN14003 to CXCR4 expression.¹⁶⁶ George et al. conducted a similar study with a different chelator entity, NOTA, to preclinically evaluate the specificity of [⁶⁸Ga]Ga-NOTA-CCIC16 or TN14003 for CXCR4-expressing cancer conditions. Radiolabeling of [⁶⁸Ga]Ga-NOTA-CCIC16 demonstrated the RCY and RCP of 52% ± 8% and 98% ± 2%, respectively. An in vitro cellular uptake study was performed on U87.CD4.CXCR4 cells together with CXCR4-low U87.CD4 cells, which demonstrated the significant (3-fold) retention of [⁶⁸Ga]Ga-NOTA-CCIC16 in U87.CD4.CXCR4 cells. This was attributed to the specific binding of [⁶⁸Ga]Ga-NOTA-CCIC16 to CXCR4. In vivo experiments showed its excellent pharmacokinetic properties with specific accumulation in tissues with great contrast, i.e., tumor-to-muscle ratio of 9.5.¹⁶⁷

Table 6 Gallium-68 radiopharmaceuticals for chemokine receptor targeting

Tracer	Structure	Status	Ref.
[^68Ga]Ga-CPCR4-2		Clinical phase	Demmer^164 and Gourni et al., 2011^165
[^68Ga]Ga-DOTA-4-FBn-TN14003		Pre-clinical phase	Hennrich et al., 2011^166
[^68Ga]Ga-NOTA-CCIC16		Pre-clinical phase	George et al., 2013^167
[^68Ga]Ga-NOTA-NFB		Clinical phase	Jacobson et al., 2011^168
[^68Ga]Ga-Pentixafor		Clinical phase	Vag et al., 2016^172

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Wang et al. translated a ⁶⁸Ga-labeled CXCR4 antagonist, i.e., [⁶⁸Ga]Ga-NOTA-NFB, based on its promising pre-clinical results.¹⁶⁸ This tracer showed good pharmacokinetics with rapid blood clearance and high target to non-target ratio. The glioma tissues showed significant tracer accumulation (SUV_max of 4.11 ± 2.90), which was consistent with the overexpression seen in the histopathological labeling of the excised tumor tissues. Zhang et al. tested [⁶⁸Ga]Ga-NOTA-NFB in breast cancer patients expressing chemokine receptors. This tracer picked all the primary lesions (SUV_max of 3.78 ± 2.03) and 11 positive lymph nodes (SUV_max of 2.85 ± 1.86) out of 14 positive on the [¹⁸F]FDG scan. Also, it demonstrated potential for both screening for CXCR4 treatment and imaging patients with breast cancer.¹⁶⁹ However, additional clinical testing is required to clinically establish the [⁶⁸Ga]Ga-NOTA-NFB tracer.¹⁷⁰

Following the successful preclinical investigations and optimization conducted by Wester's group, [⁶⁸Ga]Ga-CPCR4.2, also referred to as [⁶⁸Ga]Ga-pentixafor, showed excellent pharmacokinetics in a preliminary clinical study in patients with hematologic malignancies. This tracer demonstrated rapid clearance and low background uptake, together with substantial accumulation in the tumors.^164,165,171 Further exploring the clinical applications of [⁶⁸Ga]Ga-pentixafor, Vag and co-workers performed a clinical study involving 21 patients diagnosed with various solid tumor types, namely pancreatic cancer, laryngeal cancer, non–small cell lung cancer (NSCLC), prostate cancer, melanoma, breast cancer, hepatocellular carcinoma, glioblastoma, sarcoma, and cancer of unknown primary. The maximum accumulation of [⁶⁸Ga]Ga-pentixafor yielding a high tumor-to-background contrast was noted in patients with NSCLC and cancer of unknown primary (SUV_max of 10.9 and 13.8, respectively).¹⁷²

A pilot study involving 15 patients of suspected glioblastoma or recurrent glioblastoma was conducted to assess the sensitivity of CXCR4-targeting [⁶⁸Ga]Ga-pentixafor. Among 15 patients, 13 demonstrated [⁶⁸Ga]Ga-pentixafor uptake. Semiquantitative analysis in comparison to [¹⁸F]FET showed the lower SUV_max and SUV_mean of [⁶⁸Ga]Ga-pentixafor (5.3 ± 2.3 and 3.9 ± 2.0; 4.4 ± 2.0 and 3.0 ± 1.5, respectively) and higher tumor to background ratio. Thus, it has emerged as a potential tracer for identifying suitable patients for targeted therapy.¹⁷³ Further, several insightful clinical studies have been performed to explore the clinical utilities of [⁶⁸Ga]Ga-pentixafor in solid and advanced hematological cancers.^174–178 Due to its demonstrated diagnostic utility, [⁶⁸Ga]Ga-pentixafor has been utilized to identify patients suitable for ¹⁷⁷Lu-Pentixather therapy. To facilitate easy clinical translation, the radiochemical synthesis of [⁶⁸Ga]Ga-pentixafor has also been developed in parallel and optimised with automated synthesis modules.^179,180

Among the above-mentioned CXCR4-targeting tracers, only [⁶⁸Ga]Ga-NOTA-NFB and [⁶⁸Ga]Ga-pentixafor have been tested clinically tested. [⁶⁸Ga]Ga-NOTA-NFB has been clinically tested in patients with glioma and breast cancer, whereas [⁶⁸Ga]Ga-pentixafor has been tested in various solid and hematological cancer conditions.

5.9. Gallium-68 radiopharmaceuticals for glucagon-like peptide1 receptor imaging

Glucagon-like peptide-1 (GLP-1) receptor (GLP-1R) is an incretin hormone that regulates insulin release and glucagon secretion in healthy individuals. Physiologically, GLP-1 is produced by intestinal L cells, typically present in the duodenum until the colon.¹⁸¹ GLP-1R has been identified as a potential target for β cell imaging and managing insulinomas. β cells are usually present in the islet of Langerhans of the pancreas, and their function involves the biosynthesis and secretion of insulin as well as the regulation of blood glucose levels in the body. Exendin-4 is a naturally occurring peptide (39 amino acids) analogue of GLP-1. It binds to GLP-1R and activates it in the same manner as GLP-1.^182,183 Exendin-4 has a long in vivo biological half-life (≥20 min) compared to endogenously produced GLP-1, making it more suitable as a radiolabeled targeting probe.¹⁸⁴ Thus, it was radiolabeled with different PET and SPECT radioisotopes. Among the PET radioisotopes, ⁶⁸Ga-labeled exendin-4 showed remarkable results, due to which more extensive research has been performed involving various chelators such as DOTA, NOTA, NODAGA and DO3A, together with different linkers including Ahx, MAL and VS. In 2010, ⁶⁸Ga-labeled DOTA-conjugated modified exendin-4, i.e., [Lys40(Ahx-DOTA-⁶⁸Ga)NH₂]-exendin-4, was evaluated preclinically,¹⁸⁵ and subsequently translated into clinics. Several modifications were performed to enhance the physicochemical characteristics and biological kinetics of this tracer. Selvaraju et al. developed a ⁶⁸Ga-labeled DO3A-VS-Cys⁴⁰-exendin-4 PET imaging tracer for the preclinical evaluation of GLP-1R-expressing insulinomas. The non-decay corrected RCY and RCP obtained for [⁶⁸Ga]Ga-DO3A-VS-Cys⁴⁰-exendin-4 were 80% ± 5% and ≥95%, respectively. The small animal biodistribution study in control mice showed the uptake of [⁶⁸Ga]Ga-DO3A-VS-Cys⁴⁰-exendin-4 to be highest in the lungs, pancreas and kidneys. A similar physiological tracer distribution was noted in tumor-induced mice, together with the maximum tracer accumulation at the tumor site. The animal PET-CT imaging results were also consistent with the biodistribution results, i.e., prominent tracer uptake in INS-1 tumors with reduced background, which is essential for detecting small lesions in vivo.¹⁸⁶ A case report study was further performed using [⁶⁸Ga]Ga-DO3A-VS-Cys⁴⁰-exendin-4 in a patient with a grade II insulinoma. The PET/CT images revealed the uptake of the tracer in small GLP-1R-positive liver lesions and lymph nodes, which were not picked by other tracers such as [¹⁸F]FDG and [¹¹C]5-HTP, demonstrating its superior sensitivity.¹⁸⁷

Different derivatives of ⁶⁸Ga-labeled exendin-4, i.e., [⁶⁸Ga]Ga-Ex4NOD12, [⁶⁸Ga]Ga-Ex4NOD27 and [⁶⁸Ga]Ga-Ex4NOD40 (Table 7), were also developed and investigated preclinically to assess their effect on binding and pharmacokinetics of the peptide. Compared to unmodified exendin-4 (IC50: 4.1 nM), all the modified derivatives showed reduced binding affinities (IC50 values for ^natGa-Ex4NOD12, ^natGa-Ex4NOD27, and ^natGa-Ex4NOD40 were 29 nM, 53 nM, and 54 nM, respectively) for CHL-GLP-1R-positive cells. The in vivo biodistribution of [⁶⁸Ga]Ga-Ex4NOD12 and [⁶⁸Ga]Ga-Ex4NOD40 showed similar pharmacokinetics, whereas [⁶⁸Ga]Ga-Ex4NOD27 demonstrated slightly inferior results.¹⁸⁸

Table 7 Gallium-68 radiopharmaceuticals for GLP1 targeting

Tracer	Structure	Status	Ref.
[^68Ga]Ga-DO3A-VS-Cys^40-Exendin-4		Pre-clinical phase	Velikyan et al., 2017^198
[^68Ga]Ga-Ex4NOD12		Pre-clinical phase	Jodal et al., 2014^188
[^68Ga]Ga-Ex4NOD27		Pre-clinical phase	Jodal et al., 2014^188
[^68Ga]Ga-Ex4NOD40		Pre-clinical phase	Jodal et al., 2014^188
[^68Ga]Ga-DO3A-Tuna-2		Clinical phase	Wagner et al., 2020^197

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Based on further promising preclinical studies,^{185,186,189,19068}Ga labeled exendin-4 was translated into human studies involving patients with GLP-1R expressing insulinomas.^191–195 However, GLP-1R imaging has a major drawback, its expression in malignant insulinomas is much less compared to benign insulinomas,¹⁹⁶ making GLP-1R imaging less sensitive.

Another novel tracer, i.e., [⁶⁸Ga]Ga-DO3A-Tuna-2, has been explored preclinically to target glucagon receptors/GLP1R, and owing to the promising results obtained in in vitro and in vivo examinations, it has been translated to human clinical trials.¹⁹⁷

The treatment management of type 2 diabetes (T2D) involves targeting glucagon receptors/GLP1R. Based on this concept, [⁶⁸Ga]Ga-DO3A-Tuna-2 was utilised for the monitoring of T2D disease status by targeting glucagon receptors/GLP1R. A recent study demonstrated the GMP-compliant production of [⁶⁸Ga]Ga-DO3A-Tuna-2,¹⁹⁸ and the tracer was applied to quantify glucagon receptors/GLP-1R in humans. The reproducible GMP-compliant production of [⁶⁸Ga]Ga-DO3A-Tuna-2 revealed the non-decay corrected RCY of 45.2% ± 2.5% and RCP of 98.9% ± 0.6%. High-quality PET/CT images were obtained by administering the tracer activity of 0.47 ± 0.04 MBq per kg body weight. In PET/CT images, the biodistribution of the tracer showed specifically high uptake in the liver due to the high expression of glucagon receptors on hepatocytes.¹⁹⁹

Another clinical study has been performed to quantitatively assess the dual receptor targeting (GLP1R and Glucagon receptors) of SAR425899 in T2D patients using [⁶⁸Ga]Ga-DO3A-Tuna-2 and [⁶⁸Ga]Ga-DO3A-Exendin4.²⁰⁰ This study is part of an ongoing clinical trial (ClinicalTrials.gov NCT number: NCT03350191). Many more clinical studies are anticipated considering the potential of [⁶⁸Ga]Ga-DO3A-Tuna-2.

At present, the most clinically explored tracer for GLP-1R imaging is [⁶⁸Ga]Ga-NODAGA-exendin-4.

5.10. Gallium-68 radiopharmaceuticals for melanoma imaging

Among the various skin cancer conditions, melanoma is the most aggressive and rarest type of malignant skin cancer. In the field of molecular imaging, different alpha-melanocyte-stimulating hormone (α-MSH) peptide analogues have been developed for melanoma imaging. α-MSH is an endogenously produced melanocortin peptide, which binds to the melanocortin receptor family of proteins. Studies have shown the upregulation of the melanocortin 1 receptor (MC1R) subtype in melanoma tumor cells. This has led to the development of ⁶⁸Ga-labeled α-MSH peptide analogues for diagnostic imaging purposes.

Wei et al. investigated [⁶⁸Ga]Ga-CHX-A′′-Re(Arg11)CCMSH, a novel α-MSH peptide analogue, in B16/F1 melanoma-bearing mice. The radiolabeling efficiency obtained for [⁶⁸Ga]Ga-CHX-A′′-Re(Arg11)CCMSH was >95% with the specific activity of 1.85 GBq per μg. The biodistribution study demonstrated rapid tumor uptake with 2.68% ± 0.69% ID per g at 2 h post injection. PET imaging revealed the specificity of the tracer by showing melanoma tumor uptake in the shoulder of the mice (non-blocked) and no uptake in the tumor site of the mice given 20 μg of non-radiolabeled NDP peptide (blocked).²⁰¹

In a recent clinical study, [⁶⁸Ga]Ga-VMT02 was used to target MC1R in patients with stage IV melanoma. In the 3 h PET images, the tracer showed the best tumor to background ratio. [⁶⁸Ga]Ga-VMT02 has demonstrated the potential to identify individuals who may respond well to [²¹²Pb]Pb-VMT01 alpha-emission therapy.²⁰²

Two ⁶⁸Ga-labeled glucosamine derivatives, i.e., DOTA-RMX-GC-BNCO and DOTA-RMX-GC-MFCO, targeting the glucose transporter have also been explored for imaging metastatic melanoma. Both conjugates were radiolabeled and found to be stable in FBS and PBS up to 4 h. PET imaging showed the favourable pharmacokinetics of [⁶⁸Ga]Ga-DOTA-RMX-GC-BNCO of about >5% ID per g of tumor tissue, rapid renal clearance and no retention in other organs at 60 min post injection.²⁰³

Gai et al. synthesized 1,4,7-triazacyclononane (TACN)-based bifunctional chelators with phosphonic acid arms, i.e., p-SCN-PhPr-NE2A1P and p-SCN-PhPr-NE2P1A, and conjugated them with a peptidomimetic ligand, LLP2A-PEG4. Among them, [⁶⁸Ga]Ga-NE2P1A-PEG4-LLP2A, a very late antigen-4 (VLA-4)-targeting ligand, also known as α₄β₁, was radiolabeled and evaluated in mice bearing B16F10 tumor xenografts. The radiolabeling yield was quantitative (30% ± 4%), and less than 5% dissociation was observed up to 2 h in the serum stability test. The biodistribution study and PET imaging revealed high tumor uptake with specificity towards VLA-4 receptors overexpressed in melanoma.²⁰⁴

Another MC1R targeting tracer, [⁶⁸Ga]Ga-DOTA-GGNle-CycMSH_hex, has been preclinically evaluated and further advanced for clinical testing. Yang et al. evaluated the specificity of [⁶⁸Ga]Ga-DOTA-GGNle-CycMSH_hex towards MC1R in different cell lines (murine and human melanoma cells) and tumor models. In vitro and in vivo examinations showed the MC1R-specific targeting properties of [⁶⁸Ga]Ga-DOTA-GGNle-CycMSH_hex. [⁶⁸Ga]Ga-DOTA-GGNle-CycMSH_hex was further tested in two metastatic melanoma patients and demonstrated significant uptake in the metastatic lesions but needs more clinical studies to fully evaluate its clinical potential.²⁰⁵

Among the many investigated tracers, [⁶⁸Ga]Ga-VMT02 and [⁶⁸Ga]Ga-DOTA-GGNle-CycMSH_hex have emerged as promising tracers for targeting MC1R-expressing tumors in patients with metastatic melanoma.

5.11. Gallium-68 radiopharmaceuticals for angiogenesis imaging

To survive under hypoxic conditions, the formation of new capillaries, i.e., angiogenesis, from existing vessels helps tumors grow and proliferate.²⁰⁶ The angiogenesis process is regulated by integrins, which are a family of cell adhesion receptors and consist of αβ heterodimers in their structure. Around 24 heterodimers have been identified in humans, which are made up of 18 α and 8 β subunits. These subunits of integrins are structurally distinct. However, one sequence, i.e., arginine–glycine–aspartic acid (RGD), has been identified as a general integrin-binding motif. Therefore, to visualise angiogenesis, various peptide ligands have been developed to target integrin receptors that are overexpressed in various tumors.

Various cyclic peptides (monomeric as well as multimeric) containing RGD as a sequence have been developed, e.g., cyclo-[RGDfK], cyclo-[RGDyK], cyclo-[RGDfE], cyclo-[RGDf(NMe)V], E[c(RGDfK)]₂, and E[c(RGDyK)]₂, and optimized to increase the tracer uptake in α_vβ₃ integrin-expressing tumors.^207–210 [⁶⁸Ga]Ga-RGD peptide derivatives specifically targeting α_vβ₃ integrin receptors have been further evaluated preclinically and clinically in various disease conditions such as thyroid cancer with T_g elevated negative iodine scan (TENIS), atherosclerotic plaques, myocardial infarction, breast cancer, glioblastoma, lung cancer, and chondroblastic osteosarcoma. These studies unveiled that with an increase in peptide multiplicity (especially in tetramers), significant tracer uptake in normal organs was observed, and consequently the desired target to background ratio was not obtained. Additionally, tetramers are not cost effective. Hence, dimeric cyclic RGD peptides have been found to be optimal for α_vβ₃ integrin-expressing tumor imaging.²¹¹

Besides α_vβ₃, many integrin subtypes, i.e., α_vβ₆, α_vβ₈, and α₅β₁, have been found to be overexpressed in different cancer conditions. Thus, to target these other integrins and increase the affinity of ligands, various monomers and trimers of integrin ligands with varying affinities have been evaluated preclinically and clinically (Table 8). Recently, Quigley et al. preclinically evaluated [⁶⁸Ga]Ga-Trivehexin (a trimer with the peptide sequence cyclo[YRGDLAYp(NMe)K]), targeting the α_vβ₆ subtype of integrins, and also demonstrated the PET/CT imaging of head and neck and pancreatic cancer in humans. The radiolabeling resulted in the RCY of >95% and RCP of >99%. An in vitro assay was performed on α_vβ₆-positive H2009 cell lines, which showed its high affinity towards α_vβ₆ integrins (IC50 = 0.047 nM). The animal biodistribution and animal PET imaging showed high specific tracer uptake at the tumor site with low background uptake. These promising results were a driving force to perform human administration of [⁶⁸Ga]Ga-Trivehexin for PET/CT imaging of 4 patients with head and neck and pancreatic cancer. The results of human imaging showed significant high tracer uptake in the metastatic lesions (SUV_max in the range of 6–14) together with excretory organs, i.e., kidneys and bladder. Low-grade uptake was also noted in the tumor-associated inflammatory sites. No other uptake was noted in any organs except excretory organs and the tumor site. This makes it a promising imaging agent for tumors expressing integrins.²¹²

Table 8 Gallium-68-labeled radiopharmaceuticals targeting integrins

Tracer	Structure	Status	IC50
[^68Ga]Ga-DOTA-RGD		Clinical phase	5.5 ± 1.6 nM^207
[^68Ga]Ga-BNOTA-PRGD2		Clinical phase	82.7 nM^232
[^68Ga]Ga-NOTA-c[RGDyK]		Pre-clinical phase	3.6 ± 2.4 nM (Ki value)^233
[^68Ga]Ga-Avebetrin		Pre-clinical phase	0.22 nM^234
[^68Ga]Ga-NODAGA-FR366		Pre-clinical phase	1.3 ± 0.08 nM^235,236
[^68Ga]Ga-Aquibeprin		Pre-clinical phase	0.08 nM^234
[^68Ga]Ga-TRAP-AvB8		Pre-clinical phase	38 nM^237
[^68Ga]Ga-Triveoctin		Clinical phase	5.7 nM^238
[^68Ga]Ga-TRAP-SDM17		Pre-clinical phase	7.4 nM^239
[^68Ga]Ga-TRAP(SDM17)3		Pre-clinical phase	0.26 nM^239
[^68Ga]Ga-Avebehexin		Pre-clinical phase	0.26 nM^240
[^68Ga]Ga-Trivehexin		Clinical phase	0.047 nM^212
[^68Ga]Ga-IAC		Clinical phase	Not reported^216
[^68Ga]Ga-NODAGA-c(NGR)		Pre-clinical phase	Not reported^226
[^68Ga]Ga-Cycratide		Clinical phase	20.17 ± 1.68 nM^241

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Another potent ⁶⁸Ga-labeled peptide, i.e., 4-[2-(3,4,5,6-tetrahydropyrimidine-2-ylamino)ethyloxy]benzoyl-2-[N-(3-amino-neopenta-1-carbamyl)]-aminoethylsulfonyl-amino-β-alanine (IAC), has been evaluated clinically to target the α_vβ₃ integrin subtype for angiogenesis imaging. This peptide has been conjugated with various chelating agents to increase its tumor retention and clearance from the body.²¹³ Multiple studies are ongoing to evaluate the role of IAC as a theranostic molecule for several aggressive tumors.^214–216 A phase I/II clinical trial is ongoing involving a multicentre interventional study (ClinicalTrials.gov NCT number: NCT04480619) using [⁶⁸Ga]Ga-PEG-α_vβ₃-IAC.

Studies have shown the overexpression of the aminopeptidase N receptor (APN), also known as CD13, in angiogenic blood vessels. Therefore, it has been considered a suitable target for the detection and treatment of APN-expressing tumors. Various cancer conditions, such as melanoma, prostate, lung and ovarian cancer, have shown overexpression of APN.²¹⁷ Pasqualini et al. developed a molecule containing an asparagine-glycine-arginine tripeptide sequence (NGR), which is highly specific to APN/CD13 receptors.²¹⁸ Since then, various studies evaluating APN targeting NGR-based ⁶⁸Ga-labeled tracers have been performed. It was found that NGR-based peptides have three-times the detection efficiency of neoangiogenic vessels than RGD peptides.²¹⁹ As a result, several linear and cyclic NGR based peptides have been developed, studied and radiolabeled with ⁶⁸Ga.^220–227 Recently, Yang et al. synthesized and evaluated a cyclic NGR dimer peptide, [⁶⁸Ga]Ga-DOTA-c(NGR)₂, to study the CD13 expression in an ovarian cancer xenograft. The biodistribution study showed the excellent pharmacokinetics of the tracer with a high tumor-to-background ratio of 10.30 ± 0.26 at 1 h imaging. The tracer showed reduced uptake when the cold peptide was coinjected, which is attributed to the specificity of the tracer towards CD13.²²⁸ Alternatively, the NGR sequence tends to undergo deamidation of the asparagine (Asn) side chain,²²⁹ which can result in the formation of isoaspartic acid (isoAsp) and Asn residues.²³⁰ Therefore, to overcome the stability issues of NGR analogues, other peptides targeting the neoangiogenic process such as APN-selective LN peptide (YEVGHRC) and VEGFR-1-selective APRPG peptide, were preclinically evaluated.²³¹

The search for a suitable tracer that targets pan integrins is still underway. However, [⁶⁸Ga]Ga-Trivehexin and [⁶⁸Ga]Ga-IAC are under evaluation clinically.

5.12. Gallium-68 radiopharmaceuticals for cholecystokinin receptors imaging

The overexpression of cholecystokinin (CCK) receptors, especially CCK2, has been found in several cancer conditions such as small cell lung carcinoma (SCLC), medullary thyroid carcinomas (MTC), breast, endometrial, stromal ovarian cancers and astrocytomas.²⁴² In order to target CCK2 receptors, various radiolabeled analogues of natural ligands, i.e., minigastrin (MG) and cholecystokinin, have been developed and utilized for molecular imaging and targeted therapy of different cancer conditions such as MTC and SCLC.²⁴³ However, these radiolabeled analogues were not translated clinically because of their significantly high kidney uptake and low metabolic stability. Thus, to develop a tracer without the above-mentioned challenges, various peptide derivatives have been tested with numerous modifications such as addition, substitution or elimination of amino acids and cyclization or dimerization of their peptide sequence to enhance their pharmacokinetics and stability. Initially, in 2010, [⁶⁸Ga]Ga-DOTA–PP-F10 (DOTA-(D-Gln)6-Ala-Tyr-Gly-Trp-Met-Asp-Phe-NH₂) was used for the first time in a case study of a 59-year-old female MTC patient. The scan showed the uptake of [⁶⁸Ga]Ga-DOTA–PP-F10 in the liver lesion with SUV_max of 1.7, which was in accordance with the previous [⁶⁸Ga]Ga-DOTA-[Tyr3]octreotide scan finding. The rest of the organs showed minimal tracer (SUV_max = 0.5–1) uptake except the stomach (SUV_max = 3.1).²⁴⁴ Subsequently, [⁶⁸Ga]Ga-DOTA-PP-F11 (amino acid sequence: DGlu-DGlu-DGlu-DGlu-DGlu-DGlu-Ala-Tyr-Gly-Trp-Met-Asp-Phe-NH₂), another promising tracer for CCK2 receptor targeting was developed. Roosenburg et al. performed a preclinical study by conjugating PP-F11 with three different chelators, i.e., DOTA, NOTA and NODAGA, to see any in vivo behavioural change in the tracer. Based on the in vitro and in vivo analysis results, the authors inferred that [⁶⁸Ga]Ga-DOTA–PP-F11 showed favourable pharmacokinetics and imaging characteristics.²⁴⁵ Another case study was performed using [⁶⁸Ga]Ga-DOTA–PP-F11 in a 75-year-old male MTC patient. The scan revealed tracer uptake in the right thyroid mass with no involvement of nodes, which was also seen in the [⁶⁸Ga]Ga-DOTATE scan. Physiological uptake was observed in the stomach, liver, spleen and kidneys.²⁴⁶ The same peptide has also been radiolabeled with the SPECT radionuclide ¹¹¹In and clinical studies carried out to target CCK2 receptors expressed in MTC patients.²⁴⁷ In addition, DOTA-PP-F11 and its modified derivative, i.e., DOTA-PP-F11N, have been radiolabeled with the therapeutic radionuclide ¹⁷⁷Lu to perform targeted therapy of advanced MTC patients. A phase 0 clinical study is underway involving [¹⁷⁷Lu]Lu-DOTA–PP-F11N as a therapeutic agent for the treatment of MTC patients.²⁴⁸

Further research towards improving tumor targeting, reducing kidney uptake and increasing the in vivo enzymatic stability of the MG analogue led to the development of another novel MG analogue, DOTA-D-Glu-Ala-Tyr-Gly-Trp-(N-Me)Nle-Asp-1-Nal-NH₂ (DOTA-MGS5) (Table 9). Klingler et al. synthesized this novel CCK2-specific peptide and performed radiolabeling with ¹¹¹In, ⁶⁸Ga and ¹⁷⁷Lu to carry out an extensive preclinical study. The radiolabeling of DOTA-MGS5 with ⁶⁸Ga resulted in 95% RCP with a molar activity of 60 GBq per mmol. The labeled product was stable in PBS, saline and human serum, with more than 95% of the radiolabeled product intact in human serum for up to 4 h. The cellular study revealed more than 50–60% uptake of [⁶⁸Ga]Ga-DOTA-MGS5 in A431-CCK2R cells after 2 h incubation, which was more than that of [⁶⁸Ga]Ga-DOTA-PP-F11N (15–30%). Also, a blocking study with human gastrin revealed a decrease in uptake, i.e., below 1.5%, indicating the high specificity of the tracer towards CCK2 receptors. An animal biodistribution study revealed the physiological uptake of [⁶⁸Ga]Ga-DOTA-MGS5 in the blood, heart, spleen, lung, and liver with slightly higher uptake in the CCK2-expressing spleen and stomach. Also, significant tracer accumulation at 1 h was noted in A431-CCK2R tumor-bearing animals (23.25% ± 4.70% IA per g).²⁴⁹ This tracer was further evaluated by Hörmann et al., and to translate it into clinics, cassette-based automated synthesis was performed.²⁵⁰ Furthermore, a case study involving [⁶⁸Ga]Ga-DOTA-MGS5 vs. [¹⁸F]FDOPA in a 75-year-old patient suffering from MTC was reported. The PET/CT images showed fewer lymph node and bone lesions picked up by [⁶⁸Ga]Ga-DOTA-MGS5 compared to [¹⁸F]FDOPA. However, more liver lesions with high SUV values were detected by [⁶⁸Ga]Ga-DOTA-MGS5.²⁵¹ Another preliminary clinical study was carried out by Guggenberg et al. in 6 patients of MTC using [⁶⁸Ga]Ga-DOTA-MGS5. The tracer detected 87 lesions in total (50 bone lesions, 27 liver lesions, 8 lymph nodes and 2 local lesions) with higher uptake at 2 h than at 1 h (mean SUV_max, 7.2 vs. 6.0, respectively).²⁵² A phase I/IIa clinical trial of [⁶⁸Ga]Ga-DOTA-MGS5 is ongoing in patients with advanced NET, MTC, and gastroenteropancreatic and bronchopulmonary NET (EudraCT: 2020-003932-26). Another minigastrin analogue, i.e., [⁶⁸Ga]Ga-DOTA-MGS8, has been developed, synthesized with an automated module and evaluated preclinically by the same group.²⁵³ The promising results of this preclinical study encouraged researchers to evaluate it further to translate it into clinics. There are review articles covering the development of CCK2 receptor imaging using various novel radiopharmaceuticals.^254,255

Table 9 Gallium-68-labeled radiopharmaceuticals for CCK receptor targeting

Tracer	Structure	Status	Ref.
[^68Ga]Ga-DOTA-PP-F10		Clinical phase	Peitl et al., 2011^244
[^68Ga]Ga-DOTA−PP-F11		Clinical phase	Roosenburg et al., 2014^245
[^68Ga]Ga-DOTA-MGS5		Clinical phase	Klinger et al., 2018^249
[^68Ga]Ga-DOTA-MGS8		Pre-clinical phase	Hörmann et al., 2022^253

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The most clinically studied CCK2 receptor-targeting tracer is [⁶⁸Ga]Ga-DOTA-MGS5 but additional clinical studies are ongoing using this tracer to optimize its tumor targeting, improve its pharmacokinetics and enhance its in vivo stability.

5.13. Miscellaneous

In the last decade, due to the versatility of ⁶⁸Ga radiochemistry, many novel tracers have been investigated preclinically and successfully translated to clinical setups for numerous oncological and non-oncological applications. This involves a diverse range of molecules, ranging from small molecules and peptides to colloidal particles of varying sizes depending on the clinical application.

5.13.1. Miscellaneous oncological applications. In conventional nuclear medicine imaging, skeletal scintigraphy helps in assessing the involvement of bone metastases accurately. The most commonly employed radiopharmaceutical for skeletal scintigraphy is a phosphonate-based SPECT tracer, i.e., ^99mTc-labeled [^99mTc]Tc-methylene diphosphonate ([^99mTc]Tc-MDP). However, various other PET (Table 10) and SPECT tracers based on bisphosphonate have been explored for clinical applications. In 2020, Zha et al. performed a preclinical comparative study of [⁶⁸Ga]Ga-P15-041 and Na[¹⁸F]F in mice and rats. The biodistribution and microPET imaging study showed the high in vivo stability, longer retention, and high uptake of [⁶⁸Ga]Ga-P15-041 compared to Na[¹⁸F]F.²⁵⁶ Based on the promising results of animal studies, a recent first in human study was performed by Doot et al., which showed the higher sensitivity of [⁶⁸Ga]Ga-P15-041 given that it detected a higher number of lesions with much higher contrast than [^99mTc]Tc-MDP.²⁵⁷ Recently, another comparative human study was conducted on 51 patients with different cancer conditions to assess the potential of [⁶⁸Ga]Ga-P15-041 over [^99mTc]Tc-MDP in detecting bone lesions.²⁵⁸ The study results were in consistent with the study by Doot et al.

Table 10 Gallium-68-labeled radiopharmaceuticals for skeletal scintigraphy

Radiopharmaceutical	Structure	Status	Ref.
[^68Ga]Ga-P15-041		Clinical Phase	Doot et al., 2020^257 and Zha et al., 2020^256
[^68Ga]Ga-DOTA-PAM		Pre-clinical phase	Meckel et al., 2016^292
[^68Ga]Ga-DOTA-ZOL		Clinical phase	Meckel et al., 2016^292
[^68Ga]Ga-DOTA-BPAPD		Pre-clinical phase	Meckel et al., 2013^293
[^68Ga]Ga-DOTA-BPPED		Pre-clinical phase	Meckel et al., 2013^293
[^68Ga]Ga-NO2AP-BP		Clinical phase	Holub et al., 2014^294
[^68Ga]Ga-DOTA-BPAMD		Clinical phase	Fellner et al., 2010^295 and Wu et al., 2016^296
[^68Ga]Ga-PhenA-BPAMD		Clinical phase	Fellner et al., 2010^295 and Wu et al., 2016^296
[^68Ga]Ga-PhenA-HBP		Pre-clinical phase	Wu et al., 2016^296
[^68Ga]Ga-DOTA-(D-Asp)n		Pre-clinical phase	Ogawa et al., 2017^297
[^68Ga]Ga-EDTMP		Clinical phase	Toegel et al., 2008^298
[^68Ga]Ga-NOTA-BP		Pre-clinical phase	Suzuki et al., 2011^299 and Holub et al., 2014^294
[^68Ga]Ga-DOTA-BP		Pre-clinical phase	Suzuki et al., 2011^299 and Holub et al., 2014^294
[^68Ga]Ga-NOTAM-BP		Pre-clinical phase	Holub et al., 2014^294
[^68Ga]Ga-TRAP-(MDP)3		Pre-clinical phase	Notni et al., 2012^300
[^68Ga]Ga-TRAP-(PDP)3		Pre-clinical phase	Notni et al., 2012^300

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Multiple myeloma (MM) presents uniform overexpression of CD38 glycoprotein, which is considered the best target for therapeutic and imaging approaches. Pursuing this approach, a CD38-targeting single domain antibody i.e., Nb1053, has been developed. The binding moiety in Nb1053 is similar to that present in daratumumab, an approved monoclonal antibody for treating MMs. Wang et al. developed a novel [⁶⁸Ga]Ga-NOTA-Nb1053 immunoPET imaging tracer and performed its characterization in preclinical MM and lymphoma models. The RCY and RCP obtained in radiolabeling were 47.84% ± 12.2%, and >99%, respectively. Biodistribution and PET imaging revealed the diagnostic potential of [⁶⁸Ga]Ga-NOTA-Nb1053 over [¹⁸F]FDG in mice bearing subcutaneous MM.1S xenografts and orthotopic MM.1S. The authors demonstrated a significant reduction in renal uptake upon premedication with sodium maleate. The preclinical results of this novel tracer favor its clinical translation. However, before translating it to clinics, the high renal uptake and low tumor retention of [⁶⁸Ga]Ga-NOTA-Nb1053 need further evaluation.²⁵⁹

Targeted molecular imaging of the immune checkpoint, i.e., programmed death ligand-1 (PD-L1), and its receptor, i.e., programmed death-1 (PD-1), utilizing nanobody-based radiotracers, i.e., [⁶⁸Ga]Ga-NOTA-mal-hPD-L1 Nb and [⁶⁸Ga]Ga-NOTA-Nb109, has emerged as a potential tool to assay the expression of PD-L1/PD-1. Initially, [⁶⁸Ga]Ga-NOTA-mal-hPD-L1 Nb was introduced by Bridoux et al.²⁶⁰ and showed the feasibility of PD-L1 imaging, and subsequently [⁶⁸Ga]Ga-NOTA-Nb109 showed the potential of nanobody-based PET imaging.^261,262 Thereafter, various preclinical studies have been performed to target PD-L1/PD-1.^262–264 Jinquan et al. used a custom-synthesized PD-L1-binding peptide, i.e., WL12 (a 12-mer anti-PD-L1 peptide) and radiolabeled it with ⁶⁸Ga after conjugation with the NOTA chelator. The RCP obtained was >99% with a molar activity of 27.8–111.2 GBq per μmol. In vitro cellular and in vivo animal studies were performed together with a first in the human administration of [⁶⁸Ga]Ga-WL12 to assess the feasibility of clinical translation of this tracer for PD-L1 imaging. The study showed significant tracer uptake at primary and metastatic sites (SUV_max in the range of 2.0–6.0).²⁶⁵ This tracer is currently under a phase 1 clinical trial involving patients with gastrointestinal tumors (ClinicalTrials.gov NCT number NCT04629326). Ma et al. preclinically evaluated a novel ⁶⁸Ga labeled nanobody, [⁶⁸Ga]Ga-THP-APN09, for the assessment of PD-L1 quantification and biodistribution in tumor-bearing mice. In addition, rapid one-step radiolabeling with no further purification was demonstrated, and further a pilot clinical study involving 9 NSCLC patients was performed (ClinicalTrials.gov NCT Number: NCT05156515).²⁶⁶ Another study of PD-L1 imaging is in an early phase 1 clinical trial (ClinicalTrials.gov NCT Number: NCT05490264). This study involves nanobody based tracer, [⁶⁸Ga]Ga-NOTA-SNA002, for the PET imaging of patients with solid tumors.

Other potential biological targets have also been explored for immuno PET imaging; human CD8⁺ and CD8⁺ T cells have been targeted by various ⁶⁸Ga-labeled nanobodies to assess their distribution in the tumor environment. Different derivatives of SNA006 nanobodies, i.e., SNA006a, SNA006c and SNA006d, were synthesized and conjugated with p-SCN-Bn-NOTA, and subsequently radiolabeled with ⁶⁸Ga. This in vitro cellular study and in vivo PET imaging revealed the excellent characteristics of [⁶⁸Ga]Ga-NOTA-SNA006a for the specific detection of CD8⁺ and CD8⁺ T cells in tumor lesions as well as across the whole body.²⁶⁷ The SNA006 nanobody-based tracer [⁶⁸Ga]Ga-NODAGA-SNA006 is in an early phase 1 clinical trial (ClinicalTrials.gov NCT number: NCT05126927).

Another immune checkpoint explored for immuno PET imaging is the T cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif (ITIM) domain (TIGIT) receptor. A novel peptide antagonist was synthesized and radiolabeled with ⁶⁸Ga, i.e., [⁶⁸Ga]Ga-NOTA-GP12, to evaluate the expression of TIGIT in cancers. Wang et al. developed this tracer and performed in vitro, in vivo and in human PET imaging of TIGIT expression in 2 patients with non-small cell lung carcinoma. The novel tracer was safe and demonstrated that uptake in the primary and metastatic lesions was consistent with the uptake of [¹⁸F]FDG.²⁶⁸ Thus, to establish this promising tracer clinically, more clinical studies must be performed to unfold its potential.

The tumor microenvironment involving cancer-associated fibroblasts, cancer-associated adipocytes, immune cells, macrophages and endothelial cells, plays an essential role in the development and growth of tumors. An alteration in any of the processes of tumor microenvironment makes it a suitable cancer-specific target. Tumor-associated macrophages (TAM) have been identified as a potential target to study their expression in cancer conditions. Recently, several ⁶⁸Ga-labeled radiopharmaceuticals, i.e., [⁶⁸Ga]Ga-NOTA-anti-MMR-sdAb and [⁶⁸Ga]Ga-mannosylated serum albumin (MSA)-targeting macrophage mannose receptors (MMR) expressing TAM,^269,270 [⁶⁸Ga]Ga-NOTA-COG1410 targeting triggering receptor expressed on myeloid cells 2 (TREM2) of TAM,²⁷¹ and [⁶⁸Ga]Ga-DOTA-M2pep targeting M2 macrophage type of TAM,²⁷² have emerged as potential TAM-specific preclinical imaging tracers. However, recently, a different side chain antibody-based ⁶⁸Ga labeled tracer has undergone phase I/II clinical trials involving patients with different solid tumors (ClinicalTrials.gov NCT number: NCT04168528).

Another biological target for molecular imaging identified in the tumor microenvironment is extra domain-B fibronectin (EDB-F), an oncoprotein overexpressed in pancreatic cancer conditions. To perform the early diagnosis of pancreatic cancer, a ZD2 peptide (Thr-Val-Arg-Thr-Ser-Ala-Asp) specific to EDB-F was synthesized, radiolabeled with ⁶⁸Ga and in vitro and animal in vivo studies performed. The preclinical results obtained were promising for the early detection of pancreatic cancer.²⁷³

A variety of PET and SPECT-based folate conjugates has been developed to target folate receptor expression.²⁷⁴ In 2014, Aljammaz et al. preclinically evaluated ⁶⁸Ga-labeled NOTA-folate and NOTAM-folate conjugates for targeted imaging of folate receptor-expressing cancers such as ovarian cancer. This study demonstrated the easy and efficient radiolabeling of the tracer with a short synthesis time. The RCY and RCP obtained for the ⁶⁸Ga-labeled NOTA- and NOTAM-folate conjugates were greater than 95% (decay corrected) and 98%, respectively. The in vitro cell binding affinities of the [⁶⁸Ga]Ga-NOTA-folate and [⁶⁸Ga]Ga-NOTAM-folate conjugates were found to be 54.36 ± 6.31 nM and 78.01 ± 13.0 nM, respectively. The in vivo biodistribution study showed significant tracer uptake in nude mice bearing a human KB xenograft owing to the specificity of the tracer towards folate positive tumors.²⁷⁵ Since then, no clinical studies have been performed to evaluate the potential of [⁶⁸Ga]Ga-NOTA-folate. However, recently, another interesting preclinical study was performed to unfold the potential of [⁶⁸Ga]Ga-NOTA-folate for macrophage associated inflammation imaging.²⁷⁶

The cell cycle is an essential phenomenon that every cell undergoes for reproduction and function, which is disturbed in many cancer conditions. This has helped researchers look for potential biological targets that can facilitate the diagnosis and treatment of cancer. Consequently, cyclin-dependent kinase 4 and 6 (CDK4/6) have been identified as suitable targets due to their overexpression in various cancers, especially breast cancer.²⁷⁷ Recently, a novel tracer, i.e., [⁶⁸Ga]Ga-DOTA-palbociclib, was synthesized and preclinically evaluated for CDK4/6 positive tumors. The RCP obtained for [⁶⁸Ga]Ga-DOTA-palbociclib was >95%, and this compound was found to be stable in the in vitro and in vivo analysis. It also showed excellent pharmacokinetics, together with significant uptake in the tumor lesion with low muscle background uptake. This tracer can potentially identify suitable patients for CDK4/6 inhibitor-based treatment.²⁷⁸

A recent study for the early detection of hepatocellular carcinoma (HCC) using the [⁶⁸Ga]Ga-NOTA-G2 immunoPET imaging tracer targeting glypican 3 (GPC3), a proteoglycan, was performed by An et al. This study showed the superiority of the novel [⁶⁸Ga]Ga-NOTA-G2 over the traditional [¹⁸F]-FDG in delineating subcutaneous HCC lesions.²⁷⁹

Among the various overexpressed biomarkers, metastasis-associated lung adenocarcinoma transcript-1 (MALAT-1) has also been found to be overexpressed in many different cancer conditions such as breast cancer, gastric cancer, and HCC. As a potential target for diagnostic imaging, a novel tracer, i.e., [⁶⁸Ga]Ga-MALAT-1 ASO (antisense oligodeoxynucleotide), was developed to image malignant tumors with a high expression of MALAT-1. The study revealed excellent radiolabeling with >98% RCY and >99% RCP. In vitro analysis showed its specific binding to MHCC-LM3 cells, and significant tracer uptake (3.04% ± 0.11% ID per g) was noted in tumor-bearing mice in the biodistribution study. A similar finding was observed in microPET images, confirming the specific uptake of the tracer in the tumor-induced mouse models.²⁸⁰ This study showed promising results for this tracer. However, further optimization is needed given that the kidneys showed intense tracer uptake.

Further extending the role of molecular imaging, an interesting novel radiopharmaceutical has been developed i.e., ⁶⁸Ga-labeled “magnetic-near infrared persistent luminescent hybrid mesoporous nanoparticles”, to perform multimodal imaging together with guided chemotherapy and photodynamic therapy. The study showed the great potential of this tracer as a one-stop nanotheranostic tool.²⁸¹

Another novel tracer, i.e., [⁶⁸Ga]Ga-DOTA-ethylenediamine-phenylboronic acid ([⁶⁸Ga]Ga-DOTA-en-pba), was developed and evaluated preclinically for sialic acid overexpression in cancer cells. The authors performed in vitro studies on Mel-C and B16-F10 melanoma cells and found high specificity towards B16-F10 melanoma cells owing to sialic acid overexpression. Similar results were found in the ex vivo Mel-C and B16-F10 melanoma tumor model, confirming the specificity of the tracer for sialic acid overexpression.²⁸² However, to translate it into clinics, this tracer needs further evaluation.

Urokinase-type plasminogen activator receptors (uPARs), an established cancer biomarker, have become a key focus for cancer diagnosis and treatment. To target uPARs, which are overexpressed in several cancer conditions such as breast cancer, prostate cancer, and urinary bladder cancer, a novel peptide-based tracer, i.e., [⁶⁸Ga]Ga-NOTA-AE105, was developed, and currently is in a clinical phase.^283,284

Substance P (SP) has surfaced in response to the demand for a possible neuropeptide that can be used as a therapeutic carrier and diagnostic biomarker in inoperable cancer conditions such as GBM. It is a small undecapeptide belonging to the family of tachykinins.²⁸⁵ It is known to bind the transmembrane neurokinin type 1 receptors (NK-1R). The first clinical study using SP was in 2006.²⁸⁶ However, it has regained the attention from researchers owing to the emergence of suitable alpha emitters. Recently, [⁶⁸Ga]Ga-DOTA-[Thi⁸,Met(O₂)¹¹]-substance P ([⁶⁸Ga]Ga-DOTA-SP) has been clinically employed for the assessment of its biodistribution in GBM patients overexpressing NK-1R. PET/CT images allowed visualization of tracer distribution in the brain and body. Only 5% of the injected activity was found in the bladder.²⁸⁷ Hence, [⁶⁸Ga]Ga-DOTA-SP has emerged as an important diagnostic agent in the follow up of locoregional therapy of gliomas. Understanding the need for readily available tracers, Suthiram et al. demonstrated facile radiolabeling using a kit-like formulation of DOTA-[Thi⁸,Met(O₂)¹¹]-substance P.²⁸⁸

Gonadotrophin-releasing hormone (GnRH)-based analogues have been synthesized and radiolabeled with ⁶⁸Ga i.e., [⁶⁸Ga]Ga-DOTA-GnRH-I, to image reproductive system-associated cancers. The predominant subtypes of the GnRH receptor system expressed in different reproductive system tumors are GnRH receptor I (GnRHR-I) and GnRH receptor II (GnRHR-II). In 2008, Schottelius et al. showed that tracer uptake in GnRHR-positive OVCAR-3 xenografted nude mice was not significant. This study presented the challenges of the suitability of the tracer to target the GnRHR-system.²⁸⁹ Another study was reported in 2016 by Zoghi et al., in which they performed radiolabeling, characterization and preclinical evaluation of [⁶⁸Ga]Ga-triptorelin (TRP) for GnRHR. This tracer demonstrated significant uptake in GnRHR-positive 4T1 tumor-bearing mice between 30–120 min post injection. At 60 min, the tumor to blood and tumor to muscle ratios were found to be 28 and >50, respectively.²⁹⁰ This study presented the possibility of utilizing GnRHR peptide for diagnostic and therapeutic applications. The same group also radiolabeled a derivative of TRP with ¹⁷⁷Lu to evaluate it preclinically.²⁹¹ However, in recent times, no study has been published related to GnRHR-targeting ⁶⁸Ga-labeled peptides.

5.13.2. Other miscellaneous non-oncological applications. With the development of novel tracers, the role of nuclear medicine has also expanded towards non-oncological conditions. One of the serious ailments requiring early detection is fibrosis. Recently, two potential ⁶⁸Ga-labeled tracers, i.e., [⁶⁸Ga]Ga-NOTA-PEG2-c[CPGRVNleHGLHLGDDEGPC] ([⁶⁸Ga]Ga-NO2A-[Nle13]-Collagelin)³⁰¹ and [⁶⁸Ga]Ga-BOT5035, have been explored for imaging liver fibrosis (Table 11). Velikyan et al. synthesized a cyclic peptide, c[CPGRVNleHGLHLGDDEGPC] conjugated to 2-(4,7-bis(2-(tert-butoxy)-2-oxoethyl)-1,4,7-triazonan-1-yl) acetic acid, to perform the in vitro analysis of [⁶⁸Ga]Ga-NO2A-[Nle13]-Col, together with PET/CT imaging in liver fibrosis-induced mice. Radiolabeling of the NOTA-conjugated collagen analogue with ⁶⁸Ga resulted in a radiochemical yield of 48% ± 6% and radiochemical purity of 98% ± 2%. The in vitro binding assay showed higher uptake in diseased tissue than healthy tissue of the fibrotic mouse liver. The biodistribution study showed higher uptake in the organs of fibrosis-induced mice compared to healthy mice. No statistical difference was found in any non-target organ, including the liver, spleen, lung, and pancreas. Dynamic PET/CT imaging at 60 min post administration revealed faster blood clearance, renal excretion, and washout from most of the organs of the both healthy and fibrosis induced mice.

Table 11 Gallium-68-labeled radiopharmaceuticals for non-oncological application

Radiopharmaceutical	Structure	Application	Status
[^68Ga]Ga-NO2A-[Nle13]-Col		Liver fibrosis^251	Pre-clinical
[^68Ga]Ga-BOT5035		Liver fibrosis^252	Pre-clinical
[^68Ga]Ga-NEB		Lymphatic disorders, Chylous fistula^303–305	Clinical phase
[^68Ga]Ga-H2CHXdedpa		MPI^324	Pre-clinical phase
[^68Ga]Ga-EDTA		Renal imaging^261	Clinical phase
[^68Ga]Ga-DTPA		Renal imaging^325	Clinical phase
[^68Ga]Ga-NOTA		Renal imaging^262	Pre-clinical phase
[^68Ga]Ga-DOTA		Renal imaging^316	Clinical Phase
[^68Ga]Ga-IRDye800-tilmanocept		Renal imaging^317	Pre-clinical Phase
[^68Ga]Ga-HBED-CC-DiAsp		Renal imaging^318	Pre-clinical Phase
[^68Ga]Ga-GSA		Liver function^322	Clinical phase
[^68Ga]Ga-NOTA-insulin		Alzheimer's disease^323	Pre-clinical phase

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Velikyan et al. also demonstrated the fully automated GMP production of [⁶⁸Ga]Ga-BOT5035, which specifically targets platelet-derived growth factor receptor β (PDGFR-β) overexpressed in fibrotic pathologies. The RCY and RCP obtained in the GMP-compliant automated production were 43.7% ± 7.6% and 97.7% ± 0.4%, respectively. The biodistribution study revealed faster clearance of [⁶⁸Ga]Ga-BOT5035 in most organs, including blood. The dosimetry study demonstrated that the effective dose delivered from 75 MBq of [⁶⁸Ga]Ga-BOT5035 was 2.9 mSv in male rats and 3.4 mSv in female rats.³⁰²

Clinical studies have shown that ⁶⁸Ga-labeled 1,4,7-triazacyclononane-N,N′,N′′-triacetic acid (NOTA) conjugated with truncated Evan blue (NEB), i.e., [⁶⁸Ga]Ga-NEB, plays an essential role in the evaluation of lymphatic disorders.^303,304 This tracer showed uptake in the lymphatic channels and lymph nodes in all the patients. According to the comparison of [^99mTc]Tc-SC (sulfur colloid) lymphoscintigraphy and [⁶⁸Ga]Ga-NEB, it was found that more information with respect to the detection of leak sites and lesions was received in 5 out of 13 patients in the [⁶⁸Ga]Ga-NEB PET/CT images. Also, the acquisition time for [⁶⁸Ga]Ga-NEB was much shorter. Other recently explored non-oncological applications of [⁶⁸Ga]Ga-NEB include diagnosis of chylous fistula.³⁰⁵

Another tracer that has been evaluated for blood pool and lymph PET imaging is ⁶⁸Ga-labeled maleimide ([⁶⁸Ga]Ga-DM). The RCY and RCP obtained for this tracer was >90% and >95%, respectively. The partition coefficient determined for it was −3.15 ± 0.08. In vitro analysis showed the effective binding of [⁶⁸Ga]Ga-DM to albumin with a binding fraction of over 70%. MicroPET imaging showed the ability of this tracer to detect transient micro bleeding in rats.³⁰⁶

The advantages of PET imaging over conventional SPECT or SPECT/CT imaging have led to the substitution of ^99mTc with ⁶⁸Ga in pulmonary ventilation/perfusion (V/Q) imaging. Ventilation imaging using [⁶⁸Ga]Ga-carbon nanoparticles³⁰⁷ (Galligas) and perfusion imaging using [⁶⁸Ga]Ga-macroaggregated albumin ([⁶⁸Ga]Ga-MAA) were reported. In 2011, a pilot study was performed on patients with suspicion of pulmonary embolism (PE) by Hofman et al. The image quality obtained in PET/CT was superior to conventional SPECT in all the patients. The diagnosis made in PET/CT based on ⁶⁸Ga-labeled tracers was consistent with the conventional V/Q imaging based on ^99mTc tracers.³⁰⁸ The promising results of this study encouraged the further evaluation and optimization of Galligas and [⁶⁸Ga]Ga-MAA. Since then, various studies have been conducted to justify the potential of Galligas and [⁶⁸Ga]Ga-MAA PET/CT imaging in various oncological and non-oncological clinical conditions over conventional V/Q imaging.^309–312 A recent study revealed that MAA particles do not discriminate between different isotopes when forming bonds. This allows researchers to investigate the radiolabeling potential of MAA particles with other isotopes.

A clinical study was conducted using [⁶⁸Ga]Ga-NODAGA-ZOL to determine the correlation between tracer uptake in atherosclerosis plaques and cardiovascular risk profile patients. A positive correlation was observed between the tracer uptake of atherosclerosis plaques and atherogenic risk factors.³¹³

Various ⁶⁸Ga-labeled tracers for renal imaging have been identified, developed and under investigation. These tracers include [⁶⁸Ga]Ga-EDTA, [⁶⁸Ga]Ga-DTPA, [⁶⁸Ga]Ga-NOTA, [⁶⁸Ga]Ga-DOTA, [⁶⁸Ga]Ga-IRDye800-tilmanocept and [⁶⁸Ga]Ga-HBED-CC-DiAsp. Among them, [⁶⁸Ga]Ga-EDTA has shown superior results, and has also been evaluated in humans for glomerular filtration rate (GFR) assessment. According to the authors, the GFR obtained with [⁶⁸Ga]Ga-EDTA was consistent with the [⁵¹Cr]Cr-EDTA results.³¹⁴ [⁶⁸Ga]Ga-NOTA has also shown promising results in head-to-head comparison studies between [⁵¹Cr]Cr-EDTA and [⁶⁸Ga]Ga-NOTA for GFR estimation in mice.³¹⁵ However, the translation of [⁶⁸Ga]Ga-NOTA into humans is yet to be evaluated. Recently, David et al. performed dynamic renal imaging in humans using [⁶⁸Ga]Ga-DOTA and inferred that it can be used as a suitable alternative to conventional scintigraphy.³¹⁶

Quin et al. introduced the novel ⁶⁸Ga-labeled tilmanocept, which specifically binds to CD206 present in mesangial cells (a biomarker of diabetic nephropathy). This preclinical study showed the potential of [⁶⁸Ga]Ga-IRDye800-tilmanocept in assessing GFR non-invasively through mesangial cell uptake.³¹⁷ Another tracer, i.e., [⁶⁸Ga]Ga-HBED-CC-DiAsp, was recently studied preclinically. The introduction of two aspartic acids in the HBED-CC chelator increased its hydrophilicity, which led to rapid renal clearance. Hence, this tracer showed promising results in GFR estimation.³¹⁸

Similar to renal imaging, there are different ⁶⁸Ga-labeled tracers, i.e., [⁶⁸Ga]Ga-neolactosylated human serum albumin (LSA),³¹⁹ [⁶⁸Ga]Ga-NOTA-hexavalent lactoside (HL),³²⁰ and [⁶⁸Ga]Ga-galactosyl human serum albumin (GSA),^321,322 which have been studied for liver function imaging by targeting the asialoglycoprotein receptor expressed by hepatocytes. However, despite their promising preclinical and clinical results, they have not been translated into routine clinical studies because they showed no additional advantage over existing conventional techniques.

Taubel et al. developed a novel tracer i.e., [⁶⁸Ga]Ga-NOTA-insulin, and preclinically evaluated the role of insulin in Alzheimer's disease (AD). In vivo biodistribution and micro PET imaging demonstrated significant tracer uptake in different brain regions (the cortex, thalamus, brain stem, and cerebellum) of AD mice compared to normal mice.³²³

5.13.2.1 Gallium-68 radiopharmaceuticals for infection and inflammation imaging. Research involving ⁶⁸Ga-based imaging agents for infection and inflammation has been overshadowed by the oncological applications of ⁶⁸Ga-labeled tracers. However, a slight upsurge has been observed in the past few years towards developing new ⁶⁸Ga-labeled tracers for infection and inflammation imaging.

Generally, infection is described as the invasion and growth of pathogens or microbes inside the body. It is caused by bacteria, viruses, fungi, parasites, or prions, and its prognosis becomes poorer in cases of unclear or no diagnosis, which can lead to sepsis or death. Therefore, it becomes important to diagnose and discriminate the cause of infection early. Presently available diagnostic tools such as blood investigations (WBC counts and C-reactive protein) and radiological examinations (X-ray, MRI, CT, and ultrasound), being nonspecific and anatomical imaging, pose challenges in determining the type of infection. Hence, the treatment management suffers significantly. With the introduction of hybrid imaging modalities such as PET-CT, PET-MRI and SPECT-CT, the early diagnosis of infection has become feasible, aided by the introduction of many novel specific radiopharmaceuticals, as shown in Table 12.

Table 12 Gallium-68-labeled radiopharmaceuticals for infection imaging

Radiopharmaceutical	Structure	Clinical Indication	Status
[^68Ga]Ga-DOTA-ciprofloxacin		Staphylococcus aureus	Pre-clinical Phase^332
[^68Ga]Ga-CP-PA-SCN-BZ-DOTA		Staphylococcus aureus	Pre-clinical Phase^331
[^68Ga]Ga-CP-PA-SCN-BZ-NOTA		Staphylococcus aureus	Pre-clinical Phase^331
[^68Ga]Ga-ciprofloxacin-desferrichrome		Pseudomonas aeruginosa	Pre-clinical Phase^353
		Staphylococcus aureus
		and Klebsiella pneumoniae
[^68Ga]Ga-A8-K-DOTA		Staphylococcus aureus	Pre-clinical Phase^338
[^68Ga]Ga-A9-K-DOTA
[^68Ga]Ga-A11-GSGK-DOTA
[^68Ga]Ga-NOTA-UBI29-41		Staphylococcus aureus	Clinical Phase^354
[^68Ga]Ga-NOTA-UBI30-41
[^68Ga]Ga-NOTA-UBI31-38
[^68Ga]Ga-DOTA-TBIA101		E. coli	Pre-clinical Phase^341
[^68Ga]Ga-NODAGA-CDP1		E. coli, Staphylococcus aureus, and Mycobacterium tuberculosis	Pre-clinical Phase^344
[^68Ga]Ga-TAFC		Aspergillus fumigatus	Pre-clinical Phase^355,356
[^68Ga]Ga-FC
[^68Ga]Ga-FOXE
[^68Ga]Ga-DFO-B		P. aeruginosa and S. aureus	Pre-clinical Phase^357
[^68Ga]Ga-pyoverdine		P. aeruginosa	Pre-clinical Phase^358
[^68Ga]Ga-Ornibactin		Burkholderia cepacia	Pre-clinical Phase^359
[^68Ga]Ga-citrate		Osteomyelitis, diskitis, intra-abdominal infection, tuberculosis, interstitial nephritis	Clinical Phase^347,348

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Inflammation is a physiological phenomenon, which is necessary for healing of wounds, protection from foreign bodies, and maintaining tissue homeostasis. However, severe inflammation can cause pathological alterations and even become a disease itself. It has been seen that inflammation is associated with many serious clinical conditions, including tumor progression. Hence, its accurate diagnosis and corresponding effective treatment are needed. In recent times, with the emergence of novel specific radiopharmaceuticals, the molecular imaging and therapy field has shown some strides in the management of inflammatory diseases. The biggest challenge in molecular imaging is to employ radiopharmaceuticals that can differentiate between infection and inflammation.

The first gallium isotope used for infection and inflammation imaging was Ga-67 (SPECT) as [⁶⁷Ga]Ga-citrate, and it is still in clinical practice owing to its clinical applications in lung infections, sarcoidosis, tuberculosis, acute/chronic osteomyelitis, and retroperitoneal fibrosis.³²⁶ However, it has shortcomings, i.e., non-specific tumor accumulation, radiation burden to non-target organs, and availability. Hence, other gallium tracer options have been explored by the researchers.

5.13.2.1a Infection imaging. Specific accumulation of the ⁶⁸Ga-labeled tracer to the target, i.e., pathogens, is the prerequisite of infection imaging. Based on this hypothesis, various targeting agents have been developed, which are based on antibiotics, antimicrobial proteins and peptides, siderophores, and antibodies and their fragments.

The mechanism of action of antimicrobials enables them to specifically act on microbes.³²⁷ Utilizing this ‘infection-specific’ property, the following ⁶⁸Ga-labeled tracers have been developed.

Ciprofloxacin is the most commonly employed fluoroquinolone-based antibiotic drug to treat Gram-positive and Gram-negative bacterial infections.^328–330 Satapati et al. synthesized and radiolabeled ciprofloxacin analogues with ⁶⁸Ga to evaluate their efficacy in imaging bacterial infections in rats. The RCY obtained for both conjugates was >90%, together with in vitro stability for 4 h. Based on bacterial binding and biodistribution studies, they inferred that both antibiotic conjugates can differentiate between bacterial infection and inflammation.³³¹ Recently, a comparative study was conducted between ^99mTc and ⁶⁸Ga-labeled ciprofloxacin conjugates to study their physicochemical (stability and lipophilicity) and biological (binding study to Staphylococcus aureus and Pseudomonas aeruginosa) properties.³³²

Tracers based on antimicrobial proteins and peptides have shown superiority over antibiotic analogues because of their higher specificity for infection. The most promising results have been demonstrated by the antimicrobial peptide ubiquicidin (UBI) labeled with ⁶⁸Ga. Several UBI-derived antimicrobial peptides were investigated by Welling et al. and it was inferred that the peptide fragment (29–41) of UBI with the amino acid sequence Thr-Gly-Arg-Ala-Lys-Arg-Arg-Met-Gln-Tyr-Asn-Arg-Arg has potential to differentiate infection from inflammation.³³³ Since then, various UBI-based derivatives, namely NOTA-UBI29-41, NOTA-UBI30-41, and NOTA-UBI31-38, have been radiolabeled with ⁶⁸Ga to evaluate their efficacy in detecting infection.^334–337 Bhatt et al. performed a preliminary clinical evaluation of [⁶⁸Ga]Ga-NOTA-UBI31-38 in three patients with suspected infection and found that it gets accumulated at sites of infection. PET-CT images showed high target-to-background ratios in the order of 2.6 and 2.1 in patients with lung and knee infections, respectively. It was inferred from their study that [⁶⁸Ga]Ga-NOTA-UBI31-38 is specific for Staphylococcus aureus infection.³³⁴ Hence, for [⁶⁸Ga]Ga-NOTA-UBI31-38 to become a standard part of clinical practice in the case of Staphylococcus aureus infection, more clinical research is required.

Staphylococcus aureus is well known to form a biofilm, which often leads to serious life-threatening bacteraemia and sepsis. Various radiopharmaceuticals specific to bacteria in biofilms have been developed and studied to discriminate between infection and inflammation. Nielsen et al. evaluated ⁶⁸Ga-labeled phage-display selected peptides ([⁶⁸Ga]Ga-DOTA-A8-K, [⁶⁸Ga]Ga-DOTA-A9-K and [⁶⁸Ga]Ga-DOTA-A11-GSGK) for positron emission tomography imaging of Staphylococcus aureus biofilm-associated infections. Among them, [⁶⁸Ga]Ga-DOTA-A9-K outperformed and showed favourable characteristic features of being a novel bacteria-specific imaging tracer.³³⁸ However, Afzelius et al. conducted a study that refutes the previously cited findings. In a juvenile pig model, osteomyelitis bone lesions caused by Staphylococcus aureus did not exhibit any [⁶⁸Ga]Ga-DOTA-A9-K uptake.³³⁹

Depsipeptides are naturally occurring peptides containing more than one ester bond in their cyclic structure. The derivatives of depsipeptides exhibit different biological activities such as antiviral, antimicrobial, insecticidal, antitumor, tumor promotive, immunosuppressive, and anti-inflammatory.³⁴⁰ Based on the antimicrobial action of depsipeptides, Mokaleng et al. developed and radiolabeled a depsipeptide derivative, i.e., [⁶⁸Ga]Ga-DOTA-TBIA101, to study E. coli-infection in a BALB/c mouse model. The authors reported a low target-to-non-target uptake ratio and fast renal clearance in PET/CT images.³⁴¹ Another study was performed using [⁶⁸Ga]Ga-DOTA-TBIA101 by Ebenhan et al. to evaluate its diagnostic potential as an infection imaging agent in rabbits with various disease models, i.e., positive Staphylococcus aureus infection, sterile inflammation and Mycobacterium tuberculosis. Images showed high uptake at the sterile inflammation and Mycobacterium tuberculosis sites.³⁴²

Another tracer based on LL37, i.e., an antimicrobial peptide with a 37 amino acid chain, has been explored as a potential imaging agent for the diagnosis of infection. Primary studies revealed the selectivity of [⁶⁸Ga]Ga-CDP1 towards bacterial infection.^343,344 However, further studies must be carried out to determine the utility of [⁶⁸Ga]Ga-CDP1.

Besides these tracers, antimicrobial peptide fragment-based tracers, i.e., [⁶⁸Ga]Ga-GF-17 (peptide sequence-GFKRIVQRIKDFLRNLV-NH2) and [⁶⁸Ga]Ga-RAWVAWR-NH2, specific to E. coli and S. aureus, have also been evaluated in animals.³⁴⁵

Various novel siderophore-based tracers such as [⁶⁸Ga]Ga-desferri-triacetylfusarinine C (TAFC), [⁶⁸Ga]Ga-desferri-ferricrocin (FC), [⁶⁸Ga]Ga-ferrioxamine E (FOXE), [⁶⁸Ga]Ga-fusarinine C (FUS), [⁶⁸Ga]Ga-desferrioxamine B (DFO-B), [⁶⁸Ga]Ga-pyoverdine and [⁶⁸Ga]Ga-ornibactin have also been developed and evaluated in animals to determine their utility in different infection conditions. Peukert et al. also developed, optimized and radiolabeled artificial siderophores with ⁶⁸Ga for bacterial infection imaging. A total of 11 cyclen-based siderophores with different binding sites for iron and ⁶⁸Ga was developed. Based on the in vitro and in vivo analysis, [⁶⁸Ga]7 and [⁶⁸Ga]15 were found to be the most suitable for imaging. Both tracers showed significant uptake in mice infected with Escherichia coli.³⁴⁶

In 1971, [⁶⁷Ga]Ga-citrate was used as an infection and inflammation imaging agent. More recent advancements in PET imaging and the easy availability of ⁶⁸Ga via a generator have led to the initiation of [⁶⁸Ga]Ga-citrate into clinical studies. Among the listed ⁶⁸Ga-labeled tracers in Table 12, [⁶⁸Ga]Ga-citrate is the only tracer incorporated into clinical applications given that it exhibits high diagnostic accuracy of more than 90% for osteomyelitis and diskitis.^347,348 The diverse applications of [⁶⁸Ga]Ga-citrate in the field of molecular imaging include skeletal muscle infection and inflammation, abdominal infection, inflammatory bowel disease,³⁴⁹ tuberculosis,³⁵⁰ atherosclerosis,³⁵¹ and contagious disease imaging.

In 2011, Kumar et al. identified the detection ability of [⁶⁸Ga]Ga-apo-transferrin for Staphylococcus aureus infection induced in rat models. Specific uptake of [⁶⁸Ga]Ga-apo-transferrin in the lesions was observed, and no uptake of [⁶⁸Ga]GaCl₃ was observed in the lesions up to 2 h post injection.³⁵²

5.13.2.1b Inflammation imaging. In the last decade, numerous molecular imaging agents have been developed and experimented to diagnose inflammation. Various biomarkers such as immune cells (T- and B-lymphocytes, natural killer cells, monocytes, macrophages, neutrophils, eosinophils, and mast cells), their by-products (cytokines and chemokines), which are produced during the complex response to the inflammation, and receptors (folate and SSTR) have been targeted for imaging.

To target these biomarkers, various ⁶⁸Ga-labeled imaging agents have been investigated preclinically and clinically. Many of these tracers were reviewed extensively by Velikyan in 2018,³⁶⁰ and recently, a review article covering all the ⁶⁸Ga-labeled tracers for imaging inflammatory disorders was published.³⁶¹

Another interesting novel radiopharmaceutical, i.e., [⁶⁸Ga]Ga-DOTA-HsTX1[R14A], has been recently investigated preclinically in neuroinflammatory disease conditions overexpressing the voltage-gated potassium channel, i.e., Kv1.3. These channels have been found to be overexpressed in the post-mortem brain of patients with Alzheimer's and Parkinson's disease.^362,363 HsTX1[R14A] is an analogue of HsTX1, which is a C-terminally amidated peptide isolated from scorpion venom. In mice treated with lipopolysaccharide (LPS), PET/CT images of [⁶⁸Ga]Ga-DOTA-HsTX1[R14A] biodistribution revealed its uptake in the inflamed brain, cerebellum, and joints. In contrast, the mice given saline treatment showed no tracer uptake in their joints or brains. The tracer exhibited sensitivity to Kv1.3, which was elevated because of the LPS treatment. Thus, this study successfully demonstrated to potential of this tracer to diagnose disease conditions overexpressing Kv1.3.³⁶⁴

5.14. Gallium-68 radiopharmaceuticals for dual-target imaging

Prostate cancer is well known to express PSMA receptors on its surface. However, it also expresses a significant amount of GRP receptors in the early stages.³⁶⁵ Therefore, to enhance the detection of cancer cells expressing multiple receptors, radiolabeled peptides have been designed to target these receptors pertaining to increased tracer uptake (Table 13). [⁶⁸Ga]Ga-iPSMA-BN is a dual-targeting tracers, which was the first bispecific radioligand, synthesized and preclinically evaluated by Eder and group in 2014.³⁶⁶ After this study, several other studies were performed to evaluate [⁶⁸Ga]Ga-iPSMA-BN preclinically and optimize its pharmacokinetics for improved PET imaging of prostate cancer.^367,368 The promising preclinical results of [⁶⁸Ga]Ga-iPSMA-BN unfolded a new path of targeting PSMA and GRPR simultaneously with increased sensitivity for prostate cancer detection. Recently, a preliminary clinical study was conducted on four healthy volunteers and two biochemical recurrent prostate cancer patients by Bravo et al.³⁶⁹ to assess the biodistribution and radiation dosimetry of [⁶⁸Ga]Ga-iPSMA-BN. The PET/CT images revealed significant tracer uptake in the metastatic lesions (SUV_max 4.7) as well as in GRPR and PSMA expressing pancreas and salivary glands, respectively. The authors also found that the radiation absorbed dose received from [⁶⁸Ga]Ga-iPSMA-BN was 2.70 ± 0.05 mSv, which is nearly equivalent to the dose received from other routinely used ⁶⁸Ga-labeled tracers. The authors found that this tracer is promising for further clinical evaluation with no side effects.

Table 13 Gallium-68-labeled radiopharmaceuticals for dual-receptor targeting

Tracer	Structure	Status	Ref.
[^68Ga]Ga-iPSMA-BN		Clinical Phase	Eder et al., 2014^366
[^68Ga]Ga-NOTA-DUPA-RM26		Pre-clinical Phase	Mitran et al., 2019^370
[^68Ga]Ga-NOTA-BBN-RGD		Clinical Phase	Liu et al., 2009^377
[^68Ga]Ga-NOTA-3P-TATE-RGD		Clinical Phase	Zheng et al., 2019^371
[^68Ga]Ga-FAPI-RGD		Clinical Phase	Zang et al., 2022^373
[^68Ga]Ga-NOTA-RGD-GE11		Pre-clinical Phase	Yu et al., 2015^374
[^68Ga]Ga-NGR-RGD		Pre-clinical Phase	Gai et al., 2020^378

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Another bispecific heterodimer radioligand evaluated for prostate cancer imaging is [⁶⁸Ga]Ga-NOTA-DUPA-RM26. Its structure consists of both a PSMA-targeting moiety, i.e., DUPA (2-[3-(1,3-dicarboxy propyl)ureido]pentanedioic acid) and a GRPR-targeting moiety, i.e., RM26 (D-Phe-Gln-Trp-Ala-Val-Gly-His-Sta-Leu-NH₂ ([D-Phe6, Sta13, Leu14]-bombesin(6–14)). Labeling of the heterodimer with ⁶⁸Ga exhibited >98% RCY with high stability in the serum. The in vivo biodistribution revealed physiological tracer uptake in GRPR-expressing organs with minimal uptake in PSMA-expressing organs, and considerably higher tumor uptake in mice bearing PC3-PIP cells (at 1 h post injection 8% ± 2% ID per g). High tumor to non-tumor activity was observed at 3 h post injection. In vivo imaging showed a similar trend to that observed in the in vivo biodistribution study. This study demonstrated the excellent potential of [⁶⁸Ga]Ga-NOTA-DUPA-RM26 for targeting GRPR and PSMA-expressing prostate cancer.³⁷⁰ However, this tracer needs further evaluation before being translated into clinics.

In 2016, a clinical trial study was registered involving [⁶⁸Ga]Ga-NOTA-BBN-RGD as an imaging agent for prostate cancer patients (ClinicalTrials.gov NCT number: NCT02747290). The results of this study have yet to be published. Recently, a clinical trial was registered (ClinicalTrials.gov NCT number: NCT05549024) to evaluate a novel bispecific heterodimer radioligand, [⁶⁸Ga]Ga-RM26-RGD, as a potential imaging agent for GRPR- and α_vβ₃-positive tumors.

One more dual-targeting tracer, i.e., [⁶⁸Ga]Ga-NOTA-3P-TATE-RGD, has undergone clinical evaluation.^371,372 It outperformed the conventional [⁶⁸Ga]Ga-DOTA-TATE in detecting liver lesions and metastatic lesions.³⁷²

Another significant novel tracer, [⁶⁸Ga]Ga-FAPI-RGD, which targets both FAP and αvβ3, has been developed. Zang et al. synthesized this tracer using the quinolone-based FAPI-02 as one arm and cyclic RGDfK as the other arm, coupled to the NOTA chelator. The authors assessed the specificity, radiation dosimetry, in vivo pharmacological behaviour, and preclinical imaging of this tracer. The same team also carried out a pilot human trial with 6 patients to further translate it into clinics. The tracer demonstrated faster clearance from the urinary tract and prolonged tumor retention. The effective dose delivered by [⁶⁸Ga]Ga-FAPI-RGD was found to be 19.4 μSv per MBq. The PET/CT images revealed a higher target-to-background ratio, which further increased with time, resulting in good image quality for clinical interpretation. No significant difference was observed pertaining to SUV_max of the primary tumor and metastatic sites in 5 out of 6 patients. However, in one patient of renal carcinoma, high uptake of [⁶⁸Ga]Ga-FAPI-RGD was observed compared to [¹⁸F]FDG.³⁷³ A phase I/II clinical study has been registered with [⁶⁸Ga]Ga-FAPI-RGD involving various cancer patients (ClinicalTrials.gov NCT number: NCT05515783).

To image tumors that express α_vβ₃ and EGFR, Yu et al. successfully synthesized ⁶⁸Ga-labeled NOTA-RGD-GE11, a bispecific heterodimeric ligand.³⁷⁴In vitro study demonstrated the binding affinity of NOTA-RGD-GE11 towards both α_vβ₃ and EGFR. The in vivo biodistribution and PET imaging studies of [⁶⁸Ga]Ga-NOTA-RGD-GE11 showed the higher tumor uptake and tumor to muscle ratio, 3.446% ± 0.548% ID per g and 4.397% ± 0.972%, respectively, at 2 h post injection. The results of the bispecific heterodimer ligand were superior to that of the [⁶⁸Ga]Ga-NOTA-RGD and [⁶⁸Ga]Ga-NOTA-GE11 monomeric ligands.³⁷⁵ However, the tracer has not yet been translated into human imaging.

Long et al. preclinically assessed a bispecific heterodimer radioligand, [⁶⁸Ga]Ga-NGR-RGD, in ovarian cancer xenografts with the aim of targeting CD13 and αvβ3. The results showed that in comparison to [¹⁸F]FDG, there was a high tumor-to-background ratio, minimal inflammatory uptake, and a high tumor targeting efficacy. Thus, this tracer presents potential for further evaluation.³⁷⁶

6. Conclusion

Among the various available PET radioisotopes, ⁶⁸Ga has shown the greatest impact after ¹⁸F in gaining worldwide acknowledgement and acceptance as a radionuclide of choice in the field of molecular imaging. The underlying reason for this success is the physical and chemical properties of ⁶⁸Ga, its easy availability via a ⁶⁸Ge/⁶⁸Ga generator, the introduction of various acyclic and cyclic chelators facilitating easy radiolabeling with a wide range of biomolecules, and its short synthesis time with easy purification steps. The globally increased demand for ⁶⁸Ga has also been addressed via its alternative bulk production using a medical cyclotron exploiting the economical liquid target technique. Thus, in the last decade, many ⁶⁸Ga-based radiopharmaceuticals have been translated to clinical practice and emerged as potential diagnostic imaging agents. It also forms a tremendous theranostic pair with ¹⁷⁷Lu, which further increases the role of ⁶⁸Ga in advancing personalised medicine with better accuracy.

Author contributions

Karan S. Tanwar wrote and edited the manuscript. Mukesh K. Pandey contributed to the writing, editing, and proofreading of the manuscript.

Conflicts of interest

There are no conflicts to declare.

Data availability

The entire data generated and analyzed during this study are included in the main manuscript.

Acknowledgements

The authors thank and acknowledge the Union for International Cancer Control (UICC) for awarding a technical fellowship to Karan S. Tanwar. We are also grateful to the Department of Radiology, Mayo Clinic, Rochester, for hosting Karan S. Tanwar. The authors would also like to thank Drs Andy Rivera and Surendra Gundam Reddy for drawing some of the chemical structures and Dr. Sonia Watson for additional editing.

Notes and references

1. E. O. Lawrence and M. S. Livingston, Phys. Rev., 1932, 40, 19–35.
2. C. Morgat, E. Hindié, A. K. Mishra, M. Allard and P. Fernandez, Cancer Biother. Radiopharm., 2013, 28, 85–97.
3. L. R. Schaer, H. O. Anger and A. Gottschalk, JAMA, 1966, 198, 811–813.
4. I. Velikyan, Theranostics, 2013, 4, 47–80.
5. Ion Exchange Resins—Advances in Research and Application, ScholarlyEditions, 2013.
6. S. Huang, S. Ong, D. McKenzie, A. Mirabelli, D. C. Chen, T. Chengodu, D. G. Murphy, M. S. Hofman, N. Lawrentschuk and M. Perera, Prostate Cancer Prostatic Dis., 2024, 27, 654–664.
7. F. Rösch, Appl. Radiat. Isot., 2013, 76, 24–30.
8. G. I. Gleason, Int. J. Appl. Radiat. Isot., 1960, 8, 90–94.
9. D. M. Prince, Investigation into various aspects of radiolabelling somatostatin peptide derivatives with Ga-68 eluted from a SnO2-based Ge-68/Ga-68 generator, PhD thesis, Stellenbosch University, 2018.
10. E. Oehlke, V. S. Le, N. A. Lengkeek, P. A. Pellegrini, T. W. Jackson, I. Greguric and R. Weiner, Appl. Radiat. Isot., 2013, 82, 232–238.
11. I. Velikyan, Molecules, 2015, 20, 12913–12943.
12. J. W. Engle, V. Lopez-Rodriguez, R. E. Gaspar-Carcamo, H. F. Valdovinos, M. Valle-Gonzalez, F. Trejo-Ballado, G. W. Severin, T. E. Barnhart, R. J. Nickles and M. A. Avila-Rodriguez, Appl. Radiat. Isot., 2012, 70, 1792–1796.
13. M. K. Pandey, J. F. Byrne, H. Jiang, A. B. Packard and T. R. DeGrado, Am. J. Nucl. Med. Mol. Imaging, 2014, 4, 303–310.
14. A. Vogg, R. Lang, P. Meier-Böke, W. Scheel, S. N. Reske and B. Neumaier, in Advances in Nuclear and Radiochemistry, ed. S. M. Quaim and H. H. Coenen, Forschungszentrum Jülich, Germany, 2004.
15. M. Jensen and J. Clark, 13th Int. Workshop Targetry Target Chem. Proc., 2011, pp. 288–292.
16. M. K. Pandey, J. F. Byrne, K. N. Schlasner, N. R. Schmit and T. R. DeGrado, Nucl. Med. Biol., 2019, 74–75, 49–55.
17. F. Alves, V. H. P. Alves, S. J. C. Do Carmo, A. C. B. Neves, M. Silva and A. J. Abrunhosa, Mod. Phys. Lett. A, 2017, 32, 1740013.
18. G. Dias, C. Ramogida, C. Hoehr, K.-S. Lin, P. Schaffer and F. Benard, J. Nucl. Med., 2016, 57, 381.
19. E. Oehlke, C. Hoehr, X. Hou, V. Hanemaayer, S. Zeisler, M. J. Adam, T. J. Ruth, A. Celler, K. Buckley, F. Benard and P. Schaffer, Nucl. Med. Biol., 2015, 42, 842–849.
20. T. J. Wadas, E. H. Wong, G. R. Weisman and C. J. Anderson, Chem. Rev., 2010, 110, 2858–2902.
21. N. Lepareur, Front. Med., 2022, 9, 812050.
22. S. Kulprathipanja and D. J. Hnatowich, Int. J. Appl. Radiat. Isot., 1977, 28, 229–233.
23. J. le Roux, J. Kleynhans and S. Rubow, EJNMMI Radiopharm. Chem., 2021, 6, 15.
24. M. Eder, O. Neels, M. Müller, U. Bauder-Wüst, Y. Remde, M. Schäfer, U. Hennrich, M. Eisenhut, A. Afshar-Oromieh, U. Haberkorn and K. Kopka, Pharmaceuticals, 2014, 7, 779–796.
25. M. I. Tsionou, C. E. Knapp, C. A. Foley, C. R. Munteanu, A. Cakebread, C. Imberti, T. R. Eykyn, J. D. Young, B. M. Paterson, P. J. Blower and M. T. Ma, RSC Adv., 2017, 7, 49586–49599.
26. M. A. Joaqui-Joaqui, M. K. Pandey, A. Bansal, M. V. R. Raju, F. Armstrong-Pavlik, A. Dundar, H. L. Wong, T. R. DeGrado and V. C. Pierre, Inorg. Chem., 2020, 59, 12025–12038.
27. P. R. W. J. Davey and B. M. Paterson, Molecules, 2023, 28, 203.
28. X. Qin, H. Jiang, Y. Liu, H. Zhang and M. Tian, Eur. J. Nucl. Med. Mol. Imaging, 2022, 49, 1345–1359.
29. M. Bauwens, M. De Saint-Hubert, E. Devos, N. Deckers, C. Reutelingsperger, L. Mortelmans, U. Himmelreich, F. M. Mottaghy and A. Verbruggen, Nucl. Med. Biol., 2011, 38, 381–392.
30. Q. Chen, X. H.-F. Zhang and J. Massagué, Cancer Cell, 2011, 20, 538–549.
31. J. Huang, J. Zhang, H. Li, Z. Lu, W. Shan, I. Mercado-Uribe and J. Liu, Am. J. Transl. Res., 2013, 5, 336–346.
32. V. W. T. Cheng, N. de Pennington, R. Zakaria, J. R. Larkin, S. Serres, M. Sarkar, M. A. Kirkman, C. Bristow, P. Croal, P. Plaha, L. Campo, M. A. Chappell, S. Lord, M. D. Jenkinson, M. R. Middleton and N. R. Sibson, Clin. Cancer Res., 2022, 28, 2385–2396.
33. X. Zhang, C. Liu, F. Hu, Y. Zhang, J. Wang, Y. Gao, Y. Jiang, Y. Zhang and X. Lan, Mol. Pharmaceutics, 2018, 15, 609–618.
34. D. Zhang, M. Gao, Q. Jin, Y. Ni, H. Li, C. Jiang and J. Zhang, Mol. Imaging Biol., 2022, 24, 612–629.
35. A. Rix, N. I. Drude, A. Mrugalla, F. Baskaya, K. Y. Pak, B. Gray, H.-J. Kaiser, R. H. Tolba, E. Fiegle, W. Lederle, F. M. Mottaghy and F. Kiessling, Mol. Imaging Biol., 2020, 22, 623–633.
36. I. H. Shon, D. Kumar, M. Schreuder, J. Guille, J. Doan, C. Sathikumar, K. Van, A. Chicco and P. J. Hogg, Curr. Radiopharm., 2022, 15, 184–193.
37. I. Ho Shon, T. Hennessy, J. Guille, M. P. Gotsbacher, A. J. Lay, B. McBride, R. Codd and P. J. Hogg, Eur. J. Nucl. Med. Mol. Imaging, 2022, 49, 4037–4047.
38. V. G. Ostapchenko, J. Snir, M. Suchy, J. Fan, M. R. Cobb, B. A. Chronik, M. Kovacs, V. F. Prado, R. H. E. Hudson, S. H. Pasternak, M. A. M. Prado and R. Bartha, Contrast Media Mol. Imaging, 2019, 2019, 6403274.
39. F. Bulat, F. Hesse, B. Attili, C. Solanki, I. A. Mendichovszky, F. Aigbirhio, F. J. Leeper, K. M. Brindle and A. A. Neves, Cancers, 2023, 15, 1564.
40. A. Schonbrunn and H. Tashjian, J. Biol. Chem., 1978, 253, 6473–6483.
41. D. Hoyer, G. I. Bell, M. Berelowitz, J. Epelbaum, W. Feniuk, P. P. A. Humphrey, A.-M. O’Carroll, Y. C. Patel, A. Schonbrunn, J. E. Taylor and T. Reisine, Trends Pharmacol. Sci., 1995, 16, 86–88.
42. J. C. Reubi, L. Kvols, E. Krenning and S. W. J. Lamberts, Metabolism, 1990, 39, 78–81.
43. J. C. Reubi, J. Laissue, E. Krenning and S. W. J. Lamberts, J. Steroid Biochem. Mol. Biol., 1992, 43, 27–35.
44. M. Volante, R. Rosas, E. Allìa, R. Granata, A. Baragli, G. Muccioli and M. Papotti, Mol. Cell. Endocrinol., 2008, 286, 219–229.
45. M. Volante, F. Bozzalla-Cassione and M. Papotti, Endocr. Pathol., 2004, 15, 275–291.
46. J. Reubi, B. Waser, J.-C. Schaer and J. A. Laissue, Eur. J. Nucl. Med., 2001, 28, 836–846.
47. M. Henze, J. Schuhmacher, P. Hipp, J. Kowalski, D. W. Becker, J. Doll, H. R. Mäcke, M. Hofmann, J. Debus and U. Haberkorn, J. Nucl. Med., 2001, 42, 1053–1056.
48. M. Hofmann, H. Maecke, A. Börner, E. Weckesser, P. Schöffski, M. Oei, J. Schumacher, M. Henze, A. Heppeler, G. Meyer and W. Knapp, Eur. J. Nucl. Med., 2001, 28, 1751–1757.
49. J. C. Reubi, J.-C. Schär, B. Waser, S. Wenger, A. Heppeler, J. S. Schmitt and H. R. Mäcke, Eur. J. Nucl. Med., 2000, 27, 273–282.
50. D. Wild, H. R. Mäcke, B. Waser, J. C. Reubi, M. Ginj, H. Rasch, J. Müller-Brand and M. Hofmann, Eur. J. Nucl. Med. Mol. Imaging, 2005, 32, 724.
51. D. Wild, J. B. Bomanji, P. Benkert, H. Maecke, P. J. Ell, J. C. Reubi and M. E. Caplin, J. Nucl. Med., 2013, 54, 364–372.
52. L. Kabasakal, E. Demirci, M. Ocak, C. Decristoforo, A. Araman, Y. Ozsoy, I. Uslu and B. Kanmaz, Eur. J. Nucl. Med. Mol. Imaging, 2012, 39, 1271–1277.
53. F. Liu, T. Liu, X. Xu, X. Guo, N. Li, C. Xiong, C. Li, H. Zhu and Z. Yang, Mol. Pharmaceutics, 2018, 15, 619–628.
54. M. Fani, F. Braun, A. Mann, A. Kliewer, J. Kaufmann, W. Weber, H. Bouterfa, S. Schulz and H. Maecke, J. Nucl. Med., 2012, 53, 1686.
55. R. Mansi, K. Abid, G. P. Nicolas, L. Del Pozzo, E. Grouzmann and M. Fani, EJNMMI Res., 2020, 10, 90.
56. F. Liu, H. Zhu, C. Li, X. Lin, C. Xiong, C. Li and Z. Yang, J. Radioanal. Nucl. Chem., 2016, 307, 1069–1075.
57. M. Ginj, H. Zhang, B. Waser, R. Cescato, D. Wild, X. Wang, J. Erchegyi, J. Rivier, H. R. Mäcke and J. C. Reubi, Proc. Natl. Acad. Sci. U. S. A., 2006, 103, 16436–16441.
58. M. Fani, F. Braun, B. Waser, K. Beetschen, R. Cescato, J. Erchegyi, J. E. Rivier, W. A. Weber, H. R. Maecke and J. C. Reubi, J. Nucl. Med., 2012, 53, 1481–1489.
59. M. Fani, L. D. Pozzo, K. Abiraj, R. Mansi, M. L. Tamma, R. Cescato, B. Waser, W. A. Weber, J. C. Reubi and H. R. Maecke, J. Nucl. Med., 2011, 52, 1110–1118.
60. W. Zhu, Y. Cheng, N. Ding and L. Huo, Clin. Nucl. Med., 2020, 45, 902.
61. J. Zhang, H. R. Kulkarni, A. Singh and R. P. Baum, Clin. Nucl. Med., 2020, 45, e165.
62. J. Zhang, A. Singh, H. R. Kulkarni, C. Schuchardt, D. Müller, H.-J. Wester, T. Maina, F. Rösch, N. P. van der Meulen, C. Müller, H. Mäcke and R. P. Baum, Semin. Nucl. Med., 2019, 49, 422–437.
63. W. Zhu, Y. Cheng, X. Wang, S. Yao, C. Bai, H. Zhao, R. Jia, J. Xu and L. Huo, J. Nucl. Med., 2020, 61, 897–903.
64. P. Rawla, World J. Oncol., 2019, 10, 63–89.
65. A. Afshar-Oromieh, J. W. Babich, C. Kratochwil, F. L. Giesel, M. Eisenhut, K. Kopka and U. Haberkorn, J. Nucl. Med., 2016, 57, 79S–89S.
66. R. S. Israeli, C. T. Powell, J. G. Corr, W. R. Fair and W. D. Heston, Cancer Res., 1994, 54, 1807–1811.
67. A. Afshar-Oromieh, A. Malcher, M. Eder, M. Eisenhut, H. G. Linhart, B. A. Hadaschik, T. Holland-Letz, F. L. Giesel, C. Kratochwil, S. Haufe, U. Haberkorn and C. M. Zechmann, Eur. J. Nucl. Med. Mol. Imaging, 2013, 40, 486–495.
68. A. Afshar-Oromieh, C. M. Zechmann, A. Malcher, M. Eder, M. Eisenhut, H. G. Linhart, T. Holland-Letz, B. A. Hadaschik, F. L. Giesel, J. Debus and U. Haberkorn, Eur. J. Nucl. Med. Mol. Imaging, 2014, 41, 11–20.
69. J. J. Morigi, P. D. Stricker, P. J. van Leeuwen, R. Tang, B. Ho, Q. Nguyen, G. Hruby, G. Fogarty, R. Jagavkar, A. Kneebone, A. Hickey, S. Fanti, L. Tarlinton and L. Emmett, J. Nucl. Med., 2015, 56, 1185–1190.
70. C. Bluemel, M. Krebs, B. Polat, F. Linke, M. Eiber, S. Samnick, C. Lapa, M. Lassmann, H. Riedmiller, J. Czernin, D. Rubello, T. Bley, S. Kropf, H.-J. Wester, A. K. Buck and K. Herrmann, Clin. Nucl. Med., 2016, 41, 515–521.
71. D. Pfister, D. Porres, A. Heidenreich, I. Heidegger, R. Knuechel, F. Steib, F. F. Behrendt and F. A. Verburg, Eur. J. Nucl. Med. Mol. Imaging, 2016, 43, 1410–1417.
72. J. Schwenck, H. Rempp, G. Reischl, S. Kruck, A. Stenzl, K. Nikolaou, C. Pfannenberg and C. la Fougère, Eur. J. Nucl. Med. Mol. Imaging, 2017, 44, 92–101.
73. M. Benešová, M. Schäfer, U. Bauder-Wüst, A. Afshar-Oromieh, C. Kratochwil, W. Mier, U. Haberkorn, K. Kopka and M. Eder, J. Nucl. Med., 2015, 56, 914–920.
74. Z. Zha, K. Ploessl, S. R. Choi, Z. Wu, L. Zhu and H. F. Kung, Nucl. Med. Biol., 2018, 59, 36–47.
75. G. Wang, H. Hong, J. Zang, Q. Liu, Y. Jiang, X. Fan, Z. Zhu, L. Zhu and H. F. Kung, Eur. J. Nucl. Med. Mol. Imaging, 2022, 49, 1052–1062.
76. M. Suh, H.-J. Im, H. G. Ryoo, K. W. Kang, J. M. Jeong, S. Prakash, S. Ballal, M. P. Yadav, C. Bal, C. W. Jeong, C. Kwak and G. J. Cheon, J. Nucl. Med., 2021, 62, 1457–1460.
77. M. Weineisen, M. Schottelius, J. Simecek, R. P. Baum, A. Yildiz, S. Beykan, H. R. Kulkarni, M. Lassmann, I. Klette, M. Eiber, M. Schwaiger and H.-J. Wester, J. Nucl. Med., 2015, 56, 1169–1176.
78. A. Kumar, T. Mastren, B. Wang, J.-T. Hsieh, G. Hao and X. Sun, Bioconjugate Chem., 2016, 27, 1681–1689.
79. M. Eder, M. Schäfer, U. Bauder-Wüst, W.-E. Hull, C. Wängler, W. Mier, U. Haberkorn and M. Eisenhut, Bioconjugate Chem., 2012, 23, 688–697.
80. S.-H. Moon, M. K. Hong, Y. J. Kim, Y.-S. Lee, D. S. Lee, J.-K. Chung and J. M. Jeong, Bioorg. Med. Chem., 2018, 26, 2501–2507.
81. T. Liu, C. Han, S. Wang, P. Fang, Z. Ma, L. Xu and R. Yin, J. Hematol. Oncol., 2019, 12, 86.
82. K. Jansen, L. Heirbaut, R. Verkerk, J. D. Cheng, J. Joossens, P. Cos, L. Maes, A.-M. Lambeir, I. De Meester, K. Augustyns and P. Van Der Veken, J. Med. Chem., 2014, 57, 3053–3074.
83. K. Narra, S. R. Mullins, H.-O. Lee, B. Strzemkowski-Brun, K. Magalong, V. J. Christiansen, P. A. McKee, B. Egleston, S. J. Cohen, L. M. Weiner, N. J. Meropol and J. D. Cheng, Cancer Biol. Ther., 2007, 6, 1691–1699.
84. A. Loktev, T. Lindner, E.-M. Burger, A. Altmann, F. Giesel, C. Kratochwil, J. Debus, F. Marmé, D. Jäger, W. Mier and U. Haberkorn, J. Nucl. Med., 2019, 60, 1421–1429.
85. A. Loktev, T. Lindner, W. Mier, J. Debus, A. Altmann, D. Jäger, F. Giesel, C. Kratochwil, P. Barthe, C. Roumestand and U. Haberkorn, J. Nucl. Med., 2018, 59, 1423–1429.
86. T. Lindner, A. Loktev, A. Altmann, F. Giesel, C. Kratochwil, J. Debus, D. Jäger, W. Mier and U. Haberkorn, J. Nucl. Med., 2018, 59, 1415–1422.
87. J. Lau, E. Rousseau, D. Kwon, K.-S. Lin, F. Bénard and X. Chen, Cancers, 2020, 12, 1312.
88. F. L. Giesel, C. Kratochwil, T. Lindner, M. M. Marschalek, A. Loktev, W. Lehnert, J. Debus, D. Jäger, P. Flechsig, A. Altmann, W. Mier and U. Haberkorn, J. Nucl. Med., 2019, 60, 386–392.
89. C. Kratochwil, P. Flechsig, T. Lindner, L. Abderrahim, A. Altmann, W. Mier, S. Adeberg, H. Rathke, M. Röhrich, H. Winter, P. K. Plinkert, F. Marme, M. Lang, H.-U. Kauczor, D. Jäger, J. Debus, U. Haberkorn and F. L. Giesel, J. Nucl. Med., 2019, 60, 801–805.
90. A. Loktev, T. Lindner, E.-M. Burger, A. Altmann, F. Giesel, C. Kratochwil, J. Debus, F. Marmé, D. Jäger, W. Mier and U. Haberkorn, J. Nucl. Med., 2019, 60, 1421–1429.
91. S. Ballal, M. P. Yadav, E. S. Moon, V. S. Kramer, F. Roesch, S. Kumari, M. Tripathi, S. T. ArunRaj, S. Sarswat and C. Bal, Eur. J. Nucl. Med. Mol. Imaging, 2021, 48, 1915–1931.
92. L. Zhao, B. Niu, J. Fang, Y. Pang, S. Li, C. Xie, L. Sun, X. Zhang, Z. Guo, Q. Lin and H. Chen, J. Nucl. Med., 2022, 63, 862–868.
93. Z. T. Rosenkrans, C. F. Massey, K. Bernau, C. A. Ferreira, J. J. Jeffery, J. J. Schulte, M. Moore, F. Valla, J. M. Batterton, C. R. Drake, A. B. McMillan, N. Sandbo, A. Pirasteh and R. Hernandez, Eur. J. Nucl. Med. Mol. Imaging, 2022, 49, 3705–3716.
94. Y. Luo, Q. Pan, Z. Zhou, M. Li, Y. Wei, X. Jiang, H. Yang and F. Li, Radiology, 2023, 307, e222052.
95. D. Zboralski, A. Hoehne, A. Bredenbeck, A. Schumann, M. Nguyen, E. Schneider, J. Ungewiss, M. Paschke, C. Haase, J. L. von Hacht, T. Kwan, K. K. Lin, J. Lenore, T. C. Harding, J. Xiao, A. D. Simmons, A.-M. Mohan, N. Beindorff, U. Reineke, C. Smerling and F. Osterkamp, Eur. J. Nucl. Med. Mol. Imaging, 2022, 49, 3651–3667.
96. K. R. Chandekar, A. Prashanth, S. Vinjamuri and R. Kumar, Diagnostics, 2023, 13, 2018.
97. Z. Varasteh, S. Mohanta, S. Robu, M. Braeuer, Y. Li, N. Omidvari, G. Topping, T. Sun, S. G. Nekolla, A. Richter, C. Weber, A. Habenicht, U. A. Haberkorn and W. A. Weber, J. Nucl. Med., 2019, 60, 1743–1749.
98. L. B. N. Langer, A. Hess, Z. Korkmaz, J. Tillmanns, L. M. Reffert, J. P. Bankstahl, F. M. Bengel, J. T. Thackeray and T. L. Ross, Theranostics, 2021, 11, 7755–7766.
99. F. L. Giesel, S. Adeberg, M. Syed, T. Lindner, L. D. Jiménez-Franco, E. Mavriopoulou, F. Staudinger, E. Tonndorf-Martini, S. Regnery, S. Rieken, R. El Shafie, M. Röhrich, P. Flechsig, A. Kluge, A. Altmann, J. Debus, U. Haberkorn and C. Kratochwil, J. Nucl. Med., 2021, 62, 201–207.
100. F. M. Glatting, J. Hoppner, D. P. Liew, A. van Genabith, A.-M. Spektor, L. Steinbach, A. Hubert, C. Kratochwil, F. L. Giesel, K. Dendl, H. Rathke, H.-U. Kauczor, P. E. Huber, U. Haberkorn and M. Röhrich, J. Nucl. Med., 2022, 63, 1844–1851.
101. E. S. Moon, Y. V. Rymenant, S. Battan, J. D. Loose and A. Bracke, Molecules, 2021, 12, 3482.
102. D. J. Riese and D. F. Stern, BioEssays, 1998, 20, 41–48.
103. J. Capala and K. Bouchelouche, Curr. Opin. Oncol., 2010, 22, 559–566.
104. D. L. Nielsen, I. Kümler, J. A. E. Palshof and M. Andersson, The Breast, 2013, 22, 1–12.
105. V. Tolmachev, I. Velikyan, M. Sandström and A. Orlova, Eur. J. Nucl. Med. Mol. Imaging, 2010, 37, 1356–1367.
106. H. Miao, Y. Sun, Y. Jin, X. Hu, S. Song and J. Zhang, Front. Oncol., 2022, 12, 894767.
107. S. K. Suman, A. Mukherjee, U. Pandey, A. Chakraborty, S. Rakshit, M. Tawate and H. D. Sarma, Cancer Biother. Radiopharm., 2023, 38, 38–50.
108. S. B. M. Gaykema, C. P. Schröder, J. Vitfell-Rasmussen, S. Chua, T. H. Oude Munnink, A. H. Brouwers, A. H. H. Bongaerts, M. Akimov, C. Fernandez-Ibarra, M. N. Lub-de Hooge, E. G. E. de Vries, C. Swanton and U. Banerji, Clin. Cancer Res., 2014, 20, 3945–3954.
109. K. Tamura, H. Kurihara, K. Yonemori, H. Tsuda, J. Suzuki, Y. Kono, N. Honda, M. Kodaira, H. Yamamoto, M. Yunokawa, C. Shimizu, K. Hasegawa, Y. Kanayama, S. Nozaki, T. Kinoshita, Y. Wada, S. Tazawa, K. Takahashi, Y. Watanabe and Y. Fujiwara, J. Nucl. Med., 2013, 54, 1869–1875.
110. M. Keyaerts, C. Xavier, J. Heemskerk, N. Devoogdt, H. Everaert, C. Ackaert, M. Vanhoeij, F. P. Duhoux, T. Gevaert, P. Simon, D. Schallier, C. Fontaine, I. Vaneycken, C. Vanhove, J. De Greve, J. Lamote, V. Caveliers and T. Lahoutte, J. Nucl. Med., 2016, 57, 27–33.
111. Universitair Ziekenhuis Brussel, Quantification of 68-GaNOTA-Anti-HER2 VHH1 Uptake in Metastasis of Breast Carcinoma Patients and Assessment of Repeatability (VUBAR) – Pilot Study, clinicaltrials.gov, 2023.
112. V. Tolmachev, I. Velikyan, M. Sandström and A. Orlova, Eur. J. Nucl. Med. Mol. Imaging, 2010, 37, 1356–1367.
113. J. Sörensen, I. Velikyan, D. Sandberg, A. Wennborg, J. Feldwisch, V. Tolmachev, A. Orlova, M. Sandström, M. Lubberink, H. Olofsson, J. Carlsson and H. Lindman, Theranostics, 2016, 6, 262–271.
114. Y. Xu, L. Wang, D. Pan, C. Yu, B. Mi, Q. Huang, J. Sheng, J. Yan, X. Wang, R. Yang and M. Yang, Br. J. Radiol., 2019, 92, 20190425.
115. H. Miao, Y. Sun, Y. Jin, X. Hu, S. Song and J. Zhang, Front. Oncol., 2022, 12, 894767.
116. J. Garousi, S. Lindbo, J. Nilvebrant, M. Åstrand, J. Buijs, M. Sandström, H. Honarvar, A. Orlova, V. Tolmachev and S. Hober, Cancer Res., 2015, 75, 4364–4371.
117. B. M. Larimer, N. Phelan, E. Wehrenberg-Klee and U. Mahmood, Mol. Imaging Biol., 2018, 20, 300–308.
118. S. S. Rinne, C. Dahlsson Leitao, J. Gentry, B. Mitran, A. Abouzayed, V. Tolmachev, S. Ståhl, J. Löfblom and A. Orlova, Sci. Rep., 2019, 9, 17710.
119. S. S. Rinne, C. D. Leitao, A. Abouzayed, A. Vorobyeva, V. Tolmachev, S. Ståhl, J. Löfblom and A. Orlova, Cancers, 2021, 13, 4791.
120. Z. Yu, H. J. K. Ananias, G. Carlucci, H. D. Hoving, W. Helfrich, R. A. J. O. Dierckx, F. Wang, I. J. de Jong and P. H. Elsinga, Curr. Pharm. Des., 2013, 19, 3329–3341.
121. S. J. Mather, B. A. Nock, T. Maina, V. Gibson, D. Ellison, I. Murray, R. Sobnack, S. Colebrook, S. Wan, G. Halberrt, T. Szysko, T. Powles and N. Avril, Mol. Imaging Biol., 2014, 16, 888–895.
122. C. Van De Wiele, F. Dumont, R. Vanden Broecke, W. Oosterlinck, V. Cocquyt, R. Serreyn, S. Peers, J. Thornback, G. Slegers and R. A. Dierckx, Eur. J. Nucl. Med., 2000, 27, 1694–1699.
123. A. Prignon, V. Nataf, C. Provost, A. Cagnolini, F. Montravers, A. Gruaz-Guyon, L. Lantry, J. Talbot and A. Nunn, Nucl. Med. Biol., 2015, 42, 92–98.
124. R. Cescato, T. Maina, B. Nock, A. Nikolopoulou, D. Charalambidis, V. Piccand and J. C. Reubi, J. Nucl. Med., 2008, 49, 318–326.
125. R. Mansi, X. Wang, F. Forrer, S. Kneifel, M.-L. Tamma, B. Waser, R. Cescato, J. C. Reubi and H. R. Maecke, Clin. Cancer Res., 2009, 15, 5240–5249.
126. A. Roivainen, E. Kähkönen, P. Luoto, S. Borkowski, B. Hofmann, I. Jambor, K. Lehtiö, T. Rantala, A. Rottmann, H. Sipilä, R. Sparks, S. Suilamo, T. Tolvanen, R. Valencia and H. Minn, J. Nucl. Med., 2013, 54, 867–872.
127. E. Kähkönen, I. Jambor, J. Kemppainen, K. Lehtiö, T. J. Grönroos, A. Kuisma, P. Luoto, H. J. Sipilä, T. Tolvanen, K. Alanen, J. Silén, M. Kallajoki, A. Roivainen, N. Schäfer, R. Schibli, M. Dragic, A. Johayem, R. Valencia, S. Borkowski and H. Minn, Clin. Cancer Res., 2013, 19, 5434–5443.
128. J. Zang, F. Mao, H. Wang, J. Zhang, Q. Liu, L. Peng, F. Li, L. Lang, X. Chen and Z. Zhu, Clin. Nucl. Med., 2018, 43, 663–669.
129. J. Zhang, G. Niu, X. Fan, L. Lang, G. Hou, L. Chen, H. Wu, Z. Zhu, F. Li and X. Chen, J. Nucl. Med., 2018, 59, 922–928.
130. T. Maina, H. Bergsma, H. R. Kulkarni, D. Mueller, D. Charalambidis, E. P. Krenning, B. A. Nock, M. De Jong and R. P. Baum, Eur. J. Nucl. Med. Mol. Imaging, 2016, 43, 964–973.
131. I. L. Bakker, A. C. Fröberg, M. B. Busstra, J. F. Verzijlbergen, M. Konijnenberg, G. J. L. H. van Leenders, I. G. Schoots, E. de Blois, W. M. van Weerden, S. U. Dalm, T. Maina, B. A. Nock and M. de Jong, J. Nucl. Med., 2021, 62, 1517–1523.
132. B. A. Nock, A. Kaloudi, E. Lymperis, A. Giarika, H. R. Kulkarni, I. Klette, A. Singh, E. P. Krenning, M. de Jong, T. Maina and R. P. Baum, J. Nucl. Med., 2017, 58, 75–80.
133. E. Gourni, R. Mansi, M. Jamous, B. Waser, C. Smerling, A. Burian, F. Buchegger, J. C. Reubi and H. R. Maecke, J. Nucl. Med., 2014, 55, 1719–1725.
134. S. Gnesin, F. Cicone, P. Mitsakis, A. Van der Gucht, S. Baechler, R. Miralbell, V. Garibotto, T. Zilli and J. O. Prior, EJNMMI Res., 2018, 8, 108.
135. R. Mansi, X. Wang, F. Forrer, B. Waser, R. Cescato, K. Graham, S. Borkowski, J. C. Reubi and H. R. Maecke, Eur. J. Nucl. Med. Mol. Imaging, 2011, 38, 97–107.
136. Z. Varasteh, I. Velikyan, G. Lindeberg, J. Sörensen, M. Larhed, M. Sandström, R. K. Selvaraju, J. Malmberg, V. Tolmachev and A. Orlova, Bioconjugate Chem., 2013, 24, 1144–1153.
137. R. Carraway and S. E. Leeman, J. Biol. Chem., 1973, 248, 6854–6861.
138. Z. Wu, D. Martinez-Fong, J. Trédaniel and P. Forgez, Front. Endocrinol., 2013, 3, 184.
139. S. Dupouy, N. Mourra, V. K. Doan, A. Gompel, M. Alifano and P. Forgez, Biochimie, 2011, 93, 1369–1378.
140. F. Souazé, V. Viardot-Foucault, N. Roullet, M. Toy-Miou-Leong, A. Gompel, E. Bruyneel, E. Comperat, M. C. Faux, M. Mareel, W. Rostène, J.-F. Fléjou, C. Gespach and P. Forgez, Carcinogenesis, 2006, 27, 708–716.
141. X. Wang, L. N. Jackson, S. M. Johnson, Q. Wang and B. M. Evers, Mol. Cancer Ther., 2010, 9, 2389–2398.
142. A. Abbaci, H. Talbot, S. Saada, N. Gachard, J. Abraham, A. Jaccard, D. Bordessoule, A. L. Fauchais, T. Naves and M. O. Jauberteau, Oncogene, 2018, 37, 756–767.
143. S. Saada, P. Marget, A.-L. Fauchais, M.-C. Lise, G. Chemin, P. Sindou, C. Martel, L. Delpy, E. Vidal, A. Jaccard, D. Troutaud, F. Lalloué and M.-O. Jauberteau, J. Immunol., 2012, 189, 5293–5303.
144. A. E. Ayala-Sarmiento, D. Martinez-Fong and J. Segovia, Cell. Mol. Neurobiol., 2015, 35, 785–795.
145. F. Alshoukr, A. Prignon, L. Brans, A. Jallane, S. Mendes, J.-N. Talbot, D. Tourwé, J. Barbet and A. Gruaz-Guyon, Bioconjugate Chem., 2011, 22, 1374–1385.
146. A. Prignon, C. Provost, F. Alshoukr, D. Wendum, A. Couvelard, J. Barbet, P. Forgez, J.-N. Talbot and A. Gruaz-Guyon, Mol. Pharmaceutics, 2019, 16, 2776–2784.
147. S. Maschauer, J. Einsiedel, H. Hübner, P. Gmeiner and O. Prante, J. Med. Chem., 2016, 59, 6480–6492.
148. W. Wu, F. Yu, P. Zhang, T. Bu, J. Fu, S. Ai, Q. You, L. Shi, G. Shao, F. Wang, M. Hodolic and H. Guo, J. Nucl. Med., 2022, 63, 1394–1400.
149. S. Bodin, S. Previti, E. Jestin, D. Vimont, I. Ait-Arsa, F. Lamare, E. Rémond, E. Hindié, F. Cavelier and C. Morgat, ACS Omega, 2023, 8, 6994–7004.
150. I. D. Weiss and O. Jacobson, Theranostics, 2013, 3, 76–84.
151. C.-S. Hung, H.-Y. Su, H.-H. Liang, C.-W. Lai, Y.-C. Chang, Y.-S. Ho, C.-H. Wu, J.-D. Ho, P.-L. Wei and Y.-J. Chang, Tumor Biol., 2014, 35, 1581–1588.
152. P. Yang, S.-X. Liang, W.-H. Huang, H.-W. Zhang, X.-L. Li, L.-H. Xie, C.-W. Du and G.-J. Zhang, Curr. Mol. Med., 2014, 14, 174–184.
153. Y. Gao, C. Li, M. Nie, Y. Lu, S. Lin, P. Yuan and X. Sun, Tumour Biol., 2014, 35, 4171–4175.
154. C.-F. Liu, S.-Y. Liu, X.-Y. Min, Y.-Y. Ji, N. Wang, D. Liu, N. Ma, Z.-F. Li and K. Li, PLoS One, 2014, 9, e92629.
155. R. Maréchal, P. Demetter, N. Nagy, A. Berton, C. Decaestecker, M. Polus, J. Closset, J. Devière, I. Salmon and J.-L. Van Laethem, Br. J. Cancer, 2009, 100, 1444–1451.
156. B. A. Teicher and S. P. Fricker, Clin. Cancer Res., 2010, 16, 2927–2931.
157. A. Zlotnik, Int. J. Cancer, 2006, 119, 2026–2029.
158. J. A. Burger and T. J. Kipps, Blood, 2006, 107, 1761–1767.
159. H. Hanaoka, T. Mukai, H. Tamamura, T. Mori, S. Ishino, K. Ogawa, Y. Iida, R. Doi, N. Fujii and H. Saji, Nucl. Med. Biol., 2006, 33, 489–494.
160. R. Masuda, S. Oishi, H. Ohno, H. Kimura, H. Saji and N. Fujii, Bioorg. Med. Chem., 2011, 19, 3216–3220.
161. S. Nimmagadda, M. Pullambhatla and M. G. Pomper, J. Nucl. Med., 2009, 50, 1124–1130.
162. S. Nimmagadda, M. Pullambhatla, K. Stone, G. Green, Z. M. Bhujwalla and M. G. Pomper, Cancer Res., 2010, 70, 3935–3944.
163. R. A. D. Silva, K. Peyre, M. Pullambhatla, J. J. Fox, M. G. Pomper and S. Nimmagadda, J. Nucl. Med., 2011, 52, 986–993.
164. O. Demmer, E. Gourni, U. Schumacher, H. Kessler and H.-J. Wester, ChemMedChem, 2011, 6, 1789–1791.
165. E. Gourni, O. Demmer, M. Schottelius, C. D’Alessandria, S. Schulz, I. Dijkgraaf, U. Schumacher, M. Schwaiger, H. Kessler and H.-J. Wester, J. Nucl. Med., 2011, 52, 1803–1810.
166. U. Hennrich, L. Seyler, M. Schäfer, U. Bauder-Wüst, M. Eisenhut, W. Semmler and T. Bäuerle, Bioorg. Med. Chem., 2012, 20, 1502–1510.
167. G. P. C. George, E. Stevens, O. Åberg, Q.-D. Nguyen, F. Pisaneschi, A. C. Spivey and E. O. Aboagye, Bioorg. Med. Chem., 2014, 22, 796–803.
168. O. Jacobson, I. D. Weiss, L. P. Szajek, G. Niu, Y. Ma, D. O. Kiesewetter, A. Peled, H. S. Eden, J. M. Farber and X. Chen, J. Controlled Release, 2012, 157, 216–223.
169. M. Zhang, Z. Wang, M. Zhang, S. Wang, W. Yang and J. Wang, Oncology: Clinical Therapy and Diagnosis, Society of Nuclear Medicine, 2019, vol. 60, p. 1229.
170. Z. Wang, M. Zhang, L. Wang, S. Wang, F. Kang, G. Li, O. Jacobson, G. Niu, W. Yang, J. Wang and X. Chen, Theranostics, 2015, 5, 882–889.
171. H. J. Wester, U. Keller, M. Schottelius, A. Beer, K. Philipp-Abbrederis, F. Hoffmann, J. Šimeček, C. Gerngross, M. Lassmann, K. Herrmann, N. Pellegata, M. Rudelius, H. Kessler and M. Schwaiger, Theranostics, 2015, 5, 618–630.
172. T. Vag, C. Gerngross, P. Herhaus, M. Eiber, K. Philipp-Abbrederis, F.-P. Graner, J. Ettl, U. Keller, H.-J. Wester and M. Schwaiger, J. Nucl. Med., 2016, 57, 741–746.
173. C. Lapa, K. Lückerath, I. Kleinlein, C. M. Monoranu, T. Linsenmann, A. F. Kessler, M. Rudelius, S. Kropf, A. K. Buck, R.-I. Ernestus, H.-J. Wester, M. Löhr and K. Herrmann, Theranostics, 2016, 6, 428.
174. C. Lapa, M. Schreder, A. Schirbel, S. Samnick, K. M. Kortüm, K. Herrmann, S. Kropf, H. Einsele, A. K. Buck, H.-J. Wester, S. Knop and K. Lückerath, Theranostics, 2017, 7, 205–212.
175. C. Lapa, K. Lückerath, M. Rudelius, J.-S. Schmid, A. Schoene, A. Schirbel, S. Samnick, T. Pelzer, A. K. Buck, S. Kropf, H.-J. Wester and K. Herrmann, Oncotarget, 2016, 7, 9288–9295.
176. C. Lapa, H. Hänscheid, M. Kircher, A. Schirbel, G. Wunderlich, R. A. Werner, S. Samnick, J. Kotzerke, H. Einsele, A. K. Buck, H.-J. Wester and G. U. Grigoleit, J. Nucl. Med., 2019, 60, 60–64.
177. T. Derlin and K. Hueper, Lancet Oncol., 2018, 19, e370.
178. S. Kraus, A. Dierks, L. Rasche, O. Kertels, M. Kircher, A. Schirbel, J. Zovko, T. Steinbrunn, R. Tibes, H.-J. Wester, A. K. Buck, H. Einsele, K. M. Kortüm, A. Rosenwald and C. Lapa, J. Nucl. Med., 2022, 63, 96–99.
179. S. Spreckelmeyer, O. Schulze and W. Brenner, EJNMMI Radiopharm. Chem., 2020, 5, 8.
180. A. Watts, S. Chutani, D. Arora, V. Madivanane, S. Thakur, M. Kamboj and B. Singh, Indian J. Nucl. Med., 2021, 36, 237.
181. T. Jorsal, N. A. Rhee, J. Pedersen, C. D. Wahlgren, B. Mortensen, S. L. Jepsen, J. Jelsing, L. S. Dalbøge, P. Vilmann, H. Hassan, J. W. Hendel, S. S. Poulsen, J. J. Holst, T. Vilsbøll and F. K. Knop, Diabetologia, 2018, 61, 284–294.
182. R. Göke, H. C. Fehmann, T. Linn, H. Schmidt, M. Krause, J. Eng and B. Göke, J. Biol. Chem., 1993, 268, 19650–19655.
183. D. G. Parkes, R. Pittner, C. Jodka, P. Smith and A. Young, Metab., Clin. Exp., 2001, 50, 583–589.
184. A. J. Garber, Diabetes Care, 2011, 34(Suppl 2), S279–S284.
185. D. Wild, A. Wicki, R. Mansi, M. Béhé, B. Keil, P. Bernhardt, G. Christofori, P. J. Ell and H. R. Mäcke, J. Nucl. Med., 2010, 51, 1059–1067.
186. R. K. Selvaraju, I. Velikyan, V. Asplund, L. Johansson, Z. Wu, I. Todorov, J. Shively, F. Kandeel, B. Eriksson, O. Korsgren and O. Eriksson, Nucl. Med. Biol., 2014, 41, 471–476.
187. O. Eriksson, I. Velikyan, R. K. Selvaraju, F. Kandeel, L. Johansson, G. Antoni, B. Eriksson, J. Sörensen and O. Korsgren, J. Clin. Endocrinol. Metab., 2014, 99, 1519–1524.
188. A. Jodal, B. Lankat-Buttgereit, M. Brom, R. Schibli and M. Béhé, EJNMMI Res., 2014, 4, 31.
189. J. Li, J. Rawson, J. Chea, W. Tang, L. Miao, F. Sui, L. Li, E. Poku, J. E. Shively and F. Kandeel, Sci. Rep., 2019, 9, 5705.
190. L. Li, R. Zhao, H. Hong, G. Li, Y. Zhang, Y. Luo, Z. Zha, J. Zhu, J. Qiao, L. Zhu and H. F. Kung, Nucl. Med. Biol., 2021, 102–103, 87–96.
191. M. Boss, K. Mikkola, M. Buitinga, M. Brom, D. Wild, V. Prasad, A. Brouwers, F. Pattou, P. Nuutila and M. Gotthardt, Nuklearmedizin, 2019, 58, 124.
192. A. Sood, R. K. Basher, M. Kang, J. Shukla, A. Behera, R. Walia, R. Nada, B. R. Mittal and A. Bhattacharya, Clin. Nucl. Med., 2019, 44, e428–e430.
193. K. Antwi, G. Nicolas, M. Fani, T. Heye, F. Pattou, A. Grossman, P. Chanson, J. C. Reubi, A. Perren, B. Gloor, D. R. Vogt, D. Wild and E. Christ, J. Clin. Endocrinol. Metab., 2019, 104, 5843–5852.
194. K. Michalski, K. Laubner, C. Stoykow, M. A. Omrane, H. R. Maecke, J. Seufert, C. Goetz, P. T. Meyer and J. Ruf, Clin. Nucl. Med., 2020, 45, 519–524.
195. M. Boss, C. Rottenburger, W. Brenner, O. Blankenstein, V. Prasad, S. Prasad, P. D. Coppi, P. Kühnen, M. Buitinga, P. Nuutila, T. Otonkoski, K. Hussain, M. Brom, A. Eek, J. Bomanji, P. Shah and M. Gotthardt, J. Nucl. Med., 2022, 63, 310–315.
196. B. Waser, A. Blank, E. Karamitopoulou, A. Perren and J. C. Reubi, Mod. Pathol., 2015, 28, 391–402.
197. M. Wagner, J. G. Doverfjord, J. Tillner, G. Antoni, T. Haack, M. Bossart, I. Laitinen, L. Johansson, S. Pierrou, O. Eriksson and I. Velikyan, Pharmaceuticals, 2020, 13, 176.
198. I. Velikyan, U. Rosenstrom and O. Eriksson, Am. J. Nucl. Med. Mol. Imaging, 2017, 7, 111–125.
199. O. Eriksson, I. Velikyan, T. Haack, M. Bossart, I. Laitinen, P. J. Larsen, J. E. Berglund, G. Antoni, L. Johansson, S. Pierrou, J. Tillner and M. Wagner, J. Nucl. Med., 2021, 62, 833–838.
200. O. Eriksson, T. Haack, Y. Hijazi, L. Teichert, V. Tavernier, I. Laitinen, J. E. Berglund, G. Antoni, I. Velikyan, L. Johansson, S. Pierrou, M. Wagner and J. Tillner, Sci. Rep., 2020, 10, 16758.
201. L. Wei, X. Zhang, F. Gallazzi, Y. Miao, X. Jin, M. W. Brechbiel, H. Xu, T. Clifford, M. J. Welch, J. S. Lewis and T. P. Quinn, Nucl. Med. Biol., 2009, 36, 345–354.
202. B. M. Marks, M. Block, G. B. Johnson, C. B. Hruska, M. K. Pandey, A. Paulsen, M. K. Schultz, M. A. McDonald, E. A. Sagastume and F. L. Johnson, Cancer Res., 2023, 83, CT104.
203. I. Tworowska, S. Kapoor, K. Kloepping, E. Delpassand and M. Schultz, J. Nucl. Med., 2014, 55, 1045.
204. Y. Gai, L. Sun, X. Lan, D. Zeng, G. Xiang and X. Ma, Bioconjugate Chem., 2018, 29, 3483–3494.
205. J. Yang, J. Xu, R. Gonzalez, T. Lindner, C. Kratochwil and Y. Miao, Sci. Transl. Med., 2018, 10, eaau4445.
206. M. Simons, Circulation, 2005, 111, 1556–1566.
207. C. Decristoforo, I. Hernandez Gonzalez, J. Carlsen, M. Rupprich, M. Huisman, I. Virgolini, H.-J. Wester and R. Haubner, Eur. J. Nucl. Med. Mol. Imaging, 2008, 35, 1507–1515.
208. R. A. Dumont, F. Deininger, R. Haubner, H. R. Maecke, W. A. Weber and M. Fani, J. Nucl. Med., 2011, 52, 1276–1284.
209. P. A. Knetsch, M. Petrik, C. M. Griessinger, C. Rangger, M. Fani, C. Kesenheimer, E. Von Guggenberg, B. J. Pichler, I. Virgolini, C. Decristoforo and R. Haubner, Eur. J. Nucl. Med. Mol. Imaging, 2011, 38, 1303–1312.
210. I. Velikyan and Ö. Lindhe, Am. J. Nucl. Med. Mol. Imaging, 2018, 8, 15–31.
211. S. Liu, Bioconjugate Chem., 2009, 20, 2199–2213.
212. N. G. Quigley, K. Steiger, S. Hoberück, N. Czech, M. A. Zierke, S. Kossatz, M. Pretze, F. Richter, W. Weichert, C. Pox, J. Kotzerke and J. Notni, Eur. J. Nucl. Med. Mol. Imaging, 2022, 49, 1136–1147.
213. Y.-S. Kim, K. Nwe, D. E. Milenic, M. W. Brechbiel, S. Satz and K. E. Baidoo, Bioorg. Med. Chem. Lett., 2012, 22, 5517–5522.
214. S. Pandey, R. Walia, R. Kumar, S. Chopra, N. Rana, D. Chatterjee, S. Satz, B. R. Mittal and J. Shukla, Clin. Nucl. Med., 2023, 48, e95.
215. J. Shukla, R. Kumar, N. Singh, H. Singh, S. Pandey, S. Chopra, S. Santhosh, A. Bal, N. Gupta and S. Satz, J. Nucl. Med., 2022, 63, 2527.
216. R. P. Baum, H. R. Kulkarni, D. Müller, S. Satz, N. Danthi, Y.-S. Kim and M. W. Brechbiel, Cancer Biother. Radiopharm., 2015, 30, 152–159.
217. M. Wickström, R. Larsson, P. Nygren and J. Gullbo, Cancer Sci., 2011, 102, 501–508.
218. R. Pasqualini, E. Koivunen, R. Kain, J. Lahdenranta, M. Sakamoto, A. Stryhn, R. A. Ashmun, L. H. Shapiro, W. Arap and E. Ruoslahti, Cancer Res., 2000, 60, 722–727.
219. A. Buehler, M. A. M. J. van Zandvoort, B. J. Stelt, T. M. Hackeng, B. H. G. J. Schrans-Stassen, A. Bennaghmouch, L. Hofstra, J. P. M. Cleutjens, A. Duijvestijn, M. B. Smeets, D. P. V. de Kleijn, M. J. Post and E. D. de Muinck, Arterioscler., Thromb., Vasc. Biol., 2006, 26, 2681–2687.
220. B. Gyuricza, J. P. Szabó, V. Arató, N. Dénes, Á. Szűcs, K. Berta, A. Kis, D. Szücs, V. Forgács, D. Szikra, I. Kertész, G. Trencsényi and A. Fekete, Pharmaceutics, 2021, 13, 2103.
221. J. Zhang, X. Lu, N. Wan, Z. Hua, Z. Wang, H. Huang, M. Yang and F. Wang, Nucl. Med. Biol., 2014, 41, 268–275.
222. Y. Shao, W. Liang, F. Kang, W. Yang, X. Ma, G. Li, S. Zong, K. Chen and J. Wang, Molecules, 2014, 19, 11600–11612.
223. Y. Shao, W. Liang, F. Kang, W. Yang, X. Ma, G. Li, S. Zong, K. Chen and J. Wang, Amino Acids, 2014, 46, 2355–2364.
224. G. Máté, I. Kertész, K. N. Enyedi, G. Mező, J. Angyal, N. Vasas, A. Kis, É. Szabó, M. Emri, T. Bíró, L. Galuska and G. Trencsényi, Eur. J. Pharm. Sci., 2015, 69, 61–71.
225. D. Satpati, R. Sharma, C. Kumar, H. D. Sarma and A. Dash, MedChemComm, 2017, 8, 673–679.
226. D. Satpati, R. Sharma, H. D. Sarma and A. Dash, Chem. Biol. Drug Des., 2018, 91, 781–788.
227. A. Kis, N. Dénes, J. P. Szabó, V. Arató, I. Jószai, K. N. Enyedi, S. Lakatos, I. Garai, G. Mező, I. Kertész and G. Trencsényi, Int. J. Pharm., 2020, 589, 119881.
228. Y. Yang, J. Zhang, H. Zou, Y. Shen, S. Deng and Y. Wu, J. Cancer, 2021, 12, 244–252.
229. Y. C. Meinwald, E. R. Stimson and H. A. Scheraga, Int. J. Pept. Protein Res., 1986, 28, 79–84.
230. R. Kirikoshi, N. Manabe and O. Takahashi, Int. J. Mol. Sci., 2017, 18, 429.
231. N. Dénes, A. Kis, J. P. Szabó, I. Jószai, I. Hajdu, V. Arató, K. N. Enyedi, G. Mező, J. Hunyadi, G. Trencsényi and I. Kertész, Appl. Radiat. Isot., 2021, 174, 109778.
232. L. Lang, W. Li, N. Guo, Y. Ma, L. Zhu, D. O. Kiesewetter, B. Shen, G. Niu and X. Chen, Bioconjugate Chem., 2011, 22, 2415–2422.
233. J. M. Jeong, M. K. Hong, Y. S. Chang, Y.-S. Lee, Y. J. Kim, G. J. Cheon, D. S. Lee, J.-K. Chung and M. C. Lee, J. Nucl. Med., 2008, 49, 830–836.
234. J. Notni, K. Steiger, F. Hoffmann, D. Reich, T. G. Kapp, F. Rechenmacher, S. Neubauer, H. Kessler and H.-J. Wester, J. Nucl. Med., 2016, 57, 460–466.
235. S. Neubauer, F. Rechenmacher, A. J. Beer, F. Curnis, K. Pohle, C. D’Alessandria, H.-J. Wester, U. Reuning, A. Corti, M. Schwaiger and H. Kessler, Angew. Chem., Int. Ed., 2013, 52, 11656–11659.
236. C. D’Alessandria, K. Pohle, F. Rechenmacher, S. Neubauer, J. Notni, H.-J. Wester, M. Schwaiger, H. Kessler and A. J. Beer, Eur. J. Nucl. Med. Mol. Imaging, 2016, 43, 953–963.
237. F. Reichart, O. V. Maltsev, T. G. Kapp, A. F. B. Räder, M. Weinmüller, U. K. Marelli, J. Notni, A. Wurzer, R. Beck, H.-J. Wester, K. Steiger, S. Di Maro, F. S. Di Leva, L. Marinelli, M. Nieberler, U. Reuning, M. Schwaiger and H. Kessler, J. Med. Chem., 2019, 62, 2024–2037.
238. N. G. Quigley, K. Steiger, F. Richter, W. Weichert, S. Hoberück, J. Kotzerke and J. Notni, EJNMMI Res., 2020, 10, 133.
239. N. G. Quigley, S. Tomassi, F. S. di Leva, S. D. Maro, F. Richter, K. Steiger, S. Kossatz, L. Marinelli and J. Notni, ChemBioChem, 2020, 21, 2836–2843.
240. O. V. Maltsev, U. K. Marelli, T. G. Kapp, F. S. Di Leva, S. Di Maro, M. Nieberler, U. Reuning, M. Schwaiger, E. Novellino, L. Marinelli and H. Kessler, Angew. Chem., Int. Ed., 2016, 55, 1535–1539.
241. X. Feng, Y. Wang, D. Lu, X. Xu, X. Zhou, H. Zhang, T. Zhang, H. Zhu, Z. Yang, F. Wang, N. Li and Z. Liu, J. Nucl. Med., 2020, 61, 1461–1467.
242. J. Roy, K. S. Putt, D. Coppola, M. E. Leon, F. K. Khalil, B. A. Centeno, N. Clark, V. E. Stark, D. L. Morse and P. S. Low, Oncotarget, 2016, 7, 14605–14615.
243. P. Laverman, L. Joosten, A. Eek, S. Roosenburg, P. K. Peitl, T. Maina, H. Mäcke, L. Aloj, E. von Guggenberg, J. K. Sosabowski, M. de Jong, J.-C. Reubi, W. J. G. Oyen and O. C. Boerman, Eur. J. Nucl. Med. Mol. Imaging, 2011, 38, 1410–1416.
244. P. Kolenc-Peitl, R. Mansi, M. Tamma, T. Gmeiner-Stopar, M. Sollner-Dolenc, B. Waser, R. P. Baum, J. C. Reubi and H. R. Maecke, J. Med. Chem., 2011, 54, 2602–2609.
245. S. Roosenburg, P. Laverman, L. Joosten, M. S. Cooper, P. K. Kolenc-Peitl, J. M. Foster, C. Hudson, J. Leyton, J. Burnet, W. J. G. Oyen, P. J. Blower, S. J. Mather, O. C. Boerman and J. K. Sosabowski, Mol. Pharmaceutics, 2014, 11, 3930–3937.
246. J. Kunikowska, K. Ziemnicka, D. Pawlak, M. Ruchała, A. Kolasa, M. Janicka-Jedyńska, A. Woźniak, R. Mikołajczak and L. Królicki, Endokrynol. Pol., 2016, 67, 68–71.
247. P. A. Erba, H. Maecke, R. Mikolajczak, C. Decristoforo, K. Zaletel, T. Maina-Nock, P. K. Peitl, P. Garnuszek, A. Froberg, G. Goebel, M. de Jong, A. Jabrocka-Hybel, M. Konijnenberg, I. Virgolini, B. Nock, W. Lenda-Tracz, D. Pawlak, C. Rangger, M. Trofimiuk-Müldner, A. Sowa–Staszczak, M. Tomaszuk, E. von Guggenberg, L. Scarpa and A. Hubalewska–Dydejczyk, Pol. Arch. Intern. Med., 2018, 128, 791–795.
248. C. Rottenburger, G. P. Nicolas, L. McDougall, F. Kaul, M. Cachovan, A. H. Vija, R. Schibli, S. Geistlich, A. Schumann, T. Rau, K. Glatz, M. Behe, E. R. Christ and D. Wild, J. Nucl. Med., 2020, 61, 520–526.
249. M. Klingler, D. Summer, C. Rangger, R. Haubner, J. Foster, J. Sosabowski, C. Decristoforo, I. Virgolini and E. von Guggenberg, J. Nucl. Med., 2019, 60, 1010–1016.
250. A. A. Hörmann, M. Klingler, C. Rangger, C. Mair, C. Decristoforo, C. Uprimny, I. J. Virgolini and E. Von Guggenberg, Pharmaceuticals, 2021, 14, 575.
251. C. Uprimny, E. von Guggenberg, A. Svirydenka, R. Mikołajczak, A. Hubalewska-Dydejczyk and I. J. Virgolini, Eur. J. Nucl. Med. Mol. Imaging, 2021, 48, 935–936.
252. E. von Guggenberg, C. Uprimny, M. Klinger, B. Warwitz, A. Sviridenko, S. Bayerschmidt, G. di Santo and I. J. Virgolini, J. Nucl. Med., 2023, 64, 859–862.
253. A. A. Hörmann, E. Plhak, M. Klingler, C. Rangger, J. Pfister, G. Schwach, H. Kvaternik and E. von Guggenberg, Molecules, 2022, 27, 2034.
254. M. Klingler, A. A. Hörmann and E. V. Guggenberg, Curr. Med. Chem., 2020, 27, 7112–7132.
255. E. von Guggenberg, P. Kolenc, C. Rottenburger, R. Mikołajczak and A. Hubalewska-Dydejczyk, Cancers, 2021, 13, 5776.
256. Z. Zha, Z. Wu, S. R. Choi, K. Ploessl, M. Smith, D. Alexoff, L. Zhu and H. F. Kung, Mol. Pharmaceutics, 2020, 17, 1674–1684.
257. R. K. Doot, A. J. Young, M. E. Daube-Witherspoon, D. Alexoff, K. J. Labban, H. Lee, Z. Wu, Z. Zha, S. R. Choi, K. H. Ploessl, E. K. Schubert, H. Lee, L. Zhu, J. S. Reddin, J. S. Karp, H. Kung and D. A. Pryma, Nucl. Med. Biol., 2020, 86–87, 1.
258. R. Guo, X. Meng, F. Wang, J. Yu, Q. Xie, W. Zhao, L. Zhu, H. F. Kung, Z. Yang and N. Li, Front. Oncol., 2021, 11, 766851.
259. C. Wang, Y. Chen, Y. N. Hou, Q. Liu, D. Zhang, H. Zhao, Y. Zhang, S. An, L. Li, J. Hou, G. Huang, J. Liu, Y. J. Zhao and W. Wei, Eur. J. Nucl. Med. Mol. Imaging, 2021, 48, 2749–2760.
260. J. Bridoux, K. Broos, Q. Lecocq, P. Debie, C. Martin, S. Ballet, G. Raes, S. Neyt, C. Vanhove, K. Breckpot, N. Devoogdt, V. Caveliers, M. Keyaerts and C. Xavier, Biomolecules, 2020, 10, 1388.
261. Q. Liu, X. Wang, Y. Yang, C. Wang, J. Zou, J. Lin and L. Qiu, Quant. Imaging Med. Surg., 2022, 12, 3300–3313.
262. Q. Liu, L. Jiang, K. Li, H. Li, G. Lv, J. Lin and L. Qiu, Cancer Immunol. Immunother., 2021, 70, 1721–1733.
263. S. Qin, Y. Yu, H. Guan, Y. Yang, F. Sun, Y. Sun, J. Zhu, L. Xing, J. Yu and X. Sun, Aging, 2021, 13, 13006–13022.
264. H. Liu, M. Hu, J. Deng, Y. Zhao, D. Peng, Y. Feng, L. Wang, Y. Chen and L. Qiu, Mol. Pharmaceutics, 2022, 19, 138–147.
265. J. Jinquan, H. Zhu and Z. Yang, J. Nucl. Med., 2020, 61, 1022.
266. X. Ma, X. Zhou, B. Hu, X. Li, M. Yao, L. Li, X. Qin, D. Li, Y. Yao, X. Hou, S. Liu, Y. Chen, Z. Wang, W. Zhou, N. Li, H. Zhu, B. Jia and Z. Yang, Eur. J. Nucl. Med. Mol. Imaging, 2023, 50, 3838–3850.
267. H. Zhao, C. Wang, Y. Yang, Y. Sun, W. Wei, C. Wang, L. Wan, C. Zhu, L. Li, G. Huang and J. Liu, J. Nanobiotechnol., 2021, 19, 42.
268. X. Wang, M. Zhou, B. Chen, H. Liu, J. Fang, S. Xiang, S. Hu and X. Zhang, Eur. J. Nucl. Med. Mol. Imaging, 2022, 49, 2584–2594.
269. C. Xavier, A. Blykers, D. Laoui, E. Bolli, I. Vaneyken, J. Bridoux, H. Baudhuin, G. Raes, H. Everaert, K. Movahedi, J. A. Van Ginderachter, N. Devoogdt, V. Caveliers, T. Lahoutte and M. Keyaerts, Mol. Imaging Biol., 2019, 21, 898–906.
270. G. J. Gu, H. Chung, J. Y. Park, R. Yoo, H.-J. Im, H. Choi, Y.-S. Lee and S. H. Seok, J. Nanobiotechnol., 2023, 21, 31.
271. D. Shi, Z. Si, Z. Xu, Y. Cheng, Q. Lin, Z. Fu, W. Fu, T. Yang, H. Shi and D. Cheng, Anal. Chem., 2022, 94, 3819–3830.
272. M. Huang, R. Wang, M. Li, H. Cai and R. Tian, Pharmaceutics, 2022, 14, 2511.
273. S. Gao, J. Qin, O. Sergeeva, M. Sergeev, P. Qiao, S. Roelle, N. Avril, Z. Lee, Y. Li and Z. Lu, Am. J. Nucl. Med. Mol. Imaging, 2019, 9, 216–229.
274. C. Müller, Molecules, 2013, 18, 5005–5031.
275. I. Aljammaz, B. Al-Otaibi, N. Al-Hokbany, S. Amer and S. Okarvi, Anticancer Res., 2014, 34, 6547–6556.
276. O. Moisio, S. Palani, J. Virta, P. Elo, H. Liljenbäck, T. Tolvanen, M. Käkelä, M. G. Miner, E. A. Herre, P. Marjamäki, T. Örd, M. Heinäniemi, M. U. Kaikkonen, F. Zhang, M. Srinivasarao, J. Knuuti, P. S. Low, A. Saraste, X.-G. Li and A. Roivainen, Sci. Rep., 2020, 10, 13593.
277. G. Di Sante, J. Pagé, X. Jiao, O. Nawab, M. Cristofanilli, E. Skordalakes and R. G. Pestell, Expert Rev. Anticancer Ther., 2019, 19, 569–587.
278. C. Liu, Z. Yang, M. Liu, X. Wang, S. Song, X. Xu and Z. Yang, ACS Omega, 2021, 6, 32253–32261.
279. S. An, D. Zhang, Y. Zhang, C. Wang, L. Shi, W. Wei, G. Huang and J. Liu, Eur. J. Nucl. Med. Mol. Imaging, 2022, 49, 2682–2692.
280. Z.-F. Liu, Q.-N. Ye, J. Yang, M. Yang, D.-H. Pan and M.-J. Dong, Nucl. Med. Commun., 2021, 42, 782–791.
281. R. Zou, Y. Gao, Y. Zhang, J. Jiao, K.-L. Wong and J. Wang, ACS Appl. Mater. Interfaces, 2021, 13, 9667–9680.
282. C. Tsoukalas, S. Geninatti-Crich, A. Gaitanis, T. Tsotakos, M. Paravatou-Petsotas, S. Aime, R. Jiménez-Juárez, C. D. Anagnostopoulos, K. Djanashvili and P. Bouziotis, Mol. Imaging Biol., 2018, 20, 798–807.
283. D. Skovgaard, M. Persson, M. Brandt-Larsen, C. Christensen, J. Madsen, T. L. Klausen, S. Holm, F. L. Andersen, A. Loft, A. K. Berthelsen, H. Pappot, K. Brasso, N. Kroman, L. Højgaard and A. Kjaer, J. Nucl. Med., 2017, 58, 379–386.
284. E. A. Carlsen, M. Loft, A. Loft, A. K. Berthelsen, S. W. Langer, U. Knigge and A. Kjaer, J. Nucl. Med., 2022, 63, 1371–1377.
285. M. M. Chang, S. E. Leeman and H. D. Niall, Nat. New Biol., 1971, 232, 86–87.
286. S. Kneifel, D. Cordier, S. Good, M. C. S. Ionescu, A. Ghaffari, S. Hofer, M. Kretzschmar, M. Tolnay, C. Apostolidis, B. Waser, M. Arnold, J. Mueller-Brand, H. R. Maecke, J. C. Reubi and A. Merlo, Clin. Cancer Res., 2006, 12, 3843–3850.
287. L. Krolicki, F. Bruchertseifer, J. Kunikowska, H. Koziara, B. Królicki, M. Jakuciński, D. Pawlak, C. Apostolidis, S. Mirzadeh, R. Rola, A. Merlo and A. Morgenstern, Eur. J. Nucl. Med. Mol. Imaging, 2018, 45, 1636–1644.
288. J. Suthiram, T. Ebenhan, B. Marjanovic-Painter, M. M. Sathekge and J. R. Zeevaart, Pharmaceutics, 2021, 13, 1326.
289. M. Schottelius, S. Berger, T. Poethko, M. Schwaiger and H.-J. Wester, Bioconjugate Chem., 2008, 19, 1256–1268.
290. M. Zoghi, A. R. Jalilian, A. Niazi, F. Johari-daha, B. Alirezapour and S. Ramezanpour, Ann. Nucl. Med., 2016, 30, 400–408.
291. M. Zoghi, S. Attar Nosrati, F. Rogni, G. Shirvani and F. Johari Daha, J. Labelled Compd. Radiopharm., 2019, 62, 310–320.
292. M. Meckel, R. Bergmann, M. Miederer and F. Roesch, EJNMMI Radiopharm. Chem., 2016, 1, 14.
293. M. Meckel, M. Fellner, N. Thieme, R. Bergmann, V. Kubicek and F. Rösch, Nucl. Med. Biol., 2013, 40, 823–830.
294. J. Holub, M. Meckel, V. Kubíček, F. Rösch and P. Hermann, Contrast Media Mol. Imaging, 2015, 10, 122–134.
295. M. Fellner, R. P. Baum, V. Kubíček, P. Hermann, I. Lukeš, V. Prasad and F. Rösch, Eur. J. Nucl. Med. Mol. Imaging, 2010, 37, 834.
296. Z. Wu, Z. Zha, S. R. Choi, K. Plössl, L. Zhu and H. F. Kung, Nucl. Med. Biol., 2016, 43, 360–371.
297. K. Ogawa, A. Ishizaki, K. Takai, Y. Kitamura, A. Makino, T. Kozaka, Y. Kiyono, K. Shiba and A. Odani, Sci. Rep., 2017, 7, 13971.
298. S. Toegel, W. Wadsak, L. K. Mien, H. Viernstein, R. Kluger, H. Eidherr, D. Haeusler, K. Kletter, R. Dudczak and M. Mitterhauser, Eur. J. Pharm. Biopharm., 2008, 68, 406–412.
299. K. Suzuki, M. Satake, J. Suwada, S. Oshikiri, H. Ashino, H. Dozono, A. Hino, H. Kasahara and T. Minamizawa, Nucl. Med. Biol., 2011, 38, 1011–1018.
300. J. Notni, J. Plutnar and H.-J. Wester, EJNMMI Res., 2012, 2, 13.
301. I. Velikyan, U. Rosenström, M. Rosestedt, O. Eriksson and G. Antoni, Pharmaceuticals, 2021, 14, 990.
302. I. Velikyan, J. G. Doverfjord, S. Estrada, H. Steen, G. Van Scharrenburg and G. Antoni, Nucl. Med. Biol., 2020, 88–89, 73–85.
303. J. Zhang, L. Lang, Z. Zhu, F. Li, G. Niu and X. Chen, J. Nucl. Med., 2015, 56, 1609–1614.
304. W. Zhang, P. Wu, F. Li, G. Tong, X. Chen and Z. Zhu, Clin. Nucl. Med., 2016, 41, 302–308.
305. L. Peng, J. Zhao, F. Mao and Q. Sun, Medicine, 2020, 99, e21201.
306. L. Feng, J. Fang, X. Zeng, H. Liu, J. Zhang, L. Huang, Z. Guo, R. Zhuang and X. Zhang, ACS Omega, 2022, 7, 28597–28604.
307. F. Blanc-Béguin, P. Eliès, P. Robin, R. Tripier, N. Kervarec, C. A. Lemarié, S. Hennebicq, C. Tromeur, V. Cogulet, P.-Y. Salaün and P.-Y. Le Roux, Mol. Imaging Biol., 2021, 23, 62–69.
308. M. S. Hofman, J.-M. Beauregard, T. W. Barber, O. C. Neels, P. Eu and R. J. Hicks, J. Nucl. Med., 2011, 52, 1513–1519.
309. J. Kotzerke, M. Andreeff and G. Wunderlich, Eur. J. Nucl. Med. Mol. Imaging, 2010, 37, 175–177.
310. P.-Y. Le Roux, A. Iravani, J. Callahan, K. Burbury, P. Eu, D. P. Steinfort, E. Lau, B. Woon, P.-Y. Salaun, R. J. Hicks and M. S. Hofman, Eur. J. Nucl. Med. Mol. Imaging, 2019, 46, 1596–1604.
311. S. Siva, R. Thomas, J. Callahan, N. Hardcastle, D. Pham, T. Kron, R. J. Hicks, M. P. MacManus, D. L. Ball and M. S. Hofman, Radiother. Oncol., 2015, 115, 157–162.
312. P.-Y. Le Roux, T. L. Leong, S. A. Barnett, R. J. Hicks, J. Callahan, P. Eu, R. Manser and M. S. Hofman, Cancer Imaging, 2016, 16, 24.
313. H. Ndlovu, I. O. Lawal, G. O. Popoola, B. Brits, K. M. G. Mokoala, L. C. Maserumule, K. N. Hlongwa, J. Mahapane, C. Davis and M. M. Sathekge, Ann. Nucl. Med., 2022, 36, 684–692.
314. M. Hofman, D. Binns, V. Johnston, S. Siva, M. Thompson, P. Eu, M. Collins and R. J. Hicks, J. Nucl. Med., 2015, 56, 405–409.
315. J. Y. Lee, J. M. Jeong, Y. J. Kim, H.-J. Jeong, Y.-S. Lee, D. S. Lee and J.-K. Chung, Nucl. Med. Biol., 2014, 41, 210–215.
316. D. Kersting, M. Sraieb, R. Seifert, P. F. Costa, S. Kazek, L. Kessler, L. Umutlu, W. P. Fendler, W. Jentzen, K. Herrmann, F. Büther, M. Nader and C. Rischpler, Eur. J. Nucl. Med. Mol. Imaging, 2022, 49, 3373–3386.
317. Z. Qin, C. K. Hoh, E. S. Olson, A. H. Jahromi, D. J. Hall, C. V. Barback, Y.-H. You, M. Yanagita, K. Sharma and D. R. Vera, J. Nucl. Med., 2019, 60, 1325–1332.
318. S. Shi, L. Zhang, Z. Wu, A. Zhang, H. Hong, S. R. Choi, L. Zhu and H. F. Kung, Nucl. Med. Biol., 2020, 82–83, 17–24.
319. J. Choi, J. M. Jeong, B. C. Yoo, M. K. Hong, Y. J. Kim, Y.-S. Lee, D. S. Lee and J.-K. Chung, Nucl. Med. Biol., 2015, 42, 53–58.
320. H.-M. Yu, C.-H. Chan, J.-H. Chen, C.-Y. Chien, P.-Y. Wang, W.-C. Juan, C.-H. Yang, H.-T. Hsia, M.-H. Wang and W.-J. Lin, J. Labelled Compd. Radiopharm., 2018, 61, 885–894.
321. R. Haubner, D. R. Vera, S. Farshchi-Heydari, A. Helbok, C. Rangger, D. Putzer and I. J. Virgolini, Eur. J. Nucl. Med. Mol. Imaging, 2013, 40, 1245–1255.
322. R. Haubner, A. M. Schmid, A. Maurer, C. Rangger, L. G. Roig, B. J. Pichler and I. J. Virgolini, Mol. Imaging Biol., 2017, 19, 723–730.
323. J. C. Taubel, N. R. Nelson, A. Bansal, G. L. Curran, L. Wang, Z. Wang, H. M. Berg, C. J. Vernon, H.-K. Min, N. B. Larson, T. R. DeGrado, K. K. Kandimalla, V. J. Lowe and M. K. Pandey, Bioconjugate Chem., 2022, 33, 892–906.
324. C. F. Ramogida, D. Schindler, C. Schneider, Y. L. K. Tan, S. Huh, C. L. Ferreira, M. J. Adam and C. Orvig, RSC Adv., 2016, 6, 103763–103773.
325. D. Gündel, U. Pohle, E. Prell, A. Odparlik and O. Thews, Mol. Imaging Biol., 2018, 20, 457–464.
326. C. J. Palestro, Semin. Nucl. Med., 1994, 24, 128–141.
327. S. Auletta, F. Galli, C. Lauri, D. Martinelli, I. Santino and A. Signore, Clin. Transl. Imaging, 2016, 4, 229–252.
328. L. A. Mitscher, Chem. Rev., 2005, 105, 559–592.
329. D. C. Hooper and J. S. Wolfson, N. Engl. J. Med., 1991, 324, 384–394.
330. D. T. Chu and P. B. Fernandes, Antimicrob. Agents Chemother., 1989, 33, 131–135.
331. D. Satpati, C. Arjun, R. Krishnamohan, G. Samuel and S. Banerjee, Chem. Biol. Drug Des., 2016, 87, 680–686.
332. P. Koźmiński, W. Gawęda, M. Rzewuska, A. Kopatys, S. Kujda, M. K. Dudek, P. K. Halik, L. Królicki and E. Gniazdowska, Tomography, 2021, 7, 829–842.
333. M. M. Welling, A. Lupetti, H. S. Balter, S. Lanzzeri, B. Souto, A. M. Rey, E. O. Savio, A. Paulusma-Annema, E. K. Pauwels and P. H. Nibbering, J. Nucl. Med., 2001, 42, 788–794.
334. J. Bhatt, A. Mukherjee, A. Shinto, K. Koramadai Karuppusamy, A. Korde, M. Kumar, H. D. Sarma, K. Repaka and A. Dash, Nucl. Med. Biol., 2018, 62–63, 47–53.
335. M. Vilche, A. L. Reyes, E. Vasilskis, P. Oliver, H. Balter and H. Engler, J. Nucl. Med., 2016, 57, 622–627.
336. T. Ebenhan, N. Chadwick, M. M. Sathekge, P. Govender, T. Govender, H. G. Kruger, B. Marjanovic-Painter and J. R. Zeevaart, Nucl. Med. Biol., 2014, 41, 390–400.
337. T. Ebenhan, J. R. Zeevaart, J. D. Venter, T. Govender, G. H. Kruger, N. V. Jarvis and M. M. Sathekge, J. Nucl. Med., 2014, 55, 308–314.
338. K. M. Nielsen, M. H. Kyneb, A. K. O. Alstrup, J. J. Jensen, D. Bender, H. C. Schønheyder, P. Afzelius, O. L. Nielsen and S. B. Jensen, Nucl. Med. Biol., 2016, 43, 593–605.
339. P. Afzelius, A. Alstrup, O. Nielsen, K. Nielsen and S. Jensen, Molecules, 2020, 25, 4329.
340. M. Stawikowski and P. Cudic, in Peptide Characterization and Application Protocols, ed. G. B. Fields, Humana Press, Totowa, NJ, 2007, pp. 321–339.
341. B. B. Mokaleng, T. Ebenhan, S. Ramesh, T. Govender, H. G. Kruger, R. Parboosing, P. P. Hazari, A. K. Mishra, B. Marjanovic-Painter, J. R. Zeevaart and M. M. Sathekge, BioMed Res. Int., 2015, 2015, e284354.
342. T. Ebenhan, B. B. Mokaleng, J. D. Venter, H. G. Kruger, J. R. Zeevaart and M. Sathekge, Molecules, 2017, 22, 1403.
343. J. Dutta, S. Baijnath, A. M. Somboro, S. Nagiah, F. Albericio, B. G. de la Torre, B. Marjanovic-Painter, J. R. Zeevaart, M. Sathekge, H. G. Kruger, A. Chuturgoon, T. Naicker, T. Ebenhan and T. Govender, Chem. Biol. Drug Des., 2017, 90, 572–579.
344. A. H. Mdlophane, T. Ebenhan, B. Marjanovic-Painter, T. Govender, M. M. Sathekge and J. R. Zeevaart, J. Radioanal. Nucl. Chem., 2019, 322, 629–638.
345. S. Chopra, B. Singh, A. Koul, A. Mishra and H. Wester, J. Nucl. Med., 2016, 57, 1115.
346. C. Peukert, L. N. B. Langer, S. M. Wegener, A. Tutov, J. P. Bankstahl, B. Karge, F. M. Bengel, T. L. Ross and M. Brönstrup, J. Med. Chem., 2021, 64, 12359–12378.
347. A. Rizzello, D. Pierro, F. Lodi, S. Trespidi, G. Cicoria, D. Pancaldi, C. Nanni, M. Marengo, M. Marzola, A. Al-Nahhas, D. Rubello and S. Boschi, Nucl. Med. Commun., 2009, 30, 542–545.
348. C. Nanni, C. Errani, L. Boriani, L. Fantini, V. Ambrosini, S. Boschi, D. Rubello, C. Pettinato, M. Mercuri, A. Gasbarrini and S. Fanti, J. Nucl. Med., 2010, 51, 1932–1936.
349. V. Kumar, D. K. Boddeti, S. G. Evans and S. Angelides, Curr. Radiopharm., 2012, 5, 71–75.
350. M. Vorster, A. Maes, C. van de Wiele and M. Sathekge, Q. J. Nucl. Med. Mol. Imaging, 2019, 63, 48–55.
351. S. P. Salomäki, J. Kemppainen, U. Hohenthal, P. Luoto, O. Eskola, P. Nuutila, M. Seppänen, L. Pirilä, J. Oksi and A. Roivainen, Contrast Media Mol. Imaging, 2017, 2017, 3179607.
352. V. Kumar, D. K. Boddeti, S. G. Evans, F. Roesch and R. Howman-Giles, Nucl. Med. Biol., 2011, 38, 393–398.
353. A. Pandey, C. Savino, S. H. Ahn, Z. Yang, S. G. Van Lanen and E. Boros, J. Med. Chem., 2019, 62, 9947–9960.
354. T. Ebenhan, M. M. Sathekge, T. Lengana, M. Koole, O. Gheysens, T. Govender and J. R. Zeevaart, J. Nucl. Med., 2018, 59, 334–339.
355. M. Petrik, H. Haas, M. Schrettl, A. Helbok, M. Blatzer and C. Decristoforo, Nucl. Med. Biol., 2012, 39, 361–369.
356. M. Petrik, H. Haas, P. Laverman, M. Schrettl, G. M. Franssen, M. Blatzer and C. Decristoforo, Mol. Imaging Biol., 2014, 16, 102–108.
357. M. Petrik, E. Umlaufova, V. Raclavsky, A. Palyzova, V. Havlicek, J. Pfister, C. Mair, Z. Novy, M. Popper, M. Hajduch and C. Decristoforo, Eur. J. Nucl. Med. Mol. Imaging, 2021, 48, 372–382.
358. M. Petrik, E. Umlaufova, V. Raclavsky, A. Palyzova, V. Havlicek, H. Haas, Z. Novy, D. Dolezal, M. Hajduch and C. Decristoforo, Sci. Rep., 2018, 8, 15698.
359. K. Bendova, V. Raclavsky, R. Novotny, D. Luptakova, M. Popper, Z. Novy, M. Hajduch and M. Petrik, J. Med. Chem., 2023, 66, 7584–7593.
360. I. Velikyan, Contrast Media Mol. Imaging, 2018, 2018, 9713691.
361. M. Vorster, Semin. Nucl. Med., 2023, 53, 199–212.
362. S. Rangaraju, M. Gearing, L.-W. Jin and A. Levey, J. Alzheimers Dis., 2015, 44, 797–808.
363. S. Sarkar, H. M. Nguyen, E. Malovic, J. Luo, M. Langley, B. N. Palanisamy, N. Singh, S. Manne, M. Neal, M. Gabrielle, A. Abdalla, P. Anantharam, D. Rokad, N. Panicker, V. Singh, M. Ay, A. Charli, D. Harischandra, L.-W. Jin, H. Jin, S. Rangaraju, V. Anantharam, H. Wulff and A. G. Kanthasamy, J. Clin. Invest., 2020, 130, 4195–4212.
364. S. B. Reddiar, M. de Veer, B. M. Paterson, T. Sepehrizadeh, D. C. C. Wai, A. Csoti, G. Panyi, J. A. Nicolazzo and R. S. Norton, Mol. Pharmaceutics, 2023, 20, 255–266.
365. C. Liolios, T. S. Koutsikou, E.-A. Salvanou, F. Kapiris, E. Machairas, M. Stampolaki, A. Kolocouris, E. K. Efthimiadou and P. Bouziotis, Int. J. Pharm., 2022, 624, 122008.
366. M. Eder, M. Schäfer, U. Bauder-Wüst, U. Haberkorn, M. Eisenhut and K. Kopka, The Prostate, 2014, 74, 659–668.
367. C. Liolios, M. Schäfer, U. Haberkorn, M. Eder and K. Kopka, Bioconjugate Chem., 2016, 27, 737–751.
368. M. J. Mendoza-Figueroa, A. Escudero-Castellanos, G. J. Ramirez-Nava, B. E. Ocampo-García, C. L. Santos-Cuevas, G. Ferro-Flores, M. Pedraza-Lopez and M. A. Avila-Rodriguez, J. Radioanal. Nucl. Chem., 2018, 318, 2097–2105.
369. B. Rivera-Bravo, G. Ramírez-Nava, M. J. Mendoza-Figueroa, B. Ocampo-García, G. Ferro-Flores, M. A. Ávila-Rodríguez and C. Santos-Cuevas, Nucl. Med. Biol., 2021, 96–97, 54–60.
370. B. Mitran, Z. Varasteh, A. Abouzayed, S. S. Rinne, E. Puuvuori, M. De Rosa, M. Larhed, V. Tolmachev, A. Orlova and U. Rosenström, Cancers, 2019, 11, 1371.
371. Y. Zheng and Z. Zhu, J. Nucl. Med., 2018, 59, 1141.
372. Y. Jiang, Q. Liu, G. Wang, H. Sui, R. Wang, J. Wang and Z. Zhu, Eur. J. Nucl. Med. Mol. Imaging, 2022, 49, 4218–4227.
373. J. Zang, X. Wen, R. Lin, X. Zeng, C. Wang, M. Shi, X. Zeng, J. Zhang, X. Wu, X. Zhang, W. Miao, P. Xu, Z. Guo, J. Zhang and X. Chen, Theranostics, 2022, 12, 7180–7190.
374. H.-M. Yu, J.-H. Chen, K.-L. Lin and W.-J. Lin, J. Labelled Compd. Radiopharm., 2015, 58, 299–303.
375. C.-J. Chen, C.-H. Chan, K.-L. Lin, J.-H. Chen, C.-H. Tseng, P.-Y. Wang, C.-Y. Chien, H.-M. Yu and W.-J. Lin, Nucl. Med. Biol., 2019, 68–69, 22–30.
376. Y. Long, F. Shao, H. Ji, X. Song, X. Lv, X. Xia, Q. Liu, Y. Zhang, D. Zeng, X. Lan and Y. Gai, Front. Oncol., 2022, 12, 884554.
377. Z. Liu, Y. Yan, S. Liu, F. Wang and X. Chen, Bioconjugate Chem., 2009, 20, 1016–1025.
378. Y. Gai, Y. Jiang, Y. Long, L. Sun, Q. Liu, C. Qin, Y. Zhang, D. Zeng and X. Lan, Mol. Pharmaceutics, 2020, 17, 349–358.

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