Novel Approaches for Detection and Targeted Therapy of Prostate Cancer Using Antibodies, Aptamers, and Nanobodies

Abstract

Prostate cancer is the most frequently diagnosed malignancy in men and the second most common cancer globally, with significant annual incidence and mortality rates. Although benign in its early stages, it can progress to advanced and metastatic forms if not detected and treated early. Thus, early detection significantly improves treatment outcomes, relying primarily on screening for specific biomarkers such as prostate-specific antigen (PSA) and prostate-specific membrane antigen (PSMA) using antibodies, aptamers, and nanobodies. These small biomolecules offer notable advantages over conventional diagnostic and therapeutic approaches and are highly effective in targeting PSA and PSMA in prostate cancer. Each biomolecule possesses unique strengths and weaknesses, making them valuable tools for biomedical applications. To date, numerous anti-PSA and anti-PSMA diagnostic and therapeutic strategies, using antibodies, aptamers, and nanobodies, either in free form or conjugated with toxins or radionuclides, have been investigated in both preclinical and clinical studies. This review explores the fundamentals, diagnostic and therapeutic applications in prostate cancer, and the challenges and potential solutions associated with antibodies, aptamers, and nanobodies. Subsequent sections comparatively analyze these biomolecules in terms of stability, cost, and clinical application, highlighting both complementary advantages and critical limitations. Finally, we explore the integration of computational biology, artificial intelligence (AI), machine learning (ML), and deep learning (DL) into prostate cancer diagnosis and therapy to enhance early detection and improve the performance of anti-PSA and anti-PSMA molecules for future advancements.

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