Advancing Triage of Acute Lymphoblastic Leukemia Subtypes Diagnosis: Label-Free Raman Spectroscopy for Precise Single-Cell Phenotyping and Subtype Classification

Abstract

Acute lymphoblastic leukaemia (ALL) is a complex disease in pediatric oncology, necessitating accurate diagnostic strategies for effective treatment planning. The ability to differentiate between B-cell ALL (B-ALL) and T-cell ALL (T-ALL) is crucial for targeted interventions. However, current diagnostic methods are time-consuming and require rapid, dependable tests. This study explores the potential of label-free Raman imaging coupled with chemometrics for rapid blast phenotyping of B-ALL and T-ALL. Our findings demonstrate the efficacy of Raman spectroscopy in sensitively and specifically screening and classifying ALL, as well as its rapidity and reliability. The obtained molecular information allows for label-free and precise leukaemia diagnosis at the single-cell level, surpassing the capabilities of traditional diagnostic techniques. Raman spectra of cancer cells reveal distinctive molecular signatures, specifically heightened protein and nucleic acid content, revealing molecular signatures unique to leukemic phenotypes. Based on that, they could be distinguished from each other and their normal B and T lymphocyte counterparts. This research underscores the analytical power of Raman spectroscopy, positioning it as a valuable tool for identifying and classifying pediatric ALL subtypes. The potential translational applications in clinical practice offer a promising avenue for an expedited and accurate leukaemia diagnosis, paving the way for more targeted and personalised therapeutic approaches.

Supplementary files

Article information

Article type
Paper
Submitted
08 Len 2024
Accepted
09 Mvu 2024
First published
16 Mvu 2024

Analyst, 2024, Accepted Manuscript

Advancing Triage of Acute Lymphoblastic Leukemia Subtypes Diagnosis: Label-Free Raman Spectroscopy for Precise Single-Cell Phenotyping and Subtype Classification

P. Leszczenko, A. Nowakowska, P. Dawiec, K. Czuja, J. Jakubowska, M. Zabczynska, A. Pastorczak, S. Tott, W. Młynarski, M. Baranska, K. Ostrowska and K. Majzner, Analyst, 2024, Accepted Manuscript , DOI: 10.1039/D4AN00956H

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