Gas chromatography and mass spectrometry for prostate cancer diagnosis: perspectives and achievements

Introduction. Prostate cancer (PCa) is one of the most common malignancies among men, making the search for new methods of its early detection highly relevant. Existing diagnostic approaches, such as the determination of prostate-specific antigen (PSA) levels, have limited specificity and sensitivity, highlighting the need for more accurate and non-invasive diagnostic methods. Objecive. To analyze recent studies focused on the use of gas chromatography coupled with mass spectrometry (GC–MS) for the detection of urinary volatile organic compounds (VOCs) as potential PCa biomarkers, as well as to evaluate the prospects for the implementation of this method in clinical practice. Materials & Methods. The review includes an analysis of scientific publications available in the PubMed, Medscape, and eLibrary databases for the period from 2019 to 2024. The focus was placed on studies devoted to urine metabolomic profiling using GC–MS and investigations of metabolic pathway alterations in prostate cancer cells. Results. The results of the reviewed studies demonstrate that GC–MS enables the identification of specific VOCs associated with tumor transformation of prostate cells. This method shows high diagnostic accuracy, exceeding traditional approaches such as PSA testing. Metabolites such as sarcosine, acylcarnitine, and arachidonoilamine have been identified as demonstrating high sensitivity and specificity in the diagnosis of PCa. Alterations in carbohydrate and lipid metabolism, as well as activation of the pentose phosphate pathway, were also observed in PCa cells. Conclusion. The use of GC-MS for VOC analysis in urine is a promising method for diagnosing prostate cancer, offering high accuracy and non-invasiveness. However, implementing this method into clinical practice requires addressing several technical and methodological issues, including standardizing protocols and reducing equipment costs. Further development of metabolomics and refinement of analytical methods could significantly improve early PCa diagnosis, positively impacting prognosis and quality of life for patients.