Genomic and Phenotypic Biomarkers for Precision Medicine Guidance in Advanced Prostate Cancer.

Prostate cancer (PCa) is the second most diagnosed malignant neoplasm and is one of the leading causes of cancer-related death in men worldwide. Despite significant advances in screening and treatment of PCa, given the heterogeneity of this disease, optimal personalized therapeutic strategies remain limited. However, emerging predictive and prognostic biomarkers based on individual patient profiles in combination with computer-assisted diagnostics have the potential to guide precision medicine, where patients may benefit from therapeutic approaches optimally suited to their disease. Also, the integration of genotypic and phenotypic diagnostic methods is supporting better informed treatment decisions. Focusing on advanced PCa, this review discusses polygenic risk scores for screening of PCa and common genomic aberrations in androgen receptor (AR), PTEN-PI3K-AKT, and DNA damage response (DDR) pathways, considering clinical implications for diagnosis, prognosis, and treatment prediction. Furthermore, we evaluate liquid biopsy, protein biomarkers such as serum testosterone levels, SLFN11 expression, total alkaline phosphatase (tALP), neutrophil-to-lymphocyte ratio (NLR), tissue biopsy, and advanced imaging tools, summarizing current phenotypic biomarkers and envisaging more effective utilization of diagnostic and prognostic biomarkers in advanced PCa. We conclude that prognostic and treatment predictive biomarker discovery can improve the management of patients, especially in metastatic stages of advanced PCa. This will result in decreased mortality and enhanced quality of life and help design a personalized treatment regimen.

Current treatment options in oncology. 2023 Aug 10 [Epub ahead of print]

Fatemeh Davoudi, Afshin Moradi, Therese M Becker, John G Lock, Brian Abbey, Davide Fontanarosa, Annette Haworth, Judith Clements, Rupert C Ecker, Jyotsna Batra

School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, 4059, Australia., Ingham Institute for Applied Medical Research, University of Western Sydney and University of New South Wales, Liverpool, 2170, Australia., Department of Mathematical and Physical Sciences, School of Computing Engineering and Mathematical Sciences, La Trobe Institute for Molecular Sciences, La Trobe University, Bundoora, VIC, Australia., School of Clinical Sciences, Queensland University of Technology, Gardens Point Campus, 2 George St, Brisbane, QLD, 4000, Australia., Institute of Medical Physics, School of Physics, University of Sydney, Camperdown, NSW, 2006, Australia., School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, 4059, Australia. .