Abstract 3417: Dissecting tumor microenvironment to predict clinical outcome in prostate cancer

Abstract

Abstract Prostate cancer is one of the major causes of cancer death in males, and its prevalence is particularly high in developed countries such as the United States and Western Europe. However, death rates in developing and underdeveloped countries are greater, presumably, due to a lack of routine clinical check-ups, poor health awareness, inadequate screening resources, and clinical intervention. Much progress has already been made using cutting-edge technologies like whole genome sequencing, RNAseq, phosphoproteomics, and targeted transcriptomic Nanostring profiling, etc. However, understanding of the prostate tumor microenvironment as a whole in clinical samples remains very limited. Here we use the latest genomic, proteomics, and metabolomic tools not only to understand the biology of prostate cancers but also their correlation with patient demography and clinical outcome. We recruited 80 patients from both tertiary research hospitals and clinical centers in the eastern region of India. All of their demographic information is collected along with their clinical outcome. Pathological evaluation revealed only 50 patients with positive Prostate Carcinoma. We performed a detailed analysis using experimental data (from genomic, and proteomic) in a cohort of patients' routine biomarkers (PSA and PSMA), histopathology, and clinical outcome. Our data demonstrate no linear correlation of any of the individual markers or parameters like AR status, PSA, Prostate Specific Acid Phosphatase, Prostate-Specific Membrane Antigen (PSMA), Alpha-methylacyl-CoA racemase (AMACR), Mesothelin, PD-L1, and other potential genomic and proteomic alterations or any histopathological readouts. However, a clear understanding of the relationship between these multiparameter data, disease pathology, and clinical outcomes in a group of patients has been established. The heterogeneity of these individual data for tumor microenvironments will lead us to identify novel biomarkers for the clinical response of targeted drugs, accelerating personalized treatment strategies. Citation Format: Aritri Bhattacharjee, Manjusha Biswas, Amjad Husain, Asim Kr Das, Sourav Karmakar Karmakar, Tapan Mondal, Pinaki Roy, Manas Kr Mondal, Badal Kumar Sahu, Nabendu Murmu, Partho Nath, Chandra C. Ghosh, Pradip Kumar Majumder. Dissecting tumor microenvironment to predict clinical outcome in prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3417.