Abstract

ADVANCES IN BIOMARKER-BASED IMMUNODIAGNOSTICS FOR PROSTATE CANCER

Ashraful Alam, Daniel Kofi Nyame and Xiaohui Zhou*

ABSTRACT

The development of advanced biomarker-based immunodiagnostics is crucial in prostate cancer therapy to improve detection, risk stratification, and treatment monitoring. Currently, traditional biomarkers for prostate cancer, like PSA and its derivatives, are prone to having low specificity, necessitating unnecessary biopsies. Biomarkers emerging in various forms, such as PCA3, TMPRSS2-ERG, 4Kscore, and PHI, enhance diagnostic accuracy and immune-related biomarkers, cytokine profiling, and immune cell infiltration patterns and provide insight regarding tumor immunology. Techniques such as ELISA, immunohistochemistry (IHC), and flow cytometry improve sensitive detection of biomarkers, and techniques such as machine learning (ML) and artificial intelligence (AI) improve predictive capability and clinical decision. Liquid biopsy-based approaches, such as circulating tumor cells (CTCs) and extracellularvesicles (EVs), are integrated as a minimally invasive alternative to monitoring tumor progression in real-time. Moreover, point-of-care (POC) diagnostic platforms improve the accessibility and efficiency of PCa detection. Despite this, issues pertaining to standardization and repetition of assays, as well as lack of sensitivity and specificity and integration of multiple omics, are remaining problems. In future studies, large-scale validation studies must be conducted, AI-driven diagnostics must be refined, and personalized immunotherapeutic approaches must be developed.

Keywords: Prostate cancer, Biomarkers, Immunodiagnostics, Liquid biopsy, Machine learning.