This project aims to validate a novel diagnostic tool for prostate cancer that integrates multiplex biomarkers with AI-based spatial image analysis. The scientific objective is to establish the prognostic utility of a dual-color immunohistochemical assay targeting fibroblast activation protein (FAP) and alpha-smooth muscle actin (aSMA). By combining these biomarkers with machine learning, the goal is to improve the differentiation between aggressive and indolent prostate cancers, thereby enhancing treatment decision-making. Societal benefits include reducing unnecessary surgeries and associated complications, improving patient outcomes, and optimizing healthcare resources. This proof-of-concept approach has the potential to be extended to other biomarkers and diagnostic applications in the future.

2025

2026