Artificial Intelligence to predict prognosis and response to chemoradiotherapy in colorectal cancer through the analysis of cancer-associated fibroblasts’ and tumour-associated macrophages’ expression

This project investigates the molecular mechanisms driving colorectal cancer (CRC) and early-onset colorectal cancer (EOCRC) progression, recurrence, and therapy resistance. By analyzing the expression of cancer-associated fibroblasts (CAFs), tumor-associated macrophages (TAMs), C3aR, and PV1 in CRC and EOCRC specimens using artificial neural networks, the study aims to develop biomarkers for prognosis and treatment response. Subgroup analyses by age and stage will explore differences in cellular and molecular profiles, paving the way for targeted strategies to combat cancer progression and drug resistance.