Identification of Immuno-Diagnostic and Therapeutic Markers in Tumors and Inflammatory Diseases Based on Single-Cell and Machine Learning Methods

Background

Chemotherapy is the mainstay of systemic treatment for colorectal cancer (CRC), but drug resistance and tumor heterogeneity markedly limit survival. Mitochondrial metabolism is increasingly recognized as a regulator of tumor progression, immune contexture, and therapeutic response. However, the prognostic relevance of mitochondrial metabolism-related transcriptional patterns and their relationships with chemotherapy-response signatures and immune features in CRC remain incompletely understood.