Decoding Senescence‐Driven Heterogeneity in Early‐Onset Colorectal Cancer for Prognostic and Therapeutic Stratification

Early-onset colorectal cancer (EOCRC), diagnosed in patients under 50, is particularly aggressive, yet lacks targeted therapeutic strategies. This study aimed to explore the role of cellular senescence in driving EOCRC's malignancy and developed a senescence scoring system (EO-Senscore) to guide precision oncology. Through a multi-omics analysis of 2961 patients, we discovered that cellular senescence is more pronounced and varied in EOCRC and is not tied to chronological age. Two distinct senescence subtypes were identified: Cluster 1 (low-senescence tumors) showed prolonged survival, enhanced immunogenicity, and cell cycle activation, while Cluster 2 (high-senescence tumors) exhibited aggressive phenotypes and an immunosuppressive microenvironment. We further developed a machine learning model, the EO-Senscore, to quantify a tumor's senescence level. This score effectively stratified patients by prognosis and potential treatment response. Patients with a low EO-Senscore were predicted to respond well to immunotherapy and chemotherapy. In contrast, those with a high score had more invasive tumors but showed significant sensitivity to senolytic drugs (like ABT-263) in lab-based experiments. In conclusion, this research establishes cellular senescence as a crucial factor in EOCRC's aggressiveness. The EO-Senscore provides a practical, quantitative tool to guide clinical decisions, suggesting that patients could be directed toward immunotherapy or novel senolytic-based combination therapies for more personalized and effective cancer care.