Core Insights - The development of DiffInvex, an innovative computational framework by the Barcelona Institute of Biomedical Research, allows tracking the transformation of healthy cells into tumors and the genetic evolutionary pressures tumors face during chemotherapy [1][2] - The study, published in Nature Communications, analyzed over 11,000 samples across approximately 30 different tissue types, successfully identifying pathways that lead to tumor resistance to treatment and pinpointing genes that may trigger drug resistance [1][2] Group 1 - DiffInvex establishes a baseline for "neutral" mutation rates by analyzing mutations in important coding and non-coding gene regions, thereby eliminating uncertainties in assessments [2] - The research identified 11 genes with significantly increased mutation frequencies after specific types of chemotherapy, including known key driver genes such as IK3CA, SMAD4, and STK11 [2] - The study compared 1,722 genomes from healthy tissues and corresponding tumor types, revealing that some cancer drivers may be evolutionary products rather than direct initiators of the disease [2] Group 2 - The findings provide potential for rational drug combination designs, suggesting that combining standard chemotherapy with inhibitors targeting PIK3CA or STK11 signaling pathways may delay or prevent cancer recurrence [2] - The research contributes to improving early detection methods, potentially reducing unnecessary anxiety for patients [2] - This study represents a breakthrough in understanding tumor survival strategies and offers a new perspective on the evolutionary mechanisms of tumors during chemotherapy [3]