INVESTIGATING THE CLINICAL OUTCOMES OF COMBINATION IMMUNOTHERAPY AND TARGETED THERAPY IN ADVANCED NON SMALL CELL LUNG CANCER PATIENTS
Keywords:
EGFR Mutation, Non-Small Cell Lung Cancer, Tyrosine Kinase Inhibitors, Immune Checkpoint Inhibitors, Combination Therapy, Acquired ResistanceAbstract
Combination of tyrosine kinase and immune checkpoint inhibitors can be a potentially effective, therapeutic strategy to overcome the resistance in non-small cell lung cancer harboring a mutated EGFR and distribution of response and resistance are not uniformly distributed in clinical practice and mechanism of the response and resistance are not well understood. This mixed-methods study was a synthesis of 24 studies, including 4,872 patients, of a systematic review, meta-analysis, and qualitative synthesis, which was a mechanistic synthesis. The random-effects models were used to calculate the pooled hazard ratios of progression-free survival and overall survival. Subgroup analyses based on the mechanism of resistance, sequence of treatment and biomarker, such as radiogenomic, circulating tumor DNA, multi-omics, and ferroptosis-related markers. The third-generation TKI-ICI combinations had a better survival than the first/second-generation combinations , but The order of the treatment was also a major determinant of efficacy where anti-VEGF and ICI run simultaneously had a hazard ratio of 0.68 of progression-free survival and anti-VEGF run alone before ICI had a hazard ratio of 1.31. The ferroptosis-sensitive phenotype (GPX4 Low / ACSL4 High) was strongly correlated with the good outcomes, and the poor response with the resistant phenotype (HR 1.62). A clearance of ctDNA in week 3 (HR 0.52) and the multi-omics signatures were predicted to yield good results with an area under the curve of up to 0.81 to predict the progression-free survival at 12 months. The reaction of TKI-ICI combinations to EGFR-mutant NSCLC greatly depends on the resistance mechanism, sequence of therapy, and molecular biomarkers like the ferroptosis state and ctDNA dynamics. The foundation of adaptive, biomarker-guided combination strategies to optimize the timing of treatment and allow real-time monitoring of resistance to promote long-term clinical outcomes is based on such results.












