Biomarker-guided immunotherapy selection uses tumor expression of a predictive marker (PD-L1) to stratify patients by likelihood of response to checkpoint-inhibitor therapy relative to conventional chemotherapy, with higher marker expression associated with greater relative benefit though neither necessary nor sufficient for response. This intersects with reflex molecular/genomic testing for actionable driver mutations, which independently predicts differential benefit from targeted therapy versus immunotherapy and can carry sequencing-related toxicity risk if therapies are ordered incorrectly; testing turnaround-time tradeoffs (rapid single-marker assays vs. broader next-generation sequencing panels vs. plasma-based liquid biopsy) create a treatment-sequencing decision problem balancing time-to-treatment against completeness of predictive information. This belongs to precision/molecular oncology within non-small-cell lung cancer management, connecting biomarker science to clinical treatment-selection algorithms.
Biomarker-guided immunotherapy selection uses tumor expression of a predictive marker (PD-L1) to stratify patients by likelihood of response to checkpoint-inhibitor therapy relative to conventional c…