Optimizing T cell inflamed signature through a combination biomarker approach for predicting immunotherapy response in NSCLC
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View abstract on PubMed
Summary
This summary is machine-generated.New biomarkers combining T cell inflammation and immune alteration signatures improve prediction of anti-programmed cell death protein 1 (PD-1) therapy response in non-small cell lung cancer (NSCLC). This approach offers better patient stratification for immunotherapy.
Area Of Science
- Immunology
- Oncology
- Genomics
Background
- Anti-PD-1/PD-L1 therapies offer revolutionary treatment for advanced non-small cell lung cancer (NSCLC).
- Response rates to these therapies are modest, highlighting the need for predictive biomarkers.
- A previously established T cell-inflamed gene expression profile (GEP) failed to predict anti-PD-1 response in a large NSCLC cohort.
Purpose Of The Study
- To develop and validate novel predictive biomarkers for anti-PD-1/PD-L1 therapy in NSCLC.
- To investigate the role of myeloid and stromal cell gene signatures in predicting treatment response.
- To explore mechanistic insights into immune alterations affecting immunotherapy efficacy.
Main Methods
- Re-analysis of the Stand Up To Cancer-Mark (SU2C-MARK) Foundation NSCLC cohort.
- Development of a combination biomarker integrating T cell-inflamed GEP with immune-altered signatures using machine learning.
- Validation of the combined biomarkers in six independent cancer cohorts treated with anti-PD-1 therapy.
Main Results
- The T cell-inflamed GEP alone was not predictive in NSCLC.
- Combining the T cell-inflamed GEP with myeloid cell gene signatures significantly improved predictive performance.
- The novel combination biomarkers demonstrated enhanced predictive ability in NSCLC and gastric cancer cohorts, but not in melanoma cohorts.
Conclusions
- A combination biomarker approach integrating T cell-inflamed GEP and immune-altered signatures shows promise for predicting anti-PD-1/PD-L1 response in NSCLC.
- These novel biomarkers offer improved patient stratification for immunotherapy in NSCLC.
- The study provides mechanistic insights into immune alterations influencing immunotherapy efficacy.
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