Co-occurring genomic alterations and immunotherapy efficacy in NSCLC

Area of Science:

• Oncology
• Genetics
• Immunotherapy

Background:

• Non-small cell lung cancer (NSCLC) classification is increasingly oncogene-centric.
• Tumor heterogeneity, influenced by co-occurring mutations, can affect treatment response, particularly to immune checkpoint inhibitors (ICIs).

Purpose of the Study:

• To analyze the impact of co-occurring mutations on ICI efficacy in NSCLC.
• To develop improved prediction models for ICI benefit by incorporating mutation interaction effects.

Main Methods:

• Analysis of molecular data from 1745 NSCLC cases.
• Development and validation of prediction models incorporating single mutations and mutation interaction terms.
• Evaluation of model performance irrespective of tumor mutational burden and PD-L1 status.

Main Results:

• Identified significant interaction effects of KRAS co-mutations with TP53, STK11, PTPRD, RBM10, and ATM in nonsquamous NSCLC.
• Prediction models including interaction terms (inter-models) demonstrated improved discriminative utility over single-mutation models.
• Inter-model scores were independent predictors of ICI benefit, showing effectiveness regardless of tumor mutational burden or PD-L1 expression.

Conclusions:

• Co-occurring mutations play a critical role in NSCLC response to ICIs.
• Incorporating mutation interaction terms into prediction algorithms enhances patient selection for immunotherapy.
• This approach offers novel insights into NSCLC immunobiology and therapeutic strategies.