A Novel DNA Repair‐Gene Model to Predict Responses to Immunotherapy and Prognosis in Patients With EGFR‐Mutant Non‐Small Cell Lung Cancer

TL;DR

A new DNA repair gene model helps predict immunotherapy responses and prognosis in patients with EGFR-mutant lung cancer.

Contribution

A novel DDR-based model identifies high- and low-risk subtypes of EGFRm NSCLC with distinct immunotherapy responses and prognostic outcomes.

Findings

Two subtypes of EGFRm NSCLC were identified: DDR-activated and DDR-suppressed, with differing clinical behavior and prognosis.

A four-gene DDR model (CAPS, FAM83A, IGLV8-61, SLC7A5) serves as an independent prognostic indicator.

Low-risk patients showed better immunotherapy response and distinct immune profiles compared to high-risk patients.

Abstract

The epidermal growth factor receptor mutant (EGFRm) non‐small cell lung cancer (NSCLC) has a unique “cold” immune profile. DNA damage repair (DDR) genes are closely related to tumorigenesis and the effectiveness of immunotherapy in many tumors. However, the role and mechanism of DDR in the genesis and progression of EGFRm NSCLC remain unclear.

This study included 101 EGFRm NSCLC samples from The Cancer Genome Atlas (TCGA) dataset and a GSE31210 dataset (external set) from the GEO database. Cluster analysis was used to identify different subtypes of EGFRm NSCLC based on the expression of DDR genes. Univariate and LASSO regression analysis was used to develop a DDR‐based predictive model. The prognostic significance of this model was assessed using Cox regression, Kaplan–Meier, and receiver operating characteristic (ROC) curve analyses. Bioinformatics analysis was performed to investigate the clinicopathological characteristics and immune profiles associated with this model. In vitro experiment was performed to testify the role of DDR genes in EGFRm NSCLC.

We identified two subtypes of EGFRm NSCLC: DDR‐activated and DDR‐suppressed. The DDR‐activated subtype showed more aggressive clinical behavior and poorer prognosis and was more responsive to immunotherapy. A prognostic model for EGFRm NSCLC was constructed using four DDR genes: CAPS, FAM83A, IGLV8‐61, and SLC7A5. The derived risk score could serve as an independent prognostic indicator. High‐ and low‐risk patients exhibited distinct clinicopathological characteristics, immune profiles, and responses to immunotherapy. The T‐cell inflammation and Tumor Immune Dysfunction and Exclusion (TIDE) scores differed between the high‐ and low‐risk subgroups, with both showing enhanced effectiveness of immunotherapy in the low‐risk subgroup. Targeted therapy such as BI.2536, an inhibitor of polo‐like kinase 1, could be effective for patients with high‐risk EGFRm NSCLC. Meanwhile, in vitro detection approved the role of DDR genes in EGFRm NSCLC response.

This study demonstrated a diversity of DDR genes in EGFRm NSCLC and developed a predictive model using these genes. This model could assist in identifying potential candidates for immunotherapy and in assessing personalized treatment and prognosis of patients with EGFRm NSCLC.

We developed a novel DNA damage repair (DDR)‐based prognostic model for EGFR‐mutant non‐small cell lung cancer (NSCLC). Patients were stratified into high risk and low risk subtypes, with significant differences in clinical and biological features. This model highlights a unique molecular approach for predicting prognosis and immunotherapy responses, providing a basis for personalized treatment strategies. (The graph is generated by Figdrow).

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