WCLC 2025 - Posters & ePosters-EP.06.47 A Ten-Gene DNA Damage Repair-Related Signature for Predicting Prognosis and Treatment Response in Non-Small Cell Lung Cancer

EP.06.47 A Ten-Gene DNA Damage Repair-Related Signature for Predicting Prognosis and Treatment Response in Non-Small Cell Lung Cancer

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This study developed and validated a prognostic model based on a ten-gene DNA damage repair (DDR) signature to predict outcomes and treatment response in non-small cell lung cancer (NSCLC). DDR is crucial for maintaining genome integrity and influences cancer development, progression, and response to therapy. Given common DDR alterations in NSCLC, the authors aimed to use DDR-related gene expression to stratify patient risk and improve prognostic accuracy.<br /><br />Using publicly available datasets, the authors first curated 644 DDR-related genes. They applied univariate Cox regression and a 1000-iteration LASSO Cox regression for feature selection on the GSE68465 training cohort (n=462), retaining genes selected at high frequency. A multivariate Cox regression model was constructed from the ten identified genes: WDHD1, PIAS1, WRNIP1, DDIT4, SMARCA4, PIK3R1, ARID1A, TP53BP1, ZBTB40, and APTX. This DDR risk score stratified patients into high- and low-risk groups with significantly different overall survival (OS). The model’s prognostic value was externally validated in an independent TCGA-LUAD cohort (n=589).<br /><br />Combining the DDR score with clinical parameters into a nomogram allowed individualized survival prediction with strong calibration and discrimination metrics (concordance index and ROC). High DDR risk correlated with an immunosuppressive tumor microenvironment, characterized by increased myeloid-derived suppressor cells and reduced CD8+ T cells, B cells, macrophages, and dendritic cells, suggesting implications for immunotherapy responsiveness.<br /><br />The study concludes that the ten-gene DDR signature is a robust, clinically relevant prognostic tool for NSCLC that enhances risk stratification beyond traditional clinical factors. Future research should prospectively validate this model in larger cohorts, elucidate mechanisms linking DDR alterations to immune evasion, and explore its utility across other cancers and in predicting immunotherapy outcomes.

Asset Subtitle

Huixia Li

Meta Tag

Speaker Huixia Li

Topic Pathology and Biomarkers

Keywords

DNA damage repair

DDR signature

non-small cell lung cancer

NSCLC prognosis

ten-gene model

LASSO Cox regression

overall survival prediction

tumor microenvironment

immunotherapy response

risk stratification