Massively parallel variant-to-function mapping determines functional regulatory variants of non-small cell lung cancer

Congcong Chen, Yang Li, Yayun Gu, Qiqi Zhai, Songwei Guo, Jun Xiang, Yuan Xie, Mingxing An, Chenmeijie Li, Na Qin, Yanan Shi, Liu Yang, Jun Zhou, Xianfeng Xu, Ziye Xu, Kai Wang, Meng Zhu, Yue Jiang, Yuanlin He, Jing Xu, Rong Yin, Liang Chen, Lin Xu, Juncheng Dai, Guangfu Jin, Zhibin Hu, Cheng Wang (), Hongxia Ma () and Hongbing Shen ()
Additional contact information
Congcong Chen: Nanjing Medical University
Yang Li: Nanjing Medical University
Yayun Gu: Nanjing Medical University
Qiqi Zhai: Nanjing Medical University
Songwei Guo: Nanjing Medical University
Jun Xiang: Nanjing Medical University
Yuan Xie: Nanjing Medical University
Mingxing An: Nanjing Medical University
Chenmeijie Li: Nanjing Medical University
Na Qin: Nanjing Medical University
Yanan Shi: Nanjing Medical University
Liu Yang: Nanjing Medical University
Jun Zhou: Nanjing Medical University
Xianfeng Xu: Nanjing Medical University
Ziye Xu: Nanjing Medical University
Kai Wang: Nanjing Medical University
Meng Zhu: Nanjing Medical University
Yue Jiang: Nanjing Medical University
Yuanlin He: Nanjing Medical University
Jing Xu: The First Affiliated Hospital of Nanjing Medical University
Rong Yin: Nanjing Medical University Affiliated Cancer Hospital
Liang Chen: The First Affiliated Hospital of Nanjing Medical University
Lin Xu: Nanjing Medical University Affiliated Cancer Hospital
Juncheng Dai: Nanjing Medical University
Guangfu Jin: Nanjing Medical University
Zhibin Hu: Nanjing Medical University
Cheng Wang: Nanjing Medical University
Hongxia Ma: Nanjing Medical University
Hongbing Shen: Nanjing Medical University

Nature Communications, 2025, vol. 16, issue 1, 1-16

Abstract: Abstract Genome-wide association studies have identified thousands of genetic variants associated with non-small cell lung cancer (NSCLC), however, it is still challenging to determine the causal variants and to improve disease risk prediction. Here, we applied massively parallel reporter assays to perform NSCLC variant-to-function mapping at scale. A total of 1249 candidate variants were evaluated, and 30 potential causal variants within 12 loci were identified. Accordingly, we proposed three genetic architectures underlying NSCLC susceptibility: multiple causal variants in a single haplotype block (e.g. 4q22.1), multiple causal variants in multiple haplotype blocks (e.g. 5p15.33), and a single causal variant (e.g. 20q11.23). We developed a modified polygenic risk score using the potential causal variants from Chinese populations, improving the performance of risk prediction in 450,821 Europeans from the UK Biobank. Our findings not only augment the understanding of the genetic architecture underlying NSCLC susceptibility but also provide strategy to advance NSCLC risk stratification.

Date: 2025
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DOI: 10.1038/s41467-025-56725-w

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