Identification of genetically predicted DNA methylation markers associated with non–small cell lung cancer risk among 34,964 cases and 448,579 controls

Xiaoyu Zhao, Meiqi Yang, Jingyi Fan, Mei Wang, Yifan Wang, Na Qin, Meng Zhu, Yue Jiang, Olga Y. Gorlova, Ivan P. Gorlov, Demetrius Albanes, Stephen Lam, Adonina Tardón, Chu Chen, Gary E. Goodman, Stig E. Bojesen, Maria Teresa Landi, Mattias Johansson, Angela Risch, H. Erich WichmannHeike Bickeböller, David C. Christiani, Gad Rennert, Susanne M. Arnold, Paul Brennan, John K. Field, Sanjay Shete, Loïc Le Marchand, Geoffrey Liu, Rayjean J. Hung, Angeline S. Andrew, Lambertus A. Kiemeney, Shanbeh Zienolddiny, Kjell Grankvist, Mikael Johansson, Neil E. Caporaso, Penella J. Woll, Philip Lazarus, Matthew B. Schabath, Melinda C. Aldrich, Alpa V. Patel, Michael P.A. Davies, Hongxia Ma, Guangfu Jin, Zhibin Hu, Christopher I. Amos, Hongbing Shen, Juncheng Dai

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Although the associations between genetic variations and lung cancer risk have been explored, the epigenetic consequences of DNA methylation in lung cancer development are largely unknown. Here, the genetically predicted DNA methylation markers associated with non–small cell lung cancer (NSCLC) risk by a two-stage case-control design were investigated. Methods: The genetic prediction models for methylation levels based on genetic and methylation data of 1595 subjects from the Framingham Heart Study were established. The prediction models were applied to a fixed-effect meta-analysis of screening data sets with 27,120 NSCLC cases and 27,355 controls to identify the methylation markers, which were then replicated in independent data sets with 7844 lung cancer cases and 421,224 controls. Also performed was a multi-omics functional annotation for the identified CpGs by integrating genomics, epigenomics, and transcriptomics and investigation of the potential regulation pathways. Results: Of the 29,894 CpG sites passing the quality control, 39 CpGs associated with NSCLC risk (Bonferroni-corrected p ≤ 1.67 × 10−6) were originally identified. Of these, 16 CpGs remained significant in the validation stage (Bonferroni-corrected p ≤ 1.28 × 10−3), including four novel CpGs. Multi-omics functional annotation showed nine of 16 CpGs were potentially functional biomarkers for NSCLC risk. Thirty-five genes within a 1-Mb window of 12 CpGs that might be involved in regulatory pathways of NSCLC risk were identified. Conclusions: Sixteen promising DNA methylation markers associated with NSCLC were identified. Changes of the methylation level at these CpGs might influence the development of NSCLC by regulating the expression of genes nearby. Plain Language Summary: The epigenetic consequences of DNA methylation in lung cancer development are still largely unknown. This study used summary data of large-scale genome-wide association studies to investigate the associations between genetically predicted levels of methylation biomarkers and non–small cell lung cancer risk at the first time. This study looked at how well larotrectinib worked in adult patients with sarcomas caused by TRK fusion proteins. These findings will provide a unique insight into the epigenetic susceptibility mechanisms of lung cancer.

Original languageEnglish
Pages (from-to)913-926
Number of pages14
JournalCancer
Volume130
Issue number6
DOIs
StatePublished - Mar 15 2024

Bibliographical note

Publisher Copyright:
© 2023 American Cancer Society.

Keywords

  • DNA methylation
  • association study
  • gene expression
  • genetic prediction
  • non–small cell lung cancer risk

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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