Identification of genetically predicted DNA methylation markers associated with non–small cell lung cancer risk among 34,964 cases and 448,579 controls
Authors: Zhao Xiaoyu , Yang Meiqi , Fan Jingyi , Wang Mei , Wang Yifan , Qin Na , Zhu Meng , Jiang Yue , Gorlova Olga Y. , Gorlov Ivan P. , Albanes Demetrius , Lam Stephen , Tardón Adonina , Chen Chu , Goodman Gary E. , Bojesen Stig E. , Landi Maria Teresa , Johansson Mattias , Risch Angela , Wichmann H.‐Erich , Bickeböller Heike , Christiani David C. , Rennert Gad , Arnold Susanne M. , Brennan Paul , Field John K. , Shete Sanjay , Le Marchand Loïc , Liu Geoffrey , Hung Rayjean J. , Andrew Angeline S. , Kiemeney Lambertus A. , Zienolddiny Shanbeh , Grankvist Kjell , Johansson Mikael , Caporaso Neil E. , Woll Penella J. , Lazarus Philip , Schabath Matthew B. , Aldrich Melinda C. , Patel Alpa V. , Davies Michael P. A. , Ma Hongxia , Jin Guangfu , Hu Zhibin , Amos Christopher I. , Shen Hongbing , Dai Juncheng 
Published: December 2023

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.