A trans-omics assessment of gene-gene interaction in early-stage NSCLC

Jiajin Chen; Yunjie Song; Yi Li; Yongyue Wei; Sipeng Shen; Yang Zhao; Dongfang You; Li Su; Maria Moksnes Bjaanaes; Anna Karlsson; Maria Planck; Johan Staaf; Åslaug Helland; Manel Esteller; Hongbing Shen; David C Christiani; Ruyang Zhang; Feng Chen

doi:10.1002/1878-0261.13345

A trans-omics assessment of gene-gene interaction in early-stage NSCLC

Mol Oncol. 2023 Jan;17(1):173-187. doi: 10.1002/1878-0261.13345. Epub 2022 Dec 5.

Authors

Jiajin Chen¹, Yunjie Song¹, Yi Li², Yongyue Wei^{1

3

4}, Sipeng Shen¹, Yang Zhao¹, Dongfang You¹, Li Su^{3

5}, Maria Moksnes Bjaanaes⁶, Anna Karlsson⁷, Maria Planck⁷, Johan Staaf⁷, Åslaug Helland^{6

8}, Manel Esteller^{9

10

11

12}, Hongbing Shen^{4

13

14}, David C Christiani^{3

5}, Ruyang Zhang^{1

3

4}, Feng Chen^{1

4

14

15}

Affiliations

¹ Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
² Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
³ Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
⁴ China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China.
⁵ Pulmonary and Critical Care Division, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
⁶ Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway.
⁷ Division of Oncology, Department of Clinical Sciences Lund and CREATE Health Strategic Center for Translational Cancer Research, Lund University, Lund, Sweden.
⁸ Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
⁹ Josep Carreras Leukaemia Research Institute, Barcelona, Spain.
¹⁰ Centro de Investigacion Biomedica en Red Cancer, Madrid, Spain.
¹¹ Institucio Catalana de Recerca i Estudis Avançats, Barcelona, Spain.
¹² Physiological Sciences Department, School of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain.
¹³ Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.
¹⁴ Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Cancer Center, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China.
¹⁵ State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China.

Abstract

Epigenome-wide gene-gene (G × G) interactions associated with non-small-cell lung cancer (NSCLC) survival may provide insights into molecular mechanisms and therapeutic targets. Hence, we proposed a three-step analytic strategy to identify significant and robust G × G interactions that are relevant to NSCLC survival. In the first step, among 49 billion pairs of DNA methylation probes, we identified 175 775 G × G interactions with P_Bonferroni ≤ 0.05 in the discovery phase of epigenomic analysis; among them, 15 534 were confirmed with P ≤ 0.05 in the validation phase. In the second step, we further performed a functional validation for these G × G interactions at the gene expression level by way of a two-phase (discovery and validation) transcriptomic analysis, and confirmed 25 significant G × G interactions enriched in the 6p21.33 and 6p22.1 regions. In the third step, we identified two G × G interactions using the trans-omics analysis, which had significant (P ≤ 0.05) epigenetic cis-regulation of transcription and robust G × G interactions at both the epigenetic and transcriptional levels. These interactions were cg14391855 × cg23937960 (β_interaction = 0.018, P = 1.87 × 10^-12 ), which mapped to RELA × HLA-G (β_interaction = 0.218, P = 8.82 × 10^-11 ) and cg08872738 × cg27077312 (β_interaction = -0.010, P = 1.16 × 10^-11 ), which mapped to TUBA1B × TOMM40 (β_interaction =-0.250, P = 3.83 × 10^-10 ). A trans-omics mediation analysis revealed that 20.3% of epigenetic effects on NSCLC survival were significantly (P = 0.034) mediated through transcriptional expression. These statistically significant trans-omics G × G interactions can also discriminate patients with high risk of mortality. In summary, we identified two G × G interactions at both the epigenetic and transcriptional levels, and our findings may provide potential clues for precision treatment of NSCLC.

Keywords: G × G interactions; NSCLC; overall survival; prognosis; trans-omics.

Publication types

Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural

MeSH terms

Carcinoma, Non-Small-Cell Lung* / drug therapy
DNA Methylation / genetics
Epigenome
Humans
Lung Neoplasms* / metabolism
Small Cell Lung Carcinoma* / genetics

Abstract

Publication types

MeSH terms

Grants and funding