Independent Validation of Early-Stage Non-Small Cell Lung Cancer Prognostic Scores Incorporating Epigenetic and Transcriptional Biomarkers With Gene-Gene Interactions and Main Effects

Chest. 2020 Aug;158(2):808-819. doi: 10.1016/j.chest.2020.01.048. Epub 2020 Feb 28.

Abstract

Background: DNA methylation and gene expression are promising biomarkers of various cancers, including non-small cell lung cancer (NSCLC). Besides the main effects of biomarkers, the progression of complex diseases is also influenced by gene-gene (G×G) interactions.

Research question: Would screening the functional capacity of biomarkers on the basis of main effects or interactions, using multiomics data, improve the accuracy of cancer prognosis?

Study design and methods: Biomarker screening and model validation were used to construct and validate a prognostic prediction model. NSCLC prognosis-associated biomarkers were identified on the basis of either their main effects or interactions with two types of omics data. A prognostic score incorporating epigenetic and transcriptional biomarkers, as well as clinical information, was independently validated.

Results: Twenty-six pairs of biomarkers with G×G interactions and two biomarkers with main effects were significantly associated with NSCLC survival. Compared with a model using clinical information only, the accuracy of the epigenetic and transcriptional biomarker-based prognostic model, measured by area under the receiver operating characteristic curve (AUC), increased by 35.38% (95% CI, 27.09%-42.17%; P = 5.10 × 10-17) and 34.85% (95% CI, 26.33%-41.87%; P = 2.52 × 10-18) for 3- and 5-year survival, respectively, which exhibited a superior predictive ability for NSCLC survival (AUC3 year, 0.88 [95% CI, 0.83-0.93]; and AUC5 year, 0.89 [95% CI, 0.83-0.93]) in an independent Cancer Genome Atlas population. G×G interactions contributed a 65.2% and 91.3% increase in prediction accuracy for 3- and 5-year survival, respectively.

Interpretation: The integration of epigenetic and transcriptional biomarkers with main effects and G×G interactions significantly improves the accuracy of prognostic prediction of early-stage NSCLC survival.

Keywords: early stage; interaction; multiomics; non-small cell lung cancer; prognostic score.

Publication types

  • Multicenter Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Aged
  • Biomarkers, Tumor / genetics*
  • Carcinoma, Non-Small-Cell Lung / genetics*
  • Carcinoma, Non-Small-Cell Lung / mortality
  • Carcinoma, Non-Small-Cell Lung / pathology
  • DNA Methylation
  • Disease Progression
  • Epigenesis, Genetic*
  • Epistasis, Genetic*
  • Female
  • Humans
  • Lung Neoplasms / genetics*
  • Lung Neoplasms / mortality
  • Lung Neoplasms / pathology
  • Male
  • Middle Aged
  • Neoplasm Staging
  • Prognosis
  • Survival Analysis

Substances

  • Biomarkers, Tumor