Potentially functional genetic variants in the TNF/TNFR signaling pathway genes predict survival of patients with non-small cell lung cancer in the PLCO cancer screening trial.
Date
2019-04-15
Journal Title
Journal ISSN
Volume Title
Repository Usage Stats
views
downloads
Citation Stats
Abstract
The tumor necrosis factor (TNF)/TNF receptor (TNFR) pathway is known to influence survival of patients with cancer. We hypothesize that single nucleotide polymorphisms (SNPs) in the TNF/TNFR pathway genes related to apoptosis are associated with survival of patients with non-small cell lung cancer (NSCLC). We used 1185 patients with NSCLC in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial and 984 patients with NSCLC in the Harvard Lung Cancer Susceptibility Study as the discovery and validation datasets, respectively. We selected 6788 SNPs in 71 genes in the TNF/TNFR signaling pathway and extracted their genotyping data from the PLCO genowide-association study (GWAS) dataset. We performed Cox proportional hazards regression analysis to evaluate associations between the identified SNPs and survival and validated the significant SNPs, which were further analyzed for their functional relevance. We found that genotypes of two validated SNPs, IKBKAP rs4978754 CT + TT and TNFRSF1B rs677844 TC + CC, as well as their combined genotypes predicted a better overall survival (P = 0.004, 0.002 and <0.001, respectively). These two validated SNPs were predicted by the RegulomeDB score to be potentially functional. In addition, IKBKAP mRNA expression levels were significantly higher, while TNFRSF1B mRNA expression levels were significantly lower in lung cancer tissues than in adjacent normal tissues (P < 0.001). The Cancer Genome Atlas (TCGA)-based expression quantitative trait loci analysis showed that IKBKAP rs4978754 and TNFRSF1B rs677844 genotypes were significantly associated with their corresponding mRNA expression levels in lung cancer tissues in a recessive model (P = 0.035 and 0.045, respectively). Therefore, we identified two potentially functional SNPs (IKBKAP rs4978754 C > T and TNFRSF1B rs677844 T > C) to be associated with survival of patients with NSCLC.
Type
Department
Description
Provenance
Citation
Permalink
Published Version (Please cite this version)
Publication Info
Guo, Yi, Yun Feng, Hongliang Liu, Sheng Luo, Jeffrey W Clarke, Patricia G Moorman, Li Su, Sipeng Shen, et al. (2019). Potentially functional genetic variants in the TNF/TNFR signaling pathway genes predict survival of patients with non-small cell lung cancer in the PLCO cancer screening trial. Molecular carcinogenesis. 10.1002/mc.23017 Retrieved from https://hdl.handle.net/10161/18473.
This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
Collections
Scholars@Duke
Sheng Luo
Patricia Gripka Moorman
Dr. Moorman's research focuses on the epidemiology of women's health issues. Her work includes research on ovarian cancer, breast cancer and hysterectomy. Areas of particular interest include disparities in cancer risk factors and outcomes and the effects of hysterectomy on ovarian function. As part of the Duke Evidence Synthesis group, she has also been involved in systematic reviews and meta-analyses related to ovarian cancer, breast cancer and infertility.
Qingyi Wei
Qingyi Wei, MD, PhD, Professor in the Department of Medicine, is Associate Director for Cancer Control and Population Sciences, Co-leader of CCPS and Co-leader of Epidemiology and Population Genomics (Focus Area 1). He is a professor of Medicine and an internationally recognized epidemiologist focused on the molecular and genetic epidemiology of head and neck cancers, lung cancer, and melanoma. His research focuses on biomarkers and genetic determinants for the DNA repair deficient phenotype and variations in cell death. He is Editor-in-Chief of the open access journal "Cancer Medicine" and Associate Editor-in-Chief of the International Journal of Molecular Epidemiology and Genetics.
Area of Expertise: Epidemiology
Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.