Abstract
Lung carcinoma is one of the most deadly malignant tumors in mankind. With the rising incidence of lung cancer, searching for the high effective cures become more and more imperative. There has been sufficient research evidence that living habits and situations such as smoking and air pollution are associated with an increased risk of lung cancer. Simultaneously, the influence of individual genetic susceptibility on lung carcinoma morbidity has been confirmed, and a growing body of evidence has been accumulated on the relationship between various risk factors and the risk of different pathological types of lung cancer. Additionally, the analyses from many large-scale cancer registries have shown a degree of familial aggregation of lung cancer. To explore lung cancer-related genetic factors, Genome-Wide Association Studies (GWAS) have been used to identify several lung cancer susceptibility sites and have been widely validated. However, the biological mechanism behind the impact of these site mutations on lung cancer remains unclear. Therefore, this study applied the Summary data-based Mendelian Randomization (SMR) model through the integration of two GWAS datasets and four expression Quantitative Trait Loci (eQTL) datasets to identify susceptibility genes. Using this strategy, we found ten of Single Nucleotide Polymorphisms (SNPs) sites that affect the occurrence and development of lung tumors by regulating the expression of seven genes. Further analysis of the signaling pathway about these genes not only provides important clues to explain the pathogenesis of lung cancer but also has critical significance for the diagnosis and treatment of lung cancer.
Highlights
IntroductionAccording to the Global Cancer Statistics report, there were about 2 million newly detected lung cancer cases worldwide in 2018, accounting for 11.6% of all tumors (Bray et al, 2018)
Pulmonary carcinoma is the leading cause of cancer deaths in the world
We performed four Summary data-based Mendelian Randomization (SMR) analyses by using Genome-Wide Association Studies (GWAS) summary data from a large meta-analysis to examine the association between lung cancer and gene expression probes from four expression Quantitative Trait Loci (eQTL) data
Summary
According to the Global Cancer Statistics report, there were about 2 million newly detected lung cancer cases worldwide in 2018, accounting for 11.6% of all tumors (Bray et al, 2018). Deaths from lung cancer worldwide were roughly 1.7 million, accounting for 18.4% of tumor-related deaths. Of all diagnosed cases of lung cancer, NSCLC accounts for about 85% (Oser et al, 2015). SCLC is a small proportion, it grows and spreads faster than NSCLC and tends to metastasize early in the disease (Zakaria et al, 2015). Bearing these facts in mind, the therapy of lung cancer faces a serious challenge
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