Integrative analysis of genetic and epigenetic profiling of lung squamous cell carcinoma (LSCC) patients to identify smoking level relevant biomarkers

被引:6
|
作者
Ma, Bidong [1 ]
Huang, Zhiyou [1 ]
Wang, Qian [2 ]
Zhang, Jizhou [1 ]
Zhou, Bin [1 ]
Wu, Jiaohong [3 ]
机构
[1] Zhe Jiang Chinese Med Univ, Affiliated Chinese Med Hosp, Dept Med Oncol, Wenzhou, Zhejiang, Peoples R China
[2] Tianjia Genomes Tech CO LTD, 6 Longquan Rd, Hefei 238014, Anhui, Peoples R China
[3] Wen Zhou Med Univ, Affiliated Peoples Hosp, Dept Gynecol & Oncol, Wenzhou, Zhejiang, Peoples R China
关键词
Lung squamous cell carcinoma; Data mining; RNA-seq; Methylation; The Cancer genome atlas; Smoking intensity; BODY-MASS INDEX; OF-FUNCTION MUTATIONS; CIGARETTE-SMOKE; DOPAMINE TRANSPORTER; FGFR1; AMPLIFICATION; ENDOTHELIAL-CELL; TOBACCO-SMOKE; GENDER-DIFFERENCES; CPG METHYLATION; CANCER;
D O I
10.1186/s13040-019-0207-y
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background Incidence and mortality of lung cancer have dramatically decreased during the last decades, yet still approximately 160,000 deaths per year occurred in United States. Smoking intensity, duration, starting age, as well as environmental cofactors including air-pollution, showed strong association with major types of lung cancer. Lung squamous cell carcinoma is a subtype of non-small cell lung cancer, which represents 25% of the cases. Thus, exploring the molecular pathogenic mechanisms of lung squamous cell carcinoma plays crucial roles in lung cancer clinical diagnosis and therapy. Results In this study, we performed integrative analyses on 299 comparative datasets of RNA-seq and methylation data, collected from 513 lung squamous cell carcinoma cases in The Cancer Genome Atlas. The data were divided into high and low smoking groups based on smoking intensity (Numbers of packs per year). We identified 1002 significantly up-regulated genes and 534 significantly down-regulated genes, and explored their cellular functions and signaling pathways by bioconductor packages GOseq and KEGG. Global methylation status was analyzed and visualized in circular plot by CIRCOS. RNA-and methylation data were correlatively analyzed, and 24 unique genes were identified, for further investigation of regional CpG sites' interactive patterns by bioconductor package coMET. AIRE, PENK, and SLC6A3 were the top 3 genes in the high and low smoking groups with significant differences. Conclusions Gene functions and DNA methylation patterns of these 24 genes are important and useful in disclosing the differences of gene expression and methylation profiling caused by different smoking levels.
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页数:18
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