Bioinformatics Analysis Reveals Biomarkers With Cancer Stem Cell Characteristics in Lung Squamous Cell Carcinoma
BackgroundTumor stem cells play important roles in the survival, proliferation, metastasis and recurrence of tumors. We aimed to identify new prognostic biomarkers for lung squamous cell carcinoma (LUSC) based on the cancer stem cell theory.MethodsRNA-seq data and relevant clinical information were...
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doaj-1ce4a56d83fc4a61be89b23cd58a8b3e2020-11-25T03:01:15ZengFrontiers Media S.A.Frontiers in Genetics1664-80212020-05-011110.3389/fgene.2020.00427527635Bioinformatics Analysis Reveals Biomarkers With Cancer Stem Cell Characteristics in Lung Squamous Cell CarcinomaYi LiaoHua XiaoMengqing ChengXianming FanBackgroundTumor stem cells play important roles in the survival, proliferation, metastasis and recurrence of tumors. We aimed to identify new prognostic biomarkers for lung squamous cell carcinoma (LUSC) based on the cancer stem cell theory.MethodsRNA-seq data and relevant clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Weighted gene coexpression network analysis (WGCNA) was applied to identify significant modules and hub genes, and prognostic signatures were constructed with the prognostic hub genes.ResultsLUSC patients in the TCGA database have higher mRNA expression-based stemness index (mRNAsi) in tumor tissue than in adjacent normal tissue. In addition, some clinical features and outcomes were highly correlated with the mRNAsi. WGCNA revealed that the pink and yellow modules were the most significant modules related to the mRNAsi; the top 10 hub genes in the pink module were enriched mostly in epidermal development, the secretory granule membrane, receptor regulator activity and the cytokine-cytokine receptor interaction. The protein–protein interaction (PPI) network revealed that the top 10 hub genes were significantly correlated with each other at the transcriptional level. In addition, the top 10 hub genes were all highly expressed in LUSC, and some were differentially expressed in different TNM stages. Regarding the survival analysis, the nomogram of a prognostic signature with three hub genes showed high predictive value.ConclusionmRNAsi-related hub genes could be a potential biomarker of LUSC.https://www.frontiersin.org/article/10.3389/fgene.2020.00427/fulllung squamous cell carcinomacancer cell stemnessprognosisWGCNATCGA |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yi Liao Hua Xiao Mengqing Cheng Xianming Fan |
spellingShingle |
Yi Liao Hua Xiao Mengqing Cheng Xianming Fan Bioinformatics Analysis Reveals Biomarkers With Cancer Stem Cell Characteristics in Lung Squamous Cell Carcinoma Frontiers in Genetics lung squamous cell carcinoma cancer cell stemness prognosis WGCNA TCGA |
author_facet |
Yi Liao Hua Xiao Mengqing Cheng Xianming Fan |
author_sort |
Yi Liao |
title |
Bioinformatics Analysis Reveals Biomarkers With Cancer Stem Cell Characteristics in Lung Squamous Cell Carcinoma |
title_short |
Bioinformatics Analysis Reveals Biomarkers With Cancer Stem Cell Characteristics in Lung Squamous Cell Carcinoma |
title_full |
Bioinformatics Analysis Reveals Biomarkers With Cancer Stem Cell Characteristics in Lung Squamous Cell Carcinoma |
title_fullStr |
Bioinformatics Analysis Reveals Biomarkers With Cancer Stem Cell Characteristics in Lung Squamous Cell Carcinoma |
title_full_unstemmed |
Bioinformatics Analysis Reveals Biomarkers With Cancer Stem Cell Characteristics in Lung Squamous Cell Carcinoma |
title_sort |
bioinformatics analysis reveals biomarkers with cancer stem cell characteristics in lung squamous cell carcinoma |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Genetics |
issn |
1664-8021 |
publishDate |
2020-05-01 |
description |
BackgroundTumor stem cells play important roles in the survival, proliferation, metastasis and recurrence of tumors. We aimed to identify new prognostic biomarkers for lung squamous cell carcinoma (LUSC) based on the cancer stem cell theory.MethodsRNA-seq data and relevant clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Weighted gene coexpression network analysis (WGCNA) was applied to identify significant modules and hub genes, and prognostic signatures were constructed with the prognostic hub genes.ResultsLUSC patients in the TCGA database have higher mRNA expression-based stemness index (mRNAsi) in tumor tissue than in adjacent normal tissue. In addition, some clinical features and outcomes were highly correlated with the mRNAsi. WGCNA revealed that the pink and yellow modules were the most significant modules related to the mRNAsi; the top 10 hub genes in the pink module were enriched mostly in epidermal development, the secretory granule membrane, receptor regulator activity and the cytokine-cytokine receptor interaction. The protein–protein interaction (PPI) network revealed that the top 10 hub genes were significantly correlated with each other at the transcriptional level. In addition, the top 10 hub genes were all highly expressed in LUSC, and some were differentially expressed in different TNM stages. Regarding the survival analysis, the nomogram of a prognostic signature with three hub genes showed high predictive value.ConclusionmRNAsi-related hub genes could be a potential biomarker of LUSC. |
topic |
lung squamous cell carcinoma cancer cell stemness prognosis WGCNA TCGA |
url |
https://www.frontiersin.org/article/10.3389/fgene.2020.00427/full |
work_keys_str_mv |
AT yiliao bioinformaticsanalysisrevealsbiomarkerswithcancerstemcellcharacteristicsinlungsquamouscellcarcinoma AT huaxiao bioinformaticsanalysisrevealsbiomarkerswithcancerstemcellcharacteristicsinlungsquamouscellcarcinoma AT mengqingcheng bioinformaticsanalysisrevealsbiomarkerswithcancerstemcellcharacteristicsinlungsquamouscellcarcinoma AT xianmingfan bioinformaticsanalysisrevealsbiomarkerswithcancerstemcellcharacteristicsinlungsquamouscellcarcinoma |
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