Identification of four hub genes associated with adrenocortical carcinoma progression by WGCNA

Background Adrenocortical carcinoma (ACC) is a rare and aggressive malignant cancer in the adrenal cortex with poor prognosis. Though previous research has attempted to elucidate the progression of ACC, its molecular mechanism remains poorly understood. Methods Gene transcripts per million (TPM) dat...

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Main Authors: Wang-Xiao Xia, Qin Yu, Gong-Hua Li, Yao-Wen Liu, Fu-Hui Xiao, Li-Qin Yang, Zia Ur Rahman, Hao-Tian Wang, Qing-Peng Kong
Format: Article
Language:English
Published: PeerJ Inc. 2019-03-01
Series:PeerJ
Subjects:
ACC
Online Access:https://peerj.com/articles/6555.pdf
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spelling doaj-76f0ef2fac0d45c789e4382ebe7312302020-11-25T00:29:19ZengPeerJ Inc.PeerJ2167-83592019-03-017e655510.7717/peerj.6555Identification of four hub genes associated with adrenocortical carcinoma progression by WGCNAWang-Xiao Xia0Qin Yu1Gong-Hua Li2Yao-Wen Liu3Fu-Hui Xiao4Li-Qin Yang5Zia Ur Rahman6Hao-Tian Wang7Qing-Peng Kong8State Key Laboratory of Genetic Resources and Evolution/Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, ChinaState Key Laboratory of Genetic Resources and Evolution/Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, ChinaState Key Laboratory of Genetic Resources and Evolution/Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, ChinaState Key Laboratory of Genetic Resources and Evolution/Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, ChinaState Key Laboratory of Genetic Resources and Evolution/Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, ChinaState Key Laboratory of Genetic Resources and Evolution/Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, ChinaState Key Laboratory of Genetic Resources and Evolution/Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, ChinaState Key Laboratory of Genetic Resources and Evolution/Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, ChinaState Key Laboratory of Genetic Resources and Evolution/Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, ChinaBackground Adrenocortical carcinoma (ACC) is a rare and aggressive malignant cancer in the adrenal cortex with poor prognosis. Though previous research has attempted to elucidate the progression of ACC, its molecular mechanism remains poorly understood. Methods Gene transcripts per million (TPM) data were downloaded from the UCSC Xena database, which included ACC (The Cancer Genome Atlas, n = 77) and normal samples (Genotype Tissue Expression, n = 128). We used weighted gene co-expression network analysis to identify gene connections. Overall survival (OS) was determined using the univariate Cox model. A protein–protein interaction (PPI) network was constructed by the search tool for the retrieval of interacting genes. Results To determine the critical genes involved in ACC progression, we obtained 2,953 significantly differentially expressed genes and nine modules. Among them, the blue module demonstrated significant correlation with the “Stage” of ACC. Enrichment analysis revealed that genes in the blue module were mainly enriched in cell division, cell cycle, and DNA replication. Combined with the PPI and co-expression networks, we identified four hub genes (i.e., TOP2A, TTK, CHEK1, and CENPA) that were highly expressed in ACC and negatively correlated with OS. Thus, these identified genes may play important roles in the progression of ACC and serve as potential biomarkers for future diagnosis.https://peerj.com/articles/6555.pdfACCWGCNAHub genesProgression
collection DOAJ
language English
format Article
sources DOAJ
author Wang-Xiao Xia
Qin Yu
Gong-Hua Li
Yao-Wen Liu
Fu-Hui Xiao
Li-Qin Yang
Zia Ur Rahman
Hao-Tian Wang
Qing-Peng Kong
spellingShingle Wang-Xiao Xia
Qin Yu
Gong-Hua Li
Yao-Wen Liu
Fu-Hui Xiao
Li-Qin Yang
Zia Ur Rahman
Hao-Tian Wang
Qing-Peng Kong
Identification of four hub genes associated with adrenocortical carcinoma progression by WGCNA
PeerJ
ACC
WGCNA
Hub genes
Progression
author_facet Wang-Xiao Xia
Qin Yu
Gong-Hua Li
Yao-Wen Liu
Fu-Hui Xiao
Li-Qin Yang
Zia Ur Rahman
Hao-Tian Wang
Qing-Peng Kong
author_sort Wang-Xiao Xia
title Identification of four hub genes associated with adrenocortical carcinoma progression by WGCNA
title_short Identification of four hub genes associated with adrenocortical carcinoma progression by WGCNA
title_full Identification of four hub genes associated with adrenocortical carcinoma progression by WGCNA
title_fullStr Identification of four hub genes associated with adrenocortical carcinoma progression by WGCNA
title_full_unstemmed Identification of four hub genes associated with adrenocortical carcinoma progression by WGCNA
title_sort identification of four hub genes associated with adrenocortical carcinoma progression by wgcna
publisher PeerJ Inc.
series PeerJ
issn 2167-8359
publishDate 2019-03-01
description Background Adrenocortical carcinoma (ACC) is a rare and aggressive malignant cancer in the adrenal cortex with poor prognosis. Though previous research has attempted to elucidate the progression of ACC, its molecular mechanism remains poorly understood. Methods Gene transcripts per million (TPM) data were downloaded from the UCSC Xena database, which included ACC (The Cancer Genome Atlas, n = 77) and normal samples (Genotype Tissue Expression, n = 128). We used weighted gene co-expression network analysis to identify gene connections. Overall survival (OS) was determined using the univariate Cox model. A protein–protein interaction (PPI) network was constructed by the search tool for the retrieval of interacting genes. Results To determine the critical genes involved in ACC progression, we obtained 2,953 significantly differentially expressed genes and nine modules. Among them, the blue module demonstrated significant correlation with the “Stage” of ACC. Enrichment analysis revealed that genes in the blue module were mainly enriched in cell division, cell cycle, and DNA replication. Combined with the PPI and co-expression networks, we identified four hub genes (i.e., TOP2A, TTK, CHEK1, and CENPA) that were highly expressed in ACC and negatively correlated with OS. Thus, these identified genes may play important roles in the progression of ACC and serve as potential biomarkers for future diagnosis.
topic ACC
WGCNA
Hub genes
Progression
url https://peerj.com/articles/6555.pdf
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