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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) d...

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Autores principales: Xia, Wang-Xiao, Yu, Qin, Li, Gong-Hua, Liu, Yao-Wen, Xiao, Fu-Hui, Yang, Li-Qin, Rahman, Zia Ur, Wang, Hao-Tian, Kong, Qing-Peng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6421058/
https://www.ncbi.nlm.nih.gov/pubmed/30886771
http://dx.doi.org/10.7717/peerj.6555
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author Xia, Wang-Xiao
Yu, Qin
Li, Gong-Hua
Liu, Yao-Wen
Xiao, Fu-Hui
Yang, Li-Qin
Rahman, Zia Ur
Wang, Hao-Tian
Kong, Qing-Peng
author_facet Xia, Wang-Xiao
Yu, Qin
Li, Gong-Hua
Liu, Yao-Wen
Xiao, Fu-Hui
Yang, Li-Qin
Rahman, Zia Ur
Wang, Hao-Tian
Kong, Qing-Peng
author_sort Xia, Wang-Xiao
collection PubMed
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.
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spelling pubmed-64210582019-03-18 Identification of four hub genes associated with adrenocortical carcinoma progression by WGCNA Xia, Wang-Xiao Yu, Qin Li, Gong-Hua Liu, Yao-Wen Xiao, Fu-Hui Yang, Li-Qin Rahman, Zia Ur Wang, Hao-Tian Kong, Qing-Peng PeerJ Bioinformatics 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. PeerJ Inc. 2019-03-14 /pmc/articles/PMC6421058/ /pubmed/30886771 http://dx.doi.org/10.7717/peerj.6555 Text en © 2019 Xia et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Xia, Wang-Xiao
Yu, Qin
Li, Gong-Hua
Liu, Yao-Wen
Xiao, Fu-Hui
Yang, Li-Qin
Rahman, Zia Ur
Wang, Hao-Tian
Kong, Qing-Peng
Identification of four hub genes associated with adrenocortical carcinoma progression by WGCNA
title 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_short 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
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6421058/
https://www.ncbi.nlm.nih.gov/pubmed/30886771
http://dx.doi.org/10.7717/peerj.6555
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