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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.
Afiliação
  • Xia WX; State 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, China.
  • Yu Q; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China.
  • Li GH; Kunming Key Laboratory of Healthy Aging Study, Kunming, China.
  • Liu YW; Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing, China.
  • Xiao FH; State 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, China.
  • Yang LQ; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China.
  • Rahman ZU; Kunming Key Laboratory of Healthy Aging Study, Kunming, China.
  • Wang HT; Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing, China.
  • Kong QP; State 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, China.
PeerJ ; 7: e6555, 2019.
Article em En | MEDLINE | ID: mdl-30886771
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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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article