Dataset Information

Identification of key modules and prognostic markers in adrenocortical carcinoma by weighted gene co-expression network analysis.

ABSTRACT: Adrenocortical carcinoma (ACC) is a rare and aggressive cancer with a high relapse rate and limited treatment options. Therefore, the identification of potential prognostic markers in patients with ACC may improve early detection, survival rates and may additionally provide novel insights into the early detection of recurrence. In the present study, clinical traits and RNA-seq data of 79 patients with ACC were obtained from The Cancer Genome Atlas (TCGA). Weighted gene co-expression network analysis was carried out and 17 distinct co-expression modules were built to examine the association between the modules and the clinical traits. Of the 17 modules, two co-expression modules, which contained 214 and 168 genes, were significantly correlated with two clinical traits, tumor stage and vital status. Functional enrichment analysis was performed on the selected modules. The results showed that one of the modules was primarily enriched in cell division and the other module was enriched in metabolic pathways, suggesting their involvement in tumor progression. Furthermore, cyclin dependent kinase 1 (CDK1) and ubiquitin C (UBC) were identified as hub genes in both modules. Survival analysis revealed that the high expression of the hub genes significantly correlated with the poor survival rate of patients, suggesting that CDK1 and UBC have vital roles in the progression of ACC. In the present study, a co-expression gene module of ACC was provided and the prognostic genes that may serve as new diagnostic markers in the future were defined.

SUBMITTER: Zou Y

PROVIDER: S-EPMC6733001 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Identification of key modules and prognostic markers in adrenocortical carcinoma by weighted gene co-expression network analysis.

Zou Yong Y Jing Luanlian L

Oncology letters 20190806 4

Adrenocortical carcinoma (ACC) is a rare and aggressive cancer with a high relapse rate and limited treatment options. Therefore, the identification of potential prognostic markers in patients with ACC may improve early detection, survival rates and may additionally provide novel insights into the early detection of recurrence. In the present study, clinical traits and RNA-seq data of 79 patients with ACC were obtained from The Cancer Genome Atlas (TCGA). Weighted gene co-expression network anal ...[more]

PMID: 31516579

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Dataset Information

Identification of key modules and prognostic markers in adrenocortical carcinoma by weighted gene co-expression network analysis.

Publications

Identification of key modules and prognostic markers in adrenocortical carcinoma by weighted gene co-expression network analysis.

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