ArticleOncology letters2019
Identification of key modules and prognostic markers in adrenocortical carcinoma by weighted gene co-expression network analysis.
Article in Oncology letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 13 citations in OpenAlex.
- The Identification and Clinical Value Evaluation of CYCS Related to Asthma through Bioinformatics Analysis and Functional Experiments.Disease markers · 2023Article
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- Damage-Net: A program for DNA repair meta-analysis identifies a network of novel repair genes that facilitate cancer evolution.DNA repair · 2021Article
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- Network analysis identifies DAPK3 as a potential biomarker for lymphatic invasion and colon adenocarcinoma prognosis.iScience · 2021Article
- Establishment and Validation of a Gene Signature-Based Prognostic Model to Improve Survival Prediction in Adrenocortical Carcinoma Patients.International journal of endocrinology · 2021Article
- The underlying molecular mechanism and drugs for treatment in adrenal cortical carcinoma.International journal of medical sciences · 2021Article
- Identification of Key Modules and Hub Genes Involved in Esophageal Squamous Cell Carcinoma Tumorigenesis Using WCGNA.Cancer control : journal of the Moffitt Cancer CenterArticle
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Authors and funding
2 authors.
Funding
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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.
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