Dataset Information

Expression of CDK8 and CDK8-interacting Genes as Potential Biomarkers in Breast Cancer.

ABSTRACT: CDK8 and its paralog CDK19, in complex with CCNC, MED12 and MED13, are transcriptional regulators that mediate several carcinogenic pathways and the chemotherapy-induced tumor-supporting paracrine network. Following up on our previous observation that CDK8, CDK19 and CCNC RNA expression is associated with shorter relapse-free survival (RFS) in breast cancer, we now found by immunohistochemical analysis that CDK8/19 protein is overexpressed in invasive ductal carcinomas relative to non-malignant mammary tissues. Meta-analysis of transcriptomic data revealed that higher CDK8 expression is associated with shorter RFS in all molecular subtypes of breast cancer. These correlations were much stronger in patients who underwent systemic adjuvant therapy, suggesting that CDK8 impacts the failure of systemic therapy. The same associations were found for CDK19, CCNC and MED13. In contrast, MED12 showed the opposite association with a longer RFS. The expression levels of CDK8 in breast cancer samples were directly correlated with the expression of MYC, as well as CDK19, CCNC and MED13 but inversely correlated with MED12. CDK8, CDK19 and CCNC expression was strongly increased and MED12 expression was decreased in tumors with mutant p53. Gene amplification is the most frequent type of genetic alterations of CDK8, CDK19, CCNC and MED13 in breast cancers (9.7% of which have amplified MED13), whereas point mutations are more common in MED12. These results suggest that the expression of CDK8 and its interactive genes has a profound impact on the response to adjuvant therapy in breast cancer in accordance with the role of CDK8 in chemotherapy-induced tumor-supporting paracrine activities.

SUBMITTER: Broude EV

PROVIDER: S-EPMC4755306 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Expression of CDK8 and CDK8-interacting Genes as Potential Biomarkers in Breast Cancer.

Broude Eugenia V EV Győrffy Balázs B Chumanevich Alexander A AA Chen Mengqian M McDermott Martina S J MS Shtutman Michael M Catroppo James F JF Roninson Igor B IB

Current cancer drug targets 20150101 8

CDK8 and its paralog CDK19, in complex with CCNC, MED12 and MED13, are transcriptional regulators that mediate several carcinogenic pathways and the chemotherapy-induced tumor-supporting paracrine network. Following up on our previous observation that CDK8, CDK19 and CCNC RNA expression is associated with shorter relapse-free survival (RFS) in breast cancer, we now found by immunohistochemical analysis that CDK8/19 protein is overexpressed in invasive ductal carcinomas relative to non-malignant ...[more]

PMID: 26452386

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Project description:BackgroundTriple-negative breast cancer (TNBC) is a highly heterogeneous subtype of breast cancer, showing aggressive clinical behaviors and poor outcomes. It urgently needs new therapeutic strategies to improve the prognosis of TNBC. Bioinformatics analyses have been widely used to identify potential biomarkers for facilitating TNBC diagnosis and management.MethodsWe identified potential biomarkers and analyzed their diagnostic and prognostic values using bioinformatics approaches. Including differential expression gene (DEG) analysis, Receiver Operating Characteristic (ROC) curve analysis, functional enrichment analysis, Protein-Protein Interaction (PPI) network construction, survival analysis, multivariate Cox regression analysis, and Non-negative Matrix Factorization (NMF).ResultsA total of 105 DEGs were identified between TNBC and other breast cancer subtypes, which were regarded as heterogeneous-related genes. Subsequently, the KEGG enrichment analysis showed that these genes were significantly enriched in 'cell cycle' and 'oocyte meiosis' related pathways. Four (FAM83B, KITLG, CFD and RBM24) of 105 genes were identified as prognostic signatures in the disease-free interval (DFI) of TNBC patients, as for progression-free interval (PFI), five genes (FAM83B, EXO1, S100B, TYMS and CFD) were obtained. Time-dependent ROC analysis indicated that the multivariate Cox regression models, which were constructed based on these genes, had great predictive performances. Finally, the survival analysis of TNBC subtypes (mesenchymal stem-like [MSL] and mesenchymal [MES]) suggested that FAM83B significantly affected the prognosis of patients.ConclusionsThe multivariate Cox regression models constructed from four heterogeneous-related genes (FAM83B, KITLG, RBM24 and S100B) showed great prediction performance for TNBC patients' prognostic. Moreover, FAM83B was an important prognostic feature in several TNBC subtypes (MSL and MES). Our findings provided new biomarkers to facilitate the targeted therapies of TNBC and TNBC subtypes.

Project description:Triple‑negative breast cancer (TNBC) accounts for the worst prognosis of all types of breast cancers due to a high risk of recurrence and a lack of targeted therapeutic options. Extensive effort is required to identify novel targets for TNBC. In the present study, a robust rank aggregation (RRA) analysis based on genome‑wide gene expression datasets involving TNBC patients from the Gene Expression Omnibus (GEO) database was performed to identify key genes associated with TNBC. A total of 194 highly ranked differentially expressed genes (DEGs) were identified in TNBC vs. non‑TNBC. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analysis was utilized to explore the biological functions of the identified genes. These DEGs were mainly involved in the biological processes termed positive regulation of transcription from RNA polymerase II promoter, negative regulation of apoptotic process, response to drug, response to estradiol and negative regulation of cell growth. Genes were mainly involved in the KEGG pathway termed estrogen signaling pathway. The aberrant expression of several randomly selected DEGs were further validated in cell lines, clinical tissues and The Cancer Genome Atlas (TCGA) cohort. Furthermore, all the top‑ranked DEGs underwent survival analysis using TCGA database, of which overexpression of 4 genes (FABP7, ART3, CT83, and TTYH1) were positively correlated to the life expectancy (P<0.05) of TNBC patients. In addition, a model consisting of two genes (FABP7 and CT83) was identified to be significantly associated with the overall survival (OS) of TNBC patients by means of Cox regression, Kaplan‑Meier, and receiver operating characteristic (ROC) analyses. In conclusion, the present study identified a number of key genes as potential biomarkers involved in TNBC, which provide novel insights into the tumorigenesis of TNBC at the gene level and may serve as independent prognostic factors for TNBC prognosis.

Dataset Information

Expression of CDK8 and CDK8-interacting Genes as Potential Biomarkers in Breast Cancer.

Publications

Expression of CDK8 and CDK8-interacting Genes as Potential Biomarkers in Breast Cancer.

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