Dataset Information

Gene expression profile analysis identifies metastasis and chemoresistance-associated genes in epithelial ovarian carcinoma cells.

ABSTRACT: The purpose of this study was to identify genes that associated with higher ability of metastasis and chemotherapic resistance in epithelial ovarian carcinoma (EOC) cells. An oligonucleotide microarray with probe sets complementary to 41,000(+) unique human genes and transcripts was used to determine whether gene expression profile may differentiate three epithelial ovarian cell lines (RMG-I-C, COC1 and HO8910) from their sub-lines (RMG-I-H, COCI/DDP and HO8910/PM) with higher ability of metastasis and chemotherapic resistance. Quantitative real-time PCR and immunohistochemical staining validated the microarray results. Hierarchic cluster analysis of gene expression identified 49 genes that exhibited ≥2.0-fold change and P value ≤0.05. Highly differential expression of GCET2, NLRP4, FOXP1 and SNX29 genes was validated by quantitative PCR in all cell line samples. Finally, FOXP1 was validated at the protein level by immunohistochemistry in paraffin embedded ovarian tissues (i.e., for metastasis, 15 primary EOC and 10 omental metastasis [OM]; for chemoresistance, 13 sensitive and 13 resistant EOC). The identification of higher ability of metastasis and chemotherapic resistance-associated genes may provide a foundation for the development of new type-specific diagnostic strategies and treatment for metastasis and chemotherapic resistance in epithelial ovarian cancer.

SUBMITTER: Zhu L

PROVIDER: S-EPMC4262766 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Ovarian carcinomas have the poorest prognosis and the highest mortality among gynecological malignancies. Neoadjuvant chemotherapy (NACT) is considered as a novel therapeutic strategy and an alternative treatment for advanced epithelial ovarian cancer (AEOC). The aim of the present study was to identify the core genes related to platinum‑based NACT resistance in AEOC and to allow screening at the molecular level for the most appropriate ovarian cancer patients for NACT. We obtained three drug‑resistant microarrays GSE114206, GSE41499 and GSE33482 from the Gene Expression Omnibus (GEO) database as well as a microarray representing NACT, GSE109934. Bioinformatics analysis revealed the nature of the four potential candidate genes for using in functional enrichment analyses and interaction network construction. The potential associations and possible genetic alterations among the DEGs were summarized using the STRING database in Cytoscape and the cBioPortal visualization tool, respectively. A total of 63 genes were identified as DEGs from GSE109934 representing NACT. From the drug‑resistant GSE114206 and GSE41499 datasets, 106 DEGs containing 36 upregulated genes and 70 downregulated genes were selected, and from the drug‑resistant GSE114206 and GSE33482 datasets, 406 DEGs with 157 upregulated genes and 249 downregulated genes were selected. The 36 upregulated DEGs and the 70 downregulated genes were notably abundant in the different categories. In KEGG pathway analysis, the 157 upregulated genes and the 249 downregulated genes were concentrated in distinctive signaling pathways. Four potential genes associated with NACT and platinum‑based chemoresistance were screened, including nuclear factor of activated T‑cells, cytoplasmic 1 (NAFTc1), Kruppel‑like factor 4 (KLF4), nuclear receptor subfamily 4 group A member 3 (NR4A3) and hepatocyte growth factor (HGF). Our study showed that the mRNA expression levels of NAFTc1, NR4A3 and HGF were increased in drug‑resistant OC cell lines (all P<0.01), whereas the mRNA expression levels of KLF4 were notably lower in the SKOV3‑CDDP and HeyA8‑CDDP cell line (all P<0.01) but higher in the A2780‑CBP cell line. The NAFTc1, KLF4, NR4A3 and HGF genes may be potential therapeutic targets for NACT and platinum‑based chemoresistance factors as well as candidate biomarkers in AEOC. Determination of the expression levels of these four genes in tumor tissues before planning NACT treatment or initial surgery would be beneficial for AEOC patients.

Dataset Information

Gene expression profile analysis identifies metastasis and chemoresistance-associated genes in epithelial ovarian carcinoma cells.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure