Dataset Information

Integrated bioinformatic analysis identifies UBE2Q1 as a potential prognostic marker for high grade serous ovarian cancer.

ABSTRACT:

Background

High grade serous ovarian cancer (HGSOC) accounts for nearly 60% of total cases of epithelial ovarian cancer. It is the most aggressive subtype, which shows poor prognosis and low patient survival. For better management of HGSOC patients, new prognostic biomarkers are required to facilitate improved treatment strategies and ensure suitable healthcare decisions.

Methods

We performed genome wide expression analysis of HGSOC patient samples to identify differentially expressed genes (DEGs) using R based Limma package, Clust and other statistical tools. The identified DEGs were subjected to weighted gene co-expression network analysis (WGCNA) to identify co-expression patterns of relevant genes. Module trait and gene ontology analyses were performed to establish important gene co-expression networks and their biological functions. Overlapping the most relevant DEG cluster 4 with prominent WGCNA cyan module identified strongest correlation of UBE2Q1 with ovarian cancer and its prognostic significance on survival probability of ovarian cancer patients was investigated. The predictive value of UBE2Q1 as a potential biomarker was analysed by correlating its expression with 12-months relapse free survival of patients in response to platin/taxane, the standard first-line chemotherapy for ovarian cancer, and analysing area under the ROC curve.

Results

An integrated gene expression analysis and WGCNA, identified UBE2Q1 as a potential prognostic marker associated with poor relapse-free survival and response outcome to platin/taxane treatment of patients with high grade serous ovarian cancer.

Conclusions

Our study identifies a potential UBE2Q1 - B4GALT3 functional axis in ovarian cancer, where only the E2 conjugating enzyme showed a poor prognostic impact on the disease.

SUBMITTER: Topno R

PROVIDER: S-EPMC7934452 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Integrated bioinformatic analysis identifies UBE2Q1 as a potential prognostic marker for high grade serous ovarian cancer.

Topno Rachel R Singh Ibha I Kumar Manoj M Agarwal Pallavi P

BMC cancer 20210304 1

<h4>Background</h4>High grade serous ovarian cancer (HGSOC) accounts for nearly 60% of total cases of epithelial ovarian cancer. It is the most aggressive subtype, which shows poor prognosis and low patient survival. For better management of HGSOC patients, new prognostic biomarkers are required to facilitate improved treatment strategies and ensure suitable healthcare decisions.<h4>Methods</h4>We performed genome wide expression analysis of HGSOC patient samples to identify differentially expre ...[more]

PMID: 33663405

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Project description:PurposeOvarian cancer is the leading cause of gynecologic cancer-related death worldwide. Early diagnosis of ovarian cancer can significantly improve patient prognosis. Hence, there is an urgent need to identify key diagnostic and prognostic biomarkers specific for ovarian cancer. Because high-grade serous ovarian cancer (HGSOC) is the most common type of ovarian cancer and accounts for the majority of deaths, we identified potential biomarkers for the early diagnosis and prognosis of HGSOC.MethodsSix datasets (GSE14001, GSE18520, GSE26712, GSE27651, GSE40595, and GSE54388) were downloaded from the Gene Expression Omnibus database for analysis. Differentially expressed genes (DEGs) between HGSOC and normal ovarian surface epithelium samples were screened via integrated analysis. Hub genes were identified by analyzing protein-protein interaction (PPI) network data. The online Kaplan-Meier plotter was utilized to evaluate the prognostic roles of these hub genes. The expression of these hub genes was confirmed with Oncomine datasets and validated by quantitative real-time PCR and Western blotting.ResultsA total of 103 DEGs in patients with HGSOC-28 upregulated genes and 75 downregulated genes-were successfully screened. Enrichment analyses revealed that the upregulated genes were enriched in cell division and cell proliferation and that the downregulated genes mainly participated in the Wnt signaling pathway and various metabolic processes. Ten hub genes were associated with HGSOC pathogenesis. Seven overexpressed hub genes were partitioned into module 1 of the PPI network, which was enriched in the cell cycle and DNA replication pathways. Survival analysis revealed that MELK, CEP55 and KDR expression levels were significantly correlated with the overall survival of HGSOC patients (P < 0.05). The RNA and protein expression levels of these hub genes were validated experimentally.ConclusionBased on an integrated analysis, we propose the further investigation of MELK, CEP55 and KDR as promising diagnostic and prognostic biomarkers of HGSOC.

Project description:BackgroundETS transcription factors are known to act as either positive or negative regulators of the expression of genes involved in various biological processes. It was reported that ETS variant transcription factor 5 (ETV5), a key member of the ETS family, mainly plays a role as an potential oncogene in various malignant tumors. However, the role and mechanism of ETV5 in high-grade serous ovarian cancer (HGSOC) have not been elucidated.MethodsQuantitative real-time polymerase chain reaction (qRT-PCR) assay was used to detect ETV5 messenger ribonucleic acid (mRNA) expression in 87 HGSOC tissues and 35 normal fallopian tube tissues. Western blotting and qRT-PCR were used to detect the protein and mRNA expression of ETV5 in six ovarian cancer (OC) and human embryonic cell lines. Knockdown or overexpression of ETV5 in HGSOC cell lines, Cell Counting Kit-8, colony formation, and transwell assays were used to detect HGSOC cell proliferation, invasion, and migration capabilities. The chi-square test was used to analyze the clinicopathological characteristics of HGSOC patients. Survival analysis was performed using the Kaplan-Meier method, and the log-rank test was used to analyze the correlation between ETV5 expression and HGSOC patient prognosis. Univariate and multivariate analyses using the Cox regression model were conducted to determine the independent significance of relevant clinical covariates.ResultsBioinformatic analysis demonstrated that ETV5 expression was significantly upregulated in OC (p < 0.05). qRT-PCR showed that ETV5 was significantly overexpressed in HGSOC tissues than in fallopian tube tissues (p < 0.05). qRT-PCR and western blotting assays demonstrated that ETV5 was relatively highly expressed in OC cell lines. ETV5 overexpression was positively associated with poor survival in HGSOC patients, therefore making it a high-risk factor for HGSOC progression. Furthermore, ETV5 promoted the proliferation, migration, and invasion capabilities of HGSOC cells.ConclusionETV5 has a carcinogenic effect in HGSOC and can be used as a clinically effective biomarker to determine the prognosis of HGSOC patients.

Dataset Information

Integrated bioinformatic analysis identifies UBE2Q1 as a potential prognostic marker for high grade serous ovarian cancer.

Background

Methods

Results

Conclusions

Publications

Integrated bioinformatic analysis identifies UBE2Q1 as a potential prognostic marker for high grade serous ovarian cancer.

Similar Datasets

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