Dataset Information

Transcriptomic Analyses Reveal B-Cell Translocation Gene 2 as a Potential Therapeutic Target in Ovarian Cancer.

ABSTRACT: Ovarian cancer is the most common and aggressive type of tumor of the female reproductive system. Two factors account for this detrimental clinical presentation: (i) the lack of early detection methods and (ii) the inherently aggressive nature of this malignancy. Currently, transcriptomic analyses have become important tools to identify new targets in different cancer types. In this study, by measuring expression levels in ovarian cancer samples and stem cell samples, we identified 24 tumor suppressor genes consistently associated with poor prognosis. Combined results further revealed a potential therapeutic candidate, BTG2, which belongs to the antiproliferative gene family. Our results showed that BTG2 expression regulated ovarian cancer cell proliferation via G1/S phase cell cycle arrest by regulating Cyclin D1, CDK4, p-AKT, and p-ERK expression. BTG2 also inhibited cell migration by modulating MMP-2 and MMP-9 expression. Furthermore, xenograft models confirmed a growth inhibitory effect of BTG2 in ovarian cancer in vivo. BTG2 was significantly associated with ovarian cancer FIGO stage and grade in the clinic. Our findings indicated that BTG2 exerts a suppressive impact on ovarian cancer and could be a potential biomarker.

SUBMITTER: Wang J

PROVIDER: S-EPMC8415965 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Transcriptomic Analyses Reveal B-Cell Translocation Gene 2 as a Potential Therapeutic Target in Ovarian Cancer.

Wang Jia J Li Haonan H Wang Liang L Zhang Jing J Li Man M Qiao Liang L Zhang Jun J Liu Likun L Zhang Cuili C Gao Jingchun J Li Weiling W

Frontiers in oncology 20210817

Ovarian cancer is the most common and aggressive type of tumor of the female reproductive system. Two factors account for this detrimental clinical presentation: (i) the lack of early detection methods and (ii) the inherently aggressive nature of this malignancy. Currently, transcriptomic analyses have become important tools to identify new targets in different cancer types. In this study, by measuring expression levels in ovarian cancer samples and stem cell samples, we identified 24 tumor supp ...[more]

PMID: 34485119

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Project description:BackgroundThere has been a significant surge in the global prevalence of diabetes mellitus (DM), which increases the susceptibility of individuals to ovarian cancer (OC). However, the relationship between DM and OC remains largely unexplored. The objective of this study is to provide preliminary insights into the shared molecular regulatory mechanisms and potential biomarkers between DM and OC.MethodsMultiple datasets from the GEO database were utilized for bioinformatics analysis. Single cell datasets from the GEO database were analysed. Subsequently, immune cell infiltration analysis was performed on mRNA expression data. The intersection of these datasets yielded a set of common genes associated with both OC and DM. Using these overlapping genes and Cytoscape, a protein‒protein interaction (PPI) network was constructed, and 10 core targets were selected. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were then conducted on these core targets. Additionally, advanced bioinformatics analyses were conducted to construct a TF-mRNA-miRNA coregulatory network based on identified core targets. Furthermore, immunohistochemistry staining (IHC) and real-time quantitative PCR (RT-qPCR) were employed for the validation of the expression and biological functions of core proteins, including HSPAA1, HSPA8, SOD1, and transcription factors SREBF2 and GTAT2, in ovarian tumors.ResultsThe immune cell infiltration analysis based on mRNA expression data for both DM and OC, as well as analysis using single-cell datasets, reveals significant differences in mononuclear cell levels. By intersecting the single-cell datasets, a total of 119 targets related to mononuclear cells in both OC and DM were identified. PPI network analysis further identified 10 hub genesincludingHSP90AA1, HSPA8, SNRPD2, UBA52, SOD1, RPL13A, RPSA, ITGAM, PPP1CC, and PSMA5, as potential targets of OC and DM. Enrichment analysis indicated that these genes are primarily associated with neutrophil degranulation, GDP-dissociation inhibitor activity, and the IL-17 signaling pathway, suggesting their involvement in the regulation of the tumor microenvironment. Furthermore, the TF-gene and miRNA-gene regulatory networks were validated using NetworkAnalyst. The identified TFs included SREBF2, GATA2, and SRF, while the miRNAs included miR-320a, miR-378a-3p, and miR-26a-5p. Simultaneously, IHC and RT-qPCR reveal differential expression of core targets in ovarian tumors after the onset of diabetes. RT-qPCR further revealed that SREBF2 and GATA2 may influence the expression of core proteins, including HSP90AA1, HSPA8, and SOD1.ConclusionThis study revealed the shared gene interaction network between OC and DM and predicted the TFs and miRNAs associated with core genes in monocytes. Our research findings contribute to identifying potential biological mechanisms underlying the relationship between OC and DM.

Project description:IntroductionEndometriosis, a benign inflammatory disease whereby endometrial-like tissue grows outside the uterus, is a risk factor for endometriosis-associated ovarian cancers. In particular, ovarian endometriomas, cystic lesions of deeply invasive endometriosis, are considered the precursor lesion for ovarian clear-cell carcinoma (OCCC).MethodsTo explore this transcriptomic landscape, OCCC from women with pathology-proven concurrent endometriosis (n = 4) were compared to benign endometriomas (n = 4) by bulk RNA and small-RNA sequencing.ResultsAnalysis of protein-coding genes identified 2449 upregulated and 3131 downregulated protein-coding genes (DESeq2, P< 0.05, log2 fold-change > |1|) in OCCC with concurrent endometriosis compared to endometriomas. Gene set enrichment analysis showed upregulation of pathways involved in cell cycle regulation and DNA replication and downregulation of pathways involved in cytokine receptor signaling and matrisome. Comparison of pathway activation scores between the clinical samples and publicly-available datasets for OCCC cell lines revealed significant molecular similarities between OCCC with concurrent endometriosis and OVTOKO, OVISE, RMG1, OVMANA, TOV21G, IGROV1, and JHOC5 cell lines. Analysis of miRNAs revealed 64 upregulated and 61 downregulated mature miRNA molecules (DESeq2, P< 0.05, log2 fold-change > |1|). MiR-10a-5p represented over 21% of the miRNA molecules in OCCC with endometriosis and was significantly upregulated (NGS: log2fold change = 4.37, P = 2.43e-18; QPCR: 8.1-fold change, P< 0.05). Correlation between miR-10a expression level in OCCC cell lines and IC50 (50% inhibitory concentration) of carboplatin in vitro revealed a positive correlation (R2 = 0.93). MiR-10a overexpression in vitro resulted in a significant decrease in proliferation (n = 6; P< 0.05) compared to transfection with a non-targeting control miRNA. Similarly, the cell-cycle analysis revealed a significant shift in cells from S and G2 to G1 (n = 6; P< 0.0001). Bioinformatic analysis predicted that miR-10a-5p target genes that were downregulated in OCCC with endometriosis were involved in receptor signaling pathways, proliferation, and cell cycle progression. MiR-10a overexpression in vitro was correlated with decreased expression of predicted miR-10a target genes critical for proliferation, cell-cycle regulation, and cell survival including [SERPINE1 (3-fold downregulated; P< 0.05), CDK6 (2.4-fold downregulated; P< 0.05), and RAP2A (2-3-fold downregulated; P< 0.05)].DiscussionThese studies in OCCC suggest that miR-10a-5p is an impactful, potentially oncogenic molecule, which warrants further studies.

Dataset Information

Transcriptomic Analyses Reveal B-Cell Translocation Gene 2 as a Potential Therapeutic Target in Ovarian Cancer.

Publications

Transcriptomic Analyses Reveal B-Cell Translocation Gene 2 as a Potential Therapeutic Target in Ovarian Cancer.

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