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Integrative analysis of transcription factors and microRNAs in ovarian cancer cell spheroids.

ABSTRACT: BACKGROUND:Cancer stem cells (CSCs) can self-renew, proliferate into differentiated cells, or enter a quiescent state and are regarded to cause chemoresistance and recurrence. An integrative analysis of transcription factors (TF) and miRNAs was performed in ovarian CSC-enriched spheroid-forming cells (SFCs) to identify factors relevant to ovarian CSCs. METHODS:Fresh tumor cells from three ovarian cancer patients were cultured in standard and in selective medium. The mRNAs and miRNAs that exhibited significant differential expression between SFCs and adherent cells were identified using mRNA and miRNAs microarrays. Target genes of miRNAs were further selected if predicted with TargetScan by half of the miRNAs or more. Gene enrichment analysis was performed on over- or under-expressed mRNAs and target genes of miRNAs using DAVID tools. Complex regulatory networks were combined from TF-genes and miRNA-genes interactions using the MAGIA webtool. RESULTS:A total of 1245 mRNA and 55 miRNAs were differentially expressed (p-value

SUBMITTER: Park H

PROVIDER: S-EPMC7014770 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Integrative analysis of transcription factors and microRNAs in ovarian cancer cell spheroids.

Park Hyun H Hwang Sohyun S Jeong Ju-Yeon JY Jung Sang Geun SG Choi Min Chul MC Joo Won Duk WD Song Seung Hun SH Lee Chan C An Hee Jung HJ

Journal of ovarian research 20200211 1

<h4>Background</h4>Cancer stem cells (CSCs) can self-renew, proliferate into differentiated cells, or enter a quiescent state and are regarded to cause chemoresistance and recurrence. An integrative analysis of transcription factors (TF) and miRNAs was performed in ovarian CSC-enriched spheroid-forming cells (SFCs) to identify factors relevant to ovarian CSCs.<h4>Methods</h4>Fresh tumor cells from three ovarian cancer patients were cultured in standard and in selective medium. The mRNAs and miRN ...[more]

PMID: 32046751

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Project description:Although high-grade serous ovarian cancer (OVC) is the most lethal gynecologic malignancy in women, little is known about the regulatory mechanisms in the cellular processes that lead to this cancer. Recently, accumulated lines of evidence have shown that the interplay between transcription factors (TFs) and microRNAs (miRNAs) is critical in cellular regulation during tumorigenesis. A comprehensive investigation of TFs and miRNAs, and their target genes, may provide a deeper understanding of the regulatory mechanisms in the pathology of OVC. In this study, we have integrated three complementary algorithms into a framework, aiming to infer the regulation by miRNAs and TFs in conjunction with gene expression profiles. We demonstrated the utility of our framework by inferring 67 OVC-specific regulatory feed-forward loops (FFL) initiated by miRNAs or TFs in high-grade serous OVC. By analyzing these regulatory behaviors, we found that all the 67 FFLs are consistent in their regulatory effects on genes that are jointly targeted by miRNAs and TFs. Remarkably, we unveiled an unbalanced distribution of FFLs with different oncogenic effects. In total, 31 of the 67 coherent FFLs were mainly initiated by oncogenes. On the contrary, only 4 of the FFLs were initiated by tumor suppressor genes. These overwhelmingly observed oncogenic genes were further detected in a sub-network with 32 FFLs centered by miRNA let-7b and TF TCF7L1 to regulate cell differentiation. Closer inspection of 32 FFLs revealed that 75% of the miRNAs reportedly play functional roles in cell differentiation, especially when enriched in epithelial-mesenchymal transitions. This study provides a comprehensive pathophysiological overview of recurring coherent circuits in OVC that are co-regulated by miRNAs and TFs. The prevalence of oncogenic coherent FFLs in serous OVC suggests that oncogene-driven regulatory motifs could cooperatively act upon critical cellular processes such as cell differentiation in a highly efficient and consistent manner.

Dataset Information

Integrative analysis of transcription factors and microRNAs in ovarian cancer cell spheroids.

Publications

Integrative analysis of transcription factors and microRNAs in ovarian cancer cell spheroids.

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