Dataset Information

Integrated network analysis identifies hsa-miR-4756-3p as a regulator of FOXM1 in Triple Negative Breast Cancer.

ABSTRACT: Both aberrantly expressed mRNAs and micro(mi)RNAs play important roles in cancer cell function, which makes integration analysis difficult. In this study, we first applied master regulator analysisalgorithm and confirmed hsa-miR-4756-3p as a candidate miRNA in triple negative breast cancer (TNBC) patients; hsa-miR-4756-3p could regulate TNBC cell line apoptosis, proliferation, migration, and cell cycle as well as suppress TGF-β1 signalling andtumour growth. In TNBC, forkhead box protein M1 (FOXM1)was found to be an hsa-miR-4756-3p target gene, and FOXM1 knockout completely inhibited hsa-miR-4756-3p-induced cell migration and metastasis, TGF-β1 signalling, and epithelial mesenchymal signal activation, which indicated that hsa-miR-4756-3p functions via the FOXM1-TGFβ1-EMT axis.

SUBMITTER: Gu Y

PROVIDER: S-EPMC6761188 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Integrated network analysis identifies hsa-miR-4756-3p as a regulator of FOXM1 in Triple Negative Breast Cancer.

Gu Yuanliang Y Wang Wenjuan W Wang Xuyao X Xie Hongyi H Ye Xiaojuan X Shu Peng P

Scientific reports 20190925 1

Both aberrantly expressed mRNAs and micro(mi)RNAs play important roles in cancer cell function, which makes integration analysis difficult. In this study, we first applied master regulator analysisalgorithm and confirmed hsa-miR-4756-3p as a candidate miRNA in triple negative breast cancer (TNBC) patients; hsa-miR-4756-3p could regulate TNBC cell line apoptosis, proliferation, migration, and cell cycle as well as suppress TGF-β1 signalling andtumour growth. In TNBC, forkhead box protein M1 (FOXM ...[more]

PMID: 31554904

Similar Datasets

Project description:The aim of the present study was to identify the differentially expressed microRNAs (DEMs) between Lynch syndrome (LS) and the normal colonic (N-C) control samples, predict the target genes (TGs) and analyze the potential functions of the DEMs and TGs. The miRNA expression dataset GSE30454, which included data of 13 LS and 20 N-C tissue samples, was downloaded from the Gene Expression Omnibus. The classical t-test in Linear Models for Microarray Data package was used for DEM identification. TG prediction was performed using 5 databases. The regulatory network of the DEMs and their TGs was constructed using Cytoscape. Functional and pathway enrichment analysis was performed. The transcription factors (TFs), tumor-associated genes (TAG) and tumor suppressor genes (TSGs) were then identified. Three key DEMs hsa-miR-137, hsa-miR-520e, and hsa-miR-590-3p were identified. Hsa-miR-520e and hsa-miR-137 had 4 common TGs, including SNF related kinase, metal-regulatory transcription factor 1 (MTF1), round spermatid basic protein 1 and YTH N6-methyladenosine RNA binding protein 3; hsa-miR-590-3p and hsa-miR-137 had 14 common TGs, including NCK adaptor protein 1 (NCK1), EPH receptor A7, and stress-associated endoplasmic reticulum protein 1; hsa-miR-590-3p and hsa-miR-520e had 12 common TGs, including Krüppel-like factor (KLF) 13, twinfilin actin binding protein 1, and nuclear factor I B. Through the functional and pathway enrichments analysis, MTF1 was involved in regulation of gene expression and metabolic processes, and sequence-specific DNA binding TF activity. KLF13 was involved in regulation of gene expression and regulation of cellular metabolic processes. NCK1 was enriched in the axon guidance pathway. In addition, the functional and pathway enrichment analysis showed certain TGs, such as hypoxia-inducible factor 1α, AKT serine/threonine kinase 2, and rapamycin-insensitive companion of mammalian target of rapamycin, participated in the mTOR signaling pathway. The 3 key DEMs hsa-miR-137, hsa-miR-520e, and hsa-miR-590-3p may have important roles in the process of LS.

Project description:BackgroundIn contrast with the preceding stages of the germ cells, spermatozoa are unusually rich in small non-coding RNAs in comparison to the coding RNAs. These small RNAs may have had an essential role in the process of spermatogenesis or may have critical roles in the post-fertilization development. Sporadic efforts have identified a few differentially expressed miRNAs in infertile individuals, which do not replicate in other studies.MethodsIn order to identify miRNAs signatures of infertility or poor sperm quality, we compared miRNA differential expression data across nine datasets, followed by their analysis by real-time PCR in a case-control study. This was followed by the validation of potential biomarkers in yet another set of cases and controls. For this, total RNA was isolated from 161 sperm samples. miRNA expression levels in infertile cases and fertile controls were measured using TaqMan real-time PCR. Meta-analyses of two miRNAs (hsa-miR-9-3p and hsa-miR-122-5p) were performed using Comprehensive Meta-Analysis Software (version 2). All statistical analyses were performed with the help of GraphPad Prism Software (version 8).ResultsLiterature search identified seven miRNAs (hsa-let-7a-5p, hsa-miR-9-3p, hsa-miR-22-5p, has-miR-30b-5p, hsa-miR-103-3p, hsa-miR-122-5p and hsa-miR-335-5p) showing consistent dysregulation in infertility across a minimum of four studies. In the discovery phase, six miRNAs showed strong association with infertility with four (hsa-miR-9-3p, hsa-miR-30b-5p, hsa-miR-103-3p and hsa-miR-122-5p) showing consistent differential regulation across all sub-groups. Receiver operating characteristic (ROC) curve analysis showed that the area under curve of > 0.75 was achieved by three (hsa-mir-9-3p, hsa-miR-30b-5p and hsa-miR-122-5p) miRNAs. In the validation phase, these three miRNAs showed consistent association with infertility (hsa-mir-9-3p, hsa-miR-30b-5p, and hsa-miR-122-5p). Meta-analysis on hsa-miR-122-5p showed its significant quantitative association with infertility [Hedge's g = -2.428, p = 0.001 (Random effects)].ConclusionsThree miRNAs (hsa-miR-9-3p, hsa-miR-30b-5p and hsa-miR-122-5p) have strong linkage with infertility and a high potential as sperm quality biomarkers.

Dataset Information

Integrated network analysis identifies hsa-miR-4756-3p as a regulator of FOXM1 in Triple Negative Breast Cancer.

Publications

Integrated network analysis identifies hsa-miR-4756-3p as a regulator of FOXM1 in Triple Negative Breast Cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets