Dataset Information

MicroRNA-138 attenuates epithelial-to-mesenchymal transition by targeting SOX4 in clear cell renal cell carcinoma.

ABSTRACT: MicroRNAs (miRNAs) are small, non-coding RNAs which can serve as oncogenes or tumor suppressor genes in human cancers. Herein, the transcriptomic differences of miRNAs in ccRCC were globally assessed using publicly available microarray dataset (GSE71302) from Gene Expression Omnibus (GEO) and we identified miR-138 as a potential onco-suppressive miRNA. We further found that the expression of miR-138 was dramatically decreased in ccRCC cell lines and clinical ccRCC tissue samples, and the low miR-138 expression was closely correlated with tumor progression and prognosis in ccRCC patients. Overexpression of miR-138 inhibited, whereas downregulation of miR-138 promoted, the proliferation, migration and invasion of ccRCC cells in vitro, suggesting that miR-138 may function as a tumor suppressor in ccRCC. Furthermore, for the first time, we identified the EMT-related transcription factor SOX4 as a direct target gene of miR-138, evidenced by the direct binding of miR-138 with the 3'UTR of SOX4. Notably, the EMT marker E-cadherin or vimentin was also upregulated or downregulated upon miR-138 overexpression, and these effects were restored by SOX4 overexpression. We have also shown SOX4 overexpression reversed the attenuated migratory and invasive capacities mediated by miR-138. These results revealed that miR-138 functions as a tumor suppressor in ccRCC by targeting SOX4 and the EMT process and might represent a potential target in the treatment of human ccRCC.

SUBMITTER: Liu F

PROVIDER: S-EPMC5575175 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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MicroRNA-138 attenuates epithelial-to-mesenchymal transition by targeting SOX4 in clear cell renal cell carcinoma.

Liu Feng F Wu Linfeng L Wang Anping A Xu Yajun Y Luo Xiaodong X Liu Xing X Hua Yi Y Zhang Deying D Wu Shengde S Lin Tao T He Dawei D Wei Guanghui G Chen Shanwen S

American journal of translational research 20170815 8

MicroRNAs (miRNAs) are small, non-coding RNAs which can serve as oncogenes or tumor suppressor genes in human cancers. Herein, the transcriptomic differences of miRNAs in ccRCC were globally assessed using publicly available microarray dataset (GSE71302) from Gene Expression Omnibus (GEO) and we identified miR-138 as a potential onco-suppressive miRNA. We further found that the expression of miR-138 was dramatically decreased in ccRCC cell lines and clinical ccRCC tissue samples, and the low miR ...[more]

PMID: 28861152

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Project description:BackgroundA rising amount of data demonstrates that the epithelial-mesenchymal transition (EMT) in clear cell renal cell carcinomas (ccRCC) is connected with the advancement of the cancer. In order to understand the role of EMT in ccRCC, it is critical to integrate molecules involved in EMT into prognosis prediction. The objective of this project was to establish a prognosis prediction model using genes associated with EMT in ccRCC.MethodsWe acquired the mRNA expression profiles and clinical information about ccRCC from TCGA database. In this study, we measured differentially expressed EMT-related genes (DEEGs) by two comparison groups (tumor versus normal tissues; "stages I-II" versus "stages III-IV" tumor tissues). Based on classification and regression random forest models, we identified the most important DEEGs in predicting prognosis. Afterwards, a risk-score model was created using the identified important DEEGs. The prediction ability of the risk-score model was calculated by the area under the curve (AUC). A nomogram for prognosis prediction was built using the risk-score in combination with clinical factors.ResultsAmong the 72 DEEGs, the classification and regression random forest models identified six hub genes (DKK1, DLX4, IL6, KCNN4, RPL22L1, and SPDEF), which exhibited the highest importance values in both models. Through the expression of these six hub genes, a novel risk-score was developed for the prognosis prediction of ccRCC. ROC curves showed the risk-score performed well in both the training (0.749) and testing (0.777) datasets. According to the survival analysis, individuals who were separated into high/low-risk groups had statistically different outcomes in terms of prognosis. Besides, the risk-score model also showed outstanding ability in assessing the progression of ccRCC after treatment. In terms of nomogram, the concordance index (C-index) was 0.79. Additionally, we predicted the differences in response to chemotherapy drugs among patients from low- and high-risk groups.ConclusionGene signatures related to EMT could be useful in predicting ccRCC prognosis.

Project description:Epithelial-mesenchymal transition (EMT), a reversible cellular program, is critically important in tumor progression and is regulated by a family of transcription factors, induction factors, and an array of signaling pathway genes. The prognostic role and biological functions of EMT-related lncRNAs in ccRCC are largely unknown. In the present study, we analyzed the gene expression data and clinical information retrieved from The Cancer Genome Atlas (TCGA) database (N=512) and International Cancer Genome Consortium (ICGC) database (N=90) which served as training and external validation dataset, respectively. Then, we constructed an EMT-related lncRNA risk signature based on the comprehensive analysis of the EMT-related lncRNA expression data and clinical information. The Kaplan-Meier curve analysis revealed that patients in the low-risk and high-risk groups exhibited significant divergence in the overall survival (OS) and disease-free survival (DFS) of ccRCC, as was confirmed in the validation dataset. The Cox regression analysis of the clinical factors and risk signature in the OS and DFS demonstrated that the risk signature can be utilized as an independent prognostic predictor. Moreover, we developed an individualized prognosis prediction model relying on the nomogram and receive operator curve (ROC) analysis based on the independent factors. The Gene Set Enrichment Analysis (GSEA) indicated that patients in the low-risk group were associated with adherens junction, focal adhesion, MAPK signaling pathway, pathways in cancer, and renal cell carcinoma pathway. In addition, we identified three robust subtypes (named C1, C2 and C3) of ccRCC with distinct clinical characteristics and prognostic role in the TCGA dataset and ICGC dataset. Among them, C1 was associated with a better survival outcome, whereas C2 and C3 was associated with a worse survival outcome and have more advanced-stage patients. Moreover, C2 was more likely to respond to immunotherapy and was sensitive to chemo drugs, this may provide insights to clinicians to develop an individualized treatment. Collectively, this work developed a reliable EMT-related lncRNA risk signature that can independently predict the OS and DFS of ccRCC. Besides, we identified three stable molecular subtypes based on the EMT-related lncRNA expression, which may comprehensively be vital in elucidating the underlying molecular mechanism of ccRCC.

Dataset Information

MicroRNA-138 attenuates epithelial-to-mesenchymal transition by targeting SOX4 in clear cell renal cell carcinoma.

Publications

MicroRNA-138 attenuates epithelial-to-mesenchymal transition by targeting SOX4 in clear cell renal cell carcinoma.

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