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Identification of the Potential Prognostic Markers from the miRNA-lncRNA-mRNA Interactions for Metastatic Renal Cancer via Next-Generation Sequencing and Bioinformatics
The survival rate in patients with metastatic renal cell carcinoma (RCC) is low. In addition, metastatic RCC resists traditional treatment. Therefore, identification of novel biomarkers, signaling pathways, and therapeutic targets is an important issue. The aim of the present study is to identify no...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7235743/ https://www.ncbi.nlm.nih.gov/pubmed/32316228 http://dx.doi.org/10.3390/diagnostics10040228 |
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author | Yeh, I-Jeng Liu, Kuan-Ting Shen, Jheng-Heng Wu, Yen-Hung Liu, Yao-Hua Yen, Meng-Chi Kuo, Po-Lin |
author_facet | Yeh, I-Jeng Liu, Kuan-Ting Shen, Jheng-Heng Wu, Yen-Hung Liu, Yao-Hua Yen, Meng-Chi Kuo, Po-Lin |
author_sort | Yeh, I-Jeng |
collection | PubMed |
description | The survival rate in patients with metastatic renal cell carcinoma (RCC) is low. In addition, metastatic RCC resists traditional treatment. Therefore, identification of novel biomarkers, signaling pathways, and therapeutic targets is an important issue. The aim of the present study is to identify novel prognostic markers from the miRNA-mediated network for the regulation of metastasis of RCC. To address this issue, the RNA of human RCC cell lines, 786-O and ACHN, derived from primary and metastatic sites, respectively, were collected and subjected to RNA sequencing and small RNA sequencing. The bioinformatic analysis revealed that the pathways of the genes with different expressions were related to tumor progression, and identified miRNA and miRNA-long non-coding RNA (lncRNA) interactions, and mRNA. The results revealed that the expressions of seven miRNAs were associated with the overall survival rate of patients with RCC. Furthermore, the expressions of two lncRNA and three protein-coding genes (mRNA) were significantly associated with the increased or decreased disease-free survival rate. Although the detailed regulatory mechanism between miRNAs and targeted genes was not fully understood, our findings present novel prognostic markers and novel insight on miRNA-mediated pathways for metastatic RCC. |
format | Online Article Text |
id | pubmed-7235743 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-72357432020-05-22 Identification of the Potential Prognostic Markers from the miRNA-lncRNA-mRNA Interactions for Metastatic Renal Cancer via Next-Generation Sequencing and Bioinformatics Yeh, I-Jeng Liu, Kuan-Ting Shen, Jheng-Heng Wu, Yen-Hung Liu, Yao-Hua Yen, Meng-Chi Kuo, Po-Lin Diagnostics (Basel) Article The survival rate in patients with metastatic renal cell carcinoma (RCC) is low. In addition, metastatic RCC resists traditional treatment. Therefore, identification of novel biomarkers, signaling pathways, and therapeutic targets is an important issue. The aim of the present study is to identify novel prognostic markers from the miRNA-mediated network for the regulation of metastasis of RCC. To address this issue, the RNA of human RCC cell lines, 786-O and ACHN, derived from primary and metastatic sites, respectively, were collected and subjected to RNA sequencing and small RNA sequencing. The bioinformatic analysis revealed that the pathways of the genes with different expressions were related to tumor progression, and identified miRNA and miRNA-long non-coding RNA (lncRNA) interactions, and mRNA. The results revealed that the expressions of seven miRNAs were associated with the overall survival rate of patients with RCC. Furthermore, the expressions of two lncRNA and three protein-coding genes (mRNA) were significantly associated with the increased or decreased disease-free survival rate. Although the detailed regulatory mechanism between miRNAs and targeted genes was not fully understood, our findings present novel prognostic markers and novel insight on miRNA-mediated pathways for metastatic RCC. MDPI 2020-04-16 /pmc/articles/PMC7235743/ /pubmed/32316228 http://dx.doi.org/10.3390/diagnostics10040228 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Yeh, I-Jeng Liu, Kuan-Ting Shen, Jheng-Heng Wu, Yen-Hung Liu, Yao-Hua Yen, Meng-Chi Kuo, Po-Lin Identification of the Potential Prognostic Markers from the miRNA-lncRNA-mRNA Interactions for Metastatic Renal Cancer via Next-Generation Sequencing and Bioinformatics |
title | Identification of the Potential Prognostic Markers from the miRNA-lncRNA-mRNA Interactions for Metastatic Renal Cancer via Next-Generation Sequencing and Bioinformatics |
title_full | Identification of the Potential Prognostic Markers from the miRNA-lncRNA-mRNA Interactions for Metastatic Renal Cancer via Next-Generation Sequencing and Bioinformatics |
title_fullStr | Identification of the Potential Prognostic Markers from the miRNA-lncRNA-mRNA Interactions for Metastatic Renal Cancer via Next-Generation Sequencing and Bioinformatics |
title_full_unstemmed | Identification of the Potential Prognostic Markers from the miRNA-lncRNA-mRNA Interactions for Metastatic Renal Cancer via Next-Generation Sequencing and Bioinformatics |
title_short | Identification of the Potential Prognostic Markers from the miRNA-lncRNA-mRNA Interactions for Metastatic Renal Cancer via Next-Generation Sequencing and Bioinformatics |
title_sort | identification of the potential prognostic markers from the mirna-lncrna-mrna interactions for metastatic renal cancer via next-generation sequencing and bioinformatics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7235743/ https://www.ncbi.nlm.nih.gov/pubmed/32316228 http://dx.doi.org/10.3390/diagnostics10040228 |
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