Cargando…

Weighted miRNA co-expression networks analysis identifies circulating miRNA predicting overall survival in hepatocellular carcinoma patients

The weighted gene co-expression network analysis (WGCNA) has been used to explore gene expression datasets by constructing biological networks based on the likelihood expression profile among genes. In recent years, WGCNA found application in biomarker discovery studies, including miRNA. Serum sampl...

Descripción completa

Detalles Bibliográficos
Autores principales: Pascut, Devis, Pratama, Muhammad Yogi, Gilardi, Francesca, Giuffrè, Mauro, Crocè, Lory Saveria, Tiribelli, Claudio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7609726/
https://www.ncbi.nlm.nih.gov/pubmed/33144628
http://dx.doi.org/10.1038/s41598-020-75945-2
_version_ 1783605061368152064
author Pascut, Devis
Pratama, Muhammad Yogi
Gilardi, Francesca
Giuffrè, Mauro
Crocè, Lory Saveria
Tiribelli, Claudio
author_facet Pascut, Devis
Pratama, Muhammad Yogi
Gilardi, Francesca
Giuffrè, Mauro
Crocè, Lory Saveria
Tiribelli, Claudio
author_sort Pascut, Devis
collection PubMed
description The weighted gene co-expression network analysis (WGCNA) has been used to explore gene expression datasets by constructing biological networks based on the likelihood expression profile among genes. In recent years, WGCNA found application in biomarker discovery studies, including miRNA. Serum samples from 20 patients with hepatocellular carcinoma (HCC) were profiled through miRNA 3.0 gene array and miRNAs biomarker candidates were identified through WGCNA. Results were validated by qRT-PCR in 102 HCC serum samples collected at diagnosis. WGCNA identified 16 miRNA modules, nine of them were significantly associated with the clinical characteristics of the patient. The Red module had a significant negative correlation with patients Survival (− 0.59, p = 0.007) and albumin (− 0.52, p = 0.02), and a positive correlation with PCR (0.61, p = 0.004) and alpha-fetoprotein (0.51, p = 0.02). In the red module, 16 circulating miRNAs were significantly associated with patient survival. MiR-3185 and miR-4507 were identified as predictors of patient survival after the validation phase. At diagnosis, high expression of circulating miR-3185 and miR-4507 identifies patients with longer survival (HR 2.02, 95% CI 1.10–3.73, p = 0.0086, and HR of 1.75, 95% CI 1.02–3.02, p = 0.037, respectively). Thought a WGCNA we identified miR-3185 and miR-4507 as promising candidate biomarkers predicting a longer survival in HCC patients.
format Online
Article
Text
id pubmed-7609726
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-76097262020-11-05 Weighted miRNA co-expression networks analysis identifies circulating miRNA predicting overall survival in hepatocellular carcinoma patients Pascut, Devis Pratama, Muhammad Yogi Gilardi, Francesca Giuffrè, Mauro Crocè, Lory Saveria Tiribelli, Claudio Sci Rep Article The weighted gene co-expression network analysis (WGCNA) has been used to explore gene expression datasets by constructing biological networks based on the likelihood expression profile among genes. In recent years, WGCNA found application in biomarker discovery studies, including miRNA. Serum samples from 20 patients with hepatocellular carcinoma (HCC) were profiled through miRNA 3.0 gene array and miRNAs biomarker candidates were identified through WGCNA. Results were validated by qRT-PCR in 102 HCC serum samples collected at diagnosis. WGCNA identified 16 miRNA modules, nine of them were significantly associated with the clinical characteristics of the patient. The Red module had a significant negative correlation with patients Survival (− 0.59, p = 0.007) and albumin (− 0.52, p = 0.02), and a positive correlation with PCR (0.61, p = 0.004) and alpha-fetoprotein (0.51, p = 0.02). In the red module, 16 circulating miRNAs were significantly associated with patient survival. MiR-3185 and miR-4507 were identified as predictors of patient survival after the validation phase. At diagnosis, high expression of circulating miR-3185 and miR-4507 identifies patients with longer survival (HR 2.02, 95% CI 1.10–3.73, p = 0.0086, and HR of 1.75, 95% CI 1.02–3.02, p = 0.037, respectively). Thought a WGCNA we identified miR-3185 and miR-4507 as promising candidate biomarkers predicting a longer survival in HCC patients. Nature Publishing Group UK 2020-11-03 /pmc/articles/PMC7609726/ /pubmed/33144628 http://dx.doi.org/10.1038/s41598-020-75945-2 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Pascut, Devis
Pratama, Muhammad Yogi
Gilardi, Francesca
Giuffrè, Mauro
Crocè, Lory Saveria
Tiribelli, Claudio
Weighted miRNA co-expression networks analysis identifies circulating miRNA predicting overall survival in hepatocellular carcinoma patients
title Weighted miRNA co-expression networks analysis identifies circulating miRNA predicting overall survival in hepatocellular carcinoma patients
title_full Weighted miRNA co-expression networks analysis identifies circulating miRNA predicting overall survival in hepatocellular carcinoma patients
title_fullStr Weighted miRNA co-expression networks analysis identifies circulating miRNA predicting overall survival in hepatocellular carcinoma patients
title_full_unstemmed Weighted miRNA co-expression networks analysis identifies circulating miRNA predicting overall survival in hepatocellular carcinoma patients
title_short Weighted miRNA co-expression networks analysis identifies circulating miRNA predicting overall survival in hepatocellular carcinoma patients
title_sort weighted mirna co-expression networks analysis identifies circulating mirna predicting overall survival in hepatocellular carcinoma patients
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7609726/
https://www.ncbi.nlm.nih.gov/pubmed/33144628
http://dx.doi.org/10.1038/s41598-020-75945-2
work_keys_str_mv AT pascutdevis weightedmirnacoexpressionnetworksanalysisidentifiescirculatingmirnapredictingoverallsurvivalinhepatocellularcarcinomapatients
AT pratamamuhammadyogi weightedmirnacoexpressionnetworksanalysisidentifiescirculatingmirnapredictingoverallsurvivalinhepatocellularcarcinomapatients
AT gilardifrancesca weightedmirnacoexpressionnetworksanalysisidentifiescirculatingmirnapredictingoverallsurvivalinhepatocellularcarcinomapatients
AT giuffremauro weightedmirnacoexpressionnetworksanalysisidentifiescirculatingmirnapredictingoverallsurvivalinhepatocellularcarcinomapatients
AT crocelorysaveria weightedmirnacoexpressionnetworksanalysisidentifiescirculatingmirnapredictingoverallsurvivalinhepatocellularcarcinomapatients
AT tiribelliclaudio weightedmirnacoexpressionnetworksanalysisidentifiescirculatingmirnapredictingoverallsurvivalinhepatocellularcarcinomapatients