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MicroRNA signature for estimating the survival time in patients with bladder urothelial carcinoma

Bladder urothelial carcinoma (BLC) is one of the most common cancers in men, and its heterogeneity challenges the treatment to cure this disease. Recently, microRNAs (miRNAs) gained promising attention as biomarkers due to their potential roles in cancer biology. Identifying survival-associated miRN...

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Autores principales: Yerukala Sathipati, Srinivasulu, Tsai, Ming-Ju, Shukla, Sanjay K., Ho, Shinn-Ying, Liu, Yi, Beheshti, Afshin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8907292/
https://www.ncbi.nlm.nih.gov/pubmed/35264666
http://dx.doi.org/10.1038/s41598-022-08082-7
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author Yerukala Sathipati, Srinivasulu
Tsai, Ming-Ju
Shukla, Sanjay K.
Ho, Shinn-Ying
Liu, Yi
Beheshti, Afshin
author_facet Yerukala Sathipati, Srinivasulu
Tsai, Ming-Ju
Shukla, Sanjay K.
Ho, Shinn-Ying
Liu, Yi
Beheshti, Afshin
author_sort Yerukala Sathipati, Srinivasulu
collection PubMed
description Bladder urothelial carcinoma (BLC) is one of the most common cancers in men, and its heterogeneity challenges the treatment to cure this disease. Recently, microRNAs (miRNAs) gained promising attention as biomarkers due to their potential roles in cancer biology. Identifying survival-associated miRNAs may help identify targets for therapeutic interventions in BLC. This work aims to identify a miRNA signature that could estimate the survival in patients with BLC. We developed a survival estimation method called BLC-SVR based on support vector regression incorporated with an optimal feature selection algorithm to select a robust set of miRNAs as a signature to estimate the survival in patients with BLC. BLC-SVR identified a miRNA signature consisting of 29 miRNAs and obtained a mean squared correlation coefficient and mean absolute error of 0.79 ± 0.02 and 0.52 ± 0.32 year between actual and estimated survival times, respectively. The prediction performance of BLC-SVR had a better estimation capability than other standard regression methods. In the identified miRNA signature, 14 miRNAs, hsa-miR-432-5p, hsa-let-7e-3p, hsa-miR-652-3p, hsa-miR-629-5p, and hsa-miR-203a-3p, hsa-miR-129-5p, hsa-miR-769-3p, hsa-miR-570-3p, hsa-miR-320c, hsa-miR-642a-5p, hsa-miR-496, hsa-miR-5480-3p, hsa-miR-221-5p, and hsa-miR-7-1-3p, were found to be good biomarkers for BLC diagnosis; and the six miRNAs, hsa-miR-652-5p, hsa-miR-193b-5p, hsa-miR-129-5p, hsa-miR-143-5p, hsa-miR-496, and hsa-miR-7-1-3p, were found to be good biomarkers of prognosis. Further bioinformatics analysis of this miRNA signature demonstrated its importance in various biological pathways and gene ontology annotation. The identified miRNA signature would further help in understanding of BLC diagnosis and prognosis in the development of novel miRNA-target based therapeutics in BLC.
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spelling pubmed-89072922022-03-11 MicroRNA signature for estimating the survival time in patients with bladder urothelial carcinoma Yerukala Sathipati, Srinivasulu Tsai, Ming-Ju Shukla, Sanjay K. Ho, Shinn-Ying Liu, Yi Beheshti, Afshin Sci Rep Article Bladder urothelial carcinoma (BLC) is one of the most common cancers in men, and its heterogeneity challenges the treatment to cure this disease. Recently, microRNAs (miRNAs) gained promising attention as biomarkers due to their potential roles in cancer biology. Identifying survival-associated miRNAs may help identify targets for therapeutic interventions in BLC. This work aims to identify a miRNA signature that could estimate the survival in patients with BLC. We developed a survival estimation method called BLC-SVR based on support vector regression incorporated with an optimal feature selection algorithm to select a robust set of miRNAs as a signature to estimate the survival in patients with BLC. BLC-SVR identified a miRNA signature consisting of 29 miRNAs and obtained a mean squared correlation coefficient and mean absolute error of 0.79 ± 0.02 and 0.52 ± 0.32 year between actual and estimated survival times, respectively. The prediction performance of BLC-SVR had a better estimation capability than other standard regression methods. In the identified miRNA signature, 14 miRNAs, hsa-miR-432-5p, hsa-let-7e-3p, hsa-miR-652-3p, hsa-miR-629-5p, and hsa-miR-203a-3p, hsa-miR-129-5p, hsa-miR-769-3p, hsa-miR-570-3p, hsa-miR-320c, hsa-miR-642a-5p, hsa-miR-496, hsa-miR-5480-3p, hsa-miR-221-5p, and hsa-miR-7-1-3p, were found to be good biomarkers for BLC diagnosis; and the six miRNAs, hsa-miR-652-5p, hsa-miR-193b-5p, hsa-miR-129-5p, hsa-miR-143-5p, hsa-miR-496, and hsa-miR-7-1-3p, were found to be good biomarkers of prognosis. Further bioinformatics analysis of this miRNA signature demonstrated its importance in various biological pathways and gene ontology annotation. The identified miRNA signature would further help in understanding of BLC diagnosis and prognosis in the development of novel miRNA-target based therapeutics in BLC. Nature Publishing Group UK 2022-03-09 /pmc/articles/PMC8907292/ /pubmed/35264666 http://dx.doi.org/10.1038/s41598-022-08082-7 Text en © The Author(s) 2022, corrected publication 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Yerukala Sathipati, Srinivasulu
Tsai, Ming-Ju
Shukla, Sanjay K.
Ho, Shinn-Ying
Liu, Yi
Beheshti, Afshin
MicroRNA signature for estimating the survival time in patients with bladder urothelial carcinoma
title MicroRNA signature for estimating the survival time in patients with bladder urothelial carcinoma
title_full MicroRNA signature for estimating the survival time in patients with bladder urothelial carcinoma
title_fullStr MicroRNA signature for estimating the survival time in patients with bladder urothelial carcinoma
title_full_unstemmed MicroRNA signature for estimating the survival time in patients with bladder urothelial carcinoma
title_short MicroRNA signature for estimating the survival time in patients with bladder urothelial carcinoma
title_sort microrna signature for estimating the survival time in patients with bladder urothelial carcinoma
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8907292/
https://www.ncbi.nlm.nih.gov/pubmed/35264666
http://dx.doi.org/10.1038/s41598-022-08082-7
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