Cargando…

Identification of a 13-mRNA signature for predicting disease progression and prognosis in patients with bladder cancer

There are no reliable criteria to assess risk of progression of non-muscle invasive bladder cancer to muscle invasive bladder cancer. The aim of the present study was to identify potential markers based on gene expression profiling to improve predictive power of disease progression and prognosis in...

Descripción completa

Detalles Bibliográficos
Autores principales: Yin, Hubin, Zhang, Chen, Gou, Xin, He, Weiyang, Gan, Daoju
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6967157/
https://www.ncbi.nlm.nih.gov/pubmed/31894276
http://dx.doi.org/10.3892/or.2019.7429
_version_ 1783488893851533312
author Yin, Hubin
Zhang, Chen
Gou, Xin
He, Weiyang
Gan, Daoju
author_facet Yin, Hubin
Zhang, Chen
Gou, Xin
He, Weiyang
Gan, Daoju
author_sort Yin, Hubin
collection PubMed
description There are no reliable criteria to assess risk of progression of non-muscle invasive bladder cancer to muscle invasive bladder cancer. The aim of the present study was to identify potential markers based on gene expression profiling to improve predictive power of disease progression and prognosis in patients with bladder cancer. In the present study, we screened seventy-three differentially expressed genes by analyzing bladder cancer samples with or without progression. Forty-seven prognosis-related genes were screened, 13 of which were identified to build a progression-associated gene signature using the LASSO regression method. Based on this 13-mRNA signature, patients were divided into high- and low-risk groups, with different prognostic outcomes. The gene signature was an independent prognostic factor for overall survival. Receiver operating characteristic analysis suggested that the signature performed well in the validation cohort and its predictive power outperformed other several published signatures. CTHRC1, MMP11, AEBP1, SNCAIP, COL1A1 and S100A8 were identified as hub genes and their expression levels were detected using reverse transcriptase-quantitative polymerase chain reaction. The expression of CTHRC1 was elevated in aggressive bladder cancer compared with non-invasive type, which suggests CTHRC1 may be a valuable biomarker for prediction of prognosis and progression of bladder cancer. Collectively, this 13-mRNA signature may be useful in predicting disease progression and prognosis, thereby contributing to individualized management of patients with bladder cancer.
format Online
Article
Text
id pubmed-6967157
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher D.A. Spandidos
record_format MEDLINE/PubMed
spelling pubmed-69671572020-01-31 Identification of a 13-mRNA signature for predicting disease progression and prognosis in patients with bladder cancer Yin, Hubin Zhang, Chen Gou, Xin He, Weiyang Gan, Daoju Oncol Rep Articles There are no reliable criteria to assess risk of progression of non-muscle invasive bladder cancer to muscle invasive bladder cancer. The aim of the present study was to identify potential markers based on gene expression profiling to improve predictive power of disease progression and prognosis in patients with bladder cancer. In the present study, we screened seventy-three differentially expressed genes by analyzing bladder cancer samples with or without progression. Forty-seven prognosis-related genes were screened, 13 of which were identified to build a progression-associated gene signature using the LASSO regression method. Based on this 13-mRNA signature, patients were divided into high- and low-risk groups, with different prognostic outcomes. The gene signature was an independent prognostic factor for overall survival. Receiver operating characteristic analysis suggested that the signature performed well in the validation cohort and its predictive power outperformed other several published signatures. CTHRC1, MMP11, AEBP1, SNCAIP, COL1A1 and S100A8 were identified as hub genes and their expression levels were detected using reverse transcriptase-quantitative polymerase chain reaction. The expression of CTHRC1 was elevated in aggressive bladder cancer compared with non-invasive type, which suggests CTHRC1 may be a valuable biomarker for prediction of prognosis and progression of bladder cancer. Collectively, this 13-mRNA signature may be useful in predicting disease progression and prognosis, thereby contributing to individualized management of patients with bladder cancer. D.A. Spandidos 2020-02 2019-12-12 /pmc/articles/PMC6967157/ /pubmed/31894276 http://dx.doi.org/10.3892/or.2019.7429 Text en Copyright: © Yin et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Yin, Hubin
Zhang, Chen
Gou, Xin
He, Weiyang
Gan, Daoju
Identification of a 13-mRNA signature for predicting disease progression and prognosis in patients with bladder cancer
title Identification of a 13-mRNA signature for predicting disease progression and prognosis in patients with bladder cancer
title_full Identification of a 13-mRNA signature for predicting disease progression and prognosis in patients with bladder cancer
title_fullStr Identification of a 13-mRNA signature for predicting disease progression and prognosis in patients with bladder cancer
title_full_unstemmed Identification of a 13-mRNA signature for predicting disease progression and prognosis in patients with bladder cancer
title_short Identification of a 13-mRNA signature for predicting disease progression and prognosis in patients with bladder cancer
title_sort identification of a 13-mrna signature for predicting disease progression and prognosis in patients with bladder cancer
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6967157/
https://www.ncbi.nlm.nih.gov/pubmed/31894276
http://dx.doi.org/10.3892/or.2019.7429
work_keys_str_mv AT yinhubin identificationofa13mrnasignatureforpredictingdiseaseprogressionandprognosisinpatientswithbladdercancer
AT zhangchen identificationofa13mrnasignatureforpredictingdiseaseprogressionandprognosisinpatientswithbladdercancer
AT gouxin identificationofa13mrnasignatureforpredictingdiseaseprogressionandprognosisinpatientswithbladdercancer
AT heweiyang identificationofa13mrnasignatureforpredictingdiseaseprogressionandprognosisinpatientswithbladdercancer
AT gandaoju identificationofa13mrnasignatureforpredictingdiseaseprogressionandprognosisinpatientswithbladdercancer