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Prognostic index of aberrant mRNA splicing profiling acts as a predictive indicator for hepatocellular carcinoma based on TCGA SpliceSeq data

Alternative splicing in tumor cells may be used as a molecular marker for the differential diagnosis of certain tumor types and assessment of prognosis. The aim of the present study was to investigate the associations among alternative splicing events, splicing factors, and the survival of patients...

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Autores principales: Wu, Hua-Yu, Peng, Zhi-Gang, He, Rong-Quan, Luo, Bin, Ma, Jie, Hu, Xiao-Hua, Dang, Yi-Wu, Chen, Gang, Pan, Shang-Ling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6615926/
https://www.ncbi.nlm.nih.gov/pubmed/31268164
http://dx.doi.org/10.3892/ijo.2019.4834
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author Wu, Hua-Yu
Peng, Zhi-Gang
He, Rong-Quan
Luo, Bin
Ma, Jie
Hu, Xiao-Hua
Dang, Yi-Wu
Chen, Gang
Pan, Shang-Ling
author_facet Wu, Hua-Yu
Peng, Zhi-Gang
He, Rong-Quan
Luo, Bin
Ma, Jie
Hu, Xiao-Hua
Dang, Yi-Wu
Chen, Gang
Pan, Shang-Ling
author_sort Wu, Hua-Yu
collection PubMed
description Alternative splicing in tumor cells may be used as a molecular marker for the differential diagnosis of certain tumor types and assessment of prognosis. The aim of the present study was to investigate the associations among alternative splicing events, splicing factors, and the survival of patients with hepatocellular carcinoma (HCC). The alternative splicing event profiles of 371 patients with HCC were downloaded from The Cancer Genome Atlas (TCGA) SpliceSeq data, and the percent-splice-in value for each splicing event was calculated. The association between alternative splicing events and overall survival was evaluated. The most significant prognosis-related splicing events were used to build up a prognostic index (PI). A total of 3,082 survival-associated alternative splicing events were detected in HCC. The final PI based on all of the most significant candidate alternative splicing events exhibited better performance in distinguishing good or poor survival in patients compared to the PI based on a single type of splicing event. Receiver operating characteristic curves confirmed the high efficiency of the PI in predicting the survival of HCC patients, with an area under the curve of 0.914. The overexpression of 32 prognosis-related splicing factor genes could also predict poor prognosis in patients with HCC. In conclusion, the constructed computational prognostic model based on HCC-specific alternative splicing events may be used as a molecular marker for the prognosis of HCC.
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spelling pubmed-66159262019-07-30 Prognostic index of aberrant mRNA splicing profiling acts as a predictive indicator for hepatocellular carcinoma based on TCGA SpliceSeq data Wu, Hua-Yu Peng, Zhi-Gang He, Rong-Quan Luo, Bin Ma, Jie Hu, Xiao-Hua Dang, Yi-Wu Chen, Gang Pan, Shang-Ling Int J Oncol Articles Alternative splicing in tumor cells may be used as a molecular marker for the differential diagnosis of certain tumor types and assessment of prognosis. The aim of the present study was to investigate the associations among alternative splicing events, splicing factors, and the survival of patients with hepatocellular carcinoma (HCC). The alternative splicing event profiles of 371 patients with HCC were downloaded from The Cancer Genome Atlas (TCGA) SpliceSeq data, and the percent-splice-in value for each splicing event was calculated. The association between alternative splicing events and overall survival was evaluated. The most significant prognosis-related splicing events were used to build up a prognostic index (PI). A total of 3,082 survival-associated alternative splicing events were detected in HCC. The final PI based on all of the most significant candidate alternative splicing events exhibited better performance in distinguishing good or poor survival in patients compared to the PI based on a single type of splicing event. Receiver operating characteristic curves confirmed the high efficiency of the PI in predicting the survival of HCC patients, with an area under the curve of 0.914. The overexpression of 32 prognosis-related splicing factor genes could also predict poor prognosis in patients with HCC. In conclusion, the constructed computational prognostic model based on HCC-specific alternative splicing events may be used as a molecular marker for the prognosis of HCC. D.A. Spandidos 2019-06-27 /pmc/articles/PMC6615926/ /pubmed/31268164 http://dx.doi.org/10.3892/ijo.2019.4834 Text en Copyright: © Wu 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
Wu, Hua-Yu
Peng, Zhi-Gang
He, Rong-Quan
Luo, Bin
Ma, Jie
Hu, Xiao-Hua
Dang, Yi-Wu
Chen, Gang
Pan, Shang-Ling
Prognostic index of aberrant mRNA splicing profiling acts as a predictive indicator for hepatocellular carcinoma based on TCGA SpliceSeq data
title Prognostic index of aberrant mRNA splicing profiling acts as a predictive indicator for hepatocellular carcinoma based on TCGA SpliceSeq data
title_full Prognostic index of aberrant mRNA splicing profiling acts as a predictive indicator for hepatocellular carcinoma based on TCGA SpliceSeq data
title_fullStr Prognostic index of aberrant mRNA splicing profiling acts as a predictive indicator for hepatocellular carcinoma based on TCGA SpliceSeq data
title_full_unstemmed Prognostic index of aberrant mRNA splicing profiling acts as a predictive indicator for hepatocellular carcinoma based on TCGA SpliceSeq data
title_short Prognostic index of aberrant mRNA splicing profiling acts as a predictive indicator for hepatocellular carcinoma based on TCGA SpliceSeq data
title_sort prognostic index of aberrant mrna splicing profiling acts as a predictive indicator for hepatocellular carcinoma based on tcga spliceseq data
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6615926/
https://www.ncbi.nlm.nih.gov/pubmed/31268164
http://dx.doi.org/10.3892/ijo.2019.4834
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