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Comprehensive analysis of prognosis-related alternative splicing events in ovarian cancer

Ovarian cancer (OV) is characterized by high incidence and poor prognosis. Increasing evidence indicates that aberrant alternative splicing (AS) events are associated with the pathogenesis of cancer. We examined prognosis-related alternative splicing events and constructed a clinically applicable mo...

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Autores principales: Wang, Shizhi, Wang, Shiyuan, Zhang, Xing, Meng, Dan, Xia, Qianqian, Xie, Shuqian, Shen, Siyuan, Yu, Bingjia, Hu, Jing, Liu, Haohan, Yan, Wenjing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9397453/
https://www.ncbi.nlm.nih.gov/pubmed/35980273
http://dx.doi.org/10.1080/15476286.2022.2113148
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author Wang, Shizhi
Wang, Shiyuan
Zhang, Xing
Meng, Dan
Xia, Qianqian
Xie, Shuqian
Shen, Siyuan
Yu, Bingjia
Hu, Jing
Liu, Haohan
Yan, Wenjing
author_facet Wang, Shizhi
Wang, Shiyuan
Zhang, Xing
Meng, Dan
Xia, Qianqian
Xie, Shuqian
Shen, Siyuan
Yu, Bingjia
Hu, Jing
Liu, Haohan
Yan, Wenjing
author_sort Wang, Shizhi
collection PubMed
description Ovarian cancer (OV) is characterized by high incidence and poor prognosis. Increasing evidence indicates that aberrant alternative splicing (AS) events are associated with the pathogenesis of cancer. We examined prognosis-related alternative splicing events and constructed a clinically applicable model to predict patients’ outcomes. Public database including The Cancer Genome Atlas (TCGA), TCGA SpliceSeq, and the Genomics of Drug Sensitivity in Cancer databases were used to detect the AS expression, immune cell infiltration and IC50. The prognosis-related AS model was constructed and validated by using Cox regression, LASSO regression, C-index, calibration plots, and ROC curves. A total of eight AS events (including FLT3LG|50942|AP) were selected to establish the prognosis-related AS model. Compared with high-risk group, low-risk group had a better outcome (P = 1.794e-06), was more sensitive to paclitaxel (P = 0.022), and higher proportions of plasma cells. We explored the upstream regulatory mechanisms of prognosis-related AS and found that two splicing factor and 156 tag single nucleotide polymorphisms may be involved in the regulation of prognosis-related AS. In order to assess patient prognosis more comprehensively, we constructed a clinically applicable model combining risk score and clinicopathological features, and the 1 -, and 3-year AUCs of the clinically applicable model were 0.812, and 0.726, which were 7.5% and 3.3% higher than that of the risk score. We constructed a prognostic signature for OV patients and comprehensively analysed the regulatory characteristics of the prognostic AS events in OV.
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spelling pubmed-93974532022-08-24 Comprehensive analysis of prognosis-related alternative splicing events in ovarian cancer Wang, Shizhi Wang, Shiyuan Zhang, Xing Meng, Dan Xia, Qianqian Xie, Shuqian Shen, Siyuan Yu, Bingjia Hu, Jing Liu, Haohan Yan, Wenjing RNA Biol Research Paper Ovarian cancer (OV) is characterized by high incidence and poor prognosis. Increasing evidence indicates that aberrant alternative splicing (AS) events are associated with the pathogenesis of cancer. We examined prognosis-related alternative splicing events and constructed a clinically applicable model to predict patients’ outcomes. Public database including The Cancer Genome Atlas (TCGA), TCGA SpliceSeq, and the Genomics of Drug Sensitivity in Cancer databases were used to detect the AS expression, immune cell infiltration and IC50. The prognosis-related AS model was constructed and validated by using Cox regression, LASSO regression, C-index, calibration plots, and ROC curves. A total of eight AS events (including FLT3LG|50942|AP) were selected to establish the prognosis-related AS model. Compared with high-risk group, low-risk group had a better outcome (P = 1.794e-06), was more sensitive to paclitaxel (P = 0.022), and higher proportions of plasma cells. We explored the upstream regulatory mechanisms of prognosis-related AS and found that two splicing factor and 156 tag single nucleotide polymorphisms may be involved in the regulation of prognosis-related AS. In order to assess patient prognosis more comprehensively, we constructed a clinically applicable model combining risk score and clinicopathological features, and the 1 -, and 3-year AUCs of the clinically applicable model were 0.812, and 0.726, which were 7.5% and 3.3% higher than that of the risk score. We constructed a prognostic signature for OV patients and comprehensively analysed the regulatory characteristics of the prognostic AS events in OV. Taylor & Francis 2022-08-18 /pmc/articles/PMC9397453/ /pubmed/35980273 http://dx.doi.org/10.1080/15476286.2022.2113148 Text en © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Paper
Wang, Shizhi
Wang, Shiyuan
Zhang, Xing
Meng, Dan
Xia, Qianqian
Xie, Shuqian
Shen, Siyuan
Yu, Bingjia
Hu, Jing
Liu, Haohan
Yan, Wenjing
Comprehensive analysis of prognosis-related alternative splicing events in ovarian cancer
title Comprehensive analysis of prognosis-related alternative splicing events in ovarian cancer
title_full Comprehensive analysis of prognosis-related alternative splicing events in ovarian cancer
title_fullStr Comprehensive analysis of prognosis-related alternative splicing events in ovarian cancer
title_full_unstemmed Comprehensive analysis of prognosis-related alternative splicing events in ovarian cancer
title_short Comprehensive analysis of prognosis-related alternative splicing events in ovarian cancer
title_sort comprehensive analysis of prognosis-related alternative splicing events in ovarian cancer
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9397453/
https://www.ncbi.nlm.nih.gov/pubmed/35980273
http://dx.doi.org/10.1080/15476286.2022.2113148
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