Prognostic risk assessment model for alternative splicing events and splicing factors in malignant pleural mesothelioma

Abstract Background Malignant pleural mesothelioma (MPM) is a rare and highly malignant thoracic tumor. Although alternative splicing (AS) is associated with tumor prognosis, the prognostic significance of AS in MPM is unknown. Methods Transcriptomic data, clinical information, and splicing percenta...

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Main Authors: Yue Jiang, Chengda Zhang, Yang Chen, Shiyu Zhao, Yipeng He, Jun He
Format: Article
Language:English
Published: Wiley 2023-02-01
Series:Cancer Medicine
Online Access:https://doi.org/10.1002/cam4.5174
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author Yue Jiang
Chengda Zhang
Yang Chen
Shiyu Zhao
Yipeng He
Jun He
author_facet Yue Jiang
Chengda Zhang
Yang Chen
Shiyu Zhao
Yipeng He
Jun He
author_sort Yue Jiang
collection DOAJ
description Abstract Background Malignant pleural mesothelioma (MPM) is a rare and highly malignant thoracic tumor. Although alternative splicing (AS) is associated with tumor prognosis, the prognostic significance of AS in MPM is unknown. Methods Transcriptomic data, clinical information, and splicing percentage values for MPM were obtained from The Cancer Genome Atlas (TCGA) and TCGA SpliceSeq databases. Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analyses were performed to establish a model affecting the prognosis of MPM. Survival and ROC analyses were used to test the effects of the prognostic model. LASSO/multivariate Cox analysis was used to construct the MPM prognostic splicing factor (SF) model. The SF–AS interaction network was analyzed using Spearman correlation and visualized using Cytoscape. The association between the MPM prognostic SF model and drug sensitivity to chemotherapeutic agents such as cisplatin was analyzed using pRRophetic.R. Results The LASSO/multivariate Cox analysis identified 41 AS events and 2 SFs that were mostly associated with survival. Nine prognostic prediction models (i.e., seven types of AS model, total AS model, and SF model) were developed. An MPM prognostic SF–AS regulatory network was subsequently constructed with decreased drug sensitivity in the SF model high‐risk group (p = 0.025). Conclusion This study provides the first comprehensive analysis of the prognostic value of AS events and SFs in MPM. The SF–AS regulatory network established in this study and our drug sensitivity analysis using the SF model may provide novel targets for pharmacological studies of MPM.
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spelling doaj.art-c501c5fc84f9449ca4490d1069fb7e572023-02-28T08:51:57ZengWileyCancer Medicine2045-76342023-02-011244895490610.1002/cam4.5174Prognostic risk assessment model for alternative splicing events and splicing factors in malignant pleural mesotheliomaYue Jiang0Chengda Zhang1Yang Chen2Shiyu Zhao3Yipeng He4Jun He5Department of Clinical Medicine Southwest Medical University Luzhou ChinaDepartment of Gastroenterology The Third Hospital of Mian Yang (Sichuan Mental Health Center) Mianyang ChinaDepartment of Clinical Medicine Southwest Medical University Luzhou ChinaDepartment of Clinical Medicine Southwest Medical University Luzhou ChinaDepartment of Clinical Medicine Southwest Medical University Luzhou ChinaDepartment of Oncology The Third Hospital of Mian Yang (Sichuan Mental Health Center) Mianyang ChinaAbstract Background Malignant pleural mesothelioma (MPM) is a rare and highly malignant thoracic tumor. Although alternative splicing (AS) is associated with tumor prognosis, the prognostic significance of AS in MPM is unknown. Methods Transcriptomic data, clinical information, and splicing percentage values for MPM were obtained from The Cancer Genome Atlas (TCGA) and TCGA SpliceSeq databases. Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analyses were performed to establish a model affecting the prognosis of MPM. Survival and ROC analyses were used to test the effects of the prognostic model. LASSO/multivariate Cox analysis was used to construct the MPM prognostic splicing factor (SF) model. The SF–AS interaction network was analyzed using Spearman correlation and visualized using Cytoscape. The association between the MPM prognostic SF model and drug sensitivity to chemotherapeutic agents such as cisplatin was analyzed using pRRophetic.R. Results The LASSO/multivariate Cox analysis identified 41 AS events and 2 SFs that were mostly associated with survival. Nine prognostic prediction models (i.e., seven types of AS model, total AS model, and SF model) were developed. An MPM prognostic SF–AS regulatory network was subsequently constructed with decreased drug sensitivity in the SF model high‐risk group (p = 0.025). Conclusion This study provides the first comprehensive analysis of the prognostic value of AS events and SFs in MPM. The SF–AS regulatory network established in this study and our drug sensitivity analysis using the SF model may provide novel targets for pharmacological studies of MPM.https://doi.org/10.1002/cam4.5174
spellingShingle Yue Jiang
Chengda Zhang
Yang Chen
Shiyu Zhao
Yipeng He
Jun He
Prognostic risk assessment model for alternative splicing events and splicing factors in malignant pleural mesothelioma
Cancer Medicine
title Prognostic risk assessment model for alternative splicing events and splicing factors in malignant pleural mesothelioma
title_full Prognostic risk assessment model for alternative splicing events and splicing factors in malignant pleural mesothelioma
title_fullStr Prognostic risk assessment model for alternative splicing events and splicing factors in malignant pleural mesothelioma
title_full_unstemmed Prognostic risk assessment model for alternative splicing events and splicing factors in malignant pleural mesothelioma
title_short Prognostic risk assessment model for alternative splicing events and splicing factors in malignant pleural mesothelioma
title_sort prognostic risk assessment model for alternative splicing events and splicing factors in malignant pleural mesothelioma
url https://doi.org/10.1002/cam4.5174
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