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Updated: Aug 30, 2025
Detection of Alternative Splicing During Epithelial-Mesenchymal Transition
Published on: October 9, 2014
Prognostic risk assessment model for alternative splicing events and splicing factors in malignant pleural
Yue Jiang1, Chengda Zhang2, Yang Chen1
1Department of Clinical Medicine, Southwest Medical University, Luzhou, China.
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.
Insights
This study reveals alternative splicing (AS) events and splicing factors (SFs) as key prognostic indicators for malignant pleural mesothelioma (MPM). The developed SF-AS regulatory network and drug sensitivity analysis offer potential new therapeutic targets for MPM.
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- Malignant pleural mesothelioma (MPM) is a rare, aggressive thoracic cancer.
- The prognostic role of alternative splicing (AS) in MPM remains largely unexplored.
Purpose of the Study:
- To investigate the prognostic significance of AS events and splicing factors (SFs) in MPM.
- To develop a predictive model for MPM prognosis based on AS and SFs.
- To explore the relationship between SFs, AS, and drug sensitivity in MPM.
Main Methods:
- Utilized transcriptomic data from TCGA and TCGA SpliceSeq for MPM.
- Employed LASSO regression and multivariate Cox analyses to build prognostic models.
- Constructed an SF-AS interaction network and analyzed drug sensitivity using pRRophetic.R.
Main Results:
- Identified 41 AS events and 2 SFs significantly associated with MPM survival.
- Developed nine prognostic prediction models, including AS and SF-based models.
- Established an MPM prognostic SF-AS regulatory network and observed decreased drug sensitivity in the high-risk SF group.
Conclusions:
- This study presents the first comprehensive analysis of AS events and SFs in MPM prognosis.
- The identified SF-AS regulatory network and drug sensitivity insights may offer novel therapeutic targets for MPM treatment.
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