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

Our plain-English summary of Prognostic risk assessment model for alternative splicing events and splicing factors in malignant pleural mesothelioma, by Y. Jiang, C. Zhang, Y. Chen, et al (Cancer Medicine, 2023).

The study

• Authors: Y. Jiang, C. Zhang, Y. Chen, S. Zhao, Y. He, J. He
• Journal: Cancer Medicine
• Published: 2023;12(4):4895-4906
• Cited by: 4 articles, as counted by NIH iCite
• Read it: PubMed · Publisher · Free full text

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.

© 2022 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

In plain English

This was a computer-based (bioinformatics) analysis of publicly available genetic and clinical data on malignant pleural mesothelioma from The Cancer Genome Atlas (TCGA). It examined alternative splicing, a process by which one gene can produce different versions of its message, and splicing factors, the proteins that control this process. Asbestos exposure was not examined. Data on 87 samples were obtained, and 84 samples remained after filtering. Statistical screening left 41 splicing events linked to survival. The authors built eight splicing-based risk models. All eight were reported as independent predictors of survival. The model based on the 'alternative acceptor' splicing type was the most accurate (AUC = 0.925). Two splicing factors, written as FMP1 (elsewhere FMR1) and PPM1G, were most strongly associated with prognosis, and a model based on them had an AUC of 0.768. In a software-based drug-sensitivity analysis, patients with higher risk scores in this model had lower sensitivity to cisplatin (p = 0.025). The authors described their explanations as speculation from data analysis that needs experimental evidence, and they noted that the sample size was small.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: Bioinformatics analysis of public database data (TCGA and TCGA SpliceSeq), using statistical models to link splicing events and splicing factors to survival
• Who was studied: Malignant pleural mesothelioma tumor samples in TCGA: 87 samples obtained, 84 remaining after excluding patients without follow-up or with survival under 30 days
• Exposure: Not studied. The study analyzed alternative splicing events and splicing factors in tumor data. Asbestos exposure was not an exposure in this analysis.
• Main results:
  • After filtering, 84 samples and 28,664 splicing events were analyzed
  • LASSO/multivariate Cox analysis identified 41 splicing events and 2 splicing factors mostly associated with survival
  • Among the eight splicing models, the alternative acceptor (AA) model had the highest prognostic value (AUC = 0.925)
  • All eight splicing models were independent prognostic factors for MPM
  • 19 splicing factors were included in the splicing factor network
  • FMP1 and PPM1G were selected as the two splicing factors most strongly associated with prognosis. The model based on them gave p = 1.371e-07 and AUC = 0.768.
  • In the drug sensitivity analysis for cisplatin, patients with higher risk values in the splicing factor model had lower drug sensitivity (p = 0.025)
• The authors' conclusion: The authors concluded that the splicing factor network and drug sensitivity analysis may provide novel targets for pharmacological studies of MPM. They also stated that their mechanistic explanations are speculations from bioinformatics analysis that require experimental evidence.
• Limitations the authors state:
  • The results came from extensive data analysis and need experimental evidence
  • Because MPM is rare, the sample size was small, indicating bias in the results
  • Drug sensitivity to pemetrexed was not analyzed

Topics

The National Library of Medicine indexes this study under subjects our site covers: Mesothelioma.

Medical terms in this study, explained in our Lexicon: Pleural Mesothelioma, Prognosis, Cisplatin.

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• Immunohistochemical Expression of Serine and Arginine-Rich Splicing Factor 1 (SRSF1) in Fluoro-Edenite-Induced Malignant Mesothelioma: A Preliminary Study — G. Broggi, G. Angelico, et al. (2021)
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