Our plain-English summary of Genomic and transcriptomic analyses identify a prognostic gene signature and predict response to therapy in pleural and peritoneal mesothelioma, by N.U. Nair, Q. Jiang, J.S. Wei, et al (Cell Reports. Medicine, 2023).
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The study
- Authors: N.U. Nair, Q. Jiang, J.S. Wei, V.A. Misra, B. Morrow, C. Kesserwan, L.C. Hermida, J.S. Lee, I. Mian, J. Zhang, A. Lebensohn, M. Miettinen, M. Sengupta, J. Khan, E. Ruppin, R. Hassan
- Journal: Cell Reports. Medicine
- Published: 2023;4(2):100938
- Cited by: 26 articles, as counted by NIH iCite
- Read it: PubMed · Publisher · Free full text
Abstract
Malignant mesothelioma is an aggressive cancer with limited treatment options and poor prognosis. A better understanding of mesothelioma genomics and transcriptomics could advance therapies. Here, we present a mesothelioma cohort of 122 patients along with their germline and tumor whole-exome and tumor RNA sequencing data as well as phenotypic and drug response information. We identify a 48-gene prognostic signature that is highly predictive of mesothelioma patient survival, including CCNB1, the expression of which is highly predictive of patient survival on its own. In addition, we analyze the transcriptomics data to study the tumor immune microenvironment and identify synthetic-lethality-based signatures predictive of response to therapy. This germline and somatic whole-exome sequencing as well as transcriptomics data from the same patient are a valuable resource to address important biological questions, including prognostic biomarkers and determinants of treatment response in mesothelioma.
Published by Elsevier Inc.
In plain English
This study sequenced blood and tumor DNA from 122 patients with malignant mesothelioma treated at the US National Cancer Institute (59 pleural, 61 peritoneal and 2 tunica vaginalis) and measured tumor gene activity in 100 of them. The patients were drawn from 425 enrolled in a natural history trial between September 2013 and November 2019. Asbestos exposure was recorded by self-report. Pleural patients reported it more often than peritoneal patients (61% vs. 47.5%). Inherited BAP1 variants were the most common harmful inherited changes, found in 13.1% of the cohort. Peritoneal patients survived longer than pleural patients. The authors identified 48 genes whose higher activity was associated with worse survival. A combined score from these genes was associated with worse survival in their own patients and in two outside datasets of pleural mesothelioma patients. The CCNB1 gene alone was also associated with worse survival. A computer method predicted response to anti-PD1 immunotherapy among 16 treated patients, of whom 3 responded. The authors stated that the findings are associations, that drug-response samples were small, and that results need further validation.
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: Genomic (whole exome sequencing of blood and tumor) and transcriptomic (tumor RNA sequencing) analysis of a patient cohort from a natural history clinical trial, with survival analysis and computational drug-response prediction
- Who was studied: 122 malignant mesothelioma patients at the National Cancer Institute, Bethesda, USA: 59 pleural, 61 peritoneal, 2 tunica vaginalis. RNA sequencing was available for 100. Validation used outside pleural mesothelioma datasets (TCGA and Bueno et al.).
- Exposure: Asbestos exposure was recorded only by self-report, with no fiber types given. Pleural patients self-reported asbestos exposure more often than peritoneal patients (61% vs. 47.5%, p = 0.02). The study's main focus was tumor genetics, not asbestos exposure.
- Main results:
- Inherited (germline) pathogenic or likely pathogenic BAP1 variants were the most common, in 13.1% of the cohort, with similar rates in pleural (11.9%) and peritoneal (14.8%) patients.
- The genes most often carrying tumor (somatic) mutations were BAP1 (24.59%), NF2 (13.11%), TP53 (8.2%) and SETD2 (6.56%).
- Peritoneal mesothelioma patients showed higher overall survival than pleural mesothelioma patients in this cohort (log rank test, p = 0.043).
- In the NCI cohort, a high risk score from the 48-gene signature was associated with worse survival (hazard ratio 1.76).
- The 48-gene signature was associated with worse survival among NCI pleural patients only (HR = 1.84, p = 0.046) and among NCI peritoneal patients only (HR = 2.1, p = 0.0021).
- In the outside TCGA pleural mesothelioma dataset, higher risk scores were associated with worse survival (HR = 2.6; concordance statistic 0.772).
- Higher expression of the CCNB1 gene alone was associated with worse survival (HR = 2.54 in the TCGA dataset).
- Higher estimated M2 macrophage abundance was associated with worse survival in the NCI cohort (HR = 17.42, p = 0.027, false discovery rate 0.16). No such association was seen in the TCGA and Bueno et al. datasets.
- Of 16 NCI patients treated with anti-PD1 drugs (pembrolizumab or nivolumab), 3 (18.8%) responded. The SELECT method predicted response with ROC-AUC 0.91 (95% confidence interval 0.7 to 1).
- Among 41 patients given pemetrexed combinations, after excluding stable disease, SELECT separated responders from those with progressive disease with ROC-AUC 0.67 (95% confidence interval 0.46 to 0.88).
- Response rates predicted for 7 drugs correlated with response rates reported in published clinical trials (Spearman r = 0.64, p = 0.0348).
- The authors' conclusion: The authors concluded that, by analyzing the genomes and tumor transcriptomes of pleural and peritoneal mesothelioma patients, they identified gene expression profiles predictive of patient survival and of response to available therapies.
- Limitations the authors state:
- The 48-gene signature, including CCNB1, is only associated with survival; causal relations remain to be studied.
- Patient numbers for the anti-PD1 and pemetrexed drug-response analyses were small, and the responder and non-responder groups were imbalanced.
- Parts of the drug-response analysis were done at the cohort level, without patient-specific transcriptomic data.
- Independent validation of the signature was done only on pleural mesothelioma cohorts.
- The dataset lacks information on pathological stage.
- Survival analyses did not control for tumor histology.
- The results need further validation in laboratory studies and prospective clinical trials.
Topics
The National Library of Medicine indexes this study under subjects our site covers: Lung cancer, Mesothelioma.
Medical terms in this study, explained in our Lexicon: Peritoneal Mesothelioma, Mesothelioma, Prognosis, Biomarker.
Related studies
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- Insights Into Genomic Drivers, Transcriptomic Heterogeneity, and Therapeutic Vulnerabilities From Novel Mesothelioma Cell Lines — Y. Wu, F. Cao, et al. (2026)
- Comprehensive analysis reveals prognostic gene set that could impacts the response to chemotherapy and immunotherapy outcomes in malignant pleural mesothelioma — J. Li, H. He, et al. (2025)
- Genomic and Transcriptomic Analyses of Malignant Pleural Mesothelioma (MPM) Samples Reveal Crucial Insights for Preclinical Testing — A. Laure, A. Rigutto, et al. (2023)
- Prognostic Value of EMT Gene Signature in Malignant Mesothelioma — L. Wu, K. Yoshihara, et al. (2023)
Browse more research in Cell Reports. Medicine, or return to medical research.
How to cite it
Cite the study
N.U. Nair, Q. Jiang, J.S. Wei, V.A. Misra, B. Morrow, C. Kesserwan, et al. Genomic and transcriptomic analyses identify a prognostic gene signature and predict response to therapy in pleural and peritoneal mesothelioma. Cell Reports. Medicine 2023;4(2):100938. doi:10.1016/j.xcrm.2023.100938. PMID: 36773602.
Cite our summary
“Genomic and transcriptomic analyses identify a prognostic gene signature and predict response to therapy in pleural and peritoneal mesothelioma.” AsbestosClaims.Law Library. https://asbestosclaims.law/library/research/genomic-and-transcriptomic-analyses-identify-a-prognostic-gene.
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