Comprehensive immunoproteogenomic analyses of malignant pleural mesothelioma

Our plain-English summary of Comprehensive immunoproteogenomic analyses of malignant pleural mesothelioma, by H.S. Lee, H.J. Jang, J.M. Choi, et al (JCI Insight, 2018).

The study

• Authors: H.S. Lee, H.J. Jang, J.M. Choi, J. Zhang, V.L. de Rosen, T.M. Wheeler, J.S. Lee, T. Tu, P.T. Jindra, R.H. Kerman, S.Y. Jung, F. Kheradmand, D.J. Sugarbaker, B.M. Burt
• Journal: JCI Insight
• Published: 2018;3(7)
• Cited by: 48 articles, as counted by NIH iCite
• Read it: PubMed · Publisher · Free full text

Abstract

We generated a comprehensive atlas of the immunologic cellular networks within human malignant pleural mesothelioma (MPM) using mass cytometry. Data-driven analyses of these high-resolution single-cell data identified 2 distinct immunologic subtypes of MPM with vastly different cellular composition, activation states, and immunologic function; mass spectrometry demonstrated differential abundance of MHC-I and -II neopeptides directly identified between these subtypes. The clinical relevance of this immunologic subtyping was investigated with a discriminatory molecular signature derived through comparison of the proteomes and transcriptomes of these 2 immunologic MPM subtypes. This molecular signature, representative of a favorable intratumoral cell network, was independently associated with improved survival in MPM and predicted response to immune checkpoint inhibitors in patients with MPM and melanoma. These data additionally suggest a potentially novel mechanism of response to checkpoint blockade: requirement for high measured abundance of neopeptides in the presence of high expression of MHC proteins specific for these neopeptides.

In plain English

This laboratory study examined immune cells inside tumors from 12 consecutive patients with malignant pleural mesothelioma who had surgery without prior treatment between August 2015 and December 2015. The study did not examine asbestos as a cause; asbestos exposure was only adjusted for in one survival analysis. Using mass cytometry, the authors sorted the tumors into two immune subtypes, TiME-I and TiME-II, with 6 tumors in each. TiME-I tumors had more partially exhausted CD8+ T cells and higher measured neoantigen abundance and MHC protein levels. The median number of potential neoantigens did not differ between the subtypes. From these tumors the authors built a 137-gene signature. In 330 patients from three outside datasets, the signature was an independent predictor of survival (hazard ratio 1.74, 95% CI 1.32–2.30). TiME-I was linked with favorable survival. Among 10 patients with advanced mesothelioma given anti-PD-1 therapy, the 5 with a good-TiME signature included 3 complete responses. Of the 5 with a bad-TiME signature, 4 had progressive disease. The authors noted the small number of cases and said prospective validation is needed.

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: Laboratory study of surgically removed tumor tissue (mass cytometry, mass spectrometry, mRNA profiling). The resulting gene signature was then tested in existing patient datasets, a mouse dataset, a melanoma dataset, and a small series of mesothelioma patients treated with anti-PD-1 therapy.
• Who was studied: 12 consecutive patients with malignant pleural mesothelioma who had macroscopic complete resection without preoperative treatment at a single institution, August to December 2015. The signature was then applied to 211 (BWH), 69 (TCGA) and 50 (MSKCC) patients, 27 melanoma patients, mice, and 10 patients with advanced, unresectable mesothelioma treated with anti-PD-1 therapy between 2014 and 2016.
• Exposure: Not an asbestos exposure study; no fiber types were studied. Asbestos exposure appeared only as an adjustment variable in the multivariable survival analysis. The treatments studied were immune checkpoint inhibitors (anti-PD-1; anti-CTLA-4 in mice).
• Main results:
  • Unsupervised clustering of the 12 tumors defined two immune subtypes, TiME-I and TiME-II, with 6 tumors each.
  • TiME-I tumors had more partially exhausted CD8+ T cells and HLA-DR+ cancer cells. TiME-II tumors had more Tregs expressing high ICOS and CTLA-4.
  • In the 11 tumors tested by mass spectrometry, the median number of potential neoantigens did not differ between subtypes: 19 (range 9–27) for MHC-I and 16 (range 9–23) for MHC-II, each P greater than 0.05.
  • Average neoantigen abundance for both MHC-I and MHC-II was greater in TiME-I tumors, and TiME-I tumors had higher MHC-I and MHC-II protein levels.
  • In a merged cohort of 330 mesothelioma patients, the 137-gene TiME signature was an independent prognostic factor (P = 0.017, hazard ratio = 1.74, 95% CI 1.32–2.30). TiME-I was associated with favorable overall survival and TiME-II with unfavorable overall survival.
  • In a mouse mesothelioma dataset, the signature identified 10 of 11 mice whose tumors responded to anti-CTLA-4 treatment and 9 of 9 mice whose tumors did not respond.
  • Among 27 melanoma patients treated with anti-PD-1 antibodies, those with a good-TiME signature had statistically improved responses.
  • Among 10 mesothelioma patients given anti-PD-1 therapy, the 5 with a good-TiME signature had 3 complete responses, 1 partial response and 1 stable disease. The 5 with a bad-TiME signature had 4 progressive disease and 1 stable disease.
  • In these 10 patients, the PD-L1 clinical immunohistochemistry test did not correlate with response to anti-PD-1 therapy.
• The authors' conclusion: The authors concluded that a distinct immune tumor environment in mesothelioma could be represented by a simple molecular signature that was prognostic for survival and predicted response to checkpoint blockade. They said prospective validation is required before clinical use.
• Limitations the authors state:
  • The number of cases was small, and only surgical specimens were used to build a profile that was then applied to both earlier-stage and advanced disease.
  • Prospective validation is needed before clinical use.

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: Pleural Mesothelioma, checkpoint inhibitors.

Related studies

• Spatially-resolved analyses of muscle invasive bladder cancer microenvironment unveil a distinct fibroblast cluster associated with prognosis — C. Feng, Y. Wang, et al. (2024)
• 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)
• Novel genes and pathways modulated by syndecan-1: implications for the proliferation and cell-cycle regulation of malignant mesothelioma cells — T. Szatmári, F. Mundt, et al. (2012)
• Genomic and transcriptomic analyses identify a prognostic gene signature and predict response to therapy in pleural and peritoneal mesothelioma — N.U. Nair, Q. Jiang, et al. (2023)
• HDAC1-mSin3a-NCOR1, Dnmt3b-HDAC1-Egr1 and Dnmt1-PCNA-UHRF1-G9a regulate the NY-ESO1 gene expression — P.F. Cartron, C. Blanquart, et al. (2013)
• Extensive temporal transcriptome and microRNA analyses identify molecular mechanisms underlying mitochondrial dysfunction induced by multi-walled carbon nanotubes in human lung cells — P. Nymark, P. Wijshoff, et al. (2015)

Browse more research in JCI Insight, or return to medical research.