Unraveling tumor microenvironment heterogeneity in malignant pleural mesothelioma identifies biologically distinct immune subtypes enabling prognosis determination

Our plain-English summary of Unraveling tumor microenvironment heterogeneity in malignant pleural mesothelioma identifies biologically distinct immune subtypes enabling prognosis determination, by K. Yang, T. Yang, T. Yang, et al (Frontiers in Oncology, 2022).

The study

• Authors: K. Yang, T. Yang, T. Yang, Y. Yuan, F. Li
• Journal: Frontiers in Oncology
• Published: 2022;12:995651
• Cited by: 13 articles, as counted by NIH iCite
• Read it: PubMed · Publisher · Free full text

Abstract

Background: Malignant pleural mesothelioma (MPM) is a rare and intractable disease exhibiting a remarkable intratumoral heterogeneity and dismal prognosis. Although immunotherapy has reshaped the therapeutic strategies for MPM, patients react with discrepant responsiveness.

Methods: Herein, we recruited 333 MPM patients from 5 various cohorts and developed an in-silico classification system using unsupervised Non-negative Matrix Factorization and Nearest Template Prediction algorithms. The genomic alterations, immune signatures, and patient outcomes were systemically analyzed across the external TCGA-MESO samples. Machine learning-based integrated methodology was applied to identify a gene classifier for clinical application.

Results: The gene expression profiling-based classification algorithm identified immune-related subtypes for MPMs. In comparison with the non-immune subtype, we validated the existence of abundant immunocytes in the immune subtype. Immune-suppressed MPMs were enriched with stroma fraction, myeloid components, and immunosuppressive tumor-associated macrophages (TAMs) as well exhibited increased TGF-β signature that informs worse clinical outcomes and reduced efficacy of anti-PD-1 treatment. The immune-activated MPMs harbored the highest lymphocyte infiltration, growing TCR and BCR diversity, and presented the pan-cancer immune phenotype of IFN-γ dominant, which confers these tumors with better drug response when undergoing immune checkpoint inhibitor (ICI) treatment. Genetically, BAP1 mutation was most commonly found in patients of immune-activated MPMs and was associated with a favorable outcome in a subtype-specific pattern. Finally, a robust 12-gene classifier was generated to classify MPMs with high accuracy, holding promise value in predicting patient survival.

Conclusions: We demonstrate that the novel classification system can be exploited to guide the identification of diverse immune subtypes, providing critical biological insights into the mechanisms driving tumor heterogeneity and responsible for cancer-related patient prognoses.

Copyright © 2022 Yang, Yang, Yang, Yuan and Li.

In plain English

This was a computer-based analysis of previously published tumor gene-activity data from people with malignant pleural mesothelioma (MPM). It did not examine asbestos exposure. The authors pooled data on 333 patients from five public datasets, sorted the tumors into immune-related groups, and repeated the sorting in 87 patients from a separate dataset (TCGA). The main text classed 55 of 333 pooled tumors (16.5%) as immune-activated and 70 of 333 (21.0%) as immune-suppressed; a figure caption reverses these counts. Immune-suppressed patients had shorter survival than the other groups. In the TCGA dataset, the immune-activated group had the most favourable outcome. Among 10 patients given anti-PD-1 immunotherapy, the two immune-activated patients showed partial or complete response, while 2 of 3 immune-suppressed and 4 of 5 non-immune patients did not respond. BAP1 gene alteration was most common in immune-activated tumors. A computer-derived 12-gene classifier, built and checked only on existing datasets, sorted tumors with 90.9% accuracy in a testing set and 79.4% in the TCGA dataset. The authors noted that their analyses rested only on bulk gene-activity data, without a histology review of each sample.

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: Computational (bioinformatic) analysis of publicly available tumor gene expression datasets, with an external validation dataset and a machine-learning gene classifier
• Who was studied: Tumor expression profiles from 333 malignant pleural mesothelioma patients pooled from five public datasets (training cohort). External validation used 87 patients from the TCGA-MESO dataset. A separate set of 10 patients treated with anti-PD-1 immunotherapy was also analysed (GSE99070). Locations and dates of the original cohorts are not given in the main text.
• Exposure: Not studied. The article does not examine asbestos or any fiber exposure. It compares tumor immune subtypes defined from gene expression.
• Main results:
  • In the pooled cohort of 333, the main text classed 55 patients (16.5%) as immune-activated. The Figure 2 caption instead assigns 55/333 to the immune-suppressed group.
  • In the pooled cohort of 333, the main text classed 70 patients (21.0%) as immune-suppressed. The Figure 2 caption instead gives immune-activated as 70/125.
  • In the pooled cohort, immune-suppressed patients had shorter survival than immune-activated or non-immune patients.
  • Sarcomatoid tumors were more common in the immune-activated group than in the other subtypes: 27.3% versus 3.9% and 12.1%.
  • Among 10 patients treated with anti-PD-1 immunotherapy, the two immune-activated patients showed partial or complete response.
  • In the same anti-PD-1 group, 2 of 3 immune-suppressed patients and 4 of 5 non-immune patients did not respond.
  • In the TCGA validation cohort of 87, 24 patients (27.6%) were immune-activated and 23 (26.4%) were immune-suppressed.
  • In the TCGA cohort, immune-activated patients had the most favourable survival of the three subtypes.
  • In the TCGA cohort, tumor mutation burden did not differ significantly across the three subtypes.
  • BAP1 alteration was most common in immune-activated tumors and was associated with a favorable outcome in that subtype.
  • A computer-derived 12-gene classifier had 93.6% accuracy on the training set, 90.9% on a testing set and 79.4% on the external TCGA dataset.
• The authors' conclusion: The authors concluded that they had developed a feasible classification system for describing immune features of MPM, which they considered could guide immunotherapy strategies. They also concluded that the 12-gene classifier holds promise for clinical translation and prognosis.
• Limitations the authors state:
  • No histology evaluation was done for each sample.
  • All analyses were based only on bulk transcriptome data and cell type deconvolution, not on the spatial distribution of immune cells.
  • Whether the subtypes predict response to immunotherapy still needs to be tested in clinical trials or real-world studies.

Topics

Medical terms in this study, explained in our Lexicon: Tumor Microenvironment, Pleural Mesothelioma, Prognosis, Immunotherapy, Macrophage, checkpoint inhibitors, BAP1.

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