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Comprehensive immunoproteogenomic analyses of malignant pleural mesothelioma

Hyun-Sung Lee1, Hee-Jin Jang1, Jong Min Choi2

  • 1Division of Thoracic Surgery, Michael E. DeBakey Department of Surgery.

JCI Insight
|April 6, 2018
PubMed

Insights

Researchers identified two distinct immunologic subtypes of malignant pleural mesothelioma (MPM) using mass cytometry. A molecular signature from these subtypes predicts improved survival and response to immune checkpoint inhibitors in MPM and melanoma patients.

Area of Science:

  • Immunology
  • Oncology
  • Proteomics

Background:

  • Malignant pleural mesothelioma (MPM) is an aggressive cancer with limited treatment options.
  • Understanding the tumor microenvironment is crucial for developing effective immunotherapies.

Purpose of the Study:

  • To create a comprehensive immunologic cellular network atlas of human MPM.
  • To identify distinct immunologic subtypes of MPM and their clinical relevance.

Main Methods:

  • Mass cytometry was employed to generate high-resolution single-cell data.
  • Proteomic and transcriptomic analyses were performed to derive a molecular signature.
  • Mass spectrometry was used to identify differential neopeptide abundance.

Main Results:

  • Two distinct immunologic subtypes of MPM were identified, differing in cellular composition, activation states, and function.
  • Differential abundance of MHC-I and -II neopeptides was observed between subtypes.
  • A molecular signature associated with favorable intratumoral networks predicted improved survival in MPM and response to immune checkpoint inhibitors in MPM and melanoma.

Conclusions:

  • Immunologic subtyping provides a novel framework for understanding MPM heterogeneity.
  • The identified molecular signature holds potential for predicting patient outcomes and guiding immunotherapy selection.
  • Neopeptide abundance and MHC expression may represent a novel mechanism of response to checkpoint blockade therapy.

Keywords:
Cancer immunotherapyExpression profilingImmunologyOncologyProteomics

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