Genomic profiling of tissue and blood predicts survival outcomes in patients with resected pleural mesothelioma

Eur J Cancer. 2024 Jan:196:113457. doi: 10.1016/j.ejca.2023.113457. Epub 2023 Nov 20.

Abstract

Purpose: Pleural mesothelioma (PM) is an aggressive tumor still considered incurable, in part due to the lack of predictive biomarkers. Little is known about the clinical implications of molecular alterations in resectable PM tissues and blood. Here, we characterized genetic alterations to identify prognostic and predictive biomarkers in patients with resected PM.

Experimental design: Targeted next-generation sequencing was performed in retrospective pleural tumor tissue and paired plasma samples from stage IB-IIIB resected PM. Association between prognosis and presence of specific mutations was validated in silico.

Results: Thirty PM tissues and paired blood samples from 12 patients were analyzed. High tissue tumor mutational burden (TMB) (>10 mutations/Mb), tissue median minor allele frequency (MAF) (>9 mutations/Mb), and blood TMB (>6 mutations/Mb), tissue KMT2C, PBRM1, PKHD1,EPHB1 and blood LIFR mutations correlated with longer disease-free survival and/or overall survival. High concordance (>80%) between tissue and blood was found for some mutations.

Conclusions: Tissue TMB and MAF, blood TMB, and specific mutations correlated with outcomes in patients with resected PM and should be further studied to validate their role as prognostic biomarkers and potentially predictive factors for combinations with immune-checkpoint inhibitors. This suggest that molecular profiling could identify longer survivors in patients with resected PM.

Keywords: Blood mutations; Prognostic biomarkers; Resected pleural mesothelioma; Tissue mutations.

MeSH terms

  • Biomarkers, Tumor / genetics
  • Genomics
  • Humans
  • Mesothelioma* / genetics
  • Mesothelioma* / surgery
  • Mesothelioma, Malignant*
  • Mutation
  • Pleural Neoplasms* / genetics
  • Pleural Neoplasms* / surgery
  • Retrospective Studies

Substances

  • Biomarkers, Tumor