Journal of translational medicine · 2025
The phenogenomic landscapes of pleural mesothelioma tumor microenvironment predict clinical outcomes.
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Torricelli Federica, Spada Filomena, Bishop Cynthia, Todd Katrina, Nonaka Daisuke, Petrov Nedyalko, Barberio Manuela Terranova, Ramsay Alan G, Ellis Richard, Ciarrocchi Alessia, Apollonio Benedetta, Billè Andrea
Аннотация
BACKGROUND: Malignant pleural mesothelioma (MPM) is a rare and aggressive malignancy with limited therapeutic options. To improve patients management and treatment, more precise stratification strategies are needed. This study aimed to characterize the phenogenomic landscapes of MPM and to understand their influence on patients clinical outcomes.
METHODS: We conducted a phenogenomic analysis on 22 MPM patients using two high throughput approaches: imaging mass cytometry (IMC) with whole exome sequencing (WES). Resulting profiles were addressed for their clinical relevance to predict patients prognosis.
RESULTS: IMC revealed a highly heterogeneous tumor microenvironment (TME) with distinct tumor cell subpopulations. Notably, we identified a novel sarcomatoid-like cellular cluster associated with poor prognosis. The TME was also infiltrated with immune cells including macrophages and CD4+ T lymphocytes, that were more abundant in patients with favorable clinical outcomes. WES identified a complex genomic landscape with limited prognostic value for individual genetic alterations. However, tumor mutational burden (TMB) emerged as a potential predictive biomarker, inversely correlating with immune cell infiltration, particularly macrophages and CD4+ T lymphocytes.
CONCLUSIONS: Our findings underscore the intricate interplay between the tumor genome, TME composition, and clinical outcomes in MPM. These data support the potential of integrating genomic and TME profiling to develop more precise patient stratification strategies and potentially optimize therapeutic approaches, including immunotherapy.
METHODS: We conducted a phenogenomic analysis on 22 MPM patients using two high throughput approaches: imaging mass cytometry (IMC) with whole exome sequencing (WES). Resulting profiles were addressed for their clinical relevance to predict patients prognosis.
RESULTS: IMC revealed a highly heterogeneous tumor microenvironment (TME) with distinct tumor cell subpopulations. Notably, we identified a novel sarcomatoid-like cellular cluster associated with poor prognosis. The TME was also infiltrated with immune cells including macrophages and CD4+ T lymphocytes, that were more abundant in patients with favorable clinical outcomes. WES identified a complex genomic landscape with limited prognostic value for individual genetic alterations. However, tumor mutational burden (TMB) emerged as a potential predictive biomarker, inversely correlating with immune cell infiltration, particularly macrophages and CD4+ T lymphocytes.
CONCLUSIONS: Our findings underscore the intricate interplay between the tumor genome, TME composition, and clinical outcomes in MPM. These data support the potential of integrating genomic and TME profiling to develop more precise patient stratification strategies and potentially optimize therapeutic approaches, including immunotherapy.