Multiomic, Histologic, and scRNA-seq Profiling of Pleural Mesothelioma Reveals Negative Prognosis Associated With a Novel Uncommitted Molecular Phenotype

作者信息David T Severson, Samuel Freyaldenhoven, Benjamin Wadowski, Yin P Hung, Travis Hughes, Beow Y Yeap, William G Richards, Sanna Laaksonen, Lucian Chirieac, Matthew B Couger, Roderick V Jensen, Ahmed A Sadek, Ilkka Ilonen, Kimberly Vermilya, Simona Innocenti, Stephanie L Korle, Julianne S Barlow, Jamie Anderson, Jason Meyerovitz, Vivian Wang, Mary N Dao, Alex K Shalek, Assunta De Rienzo, Raphael Bueno
PMID41319863
期刊J Thorac Oncol
发布时间2026-04
DOI10.1016/j.jtho.2025.11.019
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摘要

Introduction: Multiomics pleural mesothelioma (PM) studies have identified prognostic molecular subsets of PM histologic types, epithelioid (ePM), biphasic (bPM), and sarcomatoid (sPM), defined by relative tumor cell content. However, the underlying biology modulating survival remains unknown. Methods: Using 93 samples from 40 patients, we performed single-cell RNA sequencing (scRNA-seq), bulk exome and RNA sequencing, optical genome mapping, spatial transcriptomics, and histologic analyses to identify candidate drivers and prognostic biomarkers of malignant cell (MC) state. Results: We identified a novel uncommitted MC state enriched in bPM tumors. Using inferred copy number variants, we observed all three MC states within individual clones suggesting MC state is not clonally restricted. We identified TGF-β and GAS6-AXL signaling as candidate MC state drivers for further study. Finally, we validated two prognostic MC state immunohistochemistry biomarkers, MEST (uncommitted) and MSLN (epithelioid). Conclusions: These multiomic, scRNA-seq analyses of primary patient tissues provide new candidate drivers of MC state and novel biomarkers to improve patient stratification. Further experimental exploration and clinical validation of these findings may reveal new treatment strategies and refine current clinical decision-making in PM.

实验方法

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10x Xenium原位分析系统10xXenium
Akoya PhenoCycler系统AkoyaPhenoCycler