Multi-omics integration reveals tumor and microenvironmental heterogeneity in malignant pleural mesothelioma

Malignant pleural mesothelioma (MPM) is a highly aggressive and molecularly heterogeneous malignancy with poor prognosis. Here, we performed an integrative multi-omic analysis combining bulk transcriptomics, copy number variation profiling, and single-cell RNA sequencing to systematically characterize MPM heterogeneity. Using non-negative matrix factorization, we identified three robust molecular subtypes (S-I, S-II, and S-III) with distinct transcriptional programs, genomic alterations, and tumor microenvironment compositions. Subtype S-I exhibited immune-inflamed signatures with abundant cytotoxic T cells and activated dendritic cells, suggesting potential responsiveness to immunotherapy. S-II was characterized by metabolic reprogramming and mTORC1 pathway activation, whereas S-III displayed stromal enrichment, extracellular matrix remodeling, and suppressed apoptotic signaling. Single-cell analysis revealed subtype-specific distributions of malignant and stromal cell subsets, corroborating bulk-level observations and highlighting intratumoral heterogeneity. Collectively, these findings refine the molecular classification of MPM, uncover subtype-specific regulatory programs, and identify potential therapeutic vulnerabilities, providing a framework for precision medicine strategies in this challenging malignancy.

Authors

Institutions

Publication Details

Journal
Discover Oncology
Published
2026-03-13
DOI
https://doi.org/10.1007/s12672-026-04725-7
Primary Topic
Occupational and environmental lung diseases
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multi-omics integration reveals tumor and microenvironmental heterogeneity in malignant pleural mesothelioma

Hai Hu, Lulu Li, Wei Bian, Xiuhua Wu
Discover Oncology
Occupational and environmental lung diseases
article

Multi-omics integration reveals tumor and microenvironmental heterogeneity in malignant pleural mesothelioma

Hai Hu, Lulu Li, Wei Bian, Xiuhua Wu
article en

Abstract

Malignant pleural mesothelioma (MPM) is a highly aggressive and molecularly heterogeneous malignancy with poor prognosis. Here, we performed an integrative multi-omic analysis combining bulk transcriptomics, copy number variation profiling, and single-cell RNA sequencing to systematically characterize MPM heterogeneity. Using non-negative matrix factorization, we identified three robust molecular subtypes (S-I, S-II, and S-III) with distinct transcriptional programs, genomic alterations, and tumor microenvironment compositions. Subtype S-I exhibited immune-inflamed signatures with abundant cytotoxic T cells and activated dendritic cells, suggesting potential responsiveness to immunotherapy. S-II was characterized by metabolic reprogramming and mTORC1 pathway activation, whereas S-III displayed stromal enrichment, extracellular matrix remodeling, and suppressed apoptotic signaling. Single-cell analysis revealed subtype-specific distributions of malignant and stromal cell subsets, corroborating bulk-level observations and highlighting intratumoral heterogeneity. Collectively, these findings refine the molecular classification of MPM, uncover subtype-specific regulatory programs, and identify potential therapeutic vulnerabilities, providing a framework for precision medicine strategies in this challenging malignancy.

Discover Oncology
Shanghai Sixth People's Hospital (CN)
Openalex Percentile: Top 23%
Occupational and environmental lung diseases
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.