This study integrates single-cell RNA sequencing, spatial transcriptomics, and multi-omics analysis to define a novel uncommitted malignant cell state in pleural mesothelioma for the first time, revealing its significant association with poor patient outcomes, and proposing MEST and MSLN as novel immunohistochemical biomarkers.
Literature Overview
The article titled 'Multi-omics, histologic, and scRNA-seq profiling of pleural mesothelioma reveals negative prognosis associated with a novel uncommitted molecular phenotype,' published in the Journal of Thoracic Oncology, reviews and summarizes an integrative multi-omics analysis based on 40 patients and 93 samples, systematically dissecting the heterogeneity of malignant cell (MC) states in pleural mesothelioma (PM). By combining single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, exome sequencing, optical genome mapping, and histopathology, the study identifies a novel 'uncommitted' MC state enriched in biphasic tumors and significantly associated with poor prognosis. Furthermore, it validates MEST and MSLN as immunohistochemical markers for this cell state, offering a new tool for clinical risk stratification. The study also reveals that MC states are not clonally restricted, suggesting that microenvironmental signals may drive phenotypic plasticity, opening new avenues for therapeutic strategies.Background Knowledge
Pleural mesothelioma is an aggressive malignancy closely linked to asbestos exposure, histologically classified into epithelioid (ePM), biphasic (bPM), and sarcomatoid (sPM) subtypes, with significantly different prognoses. Traditional molecular studies have identified key axes of variation such as epithelial-mesenchymal transition (EMT) and inflammatory signatures, but due to the use of bulk sequencing techniques, it has been difficult to disentangle contributions from malignant cells versus the tumor microenvironment (TME). Recent applications of single-cell sequencing have begun to uncover cellular heterogeneity within mesothelioma, yet understanding of dynamic changes in malignant cell states and their regulatory mechanisms remains incomplete. In particular, the existence of transitional or uncommitted cell states and their impact on prognosis remains unclear. Moreover, mesothelioma lacks targetable driver genes, limiting treatment options. Immunotherapy shows greater efficacy in non-epithelioid subtypes, underscoring the importance of molecular classification. Therefore, a deeper understanding of the molecular characteristics, regulatory mechanisms, and interactions with the TME of malignant cell states is crucial for improving patient stratification and developing novel therapies. This study fills these knowledge gaps through multimodal single-cell analysis, proposing a new cellular state classification system and potential therapeutic targets.
Research Methods and Experiments
The study included 40 patients who underwent radical pleurectomy, collecting 93 anatomically well-defined samples, including 20 epithelioid, 13 biphasic, 3 sarcomatoid mesotheliomas, and control tissues. Single-cell RNA sequencing (scRNA-seq) was performed using the Seq-Well platform, profiling 266,262 cells, with malignant cells identified via copy number variation (CNV) inference. The study employed a multi-dimensional approach to dissect tumor heterogeneity, integrating bulk RNA sequencing, whole-exome sequencing, optical genome mapping (OGM), spatial transcriptomics (10x Xenium), and spatial proteomics (PhenoCycler). A tissue microarray (TMA) containing 452 patients was constructed, and MEST and MSLN expression was evaluated by immunohistochemistry (IHC) with H-scores. Cox proportional hazards models and Kaplan-Meier analyses were used to assess the prognostic value of these biomarkers.Key Conclusions and Perspectives
Research Significance and Prospects
This study, through high-resolution multi-omics analysis, redefines the molecular classification framework of pleural mesothelioma, introducing the 'uncommitted' MC state as a novel biological and clinical entity. This finding challenges the traditional clonal evolution model of tumor heterogeneity and highlights the critical role of microenvironmental signals in driving cell state transitions, providing a theoretical foundation for targeting phenotypic plasticity. MEST and MSLN, as clinically applicable IHC markers, have the potential to be incorporated into routine pathological assessments, enhancing the accuracy of patient risk stratification and guiding personalized treatment decisions.
Future studies should further explore the developmental trajectory and stability of uncommitted cells and validate the TGF-β and GAS6-AXL pathways as therapeutic targets. Clinically, the prognostic value of the MEST/MSLN stratification model needs validation in larger, multicenter cohorts, and its ability to predict response to immunotherapy should be investigated. Additionally, developing novel therapies targeting uncommitted cells or their interactions with the microenvironment—such as AXL inhibitors—may offer new hope for high-risk patients. This study lays a crucial foundation for precision medicine in mesothelioma.
Conclusion
This study, through integrating single-cell transcriptomics, spatial omics, and multimodal pathological analyses, systematically reveals a novel 'uncommitted' malignant cell state in pleural mesothelioma, enriched in biphasic tumors and significantly associated with poor prognosis in epithelioid subtype patients. The study demonstrates that malignant cell states are not clonally restricted, suggesting their plasticity may be driven by microenvironmental signals such as TGF-β and GAS6-AXL. Importantly, MEST and MSLN are validated as immunohistochemical biomarkers for this cell state, and their combined detection effectively stratifies patients, outperforming traditional histological classification. These findings not only deepen our understanding of mesothelioma tumor heterogeneity but also provide clinicians with practical prognostic tools and potential therapeutic targets, advancing the field of precision medicine in mesothelioma. Future work should validate these biomarkers in independent cohorts and explore therapeutic strategies targeting the uncommitted cell state to improve patient outcomes.
