ArticleGigaScience2022
A molecular phenotypic map of malignant pleural mesothelioma.
Article in GigaScience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 7 citations in OpenAlex.
- Moving Beyond Morphology: Toward a Morpho-Molecular Classification of Pleural Mesothelioma.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2026Review
- Methylation biomarkers can distinguish pleural mesothelioma from healthy pleura and other pleural pathologies.Molecular oncology · 2026Article
- Genome-wide DNA methylation analysis reveals a unique methylation pattern for pleural mesothelioma compared to healthy pleura and other lung diseases.Clinical epigenetics · 2024Article
- Multi-omic dataset of patient-derived tumor organoids of neuroendocrine neoplasms.GigaScience · 2024Article
- Multiomic analysis of malignant pleural mesothelioma identifies molecular axes and specialized tumor profiles driving intertumor heterogeneity.Nature genetics · 2023Article
- A molecular phenotypic map of malignant pleural mesothelioma.GigaScience · 2022Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 3 countries.
Funding
Abstract
backgroundMalignant pleural mesothelioma (MPM) is a rare understudied cancer associated with exposure to asbestos. So far, MPM patients have benefited marginally from the genomics medicine revolution due to the limited size or breadth of existing molecular studies. In the context of the MESOMICS project, we have performed the most comprehensive molecular characterization of MPM to date, with the underlying dataset made of the largest whole-genome sequencing series yet reported, together with transcriptome sequencing and methylation arrays for 120 MPM patients.
resultsWe first provide comprehensive quality controls for all samples, of both raw and processed data. Due to the difficulty in collecting specimens from such rare tumors, a part of the cohort does not include matched normal material. We provide a detailed analysis of data processing of these tumor-only samples, showing that all somatic alteration calls match very stringent criteria of precision and recall. Finally, integrating our data with previously published multiomic MPM datasets (n = 374 in total), we provide an extensive molecular phenotype map of MPM based on the multitask theory. The generated map can be interactively explored and interrogated on the UCSC TumorMap portal (https://tumormap.ucsc.edu/?p=RCG_MESOMICS/MPM_Archetypes ).
conclusionsThis new high-quality MPM multiomics dataset, together with the state-of-art bioinformatics and interactive visualization tools we provide, will support the development of precision medicine in MPM that is particularly challenging to implement in rare cancers due to limited molecular studies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.