ArticleBritish journal of cancer2022
A combination of intrinsic and extrinsic features improves prognostic prediction in malignant pleural mesothelioma.
Article in British journal of cancer, 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, 5 citations in OpenAlex.
- Multi-omics integration in malignant pleural mesothelioma: from molecular evolution and immune ecosystems to precision therapy.Frontiers in oncology · 2026Review
- Integrative Analysis Reveals the Prognostic Effects of Epigenetic Regulators in Bladder Cancer.Cancer medicine · 2025Article
- Correlation of Histologic Features with Gene Alterations in Pleural Mesothelioma.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2025Article
- Characterization of driver mutations identifies gene signatures predictive of prognosis and treatment sensitivity in multiple myeloma.The oncologist · 2024Article
- The International Association for the Study of Lung Cancer Pleural Mesothelioma Staging Project: Updated Modeling of Prognostic Factors in Pleural Mesothelioma.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2023Article
- A Novel Two-Gene Expression-Based Prognostic Score in Malignant Pleural Mesothelioma.Diagnostics (Basel, Switzerland) · 2023Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
backgroundMalignant pleural mesothelioma (MPM) is a lung pleural cancer with very poor disease outcome. With limited curative MPM treatment available, it is vital to study prognostic biomarkers to categorise different patient risk groups.
methodsWe defined gene signatures to separately characterise intrinsic and extrinsic features, and investigated their interactions in MPM tumour samples. Specifically, we calculated gene signature scores to capture the downstream pathways of major mutated driver genes (BAP1, NF2, SETD2 and TP53) as tumour-intrinsic features. Similarly, we inferred the infiltration levels for major immune cells in the tumour microenvironment to characterise tumour-extrinsic features. Lastly, we integrated these features with clinical factors to predict prognosis in MPM.
resultsThe gene signature scores were more prognostic than the corresponding genomic mutations, mRNA and protein expression. High immune infiltration levels were associated with prolonged survival. The integrative model indicated that tumour features provided independent prognostic values than clinical factors and were complementary with each other in survival prediction.
conclusionsBy using an integrative model that combines intrinsic and extrinsic features, we can more correctly predict the clinical outcomes of patients with MPM.
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