ArticleCancer medicine2020
An integrative histopathologic clustering model based on immuno-matrix elements to predict the risk of death in malignant mesothelioma.
Article in Cancer medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 11 citations in OpenAlex.
- Deep learning-driven recognition of panoramic tumor microenvironment features in H&E sections and its application.Journal for immunotherapy of cancer · 2026Review
- High Expression ofBioMed research international · 2023Article
- Prognostic significance of inflammation-related and electrolyte laboratory variables in patients with malignant pleural mesothelioma.Frontiers in medicine · 2023Article
- Effects of different fluid management on lung and kidney during pressure-controlled and pressure-support ventilation in experimental acute lung injury.Physiological reports · 2022Article
- Review
- Pathological Characterization of Tumor Immune Microenvironment (TIME) in Malignant Pleural Mesothelioma.Cancers · 2021Review
- The Fibrosis-Targeted Collagen/Integrins Gene Profile Predicts Risk of Metastasis in Pulmonary Neuroendocrine Neoplasms.Frontiers in oncology · 2021Article
- Article
- Pulmonary Neuroendocrine Neoplasms Overexpressing Epithelial-Mesenchymal Transition Mechanical Barriers Genes Lack Immune-Suppressive Response and Present an Increased Risk of Metastasis.Frontiers in oncology · 2021Article
- An integrative histopathologic clustering model based on immuno-matrix elements to predict the risk of death in malignant mesothelioma.Cancer medicine · 2020Article
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Authors and funding
11 authors at 2 institutions in 2 countries.
Funding
Abstract
objectivePrevious studies have reported a close relationship between malignant mesothelioma (MM) and the immune matricial microenvironment (IMM). One of the major problems in these studies is the lack of adequate adjustment for potential confounders. Therefore, the aim of this study was to identify and quantify risk factors such as IMM and various tumor characteristics and their association with the subtype of MM and survival.
methodsWe examined IMM and other tumor markers in tumor tissues from 82 patients with MM. These markers were evaluated by histochemistry, immunohistochemistry, immunofluorescence, and morphometry. Logistic regression analysis, cluster analysis, and Cox regression analysis were performed.
resultsHierarchical cluster analysis revealed two clusters of MM that were independent of clinicopathologic features. The high-risk cluster included MM with high tumor cellularity, high type V collagen (Col V) fiber density, and low CD8
conclusionMorphometric analysis of Col V, CD8
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