Malignant pleural mesothelioma and mesothelial hyperplasia: A new molecular tool for the differential diagnosis

Our plain-English summary of Malignant pleural mesothelioma and mesothelial hyperplasia: A new molecular tool for the differential diagnosis, by R. Bruno, G. Alì, R. Giannini, et al (Oncotarget, 2017).

The study

• Authors: R. Bruno, G. Alì, R. Giannini, A. Proietti, M. Lucchi, A. Chella, F. Melfi, A. Mussi, G. Fontanini
• Journal: Oncotarget
• Published: 2017;8(2):2758-2770
• Cited by: 21 articles, as counted by NIH iCite
• Read it: PubMed · Publisher · Free full text

Abstract

Malignant pleural mesothelioma (MPM) is a rare asbestos related cancer, aggressive and unresponsive to therapies. Histological examination of pleural lesions is the gold standard of MPM diagnosis, although it is sometimes hard to discriminate the epithelioid type of MPM from benign mesothelial hyperplasia (MH).This work aims to define a new molecular tool for the differential diagnosis of MPM, using the expression profile of 117 genes deregulated in this tumour.The gene expression analysis was performed by nanoString System on tumour tissues from 36 epithelioid MPM and 17 MH patients, and on 14 mesothelial pleural samples analysed in a blind way. Data analysis included raw nanoString data normalization, unsupervised cluster analysis by Pearson correlation, non-parametric Mann Whitney U-test and molecular classification by the Uncorrelated Shrunken Centroid (USC) Algorithm.The Mann-Whitney U-test found 35 genes upregulated and 31 downregulated in MPM. The unsupervised cluster analysis revealed two clusters, one composed only of MPM and one only of MH samples, thus revealing class-specific gene profiles. The Uncorrelated Shrunken Centroid algorithm identified two classifiers, one including 22 genes and the other 40 genes, able to properly classify all the samples as benign or malignant using gene expression data; both classifiers were also able to correctly determine, in a blind analysis, the diagnostic categories of all the 14 unknown samples.In conclusion we delineated a diagnostic tool combining molecular data (gene expression) and computational analysis (USC algorithm), which can be applied in the clinical practice for the differential diagnosis of MPM.

In plain English

This retrospective laboratory study from the University of Pisa, Italy, tested whether gene activity in tissue samples could tell epithelioid malignant pleural mesothelioma (MPM) apart from mesothelial hyperplasia (MH), a benign condition that can look similar under the microscope. The study did not examine asbestos exposure. The authors measured 117 genes in samples from 36 MPM and 17 MH patients. Eleven MPM and 2 MH samples were dropped because of poor-quality RNA, leaving 25 MPM and 15 MH. In these samples, 35 genes were more active and 31 less active in MPM (p less than 0.05), and the MPM and MH samples fell into separate groups. A computer method built two gene sets, one of 22 genes and one of 40 genes. Both sorted every training sample correctly. Both also correctly classified 14 further samples (9 MPM, 5 MH) that were tested without knowing their diagnosis. The authors called this a preliminary study. They said larger validation is needed, and that they could not calculate predictive values because of the small number of samples.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: Retrospective laboratory study of diagnostic gene expression: gene activity was measured in stored tissue samples, a classification algorithm was trained on known cases, and it was then tested on blinded samples
• Who was studied: First part: 36 patients with epithelioid MPM and 17 with MH. Second part: 14 pleural mesothelial samples (9 MPM, 5 MH) analysed blind. The MPM patients consecutively underwent pleurectomy/decortication at the University of Pisa, 2012 to 2015.
• Exposure: Asbestos exposure was not studied. The study measured the expression of a custom panel of 117 genes, chosen as deregulated in MPM, in formalin-fixed, paraffin-embedded tissue using the nanoString system.
• Main results:
  • 11 MPM samples and 2 MH samples were excluded for poor-quality RNA. These samples came from archive material older than two years. Analysis used 25 MPM and 15 MH samples.
  • Unsupervised clustering of all 117 genes placed all MPM samples in one cluster and all MH samples in another
  • Compared with MH, 35 genes were upregulated and 31 downregulated in MPM at p less than 0.05
  • Fifty-one genes were not statistically deregulated in MPM
  • Age differed between the MPM and MH groups, but no analysed gene showed a strong and statistically significant correlation with age
  • The USC algorithm produced Classifier 1 (22 genes) and Classifier 2 (40 genes). Both had zero classification errors in the training set of 25 MPM and 15 MH samples.
  • In the blind test of 14 samples, both classifiers called 5 samples MH and 9 MPM. All 14 matched the histological diagnosis.
• The authors' conclusion: The authors concluded that, although the study was preliminary, this gene-expression and computational tool could allow better discrimination of epithelioid MPM from MH and could be applied in clinical routine after further validation
• Limitations the authors state:
  • Positive and negative predictive values could not be calculated because of the small number of samples
  • Further retrospective and prospective validation on a larger series of samples is needed
  • Older samples have lower RNA quality, so sample selection matters
  • The tool has not been evaluated on cytological specimens from pleural effusions

Topics

The National Library of Medicine indexes this study under subjects our site covers: Lung cancer, Mesothelioma.

Medical terms in this study, explained in our Lexicon: Pleural Mesothelioma, Reactive Mesothelial Hyperplasia, Differential Diagnosis, Epithelioid.

Related studies

• Differential expression of extracellular matrix constituents and cell adhesion molecules between malignant pleural mesothelioma and mesothelial hyperplasia — G. Alì, N. Borrelli, et al. (2013)
• Use of Anti-Noxa Antibody for Differential Diagnosis between Epithelioid Mesothelioma and Reactive Mesothelial Hyperplasia — K. Kushitani, V.J. Amatya, et al. (2016)
• Value of Glut-1 and Koc markers in the differential diagnosis of reactive mesothelial hyperplasia, malignant mesothelioma and pulmonary adenocarcinoma — Ö. Üçer, A.F. Dağli, et al. (2013)
• Differential Diagnosis of Malignant Pleural Mesothelioma on Cytology: A Gene Expression Panel versus BRCA1-Associated Protein 1 and p16 Tests — R. Bruno, G. Alì, et al. (2020)
• Cytological differential diagnosis among adenocarcinoma, epithelial mesothelioma, and reactive mesothelial cells in serous effusions by immunocytochemistry — X.Y. Su, G.D. Li, et al. (2011)
• Challenges and controversies in the diagnosis of mesothelioma: Part 1. Cytology-only diagnosis, biopsies, immunohistochemistry, discrimination between mesothelioma and reactive mesothelial hyperplasia, and biomarkers — D.W. Henderson, G. Reid, et al. (2013)

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