Oncotarget

Research Papers:

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

Rossella Bruno _, Greta Alì, Riccardo Giannini, Agnese Proietti, Marco Lucchi, Antonio Chella, Franca Melfi, Alfredo Mussi and Gabriella Fontanini

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Oncotarget. 2017; 8:2758-2770. https://doi.org/10.18632/oncotarget.13174

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Abstract

Rossella Bruno1, Greta Alì2, Riccardo Giannini1, Agnese Proietti2, Marco Lucchi3, Antonio Chella4, Franca Melfi3, Alfredo Mussi1,3, Gabriella Fontanini1,5

1Department of Surgical, Medical, Molecular Pathology and Critical Area, University of Pisa, Pisa, Italy

2Division of Pathological Anatomy, University Hospital of Pisa, Pisa, Italy

3Division of Thoracic Surgery, University Hospital of Pisa, Pisa, Italy

4Division of Pneumology, University Hospital of Pisa, Pisa, Italy

5Program of Pleuropulmonary Pathology, University Hospital of Pisa, Pisa, Italy

Correspondence to:

Gabriella Fontanini, email: [email protected]

Keywords: malignant pleural mesothelioma, mesothelial hyperplasia, differential diagnosis, gene profiles, classification models

Received: September 02, 2016     Accepted: October 12, 2016     Published: November 07, 2016

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.


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