help button home button Am J Pathol International Conference on Pathology of Chest Diseases
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS

This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Supplemental Material
Right arrow Purchase Article
Right arrow View Shopping Cart
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Gordon, G. J.
Right arrow Articles by Bueno, R.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Gordon, G. J.
Right arrow Articles by Bueno, R.
(American Journal of Pathology. 2005;166:1827-1840.)
© 2005 American Society for Investigative Pathology

Identification of Novel Candidate Oncogenes and Tumor Suppressors in Malignant Pleural Mesothelioma Using Large-Scale Transcriptional Profiling

Gavin J. Gordon*, Graham N. Rockwell{dagger}, Roderick V. Jensen{ddagger}, James G. Rheinwald§, Jonathan N. Glickman, Joshua P. Aronson*, Brian J. Pottorf*, Matthew D. Nitz*, William G. Richards*, David J. Sugarbaker* and Raphael Bueno*

From the Thoracic Surgery Oncology Laboratory, the Division of Thoracic Surgery,* and the Departments of Neurology,{dagger} Dermatology,§ and Pathology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts; and the Department of Physics,{ddagger} University of Massachusetts, Boston, Massachusetts

Malignant pleural mesothelioma (MPM) is a highly lethal, poorly understood neoplasm that is typically associated with asbestos exposure. We performed transcriptional profiling using high-density oligonucleotide microarrays containing ~22,000 genes to elucidate potential molecular and pathobiological pathways in MPM using discarded human MPM tumor specimens (n = 40), normal lung specimens (n = 4), normal pleura specimens (n = 5), and MPM and SV40-immortalized mesothelial cell lines (n = 5). In global expression analysis using unsupervised clustering techniques, we found two potential subclasses of mesothelioma that correlated loosely with tumor histology. We also identified sets of genes with expression levels that distinguish between multiple tumor subclasses, normal and tumor tissues, and tumors with different morphologies. Microarray gene expression data were confirmed using quantitative reverse transcriptase-polymerase chain reaction and protein analysis for three novel candidate oncogenes (NME2, CRI1, and PDGFC) and one candidate tumor suppressor (GSN). Finally, we used bioinformatics tools (ie, software) to create and explore complex physiological pathways. Combined, all of these data may advance our understanding of mesothelioma tumorigenesis, pathobiology, or both.






HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Copyright © 2005 by the American Society for Investigative Pathology.