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The pathological distinction between malignant pleural mesothelioma (MPM) and adenocarcinoma (ADCA) of the lung can be cumbersome using established methods. We propose that a simple technique, based on the expression levels of a small number of genes, can be useful in the early and accurate diagnosis of MPM and lung cancer. This method is designed to accurately distinguish between genetically disparate tissues using gene expression ratios and rationally chosen thresholds. Here we have tested the fidelity of ratio-based diagnosis in differentiating between MPM and lung cancer in 181 tissue samples (31 MPM and 150 ADCA). A training set of 32 samples (16 MPM and 16 ADCA) was used to identify pairs of genes with highly significant, inversely correlated expression levels to form a total of 15 diagnostic ratios using expression profiling data. Any single ratio of the 15 examined was at least 90% accurate in predicting diagnosis for the remaining 149 samples (e.g. test set). We then examined (in the test set) the accuracy of multiple ratios combined to form a simple diagnostic tool. Using two and three expression ratios the differential diagnosis of MPM and lung ADCA were 95% and 99% accurate, respectively. We propose that utilizing gene expression ratios is an accurate and inexpensive technique with direct clinical applicability for distinguishing between MPM and lung cancer. Furthermore, we provide evidence suggesting that this technique can be equally accurate in other clinical scenarios.
Gavin J. Gordon1, Roderick V. Jensen2, Li-Li Hsiao3, Steven R. Gullans4, Joshua E. Blumenstock2, Sridhar Ramaswamy5,6, William G. Richards1, David J. Sugarbaker1, Raphael Bueno1
1Division of Thoracic Surgery, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St., Boston, Massachusetts 02115 USA
2Department of Physics, Wesleyan University, Middletown, Connecticut 06457 USA
3Renal Division, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, Massachusetts 02115 USA
4Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, 65 Landsdowne St. Cambridge, Massachusetts 02139 USA
5Department of Adult Oncology, Dana-Farber Cancer Institute, Harvard Medical School, 44 Binney Street, Boston, MA 02115
6Whitehead Institute/MIT Center for Genome Research, 1 Kendall Square, Cambridge, MA, 02139
expression profiling, mesothelioma, lung cancer
Gavin J. Gordon
ggordon@partners.org
Raphael Bueno
rbueno@partners.org
Microarray data (Affymetrix Microarray Suite v5.0) is supplied in Microsoft Excel 97 format and text format and contains expression profiling data (Affymetrix U95A chip) for all 31 mesothelioma tumors. The "target intensity" has been set to 100 (Affymetrix Microarray Suite v5.0). Samples 114 and 76 were analyzed in triplicate to assess chip variability. The raw data (.cel files) can be found here (zip file format-105mb). Microarray data and sample data for lung adenocarcinoma samples has been previously published and can be found at www.genome.wi.mit.edu/MPR/lung. Extensive annotation of Affymetrix probe sets has been painstakingly assembled and kindly provided by Jean Marie Rouillard (University of Michigan) and can be found at dot.ped.med.umich.edu:2000/ourimage/microarrays/Affy_annot/Unigene/index.html. Additionally, expression profiling data for the 181 samples analyzed in this study (150 adenocarcinoma and 31 mesothelioma) and the identity of the training set chips is also supplied in text format. This data was generated using Affymetrix Microarray Suite v4.0 and a "target intensity" of 100. Note that the 67 internal hybridization control probe sets have been removed from this data leaving expression data for 12,533 human genes.
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©2007, Division of Thoracic Surgery at Brigham and Women's Hospital. All rights reserved.
Division of Thoracic Surgery
Brigham and Women's Hospital
75 Francis Street
Boston, MA 02115
Phone: (617) 732-6824