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Background: We have recently demonstrated that simple ratios of the expression levels of selected genes in tumor samples can be used to distinguish between types of thoracic malignancies. We examined whether this technique could predict treatment-related outcome for patients with mesothelioma. Methods: We used gene expression profiling data previously collected from 17 mesothelioma patients with different overall survival times to define two outcome-related groups of patients and to train an expression ratio-based outcome predictor model. A Student's t test was used to identify genes among the two outcome groups that had statistically significant, inversely correlated expression levels; those genes were used to form prognostic expression ratios. We used a combination of several highly accurate expression ratios and cross-validation techniques to assess the internal consistency of this predictor model, quantitative reverse transcription-polymerase chain reaction of tumor RNA to confirm the microarray data, and Kaplan-Meier survival analysis to validate the model among an independent set of 29 mesothelioma tumors. All statistical tests were two-sided. Results: We developed an expression ratio-based test capable of identifying 100% (17/17) of the samples used to train the model. This test remained highly accurate (88%, 15/17) after cross-validation. A four-gene expression ratio test statistically significantly (P = .0035) predicted treatment-related patient outcome in mesothelioma independent of the histologic subtype of the tumor Conclusions: Gene expression ratio-based analysis accurately predicts treatment-related outcome in mesothelioma samples. This technique could impact the clinical treatment of mesothelioma by allowing the preoperative identification of patients with widely divergent prognoses.
Gavin J. Gordon1, Roderick V. Jensen2, Li-Li Hsiao3, Steven R. Gullans4, Joshua E. Blumenstock2, William G. Richards1, Michael T. Jaklitsch1, David J. Sugarbaker1, Raphael Bueno1
1Division of Thoracic Surgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
2Department of Physics, Wesleyan University, Middletown, CT
3Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
4Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Cambridge, MA.
Mesothelioma, prognosis/prognostic test, expression profiling, gene ratios
Gavin J. Gordon
ggordon@partners.org
Raphael Bueno
rbueno@partners.org
Supplemental Information 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 considered in this study, including the 17 chosen for the training set of samples. 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). An expanded version of Table 2 comprehensively listing all 46 prognostic genes can be found here in MS Excel format.
Comments to: KKee@partners.org
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