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• W2783305251 abstract "7605 Background: Thymomas and thymic carcinomas (TC) are rare epithelial tumors derived from the thymic gland in the anterior mediastinum. Although all histological types of thymomas, albeit with different frequencies, can give rise to metastases, TC have a more aggressive behavior and metastasize earlier and more frequently than thymomas. We previously developed a prognostic gene signature able to accurately determine metastatic behavior of thymomas (Gökmen-Polar et al. ASCO 2012). The signature is currently used in clinical practice to identify patients at high or low risk for metastatic disease. In the current study, we sought to evaluate the utility of this signature for determining risk from TC tumors. Methods: FFPE tissue sections were macrodissected from 35 primary TC. RNA was isolated and RT-PCR was performed to assess the expression of 23 genes (19 test and four reference genes). Predictive modeling was performed using Radial Basis Machine (RBM) software from JMP Genomics (SAS), and survival analysis was done using the Kaplan-Meier method. Results: Samples from the TC cohort ranged from stage II through IVB, with a median age of 54 years. 26 samples had evidence of metastatic progression, while nine samples did not. Prediction of metastasis, based upon comparison to the previously developed thymoma training set and using a 19-gene signature, yielded an ROC = 0.66. Independent analysis of the TC cohort with the thymoma 19-gene signature resulted in a predictive model with an ROC = 0.97 (overall accuracy = 87%, sensitivity = 73% and specificity=100%). Further modeling and gene set reduction revealed a separate ten-gene signature able to segregate metastatic from non-metastatic cases with 100% accuracy. All the cases classified as high risk (n= 26) developed metastasis within 5 years while none of the cases categorized as low-risk (n= 9) had any events at 5 years of follow-up. Conclusions: A ten-gene signature was established that appears to predict metastatic behavior of TC with a high degree of accuracy; however, validation in an independent cohort is necessary. Our data suggests that the biologic determinants of the clinical course of TC maybe distinct from thymoma and could be used to improve patient management." @default.
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• W2783305251 date "2013-05-20" @default.
• W2783305251 modified "2023-10-16" @default.
• W2783305251 title "A gene signature to determine metastatic behavior in thymic carcinoma." @default.
• W2783305251 doi "https://doi.org/10.1200/jco.2013.31.15_suppl.7605" @default.
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