10.3389/fonc.2019.00078.s003 Jian-Guo Zhou Jian-Guo Zhou Hua Zhong Hua Zhong Juan Zhang Juan Zhang Su-Han Jin Su-Han Jin Raheleh Roudi Raheleh Roudi Hu Ma Hu Ma Table_3_Development and Validation of a Prognostic Signature for Malignant Pleural Mesothelioma.XLS Frontiers 2019 malignant pleural mesothelioma gene expression profile prognostic model validation overall survival 2019-02-15 04:02:59 Dataset https://frontiersin.figshare.com/articles/dataset/Table_3_Development_and_Validation_of_a_Prognostic_Signature_for_Malignant_Pleural_Mesothelioma_XLS/7723406 <p>Introduction: Dysregulated genes play a critical role in the development and progression of cancer, suggesting their potential as novel independent biomarkers for cancer diagnosis and prognosis. Prognostic model-based gene expression profiles are not widely utilized in clinical medicine. We investigated the prognostic significance of an expression profile-based gene signature for outcome prediction in patients with malignant pleural mesothelioma (MPM).</p><p>Methods: The gene expression profiles of a large cohort of patients with MPM were obtained and analyzed by repurposing publicly available microarray data. A gene-based risk score model was developed with the training dataset and then validated with the TCGA-MESO (mesothelioma) dataset. The time-dependent receiver operating characteristic (ROC) curve was used to evaluate the prognostic performance of survival prediction. The biological function of the prognostic genes was predicted using bioinformatics analysis.</p><p>Results: Three genes in the training dataset (GSE2549) were identified as significantly associated with the overall survival (OS) of patients with MPM and were combined to develop a three-gene prognostic signature to stratify patients into low-risk and high-risk groups. The MPM patients of the training dataset in the low-risk group exhibited longer OS than those in the high-risk group (HR = 0.25, 95% CI = 0.11–0.56, P < 0.001). Similar prognostic values for the three-gene signature were observed in the validated TCGA-MESO cohort (HR = 0.53 95% CI = 0.33–0.85, P = 0.008). ROC analysis also demonstrated the good performance in predicting 3-year OS in the GEO and TCGA cohorts (KM-AUC for GEO = 0.989, KM-AUC for TCGA = 0.618). The C-statistic for the 3-gene model was 0.761. Validation with TCGA-MESO confirmed the model's ability to discriminate between risk groups in an alternative data set with fair performance (C-statistic: 0.68). Functional enrichment analysis suggested that these three genes may be involved in genetic and epigenetic events with known links to MPM.</p><p>Conclusions: This study has identified and validated a novel 3-gene model to reliably discriminate patients at high and low risk of death in unselected populations of patients with MPM. Further larger, prospective multi-institutional cohort studies are necessary to validate this model.</p>