Dataset Information

MiR-score: a novel 6-microRNA signature that predicts survival outcomes in patients with malignant pleural mesothelioma.

ABSTRACT: BACKGROUND:Prognosis of malignant pleural mesothelioma (MPM) is poor, and predicting the outcomes of treatment is difficult. Here we investigate the potential of microRNA expression to estimate prognosis of MPM patients. METHODS:Candidate microRNAs from microarray profiling of tumor samples from 8 long (median: 53.7 months) and 8 short (median: 6.4 months) survivors following extrapleural pneumonectomy (EPP) were validated by RT-qPCR in 48 additional EPP samples. Kaplan-Meier log ranking was used to further explore the association between microRNA expression and overall survival (OS). Binary logistic regression was used to construct a microRNA signature (miR-Score) that was able to predict an OS of ?20 months. Performance of the miR-Score was evaluated by receiver operating characteristic (ROC) curve analysis and validated in a series of 43 tumor samples from patients who underwent palliative surgery [pleurectomy/decortication (P/D)]. RESULTS:The miR-Score, using expression data of six microRNAs (miR-21-5p, -23a-3p, -30e-5p, -221-3p, -222-3p, and -31-5p), enabled prediction of long survival with an accuracy of 92.3% for EPP and 71.9% for palliative P/D. Hazard ratios for score-negative patients were 4.12 (95% CI: 2.03-8.37) for EPP and 1.93 (95% CI: 1.01-3.69) for P/D. Importantly, adding the miR-Score to a set of clinical selection criteria (histology, age, gender) increased predictive accuracy in the independent validation set from 76.3% for clinical factors only to 87.3%. CONCLUSIONS:This study has identified a novel 6-microRNA signature (miR-Score) that can accurately predict prognosis of MPM patients.

SUBMITTER: Kirschner MB

PROVIDER: S-EPMC5528709 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature

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MiR-score: a novel 6-microRNA signature that predicts survival outcomes in patients with malignant pleural mesothelioma.

Kirschner Michaela B MB Cheng Yuen Yee YY Armstrong Nicola J NJ Lin Ruby C Y RC Kao Steven C SC Linton Anthony A Klebe Sonja S McCaughan Brian C BC van Zandwijk Nico N Reid Glen G

Molecular oncology 20141202 3

<h4>Background</h4>Prognosis of malignant pleural mesothelioma (MPM) is poor, and predicting the outcomes of treatment is difficult. Here we investigate the potential of microRNA expression to estimate prognosis of MPM patients.<h4>Methods</h4>Candidate microRNAs from microarray profiling of tumor samples from 8 long (median: 53.7 months) and 8 short (median: 6.4 months) survivors following extrapleural pneumonectomy (EPP) were validated by RT-qPCR in 48 additional EPP samples. Kaplan-Meier log ...[more]

PMID: 25497279

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Project description: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 approximately 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 which correlate 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 (RT-PCR) and protein analysis for three novel candidate oncogenes (NME2, CRI1, and PDGFC) and one candidate tumor suppressor (GSN). Finally, we used bioinformatics tools (i.e. software) to create and explore complex physiological pathways that may be relevant in mesothelioma tumorigenesis, pathobiology, or both. Tissues and cell lines profiled using microarrays. Discarded MPM surgical specimens (n=40), normal pleura specimens (n=5), and normal lung specimens (n=4) were freshly collected (and snap frozen) from patients who underwent surgery at Boston's Brigham and Women's Hospital (BWH) between October 1998 and August 2000. All of these patients underwent extrapleural pneumonectomy with heated intra-pleural cisplatin chemotherapy delivered after the specimens were removed. All normal specimens were obtained from patients who were never diagnosed with MPM. Two human MPM cell lines (MS589 and MS428) were kindly provided by Jonathan A. Fletcher, M.D., Department of Pathology, BWH. The JMN1B MPM cell line19,20 has been described previously. The SV40-immortalized, non-tumorigenic mesothelial cell line (Met-5A)21 and the MPM cell line MSTO-211H22 were purchased from the American Type Culture Collection. Normal tissues were obtained from additional consented patients undergoing treatment for diseases other than MPM. All MPM samples used in these studies contained relatively pure tumor (greater than 50% tumor cells per high power field examined in a section adjacent to the tissue used). The microscopic slides from the patients' resection specimens were reviewed by one of the authors (J.G.), and the diagnosis and histologic subclassification of MPM confirmed in all cases. Linked clinical and pathological data were obtained for all patients who contributed tumor specimens. Specimens and data were rendered anonymous to protect patient confidentiality. Studies utilizing human tissues were approved by and conducted in accordance with the policies of the Institutional Review Board at BWH.

Project description: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). 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. 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. 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.

Dataset Information

MiR-score: a novel 6-microRNA signature that predicts survival outcomes in patients with malignant pleural mesothelioma.

Publications

MiR-score: a novel 6-microRNA signature that predicts survival outcomes in patients with malignant pleural mesothelioma.

Similar Datasets

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