A Ten-microRNA Expression Signature Predicts Survival in Glioblastoma

Glioblastoma (GBM) is the most common and aggressive primary brain tumor with very poor patient median survival. To identify a microRNA (miRNA) expression signature that can predict GBM patient survival, we analyzed the miRNA expression data of GBM patients (n = 222) derived from The Cancer Genome Atlas (TCGA) dataset. We divided the patients randomly into training and testing sets with equal number in each group. We identified 10 significant miRNAs using Cox regression analysis on the training set and formulated a risk score based on the expression signature of these miRNAs that segregated the patients into high and low risk groups with significantly different survival times (hazard ratio HR] = 2.4; 95% CI = 1.4-3.8; p < 0.0001). Of these 10 miRNAs, 7 were found to be risky miRNAs and 3 were found to be protective. This signature was independently validated in the testing set (HR = 1.7; 95% CI = 1.1-2.8; p = 0.002). GBM patients with high risk scores had overall poor survival compared to the patients with low risk scores. Overall survival among the entire patient set was 35.0% at 2 years, 21.5% at 3 years, 18.5% at 4 years and 11.8% at 5 years in the low risk group, versus 11.0%, 5.5%, 0.0 and 0.0% respectively in the high risk group (HR = 2.0; 95% CI = 1.4-2.8; p < 0.0001). Cox multivariate analysis with patient age as a covariate on the entire patient set identified risk score based on the 10 miRNA expression signature to be an independent predictor of patient survival (HR = 1.120; 95% CI = 1.04-1.20; p = 0.003). Thus we have identified a miRNA expression signature that can predict GBM patient survival. These findings may have implications in the understanding of gliomagenesis, development of targeted therapy and selection of high risk cancer patients for adjuvant therapy.

Coordinate Hyperactivation of Notch1 and Ras/MAPK Pathways Correlates with Poor Patient Survival: Novel Therapeutic Strategy for Aggressive Breast Cancers

Aberrant activation of Notch and Ras pathways has been detected in breast cancers. A synergy between these two pathways has also been shown in breast cell transformation in culture. Yet, the clinical relevance of Notch-Ras cooperation in breast cancer progression remains unexplored. In this study, we show that coordinate hyperactivation of Notch1 and Ras/MAPK pathways in breast cancer patient specimens, as assessed by IHC for cleaved Notch1 and pErk1/2, respectively, correlated with early relapse to vital organs and poor overall survival. Interestingly, majority of such Notch1 (high)Erk(high) cases encompassed the highly aggressive triple-negative breast cancers (TNBC), and were enriched in stem cell markers. We further show that combinatorial inhibition of Notch1 and Ras/MAPK pathways, using a novel mAb against Notch1 and a MEK inhibitor, respectively, led to a significant reduction in proliferation and survival of breast cancer cells compared with individual inhibition. Combined inhibition also abrogated sphere-forming potential, and depleted the putative cancer stem-like cell subpopulation. Most importantly, combinatorial inhibition of Notch1 and Ras/MAPK pathways completely blocked tumor growth in a panel of breast cancer xenografts, including the TNBCs. Thus, our study identifies coordinate hyperactivation of Notch1 and Ras/MAPK pathways as novel biomarkers for poor breast cancer outcome. Furthermore, based on our preclinical data, we propose combinatorial targeting of these two pathways as a treatment strategy for highly aggressive breast cancers, particularly the TNBCs that currently lack any targeted therapeutic module. (C) 2014 AACR.