Summary Integrated genomic analyses revealed a miRNA-regulatory network, which further defined a robust integrated mesenchymal subtype associated with poor overall survival in 459 cases of serous ovarian cancer (OvCa) from The Cancer Genome Atlas and 560 cases from independent cohorts. Eight key miRNAs, including miR-506, miR-141 and miR-200a, were predicted to regulate 89% of the targets in this network. Follow-up functional experiments illustrate that miR-506 augmented E-cadherin expression, inhibited cell migration and invasion, and prevented TGFβ-induced epithelial-mesenchymal transition (EMT) by targeting SNAI2, a transcriptional repressor of E-cadherin. In human OvCa, miR-506 expression was correlated with decreased SNAI2 and VIM, elevated E-cadherin, and beneficial prognosis. Nanoparticle delivery of miR-506 in orthotopic OvCa mouse models led to E-cadherin induction and reduced tumor growth.

Gastric cancer (GC) is a highly heterogeneous disease. To identify potential clinically actionable therapeutic targets that may inform individualized treatment strategies, we performed whole-exome sequencing on 78 GCs of differing histologies and anatomic locations, as well as whole-genome sequencing on two GC cases, each with three primary tumors and two matching lymph node metastases. The data showed two distinct GC subtypes with either high-clonality (HiC) or low-clonality (LoC). The HiC subtype of intratumoral heterogeneity was associated with older age, TP53 (tumor protein P53) mutation, enriched C > G transition, and significantly shorter survival, whereas the LoC subtype was associated with younger age, ARID1A (AT rich interactive domain 1A) mutation, and significantly longer survival. Phylogenetic tree analysis of whole-genome sequencing data from multiple samples of two patients supported the clonal evolution of GC metastasis and revealed the accumulation of genetic defects that necessitate combination therapeutics. The most recurrently mutated genes, which were validated in a separate cohort of 216 cases by targeted sequencing, were members of the homologous recombination DNA repair, Wnt, and PI3K-ERBB pathways. Notably, the drugable NRG1 (neuregulin-1) and ERBB4 (V-Erb-B2 avian erythroblastic leukemia viral oncogene homolog 4) ligand-receptor pair were mutated in 10% of GC cases. Mutations of the BRCA2 (breast cancer 2, early onset) gene, found in 8% of our cohort and validated in The Cancer Genome Atlas GC cohort, were associated with significantly longer survivals. These data define distinct clinicogenetic forms of GC in the Chinese population that are characterized by specific mutation sets that can be investigated for efficacy of single and combination therapies.clonality | exome sequencing | mutation | ERBB | BRCA2 G astric cancer (GC) is the fourth most common cancer and the second leading cause of cancer death worldwide, accounting for 8% of all newly diagnosed cancers and 10% of cancer mortality(1). Environmental risk factors for GC include a high-salt diet, smoking, and infectious agents (1), including the bacterium Helicobacter pylori (2), and Epstein Barr Virus (3). Consistent with its complicated etiology (e.g., diet) and anatomical environment, GC is clinically and pathologically highly heterogeneous (4), with a large variation in 5-y survival rates in different countries, and even different cities in the same country (5, 6). This clinical heterogeneity is mirrored by concomitant heterogeneous molecular signatures in GC mRNA, protein, and miRNA expression profiles (7,8). Standard treatment strategies have largely ignored the heterogeneity and individuality of different subtypes of GC. The current approach entails surgical removal of the tumor followed by adjuvant fluoropyrimidine, taxane, and platinum-based chemotherapy doublets or triplets, especially for advanced GC, and this is exacerbated by the lack of reliable markers to predict response. Recently, the US Food and Drug Administratio...

BackgroundMost (70%) epithelial ovarian cancers (EOCs) are diagnosed late. Non-invasive biomarkers that facilitate disease detection and predict outcome are needed. The microRNAs (miRNAs) represent a new class of biomarkers. This study was to identify and validate plasma miRNAs as biomarkers in EOC.Methodology/Principal FindingsWe evaluated plasma samples of 360 EOC patients and 200 healthy controls from two institutions. All samples were grouped into screening, training and validation sets. We scanned the circulating plasma miRNAs by TaqMan low-density array in the screening set and identified/validated miRNA markers by real-time polymerase chain reaction assay in the training set. Receiver operating characteristic and logistic regression analyses established the diagnostic miRNA panel, which were confirmed in the validation sets. We found higher plasma miR-205 and lower let-7f expression in cases than in controls. MiR-205 and let-7f together provided high diagnostic accuracy for EOC, especially in patients with stage I disease. The combination of these two miRNAs and carbohydrate antigen-125 (CA-125) further improved the accuracy of detection. MiR-483-5p expression was elevated in stages III and IV compared with in stages I and II, which was consistent with its expression pattern in tumor tissues. Furthermore, lower levels of let-7f were predictive of poor prognosis in EOC patients.Conclusions/SignificanceOur findings indicate that plasma miR-205 and let-7f are biomarkers for ovarian cancer detection that complement CA-125; let-7f may be predictive of ovarian cancer prognosis.

We regret that we failed to acknowledge the unpublished data provided by Bagnoli et al. in our paper. The case material first reported by Bagnoli et al. (Oncotarget, 2012) was part of Table 1. The unpublished clinical follow-up data was generously provided by the authors and used for the curve shown in Figure 6E in our paper. The correct text on page 193 of the original article should be as follows: ''To further confirm miR-506's association with good prognosis in ovarian cancer, we obtained two miRNAs microarray data sets from GEO and ArrayExpress (Bentink Data set and Bagnoli Data set, Table 1) with 129 and 55 OvCa cases, respectively. In both data sets, miR-506 expression is significantly associated with longer progression-free survival (Bagnoli et al., personal communication) (log-rank p = 0.02 and 0.0006 for Bentink and Bagnoli Data sets, respectively, Figures 6D and 6E).'' We would like to apologize for this oversight and sincerely thank the authors for providing this unpublished data to our study.

Purpose: Our aim was to investigate whether microRNAs can predict the clinical outcome of patients with gastric cancer. We used integrated analysis of microRNA and mRNA expression profiles to identify gastric cancer microRNA subtypes and their underlying regulatory scenarios.Experimental Design: MicroRNA-based gastric cancer subtypes were identified by consensus clustering analysis of microRNA profiles of 90 gastric cancer tissues. Activated pathways in the subtypes were identified by gene expression profiles. Further integrated analysis was conducted to model a microRNA regulatory network for each subtype. RNA and protein expression were analyzed by RT-PCR and tissue microarray, respectively, in a cohort of 385 gastric cancer cases (including the 90 cases for profiling) to validate the key microRNAs and targets in the network. Both in vitro and in vivo experiments were carried out to further validate the findings.Results: MicroRNA profiles of 90 gastric cancer cases identified two microRNA subtypes significantly associated with survival. The poor-prognosis gastric cancer microRNA subtype was characterized by overexpression of epithelial-to-mesenchymal transition (EMT) markers. This gastric cancer "mesenchymal subtype" was further validated in a patient cohort comprising 385 cases. Integrated analysis identified a key microRNA regulatory network likely driving the gastric cancer mesenchymal subtype. Three of the microRNAs (miR-200c, miR-200b, and miR-125b) targeting the most genes in the network were significantly associated with survival. Functional experiments demonstrated that miR-200b suppressed ZEB1, augmented E-cadherin, inhibited cell migration, and suppressed tumor growth in a mouse model. Conclusions:We have uncovered a key microRNA regulatory network that defines the mesenchymal gastric cancer subtype significantly associated with poor overall survival in gastric cancer. Clin Cancer Res; 20(4); 878-89. Ó2013 AACR.