Objective Gastric cancer (GC) remains difficult to cure due to heterogeneity in a clinical challenge and the molecular mechanisms underlying this disease are complex and not completely understood. Accumulating evidence suggests that microRNAs (miRNAs) play an important role in GC, but the role of specific-miRNAs involved in this disease remains elusive. We performed next generation sequencing (NGS) based whole-transcriptome profiling to discover GC-specific miRNAs, followed by functional validation of results. Design NGS-based miRNA profiles were generated in matched pairs of GCs and adjacent normal mucosa (NM). Quantitative RT-PCR validation of miR-29c expression was performed in 274 gastric tissues, which included 2 cohorts of matched GC and NM specimens. Functional validation of miR-29c and its gene targets was undertaken in cell lines, as well as K19-C2mE and K19-Wnt1/C2mE transgenic mice. Results NGS analysis revealed four GC-specific miRNAs. Among these, miR-29c expression was significantly decreased in GC vs. NM tissues (P<0.001). Ectopic expression of miR-29c mimics in GC cell lines resulted in reduced proliferation, adhesion, invasion, and migration. High miR-29c expression suppressed xenograft tumor growth in nude mice. Direct interaction between miR-29c and its newly discovered target, ITGB1, was identified in cell lines and transgenic mice. MiR-29c expression demonstrated a step-wise decrease in wild type-hyperplasia-dysplasia cascade, in transgenic mice models of GC. Conclusions MiR-29c acts as a tumor suppressor in GC by directly targeting ITGB1. Loss of miR-29c expression is an early event in the initiation of gastric carcinogenesis, and may serve as a diagnostic and therapeutic biomarker for patients with GC.

The effective production and usage of ginsenosides, given their distinct pharmacological effects, are receiving increasing amounts of attention. As the ginsenosides content differs in different parts of Panax ginseng, we wanted to assess and compare the ginsenosides content in the ginseng roots, leave, stems, and berries. To extract the ginsenosides, 70% (v/v) methanol was used. The optimal ultra-performance liquid chromatography-quadrupole time of flight mass spectrometry (UPLC-QTOF/MS) method was used to profile various ginsenosides from the different parts of P. ginseng. The datasets were then subjected to multivariate analysis including principal component analysis (PCA) and hierarchical clustering analysis (HCA). A UPLC-QTOF/MS method with an in-house library was constructed to profile 58 ginsenosides. With this method, a total of 39 ginsenosides were successfully identified and quantified in the ginseng roots, leave, stem, and berries. PCA and HCA characterized the different ginsenosides compositions from the different parts. The quantitative ginsenoside contents were also characterized from each plant part. The results of this study indicate that the UPLC-QTOF/MS method can be an effective tool to characterize various ginsenosides from the different parts of P. ginseng.

Gastric cancer (GC) is the third leading cause of cancer-related deaths worldwide. Recent high-throughput analyses of genomic alterations revealed several driver genes and altered pathways in GC. However, therapeutic applications from genomic data are limited, largely as a result of the lack of druggable molecular targets and preclinical models for drug selection. To identify new therapeutic targets for GC, we performed array comparative genomic hybridization (aCGH) of DNA from 103 patients with GC for copy number alteration (CNA) analysis, and whole-exome sequencing from 55 GCs from the same patients for mutation profiling. Pathway analysis showed recurrent alterations in the Wnt signaling [APC, CTNNB1, and DLC1 (deleted in liver cancer 1)], ErbB signaling (ERBB2, PIK3CA, and KRAS), and p53 signaling/apoptosis [TP53 and BCL2L1 (BCL2-like 1)] pathways. In 18.4% of GC cases (19/103), amplification of the antiapoptotic gene BCL2L1 was observed, and subsequently a BCL2L1 inhibitor was shown to markedly decrease cell viability in BCL2L1-amplified cell lines and in similarly altered patient-derived GC xenografts, especially when combined with other chemotherapeutic agents. In 10.9% of cases (6/55), mutations in DLC1 were found and were also shown to confer a growth advantage for these cells via activation of Rho-ROCK signaling, rendering these cells more susceptible to a ROCK inhibitor. Taken together, our study implicates BCL2L1 and DLC1 as potential druggable targets for specific subsets of GC cases.gastric cancer | copy number alteration | whole-exome sequencing | patient-derived xenograft | druggable target G astric cancer (GC) is a highly prevalent malignancy and is the third leading cause of cancer-related deaths in the world (1). In unresectable and metastatic cases, the clinical outcome for this disease remains poor (median survival is 10-14 mo) (2), and other treatment options are often limited because of the lack of effective therapeutic approaches and molecular prognostic markers (2, 3). To date, with the exception of the application of trastuzumab [ERBB2 (ErbB2 receptor tyrosine kinase 2) antagonist] or ramucirumab [VEGFR2 (Vascular endothelial growth factor receptor 2) antagonist] for advanced GC cases (4, 5), drugs that target GC on a molecular level are limited.Recent genomic studies have demonstrated the heterogeneous genomic characteristics of GC (6-10). In addition, previous studies of patients with GC by whole-genome and whole-exome sequencing (WES) have identified frequent somatic mutations in tumor suppressors such as TP53, ARID1A, APC, and FAT4, and oncogenes including PI3KCA, KRAS, and RHOA (6-10). However, these findings, although academically meaningful, are far from ready for clinical applications, largely because of the lack of identified druggable molecular targets and the availability of reliable preclinical models for validation of potential target inhibitors.To identify novel therapeutic targets for GC, we explored genomic alterations in GC through an integrated genomic data set from WE...

Gastric adenocarcinoma is the third most common cause of cancer mortality worldwide. Accurate and affordable noninvasive detection methods have potential value for screening and surveillance. Herein, we identify novel methylated DNA markers (MDM) for gastric adenocarcinoma, validate their discrimination for gastric adenocarcinoma in tissues from geographically separate cohorts, explore marker acquisition through the oncogenic cascade, and describe distributions of candidate MDMs in plasma from gastric adenocarcinoma cases and normal controls. Following discovery by unbiased whole-methylome sequencing, candidate MDMs were validated by blinded methylation-specific PCR in archival case-control tissues from U.S. and South Korean patients. Top MDMs were then assayed by an analytically sensitive method (quantitative real-time allele-specific target and signal amplification) in a blinded pilot study on archival plasma from gastric adenocarcinoma cases and normal controls. Whole-methylome discovery yielded novel and highly discriminant candidate MDMs. In tissue, a panel of candidate MDMs detected gastric adenocarcinoma in 92% to 100% of U.S. and South Korean cohorts at 100% specificity. Levels of most MDMs increased progressively from normal mucosa through metaplasia, adenoma, and gastric adenocarcinoma with variation in points of greatest marker acquisition. In plasma, a 3-marker panel ( detected 86% (95% CI, 71-95) of gastric adenocarcinomas at 95% specificity. Novel MDMs appear to accurately discriminate gastric adenocarcinoma from normal controls in both tissue and plasma. The point of aberrant methylation during oncogenesis varies by MDM, which may have relevance to marker selection in clinical applications. Further exploration of these MDMs for gastric adenocarcinoma screening and surveillance is warranted. .

In the food industry and herbal markets, it is critical to control the quality of processed Panax ginseng products. In this study, ultra-performance liquid chromatography coupled to quadrupole time of flight mass spectrometry (UPLC-QTOF/MS)-based metabolomics was applied for the quality evaluation of white ginseng (WG), tae-geuk ginseng (TG), red ginseng (RG), and black ginseng (BG). Diverse metabolites including ginsenosides were profiled by UPLC-QTOF/MS, and the datasets of WG, TG, RG, and BG were then subjected to multivariate analyses. In principal component analysis (PCA), four processed ginseng products were well-differentiated, and several ginsenosides were identified as major components of each product. S-plot also characterized the metabolic changes between two processed ginseng products, and the major ginsenosides of each product were found as follows: WG (M-Rb1, M-Rb2, M-Rc, Re, Rg1), TG (Rb2, Rc, Rd, Re, Rg1), RG (Rb1, Rb2, Rc, Rd, Re, Rg1), and BG (Rd, Rk1, Rg5, Rg3). Furthermore, the quantitative contents of ginsenosides were evaluated from the four processed ginseng products. Finally, it was indicated that the proposed metabolomics approach was useful for the quality evaluation and control of processed ginseng products.