Background Gastric cancer (GC) is a leading cause of cancer deaths, and an increased number of GC patients adopt to next-generation sequencing (NGS) to identify tumor genomic alterations for precision medicine. Methods In this study, we established a hybridization capture-based NGS panel including 612 cancer-associated genes, and collected sequencing data of tumors and matched bloods from 153 gastric cancer patients. We performed comprehensive analysis of these sequencing and clinical data. Results 35 significantly mutated genes were identified such as TP53 , AKAP9 , DRD2 , PTEN , CDH1 , LRP2 et al. Among them, 29 genes were novel significantly mutated genes compared with TCGA study. TP53 is the top frequently mutated gene, and tends to mutate in male (p = 0.025) patients and patients whose tumor located in cardia (p = 0.011). High tumor mutation burden (TMB) gathered in TP53 wild-type tumors (p = 0.045). TMB was also significantly associated with DNA damage repair (DDR) genes genotype (p = 0.047), Lauren classification (p = 1.5e−5), differentiation (1.9e−7), and HER2 status (p = 0.023). 38.31% of gastric cancer patients harbored at least one actionable alteration according to OncoKB database. Conclusions We drew a comprehensive mutational landscape of 153 gastric tumors and demonstrated utility of target next-generation sequencing to guide clinical management. Electronic supplementary material The online version of this article (10.1186/s12967-019-1941-0) contains supplementary material, which is available to authorized users.

Accumulating evidence has suggested the importance of gut microbiota in the development of type 2 diabetes mellitus (T2DM). In the present study, 40 patients with T2DM were treated with liraglutide for 4 months. Feces samples and clinical characteristics were collected from these 40 T2DM patients before and after the liraglutide treatment. The diversity and composition of gut microbiota in the two groups were determined by sequencing the V4 region of bacterial 16S rRNA genes. Meanwhile, blood glucose, insulin, hemoglobin A1c (HbA1c), and lipid metabolism were also measured in the pre- and post-liraglutide-treatment groups. We find that Baseline HbA1c was associated with liraglutide treatment response (R2 = 0.527, β =  − 0.726, p < 0.0001). After adjusted for baseline HbA1c, blood urea nitrogen was associated with liraglutide treatment response. Besides, our results showed reduced gut microbial alpha diversity, different community structure distribution and altered microbial interaction network in patients treated with liraglutide. The liner discriminant analysis (LDA) effect size (LEfSe) analysis showed that 21 species of bacteria were abundant in the pre-liraglutide-treatment group and 15 species were abundant in the post-liraglutide-treatment group. In addition, we also find that Megamonas were significantly correlated with older age, diabetes duration and diabetic retinopathy, Clostridum were significantly correlated with family history of diabetes and Oscillospira were significantly correlated with both diabetic retinopathy and diabetic peripheral neuropathy. Functional analysis based on Kyoto Encyclopedia of Genes and Genomes (KEGG) and cluster of orthologous groups (COG) annotations enriched three KEGG metabolic pathways and six functional COG categories in the post-liraglutide-treatment group. In conclusion, our research suggests that baseline HbA1c, blood urea nitrogen and gut microbiota are associated with the liraglutide treatment applied on patients with T2DM. These findings may contribute to the beneficial effects of liraglutide against diabetes.

Background: Chronic obstructive pulmonary disease (COPD) is a major public health problem and cause of mortality worldwide. However, COPD in the early stage is usually not recognized and diagnosed. It is necessary to establish a risk model to predict COPD development. Methods: A total of 441 COPD patients and 192 control subjects were recruited, and 101 single-nucleotide polymorphisms (SNPs) were determined using the MassArray assay. With 5 clinical features as well as SNPs, 6 predictive models were established and evaluated in the training set and test set by the confusion matrix AU-ROC, AU-PRC, sensitivity (recall), specificity, accuracy, F1 score, MCC, PPV (precision) and NPV. The selected features were ranked.

Previous studies proved that long noncoding RNAs (lncRNAs) play important role in human cancer. However, the knowledge of genome scale expression of lncRNAs and their potential biological function in gastric cancer is still lacking. Next generation RNA sequencing (RNA-seq) was performed on tumor tissues and matched adjacent normal tissues of six diffuse gastric cancer (DGC) patients. Then we performed a comprehensive analysis on lncRNAs and mRNA. Fifty-eight lncRNAs were upregulated and 54 lncRNAs were downregulated in diffuse gastric cancer tissue compared with adjacent tissue. The numbers of up- and downregulated mRNAs were 306 and 161, respectively. In addition, we inferred the function of lncRNAs by construction of a co-expression network for deregulated mRNAs and lncRNAs. Co-expressed genes of MEF2C-AS1 and FENDRR were enriched to RAS and TGF-beta signaling pathway. MEF2C-AS1 and FENDRR expression were re-evaluated by Real-time Quantitative PCR in 42 DGC patients' tumor and normal tissues, and other 46 DGC patents' and 21 healthy controls' plasma. Validation data showed MEF2C-AS1 and FENDRR were significantly downregulated in tumor tissues compared with normal tissues. And decreased FENDRR are associated with aggressive tumor characteristics including more advanced stage (P = .030), poor differentiation (P = .043) and lymphatic metastasis (P = .001). The expression level MEF2C-AS1 was significantly lower in DGC patients' plasma than that in healthy controls' plasma. In gastric cancer cell lines, knock-down of MEF2C-AS1 or FENDRR reduced the protein levels of FAT3, NTN1 and LYVE1 (the co-expressed genes), which were related with gastric cancer cell proliferation and invasion by previous studies. In addition, knock-down of MEF2C-AS1 or FENDRR promoted aggressive tumor behaviors in in-vitro assays. In this study, we provide a valuable resource of lncRNAs which might play important roles in the function of oncogenes or tumor suppressors affecting the development and progression of diffuse gastric cancer.

Gastric cardia adenocarcinoma (GCA), which occurs at the gastroesophageal boundary, is one of the most malignant types of cancer. Over the past 30 years, the incidence of GCA has increased by approximately sevenfold, which has a more substantial increase than that of many other malignancies. However, as previous studies mainly focus on non-cardia gastric cancer, until now, the mechanisms behind GCA remain largely unknown. MicroRNAs (miRNAs) have been shown to play pivotal roles in carcinogenesis. To gain insight into the molecular mechanisms regulated by miRNAs in GCA development, we investigated miRNA expression profiles using 81 pairs of primary GCAs and corresponding non-tumorigenic tissues. First, 21 pairs of samples were used for microarray analysis, and then another 60 pairs of samples were used for further analysis. Our results showed that 464 miRNAs (237 upregulated, 227 downregulated, false discovery rate FDR <0.05) were differently expressed between GCA and non-tumor tissues. Pearson test and pathway analysis revealed that these dysregulated miRNA correlated coding RNAs may have effects on several cancer-related pathways. Four miRNAs (miR-1244, miR-135b-5p, miR-3196, and miR-628-3p) were found to be associated with GCA differentiation. One miRNA, miR-196a-5p, was found to be associated with age of GCA onset. Further, survival analysis showed that the expression level of miR-135b-5p was associated with GCA survival. Taken together, our study first provided the genome-wide expression profiles of miRNA in GCA and will be good help for further functional studies.