Circulating miR-19a-3p and miR-483-5p as Novel Diagnostic Biomarkers for the Early Diagnosis of Gastric Cancer.

BACKGROUND MicroRNAs (miRNAs) are attracting substantial interest as promising noninvasive biomarkers for gastric cancer (GC). Our study aimed to identify circulating miRNAs that are potential noninvasive markers for precancerous lesions and early gastric cancers (EGCs). MATERIAL AND METHODS Plasma specimens were obtained from 58 gastritis subjects, 54 patients with precancerous lesions, and 38 EGC patients for study. RESULTS Significant differences in the plasma expression levels of miR-19a-3p, miR-22-3p, miR-146a-5p, and miR-483-5p (all P<0.05) were observed between EGC patients and gastritis subjects. Multivariable analysis showed that age (OR, 1.054; 95% CI, 1.006-1.104), miR-19a-3p expression (OR, 3.676; 95% CI, 1.914-7.061), and miR-483-5p expression (OR, 1.589; 95% CI, 1.242-2.033) were independently associated with EGCs and precancerous lesions. A combined diagnostic model incorporating these 3 variables for the prediction of EGCs and precancerous lesions was derived. The area under the receiver operating characteristic curve (AUC) of the model was 0.84; the sensitivity was 87.7% and the specificity was 62.8% at the cutoff value of -0.08. CONCLUSIONS Plasma miR-19a-3p and miR-483-5p are promising and powerful noninvasive markers for the early detection of GC. Patients are more willing to undergo noninvasive diagnostic procedures than gastroscopy for cancer screening, economizing limited medical resources.

Analysis of Long Non-Coding RNA Expression Profile and Functional Study of LOC389332 in Early Gastric Cancer.

BACKGROUND Long non-coding RNAs (LncRNAs) could potentially function as diagnostic markers for gastric carcinoma. Nevertheless, the expression profile and biological feature of LncRNAs in early gastric cancer (EGC) remains to be explored. MATERIAL AND METHODS LncRNA expression microarray analysis was performed on 6 paired EGC tissues. One deregulated LncRNA, LOC389332, was validated using a quantitative reverse-transcription polymerase chain reaction (qRT-PCR) assay using independent tissue samples and cell lines. The Cell Counting Kit-8 (CCK-8) assay and wound healing assay were conducted to evaluate its influences on the proliferation and migration of gastric cancer cells. LncRNA expression microarray and gene ontology (GO) analysis were also performed on the LOC389332 knockdown cell line model to explore the molecular feature of LOC389332 in gastric carcinoma. RESULTS The LncRNA expression profiling showed that 72 LncRNAs were significantly differentially expressed in EGC tissues. The results in the validation phase revealed that LOC389332 was remarkably overexpressed in gastric carcinoma tissues, precancerous lesions, and gastric cancer cells. Functional study showed that knockdown of LOC389332 expression could inhibit cell proliferation and migration. LncRNA expression microarray on the LOC389332 knockdown cell line model revealed that 393 mRNAs were differentially expressed. The GO enrichment analysis indicated that the downregulated genes were mainly associated with cell membrane function, signal transmission process, and cell adhesion process. CONCLUSIONS The LncRNA expression profile between EGC and gastritis tissues was significantly different. LOC389332 was potential non-coding oncogenes in gastric cancer, and it may perform its function through altering cell membrane function, signal transmission, and cell adhesion.

Model to identify early-stage gastric cancers with deep invasion of submucosa based on endoscopy and endoscopic ultrasonography findings.

BACKGROUND: Conventional endoscopy and endoscopic ultrasonography (EUS) are used to estimate the invasion depth of early-stage gastric cancers (EGCs), but estimates made by either technique are often inaccurate. We developed a model to determine the invasion depth of EGCs using conventional endoscopy and EUS findings, with pathology results as the reference. METHODS: We performed a retrospective study of 195 patients (205 lesions) diagnosed with gastric cancers who underwent endoscopy and EUS followed by resection. Based on pathology analyses, lesions (n = 205) were assigned to categories of: mucosa invasion or minute invasion into the submucosal layer less than 500 µm from the muscularis mucosae (M-SM1) or penetration of 500 µm or more (≥SM2). The lesions were randomly assigned to derivation (138 lesions) and validation sets (67 lesions). A depth predictive model was proposed in the derivation set using multivariate logistic regression analyses. The discriminative power of this model was assessed in both sets. RESULTS: Remarkable redness (OR 5.42; 95% CI 1.32-22.29), abrupt cutting of converging folds (OR 8.58; 95% CI 1.65-44.72), lesions location in the upper third of the stomach (OR 10.26; 95% CI 2.19-48.09), and deep invasion based on EUS findings (OR 16.53; 95% CI 4.48-61.15) significantly associated with ≥SM2 invasion. A model that incorporated these 4 variables discriminated between M-SM1 and ≥SM2 lesions with the area under the ROC curve of 0.865 in the derivation set and 0.797 in the validation set. In the derivation set, a cut-off score of 8 identified lesions as ≥SM2 with 54% sensitivity and 97% specificity. The model correctly predicted the invasion depth 89.86% of lesions; it overestimated the depth of 2.17% of lesions. CONCLUSIONS: We developed a model to identify EGCs with invasion depth ≥SM2 based on endoscopy and EUS findings. This model might reduce overestimation of gastric tumor depth and prevent unnecessary gastrectomy.

A novel signature for stratifying the molecular heterogeneity of the tissue-infiltrating T-cell receptor repertoire reflects gastric cancer prognosis.

Many basic properties of the T-cell receptor (TCR) repertoire require clarification, and the changes occurring in the TCR repertoire during carcinogenesis, especially during precancerous stages, remain unclear. This study used deep sequencing analyses to examine 41 gastric tissue samples at different pathological stages, including low-grade intraepithelial neoplasia, high-grade intraepithelial neoplasia, early gastric cancer and matched adjacent tissues, to define the characteristics of the infiltrating TCRß repertoire during gastric carcinogenesis. Moreover, to illustrate the relationship between the local molecular phenotype and TCR repertoire of the microenvironment, whole-genome gene expression microarray analysis of the corresponding gastric precancerous lesions and early gastric cancer tissues was conducted. Our results showed that the degree of variation in the TCR repertoire gradually increased during tumourigenesis. Integrative analysis of microarray data and the TCR repertoire variation index using the network-based Clique Percolation Method identified an 11-gene module related to the inflammatory response that can predict the overall survival of gastric cancer (GC) patients. In conclusion, our results revealed the multistage heterogeneity of tissue-infiltrating TCR repertoire during carcinogenesis. We report a novel way for identifying prognostic biomarkers for GC patients and improves our understanding of immune responses during gastric carcinogenesis.

Validation of Ten Noninvasive Diagnostic Models for Prediction of Liver Fibrosis in Patients with Chronic Hepatitis B.

BACKGROUND AND AIMS: Noninvasive models have been developed for fibrosis assessment in patients with chronic hepatitis B. However, the sensitivity, specificity and diagnostic accuracy in evaluating liver fibrosis of these methods have not been validated and compared in the same group of patients. The aim of this study was to verify the diagnostic performance and reproducibility of ten reported noninvasive models in a large cohort of Asian CHB patients. METHODS: The diagnostic performance of ten noninvasive models (HALF index, FibroScan, S index, Zeng model, Youyi model, Hui model, APAG, APRI, FIB-4 and FibroTest) was assessed against the liver histology by ROC curve analysis in CHB patients. The reproducibility of the ten models were evaluated by recalculating the diagnostic values at the given cut-off values defined by the original studies. RESULTS: Six models (HALF index, FibroScan, Zeng model, Youyi model, S index and FibroTest) had AUROCs higher than 0.70 in predicting any fibrosis stage and 2 of them had best diagnostic performance with AUROCs to predict F≥2, F≥3 and F4 being 0.83, 0.89 and 0.89 for HALF index, 0.82, 0.87 and 0.87 for FibroScan, respectively. Four models (HALF index, FibroScan, Zeng model and Youyi model) showed good diagnostic values at given cut-offs. CONCLUSIONS: HALF index, FibroScan, Zeng model, Youyi model, S index and FibroTest show a good diagnostic performance and all of them, except S index and FibroTest, have good reproducibility for evaluating liver fibrosis in CHB patients. REGISTRATION NUMBER: ChiCTR-DCS-07000039.

[Adiponectin inhibits oxidative stress and modulates TGF-b1 and COL-1 expression via the AMPK pathway in HSC-T6 cells].

OBJECTIVE: To investigate the anti-oxidative stress and anti-fibrotic mechanisms of adiponectin by examining effects on oxidative stress levels and expression of fibrosis-related signaling factors, including transforming growth factor-beta 1 (TGFb1), collagen I (COL-1), and the adenosine monophosphate-activated protein kinase (AMPK) pathway by using an in vitro HSC-T6 cultured cell system. METHODS: Activated HSC-T6 cells were pre-treated with 1.0 mug/mL adiponectin for 0, 30, 60 and 120 min, or left untreated to serve as controls, and both groups were then exposed to 5 mumol/L H2O2; a portion of the adiponectin-treated oxidative stress-induced cells were treated with an AMPK inhibitor (Compound C). The effects on mRNA levels of TGFb1. and COL-1 were analyzed by real-time PCR, in the levels of secreted TGF-b1 and COL-1 were detected by enzyme-linked immunosorbent assay of supernatants, and in the phosphoAMPK and AMPK protein expressions were detected by Western blotting. RESULTS: Compared to the H2O2 group without adiponectin pre-treatment, the H2O2 group with adiponectin pre-treatment showed significantly increased activity of superoxide dismutase (SOD), decreased content of malondialdehyde (MDA), and decreased gene and protein expressions of TGF-b1 and COL-1 (P less than 0.05). Moreover, inhibition of the AMPK pathway inhibited these adiponectin-mediated effects. The H2O2 group with adiponectin pre-treatment also showed increased levels of phospho-AMPK protein expression, with the maximum effect detected after 120 min of the adiponectin pre-treatment (P less than 0.01). CONCLUSION: Inhibition of oxidative stress is one of the mechanisms of the anti-fibrotic effects of adiponectin. Adiponectin can attenuate oxidative stress levels, resulting in down-regulation of TGFb1 and COL-1 expression through activation of the AMPK pathway.