LINC01235-TWIST2 feedback loop facilitates epithelial-mesenchymal transition in gastric cancer by inhibiting THBS2.

Although the anomalous expression of long non-coding RNAs (lncRNAs) has been extensively investigated in numerous carcinomas including gastric cancer (GC), their function remains unclear. The aim of our study was to explore the role of LINC01235 in GC. We used real-time quantitative PCR (RT-qPCR) to measure the expression of LINC01235 and twist family bHLH transcription factor 2 (TWIST2) in GC tissues. Scratch and transwell assays were performed to evaluate cellular capacity for migration and invasion. Gene relationships were explored by Weighted Gene Co-Expression Network Analysis (WGCNA). We measured TWIST2, thrombospondin 2 (THBS2) and epithelial-mesenchymal transition (EMT)-related proteins with western blot. We also used Pearson correlation analysis and the Kaplan-Meier method to detect associations among genes and overall survival. We found that LINC01235 was upregulated in GC tissues and cells. LINC01235 down-regulation restricted migration and invasion. Interestingly, we found the LINC01235-TWIST2-THBS2 axis induced EMT. Additionally, TWIST2 upregulated LINC01235 transcription in luciferase and chromatin immunoprecipitation (ChIP) assays. Bioinformatics analysis showed that microRNA (miR)-6852-5p might be a key gene involved in the regulation of TWIST2 by LINC01235. The LINC01235-TWIST2 positive feedback loop mainly affected migration and invasion of GC cells, which suggests it may serve as a potential therapeutic target in gastric cancer.

A research of STEAP1 regulated gastric cancer cell proliferation, migration and invasion in vitro and in vivos.

Six-Transmembrane Epithelial Antigene of the Prostate 1 (STEAP1) is associated with the occurrence and development of cancer. This study aimed to clarify the role of STEAP1 in gastric cancer tumour growth and metastasis, as well as its molecular mechanism of action.Statistical methods were used for clinical data analysis. Protein expression was detected using immunohistochemistry(IHC). The mRNA and protein expression in the cell cultures were detected using reverse transcription-polymerase chain reaction(RT-PCR) and western blot analysis. Overexpression and silencing models were constructed using plasmid and lentivirus transfection. To detect cell proliferation in vitro, Cell Counting Kit-8(CCK-8), flow cytometry and colony formation assays were used; transwell and wound healing assays were used to detect cell migration and invasion;For in vivo experiments, nude BALB/c mice were used for detecting subcutaneous tumorigenesis and intraperitoneal implantation. In the results,we found STEAP1 was overexpressed in gastric cancer tissues and cell lines. Single-factor and Cox analyses showed that STEAP1 gene expression level correlated with poor prognosis. Up-regulation of STEAP1 increased cell proliferation, migration and invasion, which decreased after STEAP1 was knocked down. These changes were achieved via the activation of the AKT/FoxO1 pathway and epithelial-mesenchymal transformation (EMT). The in vivo animal experiments showed that STEAP1 knock down, resulted in a decrease in the subcutaneous tumour and peritoneal tumour formation.

A Proposal of a Personalized Surveillance Strategy for Gastric Cancer: A Retrospective Analysis of 9191 Patients.

BACKGROUND: In gastric cancer, various surveillance strategies are suggested in international guidelines. The current study is intended to evaluate the current strategies and provide more personalized proposals for personalized cancer medicine. MATERIALS AND METHODS: In the aggregate, 9191 patients with gastric cancer after gastrectomy from 1998 to 2009 were selected from the Surveillance, Epidemiology, and End Results database. Disease-specific survival was analyzed by Kaplan-Meier method and the log-rank test. Cox proportional hazards regression analyses were used to confirm the independent prognostic factors. As well, hazard ratio (HR) curves were used to compare the risk of death over time. Conditional survival (CS) was applied to dynamically assess the prognosis after each follow-up. RESULTS: Comparisons from HR curves on different stages showed that earlier stages had distinctly lower HR than advanced stages. The curve of stage IIA was flat and more likely the same as that of stage I while that of stage IIB is like that of stage III with an obvious peak. After estimating CS at intervals of three months, six months, and 12 months in different periods, stages I and IIA had high levels of CS all along, while there were visible differences among CS levels of stages IIB and III. CONCLUSIONS: The frequency of follow-up for early stages, like stages I and IIA, could be every six months or longer in the first three years and annually thereafter. And those with unfavorable conditions, such as stages IIB and III, could be followed up much more frequently and sufficiently than usual.

Source Localization in Acoustic Sensor Networks via Constrained Least-Squares Optimization Using AOA and GROA Measurements.

A constrained least-squares (CLS) 3D source localization method is presented for acoustic sensor networks with sensor position errors. The proposed approach uses angles of arrivals (AOAs) and gain ratios of arrival (GROAs) measured simultaneously at each node to estimate the source position jointly. Compared to AOA-only localization methods, the GROAs can be used in conjunction with AOA measurements so as to get more accurate results by exploiting the geometrical relationship between these two measurements. Compared to time difference of arrival localization methods, the proposed algorithm does not require accurate time synchronization over different nodes. The theoretical mean-square error matrices of the proposed approach are derived and they are exactly equal to the Cramér-Rao bound for Gaussian noise under the small error condition. Simulations validate the performance of the proposed estimator.