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Gastric cancer (GC) is a common malignant solid tumor that is characterized by high hypoxia. The transcription of genes associated with hypoxia affects tumor occurrence and development. Long non-coding RNAs (lncRNAs) have been reported to play important roles in cancer development. In this study, we screened for differentially expressed ncRNAs (non-coding RNA) and mRNAs between hypoxia-inducible factor-1 (HIF-1α) knockdown GC cells and scrambled GC cells. Microarray data revealed that HIF-1α regulated the expression of LINC01355 (Hypoxia Yield Proliferation Associated LncRNA, HYPAL). HYPAL was found to be significantly upregulated in GC cells and tissues and was correlated with poor GC prognosis. Chromatin immunoprecipitation (ChIP) and luciferase reporter assays revealed that HIF-1α promoted HYPAL expression by binding the promoter region. A regulatory network for the competing endogenous RNA (ceRNA) was constructed using bioinformatics tools. Mechanistic studies revealed that HYPAL acted as a ceRNA of miR-431-5p to regulate CDK14 expression. Carcinogenic effects of HYPAL were evaluated in vitro and in vivo. The HIF-1α/HYPAL/miR-431-5p/CDK14 (Cyclin-dependent kinase 14) axis activated the Wnt/β-catenin signaling pathway and induced GC cell proliferation while inhibiting apoptosis. In conclusion, HYPAL is a potential molecular target for GC therapy.

Background: Electrolyte disturbance and systemic inflammation contributes to poor prognosis of cancer patients. Levels of serum sodium and globulin can reflect electrolyte homeostasis and inflammatory state, respectively, therefore have potential as prognostic factors for cancer patients. In this study, we hypothesized that sodium to globulin ratio (SGR) could have superior accuracy in predicting cancer patient survival, than sodium and globulin alone. We therefore sought to investigate its efficacy in prognosis of patients with advanced gastric cancer (GC) receiving first-line chemotherapy. Methods: A total of 265 patients, with advanced GC, were recruited in this retrospective study from January 2014 to January 2019. We first determined SGR cut-off values using the receiver operating characteristic (ROC) analysis, then analyzed the relationship between pretreatment SGR and clinicopathological features and the effect of chemotherapy. Finally, we evaluated progression-free survival (PFS) and overall survival (OS) rates of the entire and subgroup populations using univariate and multivariate logistic regressions. Results: SGR recorded a cut-off value of 5.54, and had a significantly higher area under the curve (AUC) value (0.619, p = 0.001) than fibrinogen (0.575, p = 0.034) and albumin (0.610, p = 0.002) alone. Organ metastasis, and peritoneal invasion ratios, as well as neutrophil and CA72-4 levels varied significantly between the low-SGR (SGR≤ 5.54) and high SGR (SGR> 5.54) groups (all p < 0.05). Specifically, patients in the low-SGR group exhibited significantly lower disease control rates (83.4%) than those in the high-SGR group (97.2%) (p < 0.001). Results from multivariate analysis indicated that high-SGR was an independent risk factor for PFS (Hazard ratio [HR]: 0.539, p < 0.001) and OS (HR: 0.574, p < 0.001). Moreover, patients in the low-SGR group exhibited significantly worse PFS (134 vs. 221 days, p < 0.001) and OS (311 vs. 420 days, p < 0.001) than those in the high-SGR group. Furthermore, subgroup analysis revealed that SGR was still a powerful prognostic indicator in GC patients with good prognosis or normal biochemical indexes, including no peritoneal infiltration, normal neutrophil counts, and normal serum sodium and globulin levels (all p < 0.001). Conclusions: Overall, our findings indicate that SGR is a novel and promising prognostic factor for GC patients. It has superior accuracy, to sodium and globulin alone, hence it is a powerful tool for evaluating effects of treatment, PFS, and OS in patients with advanced GC, who receive first-line chemotherapy.

This paper proposes a simple and efficient technique to improve the antenna radiation performance in stacked printed circuit boards (PCBs) for Internet-of-Things (IoT) applications. In the ...

A compact dual-band loop-type antenna is proposed in a small-sized ground plane for Internet-of-Things (IoT) applications. The antenna element is comprised of two adjacent resonance loops, excited by two feeding loops at the back side of the substrate, to achieve independent control of dual-band IoT applications at 0.92 and 2.45 GHz, respectively. To improve the radiation performance of the lower band, the metal frames are adopted as ground-mode tuning structures to generate a new ground-mode resonance, producing dual-resonance characteristics at 0.9 GHz bands and generating greatly improved bandwidth and radiation efficiency. Therefore, both lower and higher bands with high performances are achieved in simulation and verified in measurement.

This study focuses on the generation of circular polarization (CP) in a small-sized ground plane by using ground-mode tuning (GMT) technique. The proposed antenna is composed of two branches, so th...

Background Gastric cancer (GC) is one of the most frequently diagnosed gastrointestinal cancers throughout the world. Novel prognostic biomarkers are required to predict the prognosis of GC. Aim To identify a multi-long noncoding RNA (lncRNA) prognostic model for GC. Methods Transcriptome data and clinical data were downloaded from The Cancer Genome Atlas. COX and least absolute shrinkage and selection operator regression analyses were performed to screen for prognosis associated lncRNAs. Receiver operating characteristic curve and Kaplan-Meier survival analyses were applied to evaluate the effectiveness of the model. Results The prediction model was established based on the expression of AC007991.4, AC079385.3, and AL109615.2 Based on the model, GC patients were divided into "high risk" and "low risk" groups to compare the differences in survival. The model was re-evaluated with the clinical data of our center. Conclusion The 3-lncRNA combination model is an independent prognostic factor for GC.

Clinically, hypoxia is associated with increased distant metastasis and poor survival in gastric cancer (GC). In this study, we set out from the cellular interaction to further explain the molecular mechanism of invasion in GC cells under hypoxic conditions. Gastric cancer cells were cultured under 1% O2 (hypoxia-cultured gastric cancer cells, HGC) and 20% O2 condition (normoxic-cultured gastric cancer cells, NGC). NGC was co-cultured with HGC-medium. Scrape and Transwell were used to evaluate invasion and migration. Exosomes from GC were extracted by ultracentrifugation. Electron microscopy images, western-blot used to analyze the size distributions and the number of exosomes. HGC-medium induced NGC dissociated. Long non-coding RNA (lncRNA) prostate cancer gene expression marker 1 (PCGEM1) was specifically expressed in HGC exosomes. HGC-derived PCGEM1-riched exosomes could promote the invasion and migration of NGC. On the mechanism, PCGEM1 maintained stability and reduced the degradation of SNAI1, which could induce the epithelial–mesenchymal transition of GC. LncRNA PCGEM1 was overexpressed in GC cells. And part of the PCGEM1 can be encapsulated into exosomes. These exosomes promoted invasion and migration of other GC cells. We considered PCGEM1 might act as a "scaffold" combined with SNAI1 and prompt the invasion and migration of GC.

The fibrinogen-to-albumin ratio (FAR), reflecting the systemic coagulation, nutritional and inflammation status of patients, has matured into a prognostic marker for several tumor types. However, only a few studies have assessed the utility of the FAR as a prognostic indicator in patients with advanced gastric cancer (GC) receiving first-line chemotherapy. In the present study, 273 patients with advanced GC who received first-line chemotherapy between January 2014 and January 2019 at the Cancer Hospital of China Medical University (Shenyang, China) were retrospectively analyzed. Using the cut-off values determined by receiver operating characteristic (ROC) analysis, the patients were divided into low-FAR (≤10.03) and high-FAR (>10.03), low-fibrinogen (

Gastric cancer (GC) is the fifth most common cancer and the third leading cause of cancer-related mortality worldwide. Inflammation and the nutritional status of patients with GC are important factors affecting the therapeutic effect and prognosis. Inflammatory and nutrition-related markers have been shown to be prognostic factors for patients with GC. However, few studies have investigated the relationship of the prealbumin-to-globulin ratio (PGR) with the prognosis of GC patients. The objective of the present study was to examine whether pretreatment PGR is related to the prognosis and chemotherapy outcomes of in-patients with advanced GC undergoing first-line chemotherapy. We retrospectively reviewed the data of 281 patients with unresectable GC from January 2013 to January 2018. The receiver operating characteristic curve analysis determined the cut-off values for the PGR. The relationship between the PGR and chemotherapy effectiveness was evaluated using the chi-square test. Kaplan-Meier’s method was used to plot progression-free survival (PFS) and overall survival (OS) curves, using multivariable Cox regression analysis to identify promising predictors of mortality. The cut-off value for the PGR was 7.21. The high-PGR (≥7.21) group had a higher disease control rate than that of the low-PGR group (93.66% vs. 78.42%, p<0.001). Kaplan-Meier’s analysis showed significantly higher median PFS (189 vs. 125 days, p<0.001) and OS (350 vs. 288 days, p<0.001) in the high-PGR group. The multivariate analyses revealed that a high PGR is an independent protective factor in patients with advanced GC, both in terms of PFS (hazard ratio [HR]: 0.672; 95% confidence interval [CI]: 0.527–0.857; p<0.001) and OS (HR: 0.675; 95% CI: 0.530–0.861; p=0.002). In conclusion, the prechemotherapy PGR can accurately predict the chemotherapy outcome, PFS, and OS of patients with advanced GC. Therefore, medical practitioners can utilize the PGR as a novel dependable prognostic tool to weigh the prognosis of patients with GC.

Gastric cancer (GC) is the most common and aggressive cancer of the digestive system and poses a serious threat to human health. Since genes do not work alone, our aim was to elucidate the potential network of mRNAs and noncoding RNAs (ncRNAs) in this study. Transcriptome data of GC were obtained from TCGA. R and Perl were used to obtain the differentially expressed RNAs and construct a competing endogenous RNA (ceRNA) regulatory network. To investigate the biological functions of differentially expressed RNAs, loss-of-function and gain-of-function experiments were performed. Real-time PCR (RT-qPCR), western blot analysis, dual-luciferase reporter assays and fluorescence in situ hybridization were conducted to explore the underlying mechanisms of competitive endogenous RNAs (ceRNAs). Based on TCGA data and bioinformatics analysis, we identified the LINC00163/miR-183/A-Kinase Anchoring Protein 12 (AKAP12) axis. We observed that AKAP12 was weakly expressed in GC and suppressed invasion and metastasis in GC cells, which could be abolished by miR-183. In addition, LINC00163 can be used as a ceRNA to inhibit the expression of miR-183, thus enhancing the anticancer effect of AKAP12. Our results demonstrated that weak LINC00163 expression in GC can sponge miR-183 to promote AKAP12. We established that the LINC00163/miR-183/AKAP12 axis plays an important role in GC invasion and metastasis and may be a potential biomarker and target for GC treatment.

Objectives The purpose of this study was to explore whether pretreatment potential prognostic factors are related to chemotherapeutic outcomes and the prognosis of inpatients with metastatic colorectal cancer (mCRC) undergoing chemotherapy. Materials and methods Data from 71 patients with mCRC were analyzed retrospectively. The relationship between the potential prognostic factors before first‐line chemotherapy and the clinicopathological characteristics and chemotherapy response of the patients was calculated using Fisher's exact test and the chi‐square test. The prognostic factors were analyzed using univariate and multivariate analyses. We analyzed the subgroups using the Mann‐Whitney U test. Results Four factors were eventually used as prognostic factors, namely the albumin‐to‐globulin ratio (AGR), the fibrinogen‐to‐albumin ratio (FAR), the prealbumin‐to‐globulin ratio (PGR), and the fibrinogen‐to‐prealbumin ratio (FPR); the cutoff values of the four potential prognostic factors were 1.40, 10.63, 5.44, and 18.49, respectively. The high AGR and PGR groups had a higher response rate than that of the low groups. Patients in the low FAR and FPR groups showed a higher objective response rate than the high FAR and FPR groups. Patients with low FPR were associated with a higher disease control rate than patients with high FPR. Higher progression‐free survival (PFS) was observed in the high AGR and PGR and low FAR and FPR groups. The AGR, FAR, PGR, and FPR were considered reliable prognostic factors for PFS in a univariate analysis. Conclusions The prechemotherapy AGR, FAR, PGR, and FPR were good prognostic factors to predict the chemotherapy response and PFS in patients with mCRC.

Aim Previous studies have confirmed that overexpression of the long non-coding RNA prostate cancer gene expression marker 1 (PCGEM1) contributes to the invasion and metastasis of gastric cancer (GC) cells. However, the expression of circulating PCGEM1 in the plasma of GC patients and its clinical value remain unclear. Methods A total of 317 patients with GC and 100 healthy subjects were enrolled in this study. Circulating PCGEM1 was detected by reverse transcription-polymerase chain reaction. The diagnostic value of plasma PCGEM1 was evaluated by receiver operating characteristic curves and the area under the curve (AUC) value. Results The expression level of PCGEM1 in the GC group was significantly higher than that in the healthy control subjects. In addition, the PCGEM1 expression level was associated with tumor differentiation and TNM stage. The AUC value of PCGEM1 was higher than that of other conventional tumor markers (CEA, CA12-5, CA72-4, AFP, and CA19-9), although the combination of all markers showed the highest predictive value. Conclusion Plasma PCGEM1 may be a potential novel circulating biomarker for GC diagnosis and prognosis.

Ministry of Science, ICT and Future Planning, Grant/Award Number: This work was supported by a grant from the Nation; National Research Foundation of Korea, Grant/Award Number: 2015R1A2A1A15055109

e15022 Background: In the past decade, cell-based immunotherapy has been reported to improve the clinical outcomes by altering tumor immune responses, improving prognosis and overall survival rates in cancer patients.This retrospective study aimed to evaluate the efficacy of cytokine-induced killer (CIK) cell infusion as an adjuvant therapy in patients with colorectal cancer. Methods: A total of 370 patients with colorectal cancer admitted to Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Insititute from March 2013 to April 2015 were retrospectively analyzed.All patients were treated with surgery for primary lesions, and then adjuvant chemotherapy was determined according to the guidelines. Among these patients, 201 patients received CIK therapy (CIK group),while the other 169 patients who had similar demographic and clinical characteristics did not receive a CIK cell infusion therapy (non-CIK group). Then we followed up these patients. Data were analyzed by Kaplan-Meier. Results: Our results showed that the 1,3,5-year overall survival (OS) rate for the CIK group versus the non-CIK group was 98.46 versus 93.61%, 85.4 versus 71.61%, 79.39 versus 67.9%, respectively. The OS was significantly longer in CIK group than in non-CIK group (P = 0.009). Meanwell, the OS of stage II and III colorectal cancer was significant in CIK group than in non-CIK group (P = 0.02 and 0.02). But the OS was not significant in Stage I and IV colorectal cancer (P = 0.347 and 0.285). We analyzed the patients between chemotherapy plus CIK therapy group and chemotherapy only group. We find that the OS has significant difference in two groups (P < 0.001). Conclusions: CIK therapy can improve the efficacy of adjuvant therapy in patients with colorectal cancer. But multicenter, large-sample randomized controlled trials are still needed to confirm it.

An integrated GPS antenna with circular polarization (CP)is proposed for smartwatches with an unbroken metal rim. By utilizing a small feeding structure in the ground plane, two dominant characteristic modes of the metal rim along the x-axis and y-axis are simultaneously excited for radiation. For CP operation, the time-phase difference between the two modes can be provided by adjusting their resonant frequencies to be inductive and capacitive, which can be further tuned by changing the values of loaded capacitors between the metal rim and ground plane. The proposed technique can generate a 3-dB axial ratio bandwidth of 10 MHz with left-hand circular polarization (RHCP)and right-hand circular polarization (LHCP)at the front side and back side, respectively.

Two ground radiation antennas with polarisation diversity performance were proposed for MIMO WLAN applications in wearable devices. The antennas can simultaneously excite the vertical mode and horizontal mode of the ground plane and the phase difference between the two modes can be controlled by utilising an inductor-loaded metal strip in the ground plane, generating circular polarisation. A 3:1 VSWR bandwidth of 140 MHz with high isolation (above 17 dB) and a 3 dB axial ratio bandwidth of 100 MHz was obtained. The opposite rotations generated by the two antennas resulted in good diversity performance, which was verified by the measured envelope correlation coefficient.

17 Background: Abnormal gene expression is closely related to the development and poor prognosis of gastric cancer (GC). Since gene does not work alone, we are aimed to elucidate the potential networks between mRNA and non-coding RNAs (ncRNAs) in this study. Methods: Based on the TCGA database, we obtained the differentially expressed RNAs and constructed the competing endogenous RNA (ceRNA) regulatory network. Results: We found a regulatory network based on ANGPT2. We observed ANGPT2 is overexpressed in GC cells and tissues and associated with poor prognosis. ANGPT2 promotes proliferation, invasion, and EMT in GC cells, which could be abolished by miR-145. In addition, LINC00184 can be used as a ceRNA to inhibit the expression of miR-145, thus enhancing the carcinogenic effect of ANGPT2. Conclusions: Our results suggested that LINC00184/miR-145/ANGPT2 axis plays an important role in the occurrence and development of GC and may be potential biomarkers and targets for the treatment of GC.

Over the past years applications of fusion technique have been growing rapidly. However, very few applications of the technique to microarray data have been reported. In this paper, we propose a new fusion method based on pseudo standard deviation minimization (PSDM) for the feature selection of microarray. This new method provides a more accurate set of features. Therefore the classification can be performed and functional meaning from the features can also be revealed. The new method is actually obtained through a combination of two different feature selection methods (FSMs). It is shown that it can explore nonperfect correlation between gene expression profile and cancer classes or feature detection algorithms. To evaluate its effectiveness, it is tested on lymphoma and leukemia microarray expression datasets and then compared with the existing methods. Self-organizing map (SOM) is used for feature classification. It can be seen through the comparison that the classification accuracy of the new fusion method is at least 2% ~ 3% higher than others.

From DNA microarray experiments, we need to deal with large datasets in which instances are described by many features. In order to reduce high data dimensionality, feature selection method (FSMs) is usually applied in the flow of data analysis. In this paper, we propose a correlational Bayesian network for feature selection. The proposed algorithm is able to effectively identify and manipulate correlational individuals so that it improves performance and provides higher accurate results than other Bayesian network learning and FSMs. Through use of Bayesian framework to infer the weights, weight decay terms and perform model selection, we can obtain neural models with high generalization capability and low complexity. As a classifier Backpropagation network is used for classification of cancer types. The experiments are carried out for verification of the proposed method. A comparison study is also done with conventional Bayesian network approach and other FSMs. From comparison it can be seen that the correlational Bayesian network (CBN) proposed in thia paper is effective.