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Objectives: The expression/activation of IL-6, p-Stat3, PD-1 and PD-L1 in gastric cancer (GC) tissues were examined to evaluate their abilities in predicting the survival prognosis in postoperative patients with GC. Methods: The clinicopathological data and paraffin-embedded tissues of 205 patients who underwent gastric cancer resection were collected at the First Affiliated Hospital of Shihezi University School of Medicine, and the patients were followed-up annually after surgery. Immunohistochemistry (IHC) was used to detect the expression of IL-6, p-Stat3, PD-1 and PD-L1 proteins using tissue microarrays derived from these patients. Statistical analyses were performed using non-parametric tests, Spearman's correlation, ROC curves, Kaplan-Meier survival analysis, Cox single-factor and multifactor regression models. In comparison, the analyses were also performed for GC patients from public databases (407 patients from TCGA and 433 patients from GEO, respectively). Results: (1) The expression levels of IL-6, p-Stat3, PD-1 and PD-L1 in GC tissues were significantly higher than adjacent normal tissues (ANT) (81.01% vs. 52.78%, P<0.001; 100% vs. 93.41%, P<0.001; 58.58% vs. 40.12%, P<0.001; 38.20% vs. 26.90%, P = 0.025, respectively). The mean optical density (MOD) values of IL-6, p-Stat3, PD-1 and PD-L1 were significantly higher in GC tissues. (2) The higher the levels of IL-6 (P<0.001), p-Stat3 (P<0.001), and PD-L1 (P = 0.003) were, the worse the survival prognoses were observed, respectively, among GC patients. The expression of PD-1 was not correlated with the prognosis of GC patients (P>0.05). The lower the degree of cell differentiation (P<0.001) was, the worse the survival prognoses were observed among GC patients. (3) Independent risk factors for postoperative prognosis in GC patients included age (≥60 years old), poor cell differentiation, invasion depth (T3/T4), lymph node metastasis (N1-3), distant metastasis (M1), and high levels of IL-6 (2+/3+). (4) A multi-factor combination (cell differentiation+IL-6+p-Stat3+PD-1+PD-L1) appeared to be the best survival predictor for GC patients as indicated by AUC (AUC 0.782, 95% CI = 0.709, 0.856, P<0.001). This combination may be the optimal predictor for postoperative survival of GC patients. (5) The levels of IL-6, p-Stat3, PD-1 and PD-L1 correlated with the infiltration levels of various tumor-infiltrating immune cells. (6) The analyses of ROC curves, calibration, DCA and Kaplan-Meier (KM) survival curves in TCGA dataset confirmed that the nomogram model could accurately predict the prognosis in GC patients. Conclusions: (1) The expressed levels of IL-6, p-Stat3, PD-1 and PD-L1 are higher in GC tissues than in adjacent normal tissues. (2) The high levels of IL-6, p-Stat3 and PD-L1 are correlated with poor survival in GC patients. (3) The high levels of IL-6, p-Stat3, PD-1 and PD-L1 have influences in GC tumor microenvironment. (4) The multi-predictor combination of "IL-6+p-Stat3+PD-1+cell differentiation" serves as an optimal survival predictor for postoperative GC patients and better than the TNM staging system. As these molecules can be examined in preoperative biopsies, these observations may provide a useful guide for clinicians to strategize individualized surgical plans for GC patients before surgery. [ABSTRACT FROM AUTHOR]

Purpose: We conducted a bidirectional two-sample Mendelian randomization (MR) study to determine whether genetically predicted basal metabolic rate (BMR) was a causal risk factor for colorectal cancer (CRC) or whether a genetically predicted CRC risk can influence the BMR level (i.e., reverse causation). Methods: We employed 1,040 genetic variants as proxies for BMR to obtain effect estimates on CRC risk. Another 58 CRC-associated variants were used to estimate effects on BMR levels. Stratified analysis by tumor site was used to examine the causal associations between BMR and colon/rectal cancer risk. Results: The inverse variance weighted (IVW) method indicated a significant causal effect of genetically determined BMR on CRC risk (ORSD = 1.27, 95% CI = 1.07–1.51). No significant reverse causal association was identified between genetically increased CRC risk and BMR levels [IVW (β = 0, 95% CI = -0.01 to 0)]. The results of MR-Egger and the weighted median method were consistent with the IVW method. Stratified analysis by CRC sites identified significant causal associations between BMR and colon cancer [IVW (ORSD = 1.45, 95% CI = 1.16-1-80)], and null evidence of a causal association between BMR and rectal cancer risk was found (p > 0.05). Conclusion: Our findings add to the current literature by validating a positive relationship between high BMR levels and CRC risk instead of reverse causality. The genetically predicted BMR level was causally associated with colon cancer risk but not rectal cancer risk. [ABSTRACT FROM AUTHOR]

Objectives: H. pylori (Hp) infection has been indicated in the pathogenesis of gastric diseases including gastric cancer (GC). This study aimed at exploring the relationships between Hp infection and gastric diseases including GC in a large dataset of routine patients undergoing gastroscopy. Methods: From November 2007 to December 2017, 70,534 first-time visiting patients aged 18–94 years with gastroscopic biopsies were histologically diagnosed and analyzed. Patients' data were entered twice in an Excel spreadsheet database and analyzed using the SPSS (version 22.0) software package and statistical significance was defined as P<0.05 for all analyses. Results: The first interesting observation was age-related twin-peak prevalence profiles (TPPs) for Hp infection, gastritis, and advanced diseases with different time spans (TS) between the first and second occurring peaks. Hp infection and gastritis had TPPs occurring at earlier ages than TPPs of gastric introepithelial neoplasia (GIN) and GC. More patients were clustered at the second occurring TPPs. The time spans (TS) from the first occurring peak of Hp infection to the first occurring peaks of other gastric diseases varied dramatically with 0–5 years for gastritis; 5–15 years for GINs, and 5–20 years for GC, respectively. The number of males with Hp infection and gastric diseases, excluding non-atrophic gastritis (NAG), was more than that of females (P<0.001). Conclusions: We have first observed age-related twin-peak prevalence profiles for Hp infection, gastritis, GIN, and GC, respectively, among a large population of patients undergoing gastroscopy. The second prevalence peak of GC is at ages of 70–74 years indicating that many GC patients would be missed during screening because the cut-off age for screening is 69 years old in China. [ABSTRACT FROM AUTHOR]

Recently, studies on competing endogenous RNA (ceRNA) networks have become prevalent, and circular RNAs (circRNAs) have crucial implications for the development and progression of carcinoma. However, studies relevant to metastatic prostate cancer (mPCa) are scant. This study aims to discover potential ceRNAs that may be related to the prognosis of mPCa. RNA-Seq data were obtained from the MiOncoCirc database and Gene Expression Omnibus (GEO). Differential expression patterns of RNAs were examined using R packages. Circular RNA Interactome, miRTarBase, miRDB and TargetScan were applied to predict the corresponding relation between circRNAs, miRNAs and mRNAs. The Gene Ontology (GO) annotations were performed to present related GO terms, and Gene Set Enrichment Analysis (GSEA) tools were applied for pathway annotations. Moreover, survival analysis was conducted for the hub genes. We found 820 circRNAs, 81 miRNAs and 179 mRNAs that were distinguishingly expressed between primary prostate cancer (PCa) and mPCa samples. A ceRNA network including 45 circRNAs, 24 miRNAs and 56 mRNAs was constructed. In addition, the protein–protein interaction (PPI) network was built, and 10 hub genes were selected by using the CytoHubba application. Among the 10 hub genes, survival analysis showed that ITGA1, LMOD1, MYH11, MYLK, SORBS1 and TGFBR3 were significantly connected with disease-free survival (DFS). The circRNA-mediated ceRNA network provides potential prognostic biomarkers for metastatic prostate cancer. [ABSTRACT FROM AUTHOR]