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Gastric adenocarcinoma (GAC) and colon adenocarcinoma (CAC) are the most common gastrointestinal cancer subtypes, with a high incidence and mortality. Numerous studies have shown that its occurrence and progression are significantly related to abnormal DNA methylation, especially CpG island methylation. However, little is known about the application of DNA methylation in GAC and CAC. The methylation profiles were accessed from the Cancer Genome Atlas database to identify promoter methylation-based cancer subtypes and signatures for GAC and CAC. Six hypo-methylated clusters for GAC and six hyper-methylated clusters for CAC were separately generated with different OS profiles, tumor progression became worse as the methylation level decreased in GAC or increased in CAC, and hypomethylation in GAC and hypermethylation in CAC were negatively correlated with microsatellite instability. Additionally, the hypo- and hyper-methylated site-based signatures with high accuracy, high efficiency and strong independence can separately predict the OS of GAC and CAC patients. By integrating the methylation-based signatures with prognosis-related clinicopathologic characteristics, two clinicopathologic-epigenetic nomograms were cautiously established with strong predictive performance and high accuracy. Our research indicates that methylation mechanisms differ between GAC and CAC, and provides novel clinical biomarkers for the diagnosis and treatment of GAC and CAC.

To facilitate the temporary importation of horses for competition and racing purposes, with a minimum risk of transmitting equine influenza, the World Organisation for Animal Health (Office International des Epizooties, or OIE), formally engaged in a public–private partnership with the Federation Equestre Internationale (FEI) and the International Federation for Horseracing Authorities (IFHA) to establish, within the context of existing OIE standards, a science-based rationale to identify the ideal time period for equine influenza vaccination prior to shipment. Field trials using vaccines based on different technologies were carried out on three continents. The antibody response post-booster vaccination at intervals aligned with the different rules/recommendations of the OIE, FEI, and IFHA, was monitored by single radial haemolysis. It was determined that 14 days was the optimum period necessary to allow horses adequate time to respond to booster vaccination and for horses that have previously received four or more doses of vaccine and are older than four years, it is adequate to allow vaccination within 180 days of shipment. In contrast, the results indicate that there is a potential benefit to younger (four years old or younger) horses in requiring booster vaccination within 90 days of shipment, consistent with the current OIE standard.

Background. Resveratrol (RSV), one of the SIRT1 agonists, has the ability of alleviating severe acute pancreatitis (SAP); however, the concrete protective mechanism remains unknown. It is noteworthy that microcirculation disturbance plays a vital role in SAP, and the SIRT1/FOX1 axis can regulate microcirculation. Therefore, this study is aimed at ascertaining what is the underlying mechanism of the protective effect of RSV on SAP, and whether it is associated with alleviating microcirculation disturbance by regulating the SIRT1/FOX1 axis. Method. The model of SAP was induced by retrograde injection of sodium taurodeoxycholate into the bile duct of the rats. The pancreatic wet/dry weight, ET/NO, and TXB2/6-keto-PGF1α ratios; microcirculatory function; and SIRT1 activity were examined. ELISA was used to examine the serum level of lipase, amylase, hemorheology, ET, NO, TXB2, and 6-keto-PGF1α and the content of SIRT1, VEGF, Ang I, and Ang II in the pancreas. RT-PCR was used to examine the mRNA level of VEGF, Ang I, and Ang II. Western blotting was used to detect SIRT1, FOXO1, and acetyl-FOXO1. Immunoprecipitation was used to examine the interaction of SIRT1 and FOXO1. Results. Resveratrol can significantly decrease the expression of lipase, amylase, acetyl-FOXO1, VEGF, Ang II, ET, NO, TXB2, and 6-keto-PGF1α and the ratio of wet/dry weight, ET/NO, and TXB2/6-keto-PGF1α by improving microcirculatory dysfunction and blood viscosity in SAP. Moreover, resveratrol can also promote the interaction of SIRT1 and FOXO1 and increase SIRT1 activity and the expression of SIRT1 and Ang I. The SIRT1 inhibitor, Sirtinol (EX527), obliviously reversed the effects of RSV on SAP. Conclusion. Resveratrol can protect rats against SAP, and its protective mechanism is associated with suppressing microcirculation disturbance through activating SIRT1-FOXO1 axis.

No abstract

Background Although numerous studies demonstrate the role of cancer stem cells in occurrence, recurrence, and distant metastases in gastric cancer (GC), little is known about the evolving genetic and epigenetic changes in the stem and progenitor cells. The purpose of this study was to identify the stem cell subtypes in GC and examine their clinical relevance. Methods Two publicly available datasets were used to identify GC stem cell subtypes, and consensus clustering was performed by unsupervised machine learning methods. The cancer stem cell (CSC) typing-related risk scoring (RS) model was established through multivariate Cox regression analysis. Results Cross-platform dataset-based two stable GC stem cell subtypes, namely low stem cell enrichment (SCE_L) and high stem cell enrichment (SCE_H), were prudently identified. Gene set enrichment analysis revealed that the classical oncogenic pathways, immune-related pathways, and regulation of stem cell division were active in SCE_H; ferroptosis, NK cell activation, and post-mutation repair pathways were active in SCE_L. GC stem cell subtypes could accurately predict clinical outcomes in patients, tumor microenvironment cell-infiltration characteristics, somatic mutation landscape, and potential responses to immunotherapy, targeted therapy, and chemotherapy. Additionally, a CSC typing-related RS model was established; it was strongly independent and could accurately predict the patient’s overall survival. Conclusions This study demonstrated the complex oncogenic mechanisms underlying GC. The findings provide a basis and reference for the diagnosis and treatment of GC.

Background: The potential role of pyroptosis in tumor microenvironment (TME) reprogramming and immunotherapy has received increasing attention. As most studies have concentrated on a single TME cell type or a single pyroptosis regulator (PR), the overall TME cell-infiltrating characteristics mediated by the integrated roles of multiple PRs have not been comprehensively recognized. Methods: This study curated 33 PRs and conducted consensus clustering to identify distinct pyroptosis patterns in gastric cancer (GC) patients. A single-sample gene set enrichment analysis algorithm was used to quantify the infiltration density of TME immune cells and the enrichment scores of well-defined biological signatures. The pyroptosis patterns of individuals were quantified using a principal component analysis algorithm called the pyroptosis score (PS). Results: Three distinct pyroptosis patterns with significant survival differences were identified from 1422 GC samples; these patterns were closely associated with three TME cell-infiltrating landscapes—namely, the immune-inflamed, immune-excluded, and immune-desert phenotypes. The PS model generated on the basis of the pyroptosis pattern-related signature genes could accurately predict the TME status, existing molecular subtypes, genetic variation, therapeutic response, and clinical outcome; among which, a relatively high PS was highly consistent with immune activation, molecular subtypes with survival advantages, high tumor mutation burden, high microsatellite instability, and other favorable characteristics. In particular, from the Cancer Genome Atlas database, the PS model exhibited significant prognostic relevance in a pan-cancer analysis, and patients with a relatively high PS exhibited durable therapeutic advantages and better prognostic benefits in anti-PD1/L1 therapy. Conclusions: This study demonstrates that pyroptosis is prominently correlated with TME diversity and complexity, and quantification of the pyroptosis patterns of individuals will enhance our cognition of TME infiltration landscapes and help in formulating more effective immunotherapeutic strategies.

Background: The construction of ferroptosis-related lncRNA prognostic models in malignancies has been an intense area of research recently. However, most of the studies focused on the exact expression of lncRNAs and had limited application values. Herein, we aim to establish a novel prognostic model for gastric cancer (GC) patients and discuss its correlation with immune landscapes and treatment responses.Methods: The present study retrieved transcriptional data of GC patients from the Cancer Genome Atlas (TCGA) database. We identified differentially expressed ferroptosis-related lncRNAs between tumor and normal controls of GC samples. Based on a new method of cyclically single pairing, we constructed a 0 or 1 matrix of ferroptosis-related lncRNA pairs (FRLPs). A risk score signature consisting of 10 FRLPs was established using multi-step Cox regression analysis. Next, we performed a series of systematic analyses to investigate the association of the FRLP model and tumor microenvironment, biological function, and treatment responses. An alternative model to the FRLP risk score signature, the gene set score (GS) model was also constructed, which could represent the former when lncRNA expression was not available.Results: We established a novel prognostic signature of 10 ferroptosis-related lncRNA pairs. High-risk patients in our risk score model were characterized by high infiltration of immune cells, upregulated carcinogenic and stromal activities, and heightened sensitivity to a wide range of anti-tumor drugs, whereas low-risk patients were associated with better responses to methotrexate treatment and elevated immunotherapeutic sensitivity. The practicability of the FRLP risk score model was also validated in two independent microarray datasets downloaded from Gene Expression Omnibus (GEO) using the GS model. Finally, two online dynamic nomograms were built to enhance the clinical utility of the study.Conclusion: In this study, we developed a ferroptosis-related lncRNA pair-based risk score model that did not rely on the exact lncRNA expression level. This novel model might provide insights for the accurate prediction and comprehensive management for GC patients.