Risk Factor For Gastric Cancer Research Articles

Chemical burn wounds as a risk factor for gastric cancer: in-silico analyses-experimental research

Introduction: The present study employs bioinformatics tools to identify shared upregulated genes between chemical burns and gastric cancer. Methods: GEO retrieved gene sets for this investigation. GSEs with P-value <0.05 and LOG fold change (FC) >1 were valid and upregulated. Gastric cancer and chemical burn common elevated genes were found using Venn diagram online tools. In the second stage, the “string” visualized gastric cancer elevated genes network, and non-coding RNAs were deleted, and “interaction” >1 was examined to choose important gene nodes. Next, they explored the String gene-interaction network for common genes. To determine the most interacting genes, Gephi (V 0.9.7) used “betweenness centrality” > “0” to evaluate the twenty-gene network. TISIDB and drug banks provide gene-related medications. Results: In the present study, two genes, including ALOX5AP and SERPINB2, were obtained, with the highest centrality among chemical burns and gastric cancer shared genes. Additionally, the current study presented five drugs, including Urokinase, Tenecteplase, DG031, AM103, and Fiboflapon, which can have predicted effects on gastric cancer following chemical burns. Conclusion: According to current in-silicon analyses, ALOX5AP and SERPINB2 are linked genetic keys between gastric chemical burn and cancer. Considering that burn is an environmental factor that leads to the upregulation of the two genes thus, the chemical burn can be related to the incidence of gastric cancer.

Predictive modeling of lower extreme deep vein thrombosis following radical gastrectomy for gastric cancer: based on multiple machine learning methods.

Postoperative venous thromboembolic events (VTEs), such as lower extremity deep vein thrombosis (DVT), are major risk factors for gastric cancer (GC) patients following radical gastrectomy. Accurately predicting and managing these risks is crucial for optimal patient care.This retrospective case‒control study involved 693 GC patients from our hospital who underwent radical gastrectomy. We collected plentiful and comprehensive clinical indicators including a total of 49 baseline, preoperative, surgical and pathological clinical data. Using univariate logistic regression, we identified potential risk factors, followed by feature selection through the Boruta algorithm. We then constructed the final predictive model using multivariate logistic regression and evaluated it using receiver operating characteristic (ROC) curve analysis, calibration plots, decision curve analysis, and other methods. Additionally, we applied various machine learning techniques, including decision trees and random forests, to assess our model's predictive strength.This retrospective case‒control study involved 693 GC patients from our hospital who underwent radical gastrectomy. We collected plentiful and comprehensive clinical indicators including a total of 49 baseline, preoperative, surgical and pathological clinical data. Using univariate logistic regression, we identified potential risk factors, followed by feature selection through the Boruta algorithm. We then constructed the final predictive model using multivariate logistic regression and evaluated it using receiver operating characteristic (ROC) curve analysis, calibration plots, decision curve analysis, and other methods. Additionally, we applied various machine learning techniques, including decision trees and random forests, to assess our model's predictive strength.Univariate logistic analysis revealed 14 risk factors associated with postoperative lower limb DVT. Based on the Boruta algorithm, six significant clinical factors were selected, namely, age, D-dimer (D-D) level, low-density lipoprotein, CA125, and calcium and chloride ion levels. A nomogram was developed using the outcomes from the multivariate logistic regression analysis. The predictive model showed high accuracy, with an area under the curve of 0.936 in the training set and 0.875 in the validation set. Various machine learning algorithms confirmed its strong predictive capacity. MR analysis revealed meaningful causal relationships between key clinical factors and DVT risk.Based on various machine learning methods, we developed an effective predictive diagnostic model for postoperative lower extremity DVT in GC patients. This model demonstrated excellent predictive value in both the training and validation sets. This novel model is a valuable tool for clinicians to use in identifying and managing thrombotic risks in this patient population.

Predictive modeling of lower extreme deep vein thrombosis following radical gastrectomy for gastric cancer: based on multiple machine learning methods.

Postoperative venous thromboembolic events (VTEs), such as lower extremity deep vein thrombosis (DVT), are major risk factors for gastric cancer (GC) patients following radical gastrectomy. Accurately predicting and managing these risks is crucial for optimal patient care.This retrospective case‒control study involved 693 GC patients from our hospital who underwent radical gastrectomy. We collected plentiful and comprehensive clinical indicators including a total of 49 baseline, preoperative, surgical and pathological clinical data. Using univariate logistic regression, we identified potential risk factors, followed by feature selection through the Boruta algorithm. We then constructed the final predictive model using multivariate logistic regression and evaluated it using receiver operating characteristic (ROC) curve analysis, calibration plots, decision curve analysis, and other methods. Additionally, we applied various machine learning techniques, including decision trees and random forests, to assess our model's predictive strength.This retrospective case‒control study involved 693 GC patients from our hospital who underwent radical gastrectomy. We collected plentiful and comprehensive clinical indicators including a total of 49 baseline, preoperative, surgical and pathological clinical data. Using univariate logistic regression, we identified potential risk factors, followed by feature selection through the Boruta algorithm. We then constructed the final predictive model using multivariate logistic regression and evaluated it using receiver operating characteristic (ROC) curve analysis, calibration plots, decision curve analysis, and other methods. Additionally, we applied various machine learning techniques, including decision trees and random forests, to assess our model's predictive strength.Univariate logistic analysis revealed 14 risk factors associated with postoperative lower limb DVT. Based on the Boruta algorithm, six significant clinical factors were selected, namely, age, D-dimer (D-D) level, low-density lipoprotein, CA125, and calcium and chloride ion levels. A nomogram was developed using the outcomes from the multivariate logistic regression analysis. The predictive model showed high accuracy, with an area under the curve of 0.936 in the training set and 0.875 in the validation set. Various machine learning algorithms confirmed its strong predictive capacity. MR analysis revealed meaningful causal relationships between key clinical factors and DVT risk.Based on various machine learning methods, we developed an effective predictive diagnostic model for postoperative lower extremity DVT in GC patients. This model demonstrated excellent predictive value in both the training and validation sets. This novel model is a valuable tool for clinicians to use in identifying and managing thrombotic risks in this patient population.

Two-sample Mendelian randomization analysis of the relationship between periodontitis and risk of upper gastrointestinal cancers.

The aim of the present study is to explore the possible association between periodontitis and upper gastrointestinal (UGI) cancers, including esophageal and gastric cancers, utilizing the Mendelian randomization method. In this research, we utilized the Mendelian randomization method to examine the causal association between periodontitis and UGI cancers. Genome-wide association studies data for periodontitis were obtained from the Gene-Lifestyle Interactions in Dental Endpoints consortium, while UGI cancers' data were accessed from FinnGen's Biobank. After rigorously screening instrumental variables for periodontitis, we analyzed them with UGI cancers primarily using the inverse variance weighted. Finally, to identify outliers, the results were subjected to a leave-one-out sensitivity analysis. Inverse variance weighted (fixed effect) results revealed that periodontitis is a risk factor for gastric cancer (OR = 1.7735, 95% CI: 1.1576 to 2.7170, P = 0.0085). As for esophageal cancer, no statistically significant correlation was observed. Furthermore, no outliers were detected in any of the results. Our two-sample Mendelian randomization study obviously demonstrates a significant positive association between periodontitis and gastric cancer, while no statistically significant correlation was found for esophageal cancer.

Understanding the relationship between obesity and in-hospital outcomes in gastric cancer patients : A nationwide analysis.

e16050 Background: Gastric cancer is the fifth most common form of cancer and the third leading cause of cancer-related deaths worldwide. Obesity has been identified as a significant risk factor for gastric cancer, associated with increased incidence and heightened complications in hospitalized patients. Our analysis comprehensively evaluates obesity's impact on hospital-admitted gastric cancer patients. Methods: Using the National Inpatient Sample (NIS) 2020, we identified gastric cancer patients with regional and advanced metastatic disease, and they were stratified into patients with and without obesity. The primary outcome was mortality, and secondary outcomes included length of stay, the total cost of hospitalization, and other in-hospital adverse outcomes. Multivariate logistic regression analysis was used to calculate the outcomes after adjusting for confounding variables. Results: A total of 17560 patients were hospitalized with gastric cancer, among which 1720(9.8%) had the concurrent diagnosis of Obesity. The mean age of patients with and without Obesity was 63 (+/- 13.88) and 66 (+/- 12.93),p<0.001 respectively. The obese category had the greater percentage of male patients as compared to females (58.14% vs 44.85% respectively, p<0.001). After adjusting for confounding variables, Obesity was not considered as an independent predictor of mortality in patients with gastric cancer (OR=1.06(0.59-1.92); p=0.90). However, patients with Obesity had prolonged length of stay (+ 1.52 days(1.49-2.26); p=0.004) and total cost of hospitalization (+ $30977(12320-49633); p=0.001). Similarly, obese patients had an increased likelihood of Acute kidney injury (OR=1.47(1.09-1.96); p=0.01), ICU admission (OR=2.01(1.30-3.09); p=0.002), invasive (OR=2.14(1.29-3.54); p=0.003) Noninvasive mechanical ventilation (OR=5.36(2.17-13.14); p<0.001) and Heart failure (OR=1.68(1.09-2.57); p=0.02). No difference was noted in the risk of cardiac arrest (OR=1.26(0.28-5.68); p=0.76), and sepsis(OR=1.76(0.99-3.13); p=0.05). Conclusions: Obesity in patients with gastric cancer is not an independent predictor of mortality but is associated with increased length of stay, the total cost of hospitalization, increased risk of mechanical ventilation, and ICU admissions. Management of obesity can prove crucial in averting a wide range of potential health complications and significantly enhancing the overall quality of life in gastric cancer patients. [Table: see text]

Prevalence of H. pylori and gastric intestinal metaplasia in BRCA1 and BRCA2 carriers.

BRCA1 and BRCA2 carriers may be at increased risk for gastric cancer (GC), however the mechanisms of gastric carcinogenesis remain poorly understood. We sought to determine the prevalence of GC risk factors Helicobacter pylori (H. pylori) infection and gastric intestinal metaplasia (GIM) among BRCA1/2 carriers to gain insight into the pathogenesis of GC in this population. 100 unselected BRCA1/2 carriers undergoing endoscopic ultrasound from 3/2022-3/2023 underwent concomitant upper endoscopy with non-targeted gastric antrum and body biopsies. The study population (70% women; mean age: 60.1) included 66% BRCA2 carriers. H. pylori was detected in one (1%) individual, 7 (7%) had GIM, 2 (2%) had autoimmune atrophic gastritis, and no GCs were diagnosed. Among BRCA1/2 carriers, H. pylori prevalence was low and GIM prevalence was similar to the general population, however identification of H. pylori or GIM may help inform future GC risk management strategies in BRCA1/2 carriers.

Hotspots and trends of risk factors in gastric cancer: A visualization and bibliometric analysis.

The lack of specific symptoms of gastric cancer (GC) causes great challenges in its early diagnosis. Thus it is essential to identify the risk factors for early diagnosis and treatment of GC and to improve the survival rates. To assist physicians in identifying changes in the output of publications and research hotspots related to risk factors for GC, constructing a list of key risk factors, and providing a reference for early identification of patients at high risk for GC. Research articles on risk factors for GC were searched in the Web of Science core collection, and relevant information was extracted after screening. The literature was analyzed using Microsoft Excel 2019, CiteSpace V, and VOSviewer 1.6.18. A total of 2514 papers from 72 countries and 2507 research institutions were retrieved. China (n = 1061), National Cancer Center (n = 138), and Shoichiro Tsugane (n = 36) were the most productive country, institution, or author, respectively. The research hotspots in the study of risk factors for GC are summarized in four areas, namely: Helicobacter pylori (H. pylori) infection, single nucleotide polymorphism, bio-diagnostic markers, and GC risk prediction models. In this study, we found that H. pylori infection is the most significant risk factor for GC; single-nucleotide polymorphism (SNP) is the most dominant genetic factor for GC; bio-diagnostic markers are the most promising diagnostic modality for GC. GC risk prediction models are the latest current research hotspot. We conclude that the most important risk factors for the development of GC are H. pylori infection, SNP, smoking, diet, and alcohol.

SOX9 is regulated by AURKA in response to Helicobacter pylori infection via EIF4E-mediated cap-dependent translation

Helicobacter pylori (H. pylori) infection is the main risk factor for gastric cancer. The SRY-Box Transcription Factor 9 (SOX9) serves as a marker of stomach stem cells. We detected strong associations between AURKA and SOX9 expression levels in gastric cancers. Utilizing in vitro and in vivo mouse models, we demonstrated that H. pylori infection induced elevated levels of both AURKA and SOX9 proteins. Notably, the SOX9 protein and transcription activity levels were dependent on AURKA expression. AURKA knockdown led to a reduction in the number and size of gastric gland organoids. Conditional knockout of AURKA in mice resulted in a decrease in SOX9 baseline level in AURKA-knockout gastric glands, accompanied by diminished SOX9 induction following H. pylori infection. We found an AURKA-dependent increase in EIF4E and cap-dependent translation with an AURKA-EIF4E-dependent increase in SOX9 polysomal RNA levels. Immunoprecipitation assays demonstrated binding of AURKA to EIF4E with a decrease in EIF4E ubiquitination. Immunohistochemistry analysis on tissue arrays revealed moderate to strong immunostaining of AURKA and SOX9 with a significant correlation in gastric cancer tissues. These findings elucidate the mechanistic role of AURKA in regulating SOX9 levels via cap-dependent translation in response to H. pylori infection in gastric tumorigenesis.

Helicobacter pylori cagA, vacA, and iceA genotypes and clinical outcomes: a cross-sectional study in central Vietnam.

Helicobacter pylori is the most common cause of gastroduodenal diseases. The concept that cagA-positive H. pylori is a risk factor for gastric cancer appears to be true only for H. pylori strains from Western countries. Other virulent genes may have a synergistic interaction with cagA during pathogenesis. This study aims to investigate H. pylori cagA, vacA, and iceA prevalence, genotypes, and their association to clinical outcomes in Vietnamese patients. The cagA status and vacA and iceA genotypes were determined using the PCR technique on DNA extracted from gastric biopsies of 141 patients with gastroduodenal diseases. After performing molecular analysis for cagA, vacA, and iceA genes, samples with mixed H. pylori strains, positivity, or negativity for both cagA and cagPAI-empty site, or unidentified genotypes were excluded. Finally, 107 samples were examined. The presence of the cagA, vacA, and iceA genes were detected in 77.6%, 100%, and 80.4% of cases, respectively. Notably, cagA( +) with EPIYA-ABD, vacA s1i1m1, vacA s1i1m2, iceA1, and iceA2 accounted for 73.8%, 44.9%, 33.6%, 48.6%, and 31.8% of cases, respectively. Four iceA2 subtypes (24-aa, 59-aa, 94-aa, and 129-aa variants) were found, with the 59-aa variant the most prevalent (70.6%). The cagA( +)/vacAs1i1m1/iceA1 and cagA( +)/vacAs1i1m2/iceA1 combinations were found in 26.2% and 25.1% of cases, respectively. A multivariable logistic regression analysis was performed, after adjusting for age and gender, with the gastritis group was used as a reference control. Statistically significant associations were found between the vacA s1i1m2 genotype, the iceA1 variant, and the cagA( +)/vacAs1i1m2/iceA1 combination and gastric cancer; the adjusted ORs were estimated as 18.02 (95% CI: 3.39-95.81), 4.09 (95% CI: 1.1-15.08), and 16.19 (95% CI: 3.42-76.66), respectively. Interestingly, for the first time, our study found that vacA s1i1m2, but not vacA s1i1m1, was a risk factor for gastric cancer. This study illustrates the genetic diversity of the H. pylori cagA, vacA, and iceA genes across geographical regions and contributes to understanding the importance of these genotypes for clinical outcomes.

An Overview of the Spices Used for the Prevention and Potential Treatment of Gastric Cancer.

Gastric cancer (GC) ranks third in terms of cancer-related deaths and is the fifth most commonly diagnosed type of cancer. Its risk factors include Helicobacter pylori infection, Epstein-Barr virus infection, the consumption of broiled and charbroiled animal meats, salt-preserved and smoke-enhanced foods, alcohol drinking, tobacco smoking, exposure to ionizing radiation, and positive family history. The limited effectiveness of conventional therapies and the widespread risk factors of GC encourage the search for new methods of treatment and prevention. In the quest for cheap and commonly available medications, numerous studies focus on herbal medicine, traditional brews, and spices. In this review, we outline the potential use of spices, including turmeric, ginger, garlic, black cumin, chili pepper, saffron, black pepper, rosemary, galangal, coriander, wasabi, cinnamon, oregano, cardamom, fenugreek, caraway, clove, dill, thyme, Piper sarmentosum, basil, as well as the compounds they contain, in the prevention and treatment of GC. We present the potential molecular mechanisms responsible for the effectivity of a given seasoning substance and their impact on GC cells. We discuss their potential effects on proliferation, apoptosis, and migration. For most of the spices discussed, we also outline the unavailability and side effects of their use.

A Cost-Effective Model for Predicting Recurrent Gastric Cancer Using Clinical Features.

This study used artificial intelligence techniques to identify clinical cancer biomarkers for recurrent gastric cancer survivors. From a hospital-based cancer registry database in Taiwan, the datasets of the incidence of recurrence and clinical risk features were included in 2476 gastric cancer survivors. We benchmarked Random Forest using MLP, C4.5, AdaBoost, and Bagging algorithms on metrics and leveraged the synthetic minority oversampling technique (SMOTE) for imbalanced dataset issues, cost-sensitive learning for risk assessment, and SHapley Additive exPlanations (SHAPs) for feature importance analysis in this study. Our proposed Random Forest outperformed the other models with an accuracy of 87.9%, a recall rate of 90.5%, an accuracy rate of 86%, and an F1 of 88.2% on the recurrent category by a 10-fold cross-validation in a balanced dataset. We identified clinical features of recurrent gastric cancer, which are the top five features, stage, number of regional lymph node involvement, Helicobacter pylori, BMI (body mass index), and gender; these features significantly affect the prediction model's output and are worth paying attention to in the following causal effect analysis. Using an artificial intelligence model, the risk factors for recurrent gastric cancer could be identified and cost-effectively ranked according to their feature importance. In addition, they should be crucial clinical features to provide physicians with the knowledge to screen high-risk patients in gastric cancer survivors as well.

The differences in gastric cancer epidemiological data between SEER and GBD: a joinpoint and age-period-cohort analysis

BackgroundThe burden of gastric cancer (GC) should be further clarified worldwide, and helped us to understand the current situation of GC.MethodsIn the present study, we estimated disability-adjusted life-years (DALYs) and mortality rates attributable to several major GC risk factors, including smoking, dietary risk, and behavioral risk. In addition, we evaluated the incidence rate and trends of incidence-based mortality (IBM) due to GC in the United States (US) during 1992–2018.ResultsGlobally, GC incidences increased from 883,395 in 1990 to 1,269,805 in 2019 while GC-associated mortality increased from 788,316 in 1990 to 957,185 in 2019. In 2019, the age-standardized rate (ASR) of GC exhibited variations around the world, with Mongolia having the highest observed ASR (43.7 per 100,000), followed by Bolivia (34 per 100,000) and China (30.6 per 100,000). A negative association was found among estimated annual percentage change (EAPC) and ASR (age-standardized incidence rate (ASIR): r = − 0.28, p < 0.001; age-standardized death rate (ASDR): r = − 0.19, p = 0.005). There were 74,966 incidences of GC and 69,374 GC-related deaths recorded between 1992 and 2018. The significant decrease in GC incidences as well as decreasing trends in IBM of GC were first detected in 1994. The GC IBM significantly increased at a rate of 35%/y from 1992 to 1994 (95% CI 21.2% to 50.4%/y), and then begun to decrease at a rate of − 1.4%/y from 1994 to 2018 (95% CI − 1.6% to − 1.2%/y).ConclusionThese findings mirror the global disease burden of GC and are important for development of targeted prevention strategies.

Helicobacter pylori infection induces gastric cancer cell malignancy by targeting HOXA-AS2/miR-509-3p/MMD2 axis.

Helicobacter pylori (Hp) infection is considered to be the strongest risk factor for gastric cancer (GC). Long non-coding RNA HOXA cluster antisense RNA 2 (HOXA-AS2) has been indicated to be significantly related to Hp infection in GC patients. To investigate the detailed role and molecular mechanism of lncRNA HOXA-AS2 in Hp-induced GC. GC cells were treated with Hp filtrate for cell infection. Bioinformatics tools were utilized for survival analysis and prediction of HOXA-AS2 downstream molecules. Western blotting and RT-qPCR were utilized for assessing protein and RNA levels, respectively. Flow cytometry, colony formation and CCK-8 assays were implemented for testing HOXA-AS2 functions in Hp-infected GC cells. HOXA-AS2 localization in cells was determined by subcellular fractionation assay. The relationship between RNAs were measured by luciferase reporter assay. Hp infection induced HOXA-AS2 upregulation in GC cells. Knocking down HOXA-AS2 restrained cell proliferation but promoted cell apoptosis with Hp infection. HOXA-AS2 bound to miR-509-3p, and miR-509-3p targeted monocyte to macrophage differentiation associated 2 (MMD2). Overexpressing MMD2 reversed HOXA-AS2 depletion-mediated suppression on cell aggressiveness with Hp infection. Hp infection induces the aggressiveness of GC cells by regulating HOXA-AS2/miR-509-3p/MMD2 axis.

Gastric cancer and metabolic syndrome

Gastric cancer (GC), a prevalent disease in Asian countries, presents a substantial global health challenge. The risk factors for GC include Helicobacter pylori infection, diet, smoking, alcohol, and metabolic syndrome (MetS). This review meticulously examines the intricate connections between MetS and GC, focusing on visceral adipocytes, hormonal factors, obesity, and their impact on survival outcomes. Visceral adipocytes, which secrete inflammatory cytokines and hormones, play a pivotal role in influencing cancer development. Hormonal factors demonstrate nuanced associations with specific GC subtypes, underscoring the complexity of their impact. Large-scale studies exploring obesity-related factors reveal sex-specific nuances and underscore the importance of considering overall weight and body composition. Furthermore, the review explores the impact of eradication therapy for H. pylori infection, which is the most significant factor in the onset of GC, on the components of MetS. Additionally, the influence of MetS on postoperative outcomes and survival in GC patients highlights the interplay between therapeutic interventions and lifestyle factors. This comprehensive exploration sheds light on the multifaceted relationship between MetS and GC, providing valuable insights for future research and preventive strategies.

Severe induction of aberrant DNA methylation by nodular gastritis in adults.

Nodular gastritis (NG) is characterized by marked antral lymphoid follicle formation, and is a strong risk factor for diffuse-type gastric cancer in adults. However, it is unknown whether aberrant DNA methylation, which is induced by atrophic gastritis (AG) and is a risk for gastric cancer, is induced by NG. Here, we analyzed methylation induction by NG. Gastric mucosal samples were obtained from non-cancerous antral tissues of 16 NG and 20 AG patients with gastric cancer and 5 NG and 6 AG patients without, all age- and gender-matched. Genome-wide methylation analysis and expression analysis were conducted by a BeadChip array and RNA-sequencing, respectively. Clustering analysis of non-cancerous antral tissues of NG and AG patients with gastric cancer was conducted using methylation levels of 585 promoter CpG islands (CGIs) of methylation-resistant genes, and a large fraction of NG samples formed a cluster with strong methylation induction. Promoter CGIs of CDH1 and DAPK1 tumor-suppressor genes were more methylated in NG than in AG. Notably, methylation levels of these genes were also higher in the antrum of NG patients without cancer. Genes related to lymphoid follicle formation, such as CXCL13/CXCR5 and CXCL12/CXCR4, had higher expression in NG, and genes involved in DNA demethylation TET2 and IDH1, had only half the expression in NG. Severe aberrant methylation, involving multiple tumor-suppressor genes, was induced in the gastric antrum and body of patients with NG, in accordance with their high gastric cancer risk.

Effects of Helicobacter pylori and Moluodan on the Wnt/β-catenin signaling pathway in mice with precancerous gastric cancer lesions.

Helicobacter pylori (H. pylori) is the primary risk factor for gastric cancer (GC), the Wnt/β-Catenin signaling pathway is closely linked to tumourigenesis. GC has a high mortality rate and treatment cost, and there are no drugs to prevent the progression of gastric precancerous lesions to GC. Therefore, it is necessary to find a novel drug that is inexpensive and preventive to against GC. To explore the effects of H. pylori and Moluodan on the Wnt/β-Catenin signaling pathway and precancerous lesions of GC (PLGC). Mice were divided into the control, N-methyl-N-nitrosourea (MNU), H. pylori + MNU, and Moluodan groups. We first created an H. pylori infection model in the H. pylori + MNU and Moluodan groups. A PLGC model was created in the remaining three groups except for the control group. Moluodan was fed to mice in the Moloudan group ad libitum. The general condition of mice were observed during the whole experiment period. Gastric tissues of mice were grossly and microscopically examined. Through quantitative real-time PCR (qRT-PCR) and Western blotting analysis, the expression of relevant genes were detected. Mice in the H. pylori + MNU group showed the worst performance in general condition, gastric tissue visual and microscopic observation, followed by the MNU group, Moluodan group and the control group. QRT-PCR and Western blotting analysis were used to detect the expression of relevant genes, the results showed that the H. pylori + MNU group had the highest expression, followed by the MNU group, Moluodan group and the control group. H. pylori can activate the Wnt/β-catenin signaling pathway, thereby facilitating the development and progression of PLGC. Moluodan suppressed the activation of the Wnt/β-catenin signaling pathway, thereby decreasing the progression of PLGC.

Establishment of Golgi apparatus-related genes signature to predict the prognosis and immunotherapy response in gastric cancer patients.

The Golgi apparatus plays a crucial role in intracellular protein transportation, processing, and sorting. Dysfunctions of the Golgi apparatus have been implicated in tumorigenesis and drug resistance. This study aimed to investigate the prognostic and treatment response assessment value of Golgi apparatus-related gene (GARGs) features in gastric cancer patients. Transcriptome data and clinical information of gastric cancer patients were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. Cox regression analysis was employed to assess the prognostic significance of GARGs and construct risk features. The immune landscape, drug sensitivity, immune therapy response, gene expression patterns, and somatic mutation characteristics were analyzed between different risk groups. A nomogram model for predicting gastric cancer prognosis was developed and evaluated. Among 1643 GARGs examined, 365 showed significant associations with gastric cancer prognosis. Five independent prognostic GARGs (NGF, ABCG1, CHAC1, GBA2, PCSK7) were selected to construct risk features for gastric cancer patients. These risk features effectively stratified patients into high-risk and low-risk groups, with the former exhibiting worse prognosis than the latter. Patients in the high-risk group displayed higher levels of immune cell infiltration, while the expression levels of NGF, CHAC1, GBA2, PCSK7 were significantly correlated with immune cell infiltration. Notably, the low-risk group exhibited higher sensitivity to epothilone.B, metformin, and tipifarnib compared to the high-risk group. Moreover, patients in the low-risk group demonstrated greater responsiveness to immune therapy than those in the high-risk group. In terms of biological processes and KEGG pathways related to immunity regulation, significant suppression was observed in the high-risk group compared to the low-risk group; meanwhile cell cycle pathways exhibited significant activation in the high-risk group. Furthermore, the low-risk group exhibited a higher tumor mutation burden compared to the high-risk group. The risk features derived from GARGs, in conjunction with age, were identified as independent risk factors for gastric cancer. The nomogram incorporating these factors demonstrated improved performance in predicting gastric cancer prognosis. Our study established risk features derived from GARGs that hold potential clinical utility in prognostic assessment and immune therapy response evaluation of gastric cancer patients.

DIABETES MELLITUS A RISK FACTOR OF GASTRIC CANCER : SYSTEMATIC REVIEW

Background: It is estimated that 500 million individuals globally would have diabetes mellitus (DM) by 2030. A deadly tumor that affects the digestive tract is called gastric cancer (GC). It ranks as the fourth leading cause of cancer death worldwide and the fifth most common kind of cancer. Every year, there are around 700,000 fatalities and one million new cases of GC globally. Aims : This systematic review is to review the association of diabetes mellitus as a risk factor of gastric cancer. Methods: This study demonstrated compliance with all requirements by means of a comparison with the standards established by the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020. Thus, the specialists were able to guarantee that the research was as current as feasible. Publications released between 2014 and 2024 were considered for this search strategy. This was accomplished by utilizing a number of distinct online reference sites, including Pubmed, ScienceDirect, and SagePub. It was determined that reviews, previously published works, and partially completed works would not be included. Result: In the PubMed database, the results of our search brought up 343 articles, whereas the results of our search on SAGEPUB brought up 2178 articles, our search on SCIENCE DIRECT brought up 23102 articles. The results of the search conducted for the last year of 2014 yielded a total 231 articles for PubMed, 1017 articles for SAGEPUB and 12260 articles for SCIENCE DIRECT. In the end, we compiled a total of 5 papers, 2 of which came from PubMed, 1 of which came from SAGEPUB and 2 of which came from SCIENCE DIRECT. We included five research that met the criteria. Conclusion: In summary, there is no direct association of diabetes mellitus and gastric cancer, but diabetes mellitus can increase the risk factor of gastric cancer cases.

Volatilomic signatures of different strains of Helicobacter pylori.

Helicobacter pylori (H. pylori) infection is the most extensively studied risk factor for gastric cancer. As with any bacteria, H. pylori will release distinctive odors that result from an emission of volatile metabolic byproducts in unique combinations and proportions. Effectively capturing and identifying these volatiles can pave the way for the development of innovative and non-invasive diagnostic methods for determining infection. Here we characterize the H. pylori volatilomic signature, pinpoint potential biomarkers of its presence, and evaluate the variability of volatilomic signatures between different H. pylori isolates. Using needle trap extraction, volatiles in the headspace above H. pylori cultures were collected and, following thermal desorption at 290°C in a splitless mode, were analyzed using gas chromatography-mass spectrometry. The resulting volatilomic signatures of H. pylori cultures were compared to those obtained from an analysis of the volatiles in the headspace above the cultivating medium only. Amongst the volatiles detected, 21 showed consistent differences between the bacteria cultures and the cultivation medium, with 11 compounds being elevated and 10 showing decreased levels in the culture's headspace. The 11 elevated volatiles are four ketones (2-pentanone, 5-methyl-3-heptanone, 2-heptanone, and 2-nonanone), three alcohols (2-methyl-1-propanol, 3-methyl-1-butanol, and 1 butanol), one aromatic (styrene), one aldehyde (2-ethyl-hexanal), one hydrocarbon (n-octane), and one sulfur compound (dimethyl disulfide). The 10 volatiles with lower levels in the headspace of the cultures are four aldehydes (2-methylpropanal, benzaldehyde, 3-methylbutanal, and butanal), two heterocyclic compounds (2-ethylfuran and 2-pentylfuran), one ketone (2-butanone), one aromatic (benzene), one alcohol (2-butanol) and bromodichloromethane. Of the volatile species showing increased levels, the highest emissions are found to be for 3-methyl-1-butanol, 1-butanol and dimethyl disulfide. Qualitative variations in their emissions from the different isolates was observed. The volatiles emitted by H. pylori provide a characteristic volatilome signature that has the potential of being developed as a tool for monitoring infections caused by this pathogen. Furthermore, using the volatilome signature, we are able to differentiate different isolates of H. pylori. However, the volatiles also represent potential confounders for the recognition of gastric cancer volatile markers.

Vonoprazan: A Review in Helicobacter pylori Infection.

Treatment for the eradication of Helicobacter pylori infection, a leading cause of peptic ulcer disease and an important risk factor for gastric cancer and mucosa-associated lymphoid tissue lymphoma, is indicated whenever infection is identified. However, treatment success rates with current guideline-recommended proton-pump inhibitor (PPI)-based regimens remain suboptimal, with one potential factor associated with treatment failure being inadequate acid suppression. Vonoprazan (Voquezna®) is a first-in-class potassium-competitive acid blocker with the potential to provide potent and sustained acid suppression. Following clinical trials conducted mainly in Asia (supported by post-marketing experience from Asia) and the phaseIII PHALCON-HP trial conducted in the USA and Europe, vonoprazan is now approved in the USA for use in combination with amoxicillin (dual therapy) or amoxicillin and clarithromycin (triple therapy) for the treatment of H.pylori infection in adults. The vonoprazan-based dual and triple therapy regimens were generally well tolerated in PHALCON-HP. In addition, vonoprazan has advantages including a rapid onset of action and no food effect, making vonoprazan-based dual and triple therapy regimens valuable alternatives to standard PPI-based triple therapy in the treatment of H.pylori infection.