High Risk Of Gastric Cancer Research Articles

Big data approach in the field of gastric and colorectal cancer research.

Big data is characterized by three attributes: volume, variety,, and velocity. In healthcare setting, big data refers to vast dataset that is electronically stored and managed in an automated manner and has the potential to enhance human health and healthcare system. In this review, gastric cancer (GC) and postcolonoscopy colorectal cancer (PCCRC) will be used to illustrate application of big data approach in the field of gastrointestinal cancer research. Helicobacter pylori (HP) eradication only reduces GC risk by 46% due to preexisting precancerous lesions. Apart from endoscopy surveillance, identifying medications that modify GC risk is another strategy. Population-based cohort studies showed that long-term use of proton pump inhibitors (PPIs) associated with higher GC risk after HP eradication, while aspirin and statins associated with lower risk. While diabetes mellitus conferred 73% higher GC risk, metformin use associated with 51% lower risk, effect of which was independent of glycemic control. Nonetheless, nonsteroidal anti-inflammatory drugs (NA-NSAIDs) are not associated with lower GC risk. CRC can still occur after initial colonoscopy in which no cancer was detected (i.e. PCCRC). Between 2005 and 2013, the rate of interval-type PCCRC-3y (defined as CRC diagnosed between 6 and 36months of index colonoscopy which was negative for CRC) was 7.9% in Hong Kong, with >80% being distal cancers and higher cancer-specific mortality compared with detected CRC. Certain clinical and endoscopy-related factors were associated with PCCRC-3 risk. Medications shown to have chemopreventive effects on PCCRC include statins, NA-NSAIDs, and angiotensin-converting enzyme inhibitors/angiotensin receptor blockers.

Optimal extent of lymph node dissection for high-risk gastric cancer stratified by a national clinical database risk calculator.

For patients with gastric cancer, a well-balanced treatment that considers both oncological aspects and surgical risk is demanded. This study aimed to explore the optimal extent of lymph node dissection (LND) for patients with gastric cancer according to surgical risk, stratified by the risk calculator system produced by the Japan National Clinical Database (NCD). We retrospectively evaluated 187 patients who underwent radical gastrectomy for gastric cancer. Using the median predicted anastomotic leak rate obtained by the NCD risk calculator as the cutoff value, we classified 97 and 90 patients as having high and low risks, respectively. In low-risk patients, although limited LND reduced the postoperative intraabdominal infectious complications (IAIC), multivariate analysis revealed standard LND as an independent prognostic factor that improved Relapse-free survival (RFS). In high-risk patients, the rates of postoperative IAIC and RFS were similar between standard and limited LND. Pancreatic fistula was not observed in the limited dissection group. Limited LND might be the optimal treatment strategy for patients with gastric cancer with high surgical risk.

Effect of vegetable consumption on risk of gastric cancer: a systematic review and multi-level meta-analysis of prospective studies.

Vegetables are known to be beneficial to human health, but the association between vegetable consumption and gastric cancer remains uncertain. To synthesise knowledge about the relationship between vegetable group consumption and gastric cancer risk, update present meta-analyses and estimate associations between vegetable consumption and gastric cancer risk based solely on prospective studies, we perform a PRISMA-compliant three-level meta-analysis. Systematic search identified thirteen prospective studies with fifty-two effect sizes that met all inclusion criteria and no exclusion criteria for our meta-analysis. Pooled risk ratios (RRs) showed a positive association between high vegetable consumption and low gastric cancer risk (pooled RR 0·93, 95% confidence interval 0·90-0·97, P = 0·06). In moderator analyses for indicators of gender, region and quantity of vegetable intake, there was no significant difference between subgroups. However, the effect became significant in populations with lower than the minimum risk exposure level (TMREL) of vegetable consumption (P < 0·05). Higher vegetable intake is associated with a decreased risk of gastric cancer. This effect may be limited to specific populations, such as ones with lower vegetable consumption. Evidence from our study has important public health implications for dietary recommendations.

Association Between Vonoprazan and the Risk of Gastric Cancer After Helicobacter pylori Eradication

Potassium-competitive acid blockers (PCABs) have been increasingly used to treat upper gastrointestinal disorders, replacing proton pump inhibitors (PPIs). Whereas PPIs are associated with an increased risk of gastric cancer (GC) after Helicobacter pylori (Hp) eradication, it is uncertain whether PCABs carry the same risk. Using a population-based claims database in Japan, we identified patients who were prescribed a clarithromycin-based first regimen of Hp eradication between 2015 and 2018. Patients who failed this regimen and those diagnosed with GC before or within 1 year after Hp eradication were excluded. We compared GC incidence between PCAB users and histamine type-2 receptor antagonist (H2RA) users, matching them on the basis of propensity scores calculated with considerations for age, sex, smoking, alcohol consumption, comorbidities, and co-administered medications. PCABs included only vonoprazan in this study. Among 54,055 patients, 568 (1.05%) developed GC during the follow-up period (mean, 3.65 years). The cumulative incidence of GC was 1.64% at 3 years, 2.02% at 4 years, and 2.36% at 5 years in PCAB users and 0.71% at 3 years, 1.04% at 4 years, and 1.22% at 5 years in H2RA users. The use of PCABs was associated with a higher GC risk (matched hazard ratio, 1.92; 95% confidence interval, 1.13-3.25; P= .016). Longer PCAB use and high-dose PCAB use were significantly associated with higher incidence of GC. Sensitivity analyses showed the risk of GC incidence among PCAB users was comparable with that of PPI users. The use of PCABs was associated with an increased risk of GC among Hp-eradicated patients, with duration/dose response effects.

Spatial Variation of the Gastrointestinal Microbiota in Response to Long-Term Administration of Vonoprazan in Mice With High Risk of Gastric Cancer.

Vonoprazan, a potassium-competitive acid blocker, is superior to traditional proton pump inhibitor (PPI) in acid suppression and has been approved in the treatment of acid-related disorders. Accumulating evidence suggest associations between PPI use and gut microbiota, yet the effect of vonoprazan on GI microbiota is obscure. Transgenic FVB/N insulin-gastrin (INS-GAS) mice as a model of gastric cancer (GC) were administered vonoprazan by gavage every other day for 12 weeks. Stomachs were evaluated by histopathology, Ki-67 proliferation index, and inflammatory cytokines. The mucosal and lumen microbiota from stomach, jejunum, ileum, cecum, and feces were detected using 16S rRNA gene sequencing. Higher incidence of intestinal metaplasia and epithelial proliferation were observed in the vonoprazan group than that in the control mice. Vonoprazan also elevated the gastric expression of proinflammatory cytokines, including TNF-α, IL-1β, and IL-6. Each mice comprised a unique microbiota composition that was consistent across different niches. The structure of GI microbiota changed dramatically after vonoprazan treatment with the stomach being the most disturbed segment. Vonoprazan administration shifted the gut microbiota toward the enrichment of pathogenic Streptococcus, Staphylococcus, Bilophila, and the loss of commensal Prevotella, Bifidobacterium, and Faecalibacterium. Interestingly, compared to the controls, microbial interactions were weaker in the stomach while stronger in the jejunum of the vonoprazan group. Long-term vonoprazan treatment promoted gastric lesions in male INS-GAS mice, with the disequilibrium of GI microbiome. The clinical application of vonoprazan needs to be judicious particularly among those with high risk of GC.

A deep learning model based on magnifying endoscopy with narrow-band imaging to evaluate intestinal metaplasia grading and OLGIM staging: A multicenter study

Background and PurposePatients with stage III or IV of operative link for gastric intestinal metaplasia assessment (OLGIM) are at a higher risk of gastric cancer (GC). We aimed to construct a deep learning (DL) model based on magnifying endoscopy with narrow-band imaging (ME-NBI) to evaluate OLGIM staging. MethodsThis study included 4473 ME-NBI images obtained from 803 patients at three endoscopy centres. The endoscopic expert marked intestinal metaplasia (IM) regions on endoscopic images of the target biopsy sites. Faster Region-Convolutional Neural Network model was used to grade IM lesions and predict OLGIM staging. ResultsThe diagnostic performance of the model for IM grading in internal and external validation sets, as measured by the area under the curve (AUC), was 0.872 and 0.803, respectively. The accuracy of this model in predicting the high-risk stage of OLGIM was 84.0%, which was not statistically different from that of three junior (71.3%, p = 0.148) and three senior endoscopists (75.3%, p = 0.317) specially trained in endoscopic images corresponding to pathological IM grade, but higher than that of three untrained junior endoscopists (64.0%, p = 0.023). ConclusionThis DL model can assist endoscopists in predicting OLGIM staging using ME-NBI without biopsy, thereby facilitating screening high-risk patients for GC.

Carbon footprint and cost reduction by endoscopic grading of gastric intestinal metaplasia using narrow-band imaging.

Gastric intestinal metaplasia (GIM) is a high-risk factor for the development of gastric cancer. Narrow-band imaging (NBI) enables endoscopic grading of GIM (EGGIM). In the era of climate change, gastrointestinal endoscopists are expected to reduce greenhouse gas emissions and medical waste. Based on the diagnostic performance of NBI endoscopy, this study measured the environmental impact and reduced cost of implementing EGGIM during gastroscopy. Using NBI endoscopy in 242 patients, EGGIM classification and operative link on GIM (OLGIM) staging were prospectively performed in five different areas (lesser and greater curvatures of the corpus and antrum, and the incisura angularis). We estimated the environmental impact and cost reduction of the biopsy procedures and pathological processing if EGGIM were used instead of OLGIM. The diagnostic accuracy of NBI endoscopy for GIM was 93.0-97.1% depending on the gastric area. When a high EGGIM score ≥5 was the cut-off value for predicting OLGIM stages III-IV, the area under the curve was 0.862, sensitivity was 81.9%, and specificity was 90.4%. The reduction in the carbon footprint by EGGIM was -0.4059kg carbon dioxide equivalents per patient, equivalent to 1 mile driven by a gasoline-powered car. The cost savings were calculated to be $47.36 per patient. EGGIM is a reliable method for identifying high-risk gastric cancer patients, thereby reducing the carbon footprint and medical costs in endoscopy practice.

Clinical and morphological characteristics of patients with chronic gastritis and high risk of gastric cancer

The purpose of this study is to conduct a clinical and morphological analysis of cases of chronic gastritis with a high risk of gastric cancer (GC). Materials and methods. The study included 26 cases of chronic atrophic gastritis of stages 3 and 4 with a high risk of developing GC according to the assessment using the OLGA system (Operative Link for Gastritis Assessment). The cases were diagnosed on material of gastric tissue biopsy in 2022. In total, 678 histological studies were performed during the year. Cases of chronic gastritis with a high risk of developing GC accounted for 3.8% of all chronic gastritis. Results. Cases of chronic gastritis with a high risk of developing GC were more often observed in older men (average age 67±12 years, ratio 2.25:1). Multifocal atrophic gastritis was in the first place in frequency of occurrence (61.5%), the connection with helicobacter infection was confirmed only in a third of cases (34.6%). Morphological changes were characterized by a predominant lesion of the antrum of the stomach and mixed complete and incomplete intestinal metaplasia. With the exception of one case in which pseudopancreatic metaplasia was detected in the antrum of the stomach, all cases of autoimmune gastritis (n=26) were assigned to stage 2 with a low risk of developing GC, which seems controversial to us. Conclusion. The results of our study showed a high percentage of pre-existing tumor lesions of the stomach in the group of chronic gastritis with a high risk of developing GC. Dysplasia was diagnosed in 5 out of 26 cases, GC with previously performed mucosectomy in 3 out of 26 cases. In addition, the patients had other tumor and precancerous lesions of the gastrointestinal tract. These data show the validity and practical value of using the OLGA system to identify high-risk groups for the development of tumors not only of the stomach, but also of gastrointestinal tumors of other localizations.

In-depth metaproteomics analysis of tongue coating for gastric cancer: a multicenter diagnostic research study

BackgroundOur previous study revealed marked differences in tongue images between individuals with gastric cancer and those without gastric cancer. However, the biological mechanism of tongue images as a disease indicator remains unclear. Tongue coating, a major factor in tongue appearance, is the visible layer on the tongue dorsum that provides a vital environment for oral microorganisms. While oral microorganisms are associated with gastric and intestinal diseases, the comprehensive function profiles of oral microbiota remain incompletely understood. Metaproteomics has unique strength in revealing functional profiles of microbiota that aid in comprehending the mechanism behind specific tongue coating formation and its role as an indicator of gastric cancer.MethodsWe employed pressure cycling technology and data-independent acquisition (PCT-DIA) mass spectrometry to extract and identify tongue-coating proteins from 180 gastric cancer patients and 185 non-gastric cancer patients across 5 independent research centers in China. Additionally, we investigated the temporal stability of tongue-coating proteins based on a time-series cohort. Finally, we constructed a machine learning model using the stochastic gradient boosting algorithm to identify individuals at high risk of gastric cancer based on tongue-coating microbial proteins.ResultsWe measured 1432 human-derived proteins and 13,780 microbial proteins from 345 tongue-coating samples. The abundance of tongue-coating proteins exhibited high temporal stability within an individual. Notably, we observed the downregulation of human keratins KRT2 and KRT9 on the tongue surface, as well as the downregulation of ABC transporter COG1136 in microbiota, in gastric cancer patients. This suggests a decline in the defense capacity of the lingual mucosa. Finally, we established a machine learning model that employs 50 microbial proteins of tongue coating to identify individuals at a high risk of gastric cancer, achieving an area under the curve (AUC) of 0.91 in the independent validation cohort.ConclusionsWe characterized the alterations in tongue-coating proteins among gastric cancer patients and constructed a gastric cancer screening model based on microbial-derived tongue-coating proteins. Tongue-coating proteins are shown as a promising indicator for identifying high-risk groups for gastric cancer.1cCPG45EGUX3nZjXKAFgvfVideo

A feasibility study on utilizing machine learning technology to reduce the costs of gastric cancer screening in Taizhou, China.

To optimize gastric cancer screening score and reduce screening costs using machine learning models. This study included 228,634 patients from the Taizhou Gastric Cancer Screening Program. We used three machine learning models to optimize Li's gastric cancer screening score: Gradient Boosting Machine (GBM), Distributed Random Forest (DRF), and Deep Learning (DL). The performance of the binary classification models was evaluated using the area under the curve (AUC) and area under the precision-recall curve (AUCPR). In the binary classification model used to distinguish low-risk and moderate- to high-risk patients, the AUC in the GBM, DRF, and DL full models were 0.9994, 0.9982, and 0.9974, respectively, and the AUCPR was 0.9982, 0.9949, and 0.9918, respectively. Excluding Helicobacter pylori IgG antibody, pepsinogen I, and pepsinogen II, the AUC in the GBM, DRF, and DL models were 0.9932, 0.9879, and 0.9900, respectively, and the AUCPR was 0.9835, 0.9716, and 0.9752, respectively. Remodel after removing variables IgG, PGI, PGII, and G-17, the AUC in GBM, DRF, and DL was 0.8524, 0.8482, 0.8477, and AUCPR was 0.6068, 0.6008, and 0.5890, respectively. When constructing a tri-classification model, we discovered that none of the three machine learning models could effectively distinguish between patients at intermediate and high risk for gastric cancer (F1 scores in the GBM model for the low, medium and high risk: 0.9750, 0.9193, 0.5334, respectively; F1 scores in the DRF model for low, medium, and high risks: 0.9888, 0.9479, 0.6694, respectively; F1 scores in the DL model for low, medium, and high risks: 0.9812, 0.9216, 0.6394, respectively). We concluded that gastric cancer screening indicators could be optimized when distinguishing low-risk and moderate to high-risk populations, and detecting gastrin-17 alone can achieve a good discriminative effect, thus saving huge expenditures.

Research Challenges for Augmenting Endoscopy Image Datasets using Image Combination Methodologies

Metaplasia detection in upper gastrointestinal endoscopy is crucial to identify patients at higher risk of gastric cancer. Deep learning algorithms can be useful for detecting and localising these lesions during an endoscopy exam. However, to train these types of models, a lot of annotated data is needed, which can be a problem in the medical field. To overcome this, data augmentation techniques are commonly applied to increase the dataset’s variability but need to be adapted to the specificities of the application scenario. In this study, we discuss the potential benefits and identify four key research challenges of a promising data augmentation approach, namely image combination methodologies, such as CutMix, for metaplasia detection and localisation in gastric endoscopy imaging modalities.

Using the Electronic Health Record to Develop a Gastric Cancer Risk Prediction Model

Background and aimsGastric cancer (GC) is a leading cause of cancer incidence and mortality globally. Population screening is limited by the low incidence and prevalence of GC in the United States. A risk prediction algorithm to identify high-risk patients allows for targeted GC screening. We aimed to determine the feasibility and performance of a logistic regression model based on electronic health records (EHR) to identify individuals at high risk for non-cardia gastric cancer (NCGC). MethodsWe included 614 patients who had a diagnosis of NCGC between ages 40-80 years and who were seen at our large tertiary medical center in multiple states between 2010 and 2021. Controls without a diagnosis of NCGC were randomly selected in a 1:10 ratio of cases to controls. Multiple imputation by chained equation for missing data followed by logistic regression on imputed datasets was used to estimate the probability of NCGC. Area under the curve (AUC) and the 0.632 estimator was used as the estimate for discrimination. ResultsThe 0.632 estimator value was 0.731, indicating robust model performance. Probability of NCGC was higher with increasing age (odds ratio [OR]=1.16, 95% confidence interval [CI]: 1.04 – 1.3), male sex (OR = 1.97; 95% CI: 1.64-2.36), Black (OR= 3.07; 95% CI: 2.46-3.83) or Asian race (OR=4.39; 95% CI: 2.60-7.42), tobacco use (OR=1.61; 95% CI: 1.34-1.94), anemia (OR=1.35; 95% CI: 1.09-1.68) and pernicious anemia (OR=6.12, 95% CI: 3.42-10.95). ConclusionWe demonstrate the feasibility and good performance of an EHR-based logistic regression model for estimating the probability of NCGC. Future studies will refine and validate this model, ultimately identifying a high-risk cohort who could be eligible for NCGC screening.

Gastric Section Correlation Network for Gastric Precancerous Lesion Diagnosis.

Goal: Diagnosing the corpus-predominant gastritis index (CGI) which is an early precancerous lesion in the stomach has been shown its effectiveness in identifying high gastric cancer risk patients for preventive healthcare. However, invasive biopsies and time-consuming pathological analysis are required for the CGI diagnosis. Methods: We propose a novel gastric section correlation network (GSCNet) for the CGI diagnosis from endoscopic images of three dominant gastric sections, the antrum, body and cardia. The proposed network consists of two dominant modules including the scaling feature fusion module and section correlation module. The front one aims to extract scaling fusion features which can effectively represent the mucosa under variant viewing angles and scale changes for each gastric section. The latter one aims to apply the medical prior knowledge with three section correlation losses to model the correlations of different gastric sections for the CGI diagnosis. Results: The proposed method outperforms competing deep learning methods and achieves high testing accuracy, sensitivity, and specificity of 0.957, 0.938 and 0.962, respectively. Conclusions: The proposed method is the first method to identify high gastric cancer risk patients with CGI from endoscopic images without invasive biopsies and time-consuming pathological analysis.

Causal relationships between coffee intake, apolipoprotein B and gastric, colorectal, and esophageal cancers: univariable and multivariable Mendelian randomization.

Coffee intake and apolipoprotein B levels have been linked to gastric, colorectal, and esophageal cancers in numerous recent studies. However, whether these associations are all causal remains unestablished. This study aimed to assess the potential causal associations of apolipoprotein B and coffee intake with the risk of gastric, colorectal, and esophageal cancers using Mendelian randomization analysis. In this study, we utilized a two-sample Mendelian randomization analysis to access the causal effects of coffee intake and apolipoprotein B on gastric, colorectal, and esophageal cancers. The summary statistics of coffee intake (n = 428,860) and apolipoprotein B (n = 439,214) were obtained from the UK Biobank. In addition, the summary statistics of gastric cancer, colorectal cancer, and esophageal cancer were obtained from the FinnGen biobank (n = 218,792). Inverse variance weighted, MR-Egger, weighted median, and weighted mode were applied to examine the causal relationship between coffee intake, apolipoprotein B and gastric, colorectal, and esophageal cancers. MR-Egger intercept test, Cochran's Q test, and leave-one-out analysis were performed to evaluate possible heterogeneity and pleiotropy. Steiger filtering and bidirectional mendelian randomization analysis were performed to evaluate the possible reverse causality. The result of the inverse variance weighted method indicated that apolipoprotein B levels were significantly associated with a higher risk of gastric cancer (OR = 1.392, 95% CI 1.027-1.889, P = 0.0333) and colorectal cancer (OR = 1.188, 95% CI 1.001-1.411, P = 0.0491). Furthermore, multivariable Mendelian randomization analysis also revealed a positive association between apolipoprotein B levels and colorectal cancer risk, but the effect of apolipoprotein B on gastric cancer risk disappeared after adjustment of coffee intake, body mass index or lipid-related traits. However, we did not discover any conclusive evidence linking coffee intake to gastric, colorectal, or esophageal cancers. This study suggested a causal association between genetically increased apolipoprotein B levels and higher risk of colorectal cancer. No causal relationship was observed between coffee intake and gastric, colorectal, or esophageal cancers.

Risk of gastric cancer in relation with serum cholesterol profiles: A nationwide population-based cohort study.

Obesity is a known risk factor for gastric cancer. However, the relationship between serum lipids and gastric cancer risk has not been fully established. We investigated the relationship between serum cholesterol levels and gastric cancer risk using a nationwide population cohort. Adults who received health care screening in 2009 from the Korean National Health Insurance Service were enrolled. Gastric cancer risk in relation to quartiles of high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and total cholesterol (TC) were compared according to sex, using adjusted hazard ratios (aHRs) with 95% confidence intervals (CIs). Among 9690,168 subjects enrolled, 92,403 gastric cancer cases were diagnosed. Higher HDL-C levels were associated with lower gastric cancer risk in the total population, men, and women (aHR [for the highest quartile] = 0.98 [0.96-0.99, P < .0001], aHR = 0.98 [0.96-1.004, P = .0004], and aHR = 0.91 [0.88-0.94, P < .0001], respectively). HDL-C showed consistent trends regardless of age or statin use. Higher LDL-C levels were also associated with lower gastric cancer risk in the total population (aHR = 0.92 [0.91-0.94], P < .0001) and men (aHR = 0.94 [0.91-0.96], P < .0001), but not in women (P = .4073). A subgroup analysis of LDL-C showed significant interactions with age and statin use (Pinteraction < .0001 and Pinteraction = .0497, respectively). The risk of gastric cancer was higher in subjects with elevated LDL-C levels in the younger group (age < 55, HR [for the highest quartile] = 1.02 [0.99-1.04] in the total population; HR = 1.03 [1.003-1.06] in men), the risk was lower in subjects with elevated LDL-C in the elderly (age ≥ 55, HR = 0.93 [0.91-0.95] in the total population; HR = 0.94 [0.92-0.96] in men). Elevated TC was associated with lower gastric cancer risk in the total population (aHR = 0.95 [0.94-0.97], P < .0001), but not in each sex separately (P = .3922 in men; P = .1046 in women). Overall, higher HDL-C levels may play a protective role in gastric cancer pathogenesis. The association between LDL-C/TC and gastric cancer seems to vary according to sex, age, and statin use. Especially in young males under age 55, high LDL-C and TC levels were associated with higher risk of gastric cancer.

Helicobacter pylori ancestors from an area of Nariño with high risk of gastric cancer

Objetivo: Determinar la ancestría de Helicobacter pylori aislado de pacientes provenientes de una zona de alto riesgo de cáncer gástrico del departamento de Nariño. Materiales y Métodos: Se incluyeron 16 pacientes con síntomas de dispepsia e infectados con Helicobacter pylori. Se utilizaron biopsias gástricas para el cultivo de Helicobacter pylori y subsecuente secuenciación del genoma total por Illumina MiSeq, 2x300 pb. El ensamblaje y anotación de los genomas se procedió mediante el uso de los algoritmos SPAdes y RASTtk. Las proporciones ancestrales de Helicobacter pylori se determinaron por STRUCTURE con el modelo de mezcla. Las diferencias entre estas proporciones se establecieron con las pruebas H de Kruskal Wallis y post hoc. Resultados: La estructura de la población de Helicobacter pylori deriva de cuatro poblaciones ancestrales: Ancestral Europa (AE) (61.2%), Ancestral Africa1 (AA1) (35.7%), Ancestral Este de Asia (AEA) (3%) y Ancestral Africa2 (AA2) (0.1%), siendo significativas las diferencias entre las proporciones de los ancestros de Helicobacter pylori (p&lt;0.05). Se identificaron diferencias estadísticamente significativas entre: AA2 y AEA (p=0.022); AA2 y AA1 (p&lt;0.05); AA2 y AE (p&lt;0.05); AEA y AA1 (p=0.014) y AEA con AE (p&lt;0.05), sin embargo, no se encontró diferencias significativas entre AA1 y AE (p=0.098), evaluadas por post hoc. Conclusión: Helicobacter pylori que coloniza la mucosa gástrica de una población de alto riesgo de cáncer gástrico en Nariño, deriva su acervo genético principalmente de ancestros europeos y africanos, confiriéndole a la bacteria alta capacidad competitiva asociada al desarrollo de lesiones severas en nichos gástricos amerindios.

OGBN P16 Endoscopic surveillance allows prediction of burden of early signet ring cell carcinoma in Hereditary Diffuse Gastric Cancer syndrome

Abstract Background Hereditary diffuse gastric cancer (HDGC) syndrome is commonly linked to CDH1 germline pathogenic variants (PV) and carries a high lifetime risk of diffuse gastric cancer (DGC). Definitive treatment remains prophylactic total gastrectomy (PTG). However, endoscopic surveillance can be offered to inform decision-making around surgery, although the optimal time for treatment escalation remains unclear. This study aims to establish whether histopathological assessment of endoscopic biopsies can predict burden of early signet ring cell (SRC) carcinoma on PTG specimens. Methods We performed a retrospective review of prospectively collected data on endoscopic and surgical histopathologic results from CDH1 PV carriers who underwent PTG at Addenbrooke’s Hospital between January 2006 and May 2023. Targeted and systematic Cambridge protocol biopsies were performed. Patients with confirmed DGC (stage 2 or higher) at baseline endoscopy were excluded. Pearson correlation was performed to assess the relationship between number of SRC foci on endoscopy and surgical specimens. Results 46 patients underwent PTG with median of 3 pre-operative surveillance endoscopies over 22 months. Final stage was pT1aN0M0 in 41 patients and pT0N0M0 in 5 patients. The number of SRC foci on PTG specimens ranged from 0 to 273. There was a strong correlation between number of SRC foci on gastrectomy specimens and from targeted and random biopsies when evaluated separately and together for last 2 and all endoscopies. The strongest correlation was seen with total number of SRC foci on random biopsies for last 2 endoscopies (r=0.738, p-value&amp;lt;0.001). Random biopsies outperformed targeted biopsies in prediction of early SRC burden. Conclusions Endoscopic surveillance with systematic targeted and random biopsies by expert endoscopists within a dedicated specialist service provides useful information to estimate the burden of early SRCC. Low number of SRC foci at last two endoscopies indicate scarce gastric neoplastic involvement.

The prediction model of operative link on gastric intestinal metaplasia stage III-IV: A multicenter study

PurposeIntestinal metaplasia plays a crucial role in the risk stratification of gastric cancer development. The objective of the study was to develop a prediction model for Operative Link on Gastric Intestinal Metaplasia (OLGIM) Stage III-IV. MethodsWe analyzed 7945 high-risk gastric cancer individuals from 115 hospitals who underwent questionnaires and gastroscope. The participants were assigned to either the development or validation cohort randomly. Demographics and clinical characteristics were obtained. The outcome measurement was OLGIM III-IV. Univariate logistic regression was used for feature selection and multivariate logistic analysis was performed to develop the nomogram. Area under the curves, calibration plots, decision curve and clinical impact analysis were used to assess the performance of the nomogram. Results4600 individuals and 3345 individuals were included in the development and validation cohort, of which 124 and 86 individuals were diagnosed with OLGIM III-IV, respectively. Parameters in the training validation cohort matched well and there was no significant difference between two cohorts. A nomogram model for predicting OLGIM Stage III-IV consisted of 4 significantly associated variables, including age, gender, PG I and G-17 (AUC 0.723 and 0.700 for the 2 cohorts). The nomogram demonstrated excellent performance in the calibration curve. Decision curve and clinical impact analysis suggested clinical benefit of the prediction model. ConclusionsThis reliable individualized nomogram might contribute to more accurate management for patients with OLGIM III-IV. Therefore, we suggest that this study be used as an incentive to promote the application.

Spatiotemporal genomic profiling of intestinal metaplasia reveals clonal dynamics of gastric cancer progression

Intestinal metaplasia (IM) is a pre-malignant condition of the gastric mucosa associated with increased gastric cancer (GC) risk. Analyzing 1,256 gastric samples (1,152 IMs) across 692 subjects from a prospective 10-year study, we identify 26 IM driver genes in diverse pathways including chromatin regulation (ARID1A) and intestinal homeostasis (SOX9). Single-cell and spatial profiles highlight changes in tissue ecology and IM lineage heterogeneity, including an intestinal stem-cell dominant cellular compartment linked to early malignancy. Expanded transcriptome profiling reveals expression-based molecular subtypes of IM associated with incomplete histology, antral/intestinal cell types, ARID1A mutations, inflammation, and microbial communities normally associated with the healthy oral tract. We demonstrate that combined clinical-genomic models outperform clinical-only models in predicting IMs likely to transform to GC. By highlighting strategies for accurately identifying IM patients at high GC risk and a role for microbial dysbiosis in IM progression, our results raise opportunities for GC precision prevention and interception.

Toll-like receptor 9 (-1237 T/C, -1486 T/C) and the risk of gastric cancer: a meta-analysis of genetic association studies

BackgroundGastric cancer has a complex aetiology including genetic factors. Individual case-control studies of toll like receptor (TLR) 9 (-1237 T/C, -1486 T/C) polymorphisms in the gastric cancer risk were available, and they showed variation in the findings. Therefore, we performed a meta-analysis to synthesize the evidence on the association between polymorphisms of TLR 9 (-1237 T/C, -1486 T/C) and the risk of gastric cancer using data from eligible studies.MethodsThis study followed the PRISMA 2020 Checklist. Studies were searched in health-related databases. The methodological quality of studies was evaluated with the use of Newcastle-Ottawa Scale criteria. The summary odds ratio (OR) and its 95% confidence interval (CI) were used to determine the strength of association between each polymorphism and the risk of gastric cancer using five genetic models. Stratification was done by ethnic groups. For the robustness of the analysis, a leave-one-out meta-analysis was performed.ResultsEight case-control studies with 3,644 participants (1914 cases, 1730 controls) were conducted across six countries. Half of the studies were conducted in China. In the NOS methodological quality assessment, only three studies received a high-quality rating (i.e., a score of ≥ 7). TLR 9 (-1486 T/C) polymorphism and the risk of gastric cancer were assessed in six studies, four of Asian ethnicity and two of non-Asian. Under the dominant model, only in the Asian ethnic group showed a marginally and significantly increased risk of gastric cancer (overall: OR = 1.22, 95%CI = 0.90–1.67, I2 = 56%; Asian: OR = 1.24, 95%CI = 1.00-1.54, I2 = 0%, non-Asian: OR = 1.25, 95%CI = 0.38–4.09, I2 = 89%). Under the recessive model in the absence of heterogeneity, only the Asian group had a significantly higher risk of developing gastric cancer (overall: OR = 1.4, 95% CI = 0.74–2.64, I2 = 85%; Asian: OR: 1.41, 95% CI = 1.07–1.86, I2 = 0%, non-Asian: OR = 1.18, 95% CI = 0.12–11.76, I2 = 97%). Under the heterozygous model, there was no significant association with the risk of gastric cancer overall or among any ethnic subgroup. Under the homozygous model in the absence of heterogeneity, only the Asian group had a significantly higher risk of gastric cancer (overall, OR = 1.47, 95% CI = 0.76–2.86, I2 = 82%; Asian: OR = 1.54, 95% CI = 1.13–2.1, I2 = 0%; non-Asian: OR = 1.19, 95% CI = 0.1-14.33, I2 = 96%). Under the allele model, a significantly increased risk of gastric cancer was observed only in the Asian group (overall: OR = 1.23, 95% CI = 0.89–1.71, I2 = 84%; Asian: OR = 1.22, 95% CI = 1.05–1.41, I2 = 0%; non-Asian: OR = 1.24, 95% CI = 0.34–4.59, I2 = 97%). Four studies investigated the association between TLR 9 (-1237 T/C) polymorphism and the risk of developing gastric cancer. Under any of the five genetic models, there was no association between TLR 9 (-1237 T/C) and the development of gastric cancer in overall or in any ethnic subgroup. Sensitivity analysis revealed that the effect was unstable. With a small number of studies with a small number of participants, we addressed the issue of insufficient power for drawing conclusions.ConclusionsThe findings suggested that TLR9 (-1486 T/C) may play a role in the risk of gastric cancer specific to the Asian ethnic group. To substantiate the findings on the association between these two polymorphisms (TLR9 -1237 T/C, -1486 T/C) and the risk of gastric cancer, future well-designed case-control studies with a sufficient number of participants in multi-ethnic groups are recommended.