Molecular evolution of intestinal-type early gastric cancer according to Correa cascade.

Early screening is crucial for the prevention of intestinal-type gastric cancer. The objective of the current study was to ascertain molecular evolution of intestinal-type gastric cancer according to the Correa cascade for the precise gastric cancer screening. We collected sequential lesions of the Correa cascade in the formalin-fixed and paraffin-embedded endoscopic submucosal dissection-resected specimens from 14 Chinese patients by microdissection, and subsequently determined the profiles of somatic aberrations during gastric carcinogenesis using the whole exome sequencing, identifying multiple variants at different Correa stages. The results showed that TP53, PCLO, and PRKDC were the most frequently mutated genes in the early gastric cancer (EGC). A high frequency of TP53 alterations was found in low-grade intraepithelial neoplasia (LGIN), which further increased in high-grade intraepithelial neoplasia (HGIN) and EGC. Intestinal metaplasia (IM) had no significant correlation with EGC in terms of mutational spectra, whereas both LGIN and HGIN showed higher genomic similarities to EGC, compared with IM. Based on Jaccard similarity coefficients, three evolutionary models were further constructed, and most patients showed linear progression from LGIN to HGIN, ultimately resulting in EGC. The ECM-receptor interaction pathway was revealed to be involved in the linear evolution. Additionally, the retrospective validation study of 39 patients diagnosed with LGIN indicated that PRKDC mutations, in addition to TP53 mutations, may drive LGIN progression to HGIN or EGC. In conclusion, the current study unveils the genomic evolution across the Correa cascade of intestinal-type gastric cancer, elucidates the underlying molecular mechanisms of gastric carcinogenesis, and provides some evidence for potential personalized gastric cancer surveillance.

Machine Learning Identify Ferroptosis-Related Genes as Potential Diagnostic Biomarkers for Gastric Intestinal Metaplasia.

BACKGROUND: Gastric intestinal metaplasia(GIM) is an independent risk factor for GC, however, its pathogenesis is still unclear. Ferroptosis is a new type of programmed cell death, which may be involved in the process of GIM. The purpose of this study was to analyze the expression of ferroptosis-related genes (FRGs) in GIM tissues and to explore the relationship between ferroptosis and GIM. METHOD: The results of GIM tissue full transcriptome sequencing were downloaded from Gene Expression Omnibus(GEO) database. R software (V4.2.0) and R packages were used for screening and enrichment analysis of differentially expressed genes(DEGs). The key genes were screened by least absolute shrinkage and selection operator(LASSO) and support vector machine-recursive feature elimination(SVM-RFE) algorithm. Receiver operating characteristic(ROC) curve was used to evaluate the diagnostic efficacy of key genes in GIM. Clinical samples were used to further validate hub genes. RESULTS: A total of 12 differentially expressed ferroptosis-related genes (DEFRGs) were identified. Using two machine learning algorithms, GOT1, ALDH3A2, ACSF2 and SESN2 were identified as key genes. The area under ROC curve (AUC) of GOT1, ALDH3A2, ACSF2 and SESN2 in the training set were 0.906, 0.955, 0.899 and 0.962 respectively, and the AUC in the verification set were 0.776, 0.676, 0.773 and 0.880, respectively. Clinical samples verified the differential expression of GOT1, ACSF2, and SESN2 in GIM. CONCLUSION: We found that there was a significant correlation between ferroptosis and GIM. GOT1, ACSF2 and SESN2 can be used as diagnostic markers to effectively identify GIM.

Gastric intestinal metaplasia regression in United States population: A retrospective longitudinal study.

Background and Aim: Gastric cancer is a health concern and contributes to cancer-related deaths. Gastric intestinal metaplasia (GIM) is a premalignant lesion of gastric cancer. Currently, factors associated with GIM regression are under-investigated. This study aims to assess the rate of GIM regression and identify factors associated with it. Methods: This study was conducted at Medstar Washington Hospital Center. We included patients who had GIM between January 2015 and December 2020. Population was divided into GIM persistence or regression. Data included demographics, esophagogastroduodenoscopy findings, Helicobacter pylori status, and laboratory results. Statistical analyses included Kaplan-Meier and Cox proportional models to explore predictors of GIM regression. Results: Among 2375 patients, 9.1% had GIM. Notably, 85 patients had GIM regression and 132 patients had persistent GIM. African Americans constituted (75%) of the regression group and (76%) of the persistence group. Peptic ulcer disease (PUD) was noted in 12.9% of the regression group at baseline, and 5.9% at follow-up; the persistence group showed 11.4% at baseline and 5.3% at follow-up (P = 0.89). Regression analysis revealed that the presence of PUD was associated with a higher rate of regression (hazard ratio [HR] 2.46, P = 0.013). Smoking status showed lower rates of regression (HR 0.54 and 0.62, P = 0.038 and 0.169). On gastric mapping, African Americans, Hispanics, and individuals of other races/ethnicities displayed lower rates of GIM regression (HR 0.68, 0.78 and 0.69). Conclusion: PUD was associated with a higher rate of GIM regression, while smoking showed lower regression rates. Results provide insights into factors influencing GIM regression in African American population and may inform future surveillance and treatment strategies.

Weiwei Decoction alleviates gastric intestinal metaplasia through the olfactomedin 4/nucleotide-binding oligomerization domain 1/caudal-type homeobox gene 2 signaling pathway.

BACKGROUND: Gastric intestinal metaplasia (IM) is a precancerous lesion that is associated with an elevated risk of gastric carcinogenesis. Weiwei Decoction (WWD) is a promising traditional Chinese herbal formula widely employed in clinical for treating IM. Previous studies suggested the potential involvement of the olfactomedin 4 (OLFM4)/nucleotide-binding oligomerization domain 1 (NOD1)/caudal-type homeobox gene 2 (CDX2) signaling pathway in IM regulation. AIM: To verify the regulation of the OLFM4/NOD1/CDX2 pathway in IM, specifically investigating WWD's effectiveness on IM through this pathway. METHODS: Immunohistochemistry for OLFM4, NOD1, and CDX2 was conducted on tissue microarray. GES-1 cells treated with chenodeoxycholic acid were utilized as IM cell models. OLFM4 short hairpin RNA (shRNA), NOD1 shRNA, and OLFM4 pcDNA were transfected to clarify the pathway regulatory relationships. Protein interactions were validated by co-immunoprecipitation. To explore WWD's pharmacological actions, IM rat models were induced using N-methyl-N'-nitro-N-nitrosoguanidine followed by WWD gavage. Gastric cells were treated with WWD-medicated serum. Cytokines and chemokines content were assessed by enzyme-linked immunosorbent assay and quantitative reverse transcription polymerase chain reaction. RESULTS: The OLFM4/NOD1/CDX2 axis was a characteristic of IM. OLFM4 exhibited direct binding and subsequent down-regulation of NOD1, thereby sustaining the activation of CDX2 and promoting the progression of IM. WWD improved gastric mucosal histological lesions while suppressing intestinal markers KLF transcription factor 4, villin 1, and MUCIN 2 expression in IM rats. Regarding pharmacological actions, WWD suppressed OLFM4 and restored NOD1 expression, consequently reducing CDX2 at the mRNA and protein levels in IM rats. Parallel regulatory mechanisms were observed at the protein level in IM cells treated with WWD-medicated serum. Furthermore, WWD-medicated serum treatment strengthened OLFM4 and NOD1 interaction. In case of anti-inflammatory, WWD restrained interleukin (IL)-6, interferon-gamma, IL-17, macrophage chemoattractant protein-1, macrophage inflammatory protein 1 alpha content in IM rat serum. WWD-medicated serum inhibited tumor necrosis factor alpha, IL-6, IL-8 transcriptions in IM cells. CONCLUSION: The OLFM4/NOD1/CDX2 pathway is involved in the regulation of IM. WWD exerts its therapeutic efficacy on IM through the pathway, additionally attenuating the inflammatory response.

Convolutional Neural Network Model for Intestinal Metaplasia Recognition in Gastric Corpus Using Endoscopic Image Patches.

Gastric cancer (GC) is a significant healthcare concern, and the identification of high-risk patients is crucial. Indeed, gastric precancerous conditions present significant diagnostic challenges, particularly early intestinal metaplasia (IM) detection. This study developed a deep learning system to assist in IM detection using image patches from gastric corpus examined using virtual chromoendoscopy in a Western country. Utilizing a retrospective dataset of endoscopic images from Sant'Andrea University Hospital of Rome, collected between January 2020 and December 2023, the system extracted 200 × 200 pixel patches, classifying them with a voting scheme. The specificity and sensitivity on the patch test set were 76% and 72%, respectively. The optimization of a learnable voting scheme on a validation set achieved a specificity of 70% and sensitivity of 100% for entire images. Despite data limitations and the absence of pre-trained models, the system shows promising results for preliminary screening in gastric precancerous condition diagnostics, providing an explainable and robust Artificial Intelligence approach.

The Impact of Tobacco Smoking and Alcohol Consumption on the Development of Gastric Cancers.

Chronic infection of Helicobacter pylori is considered the principal cause of gastric cancers, but evidence has accumulated regarding the impact of tobacco smoking and alcohol consumption on the development of gastric cancers. Several possible mechanisms, including the activation of nicotinic acetylcholine receptors, have been proposed for smoking-induced gastric carcinogenesis. On the other hand, local acetaldehyde exposure and ethanol-induced mucosal inflammation have been proposed as the mechanisms involved in the development of gastric cancers in heavy alcohol drinkers. In addition, genetic polymorphisms are also considered to play a pivotal role in smoking-related and alcohol-related gastric carcinogenesis. In this review, we will discuss the molecular mechanisms involved in the development of gastric cancers in relation to tobacco smoking and alcohol consumption.

Non-Invasive Markers for the Detection of Gastric Precancerous Conditions.

Gastric cancer (GC) is still one of the most prevalent cancers worldwide, with a high mortality rate, despite improvements in diagnostic and therapeutic strategies. To diminish the GC burden, a modification of the current diagnostic paradigm, and especially endoscopic diagnosis of symptomatic individuals, is necessary. In this review article, we present a broad review and the current knowledge status on serum biomarkers, including pepsinogens, gastrin, Gastropanel®, autoantibodies, and novel biomarkers, allowing us to estimate the risk of gastric precancerous conditions (GPC)-atrophic gastritis and gastric intestinal metaplasia. The aim of the article is to emphasize the role of non-invasive testing in GC prevention. This comprehensive review describes the pathophysiological background of investigated biomarkers, their status and performance based on available data, as well as their clinical applicability. We point out future perspectives of non-invasive testing and possible new biomarkers opportunities.

Gastric intestinal metaplasia: Prevalence in a large Australian center and nationwide survey of endoscopic practice.

Background and Aim: Atrophic gastritis (AG) and gastric intestinal metaplasia (GIM) are early changes in the stepwise progression to gastric adenocarcinoma. There is heterogeneity in international guidelines regarding the endoscopic diagnosis and surveillance of AG and GIM. This study aims to determine the prevalence of GIM in an Australian center and assess the approach of Australian endoscopists for these two conditions. Methods: We conducted a single-center retrospective study of adult patients between January 2015 and December 2020 diagnosed with GIM on gastric biopsy following upper gastric endoscopy. A web-based, 25-question, investigator-designed, multiple-choice survey was distributed among all registered endoscopists in Australia. Results: The overall prevalence of GIM within a single Australian center was 11.7% over 5 years. Of the 1026 patients identified, only 58.7% underwent mapping biopsies using the modified Sydney protocol. Among the cohort, 1.6% had low-grade dysplasia, 0.9% had high-grade dysplasia, and 1.8% had malignancy on initial gastroscopy. Two hundred and sixty-seven (7.2%) endoscopists completed the survey, 44.2% indicated they would perform mapping for all patients, and 36% only for high-risk patients. Only 1.5% (n = 4) of respondents were able to correctly identify all six endoscopic photos of GIM/AG. Conclusion: This study demonstrates that in a large tertiary center, GIM is a prevalent endoscopic finding, but the associated rates of dysplasia and cancer were low. Additionally, among a small proportion of surveyed Australian endoscopists, there is notable variability in the endoscopic approach for AG and GIM and significant knowledge gaps. More training is required to increase the recognition of GIM and compliance with histological mapping.

Artificial intelligence for gastric cancer in endoscopy: From diagnostic reasoning to market.

Recognition of gastric conditions during endoscopy exams, including gastric cancer, usually requires specialized training and a long learning curve. Besides that, the interobserver variability is frequently high due to the different morphological characteristics of the lesions and grades of mucosal inflammation. In this sense, artificial intelligence tools based on deep learning models have been developed to support physicians to detect, classify, and predict gastric lesions more efficiently. Even though a growing number of studies exists in the literature, there are multiple challenges to bring a model to practice in this field, such as the need for more robust validation studies and regulatory hurdles. Therefore, the aim of this review is to provide a comprehensive assessment of the current use of artificial intelligence applied to endoscopic imaging to evaluate gastric precancerous and cancerous lesions and the barriers to widespread implementation of this technology in clinical routine.

Revealing the pathogenesis of gastric intestinal metaplasia based on the mucosoid air-liquid interface.

BACKGROUND: Gastric intestinal metaplasia (GIM) is an essential precancerous lesion. Although the reversal of GIM is challenging, it potentially brings a state-to-art strategy for gastric cancer therapeutics (GC). The lack of the appropriate in vitro model limits studies of GIM pathogenesis, which is the issue this work aims to address for further studies. METHOD: The air-liquid interface (ALI) model was adopted for the long-term culture of GIM cells in the present work. This study conducted Immunofluorescence (IF), quantitative real-time polymerase chain reaction (qRT-PCR), transcriptomic sequencing, and mucoproteomic sequencing (MS) techniques to identify the pathways for differential expressed genes (DEGs) enrichment among different groups, furthermore, to verify novel biomarkers of GIM cells. RESULT: Our study suggests that GIM-ALI model is analog to the innate GIM cells, which thus can be used for mucus collection and drug screening. We found genes MUC17, CDA, TRIM15, TBX3, FLVCR2, ONECUT2, ACY3, NMUR2, and MAL2 were highly expressed in GIM cells, while GLDN, SLC5A5, MAL, and MALAT1 showed down-regulated, which can be used as potential biomarkers for GIM cells. In parallel, these genes that highly expressed in GIM samples were mainly involved in cancer-related pathways, such as the MAPK signal pathway and oxidative phosphorylation signal pathway. CONCLUSION: The ALI model is validated for the first time for the in vitro study of GIM. GIM-ALI model is a novel in vitro model that can mimic the tissue micro-environment in GIM patients and further provide an avenue for studying the characteristics of GIM mucus. Our study identified new markers of GIM as well as pathways associated with GIM, which provides outstanding insight for exploring GIM pathogenesis and potentially other related conditions.

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 PURPOSE: Patients 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. METHODS: This 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. RESULTS: The 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). CONCLUSION: This DL model can assist endoscopists in predicting OLGIM staging using ME-NBI without biopsy, thereby facilitating screening high-risk patients for GC.

A mechanistic study of Anwei decoction intervention in a rat model of gastric intestinal metaplasia through the endoplasmic reticulum stress - Autophagy pathway.

OBJECTIVE: To investigate the mechanism of Anwei decoction (AWD) intervention on gastric intestinal metaplasia (GIM) using a rat model through the endoplasmic reticulum stress-autophagy pathway. METHODS: Gastric intestinal metaplasia was induced in rats using 1-methyl-3-nitro-1-nitrosoguanidine. The experiment included a normal control group, a model group, and low-, medium- and high-dose AWD groups. The specificity of intestinal epithelial cells was determined for model establishment and drug efficacy by detecting the protein expression of markers such as MUC2, VILLIN and CDX2 through western blotting (WB). The effects of AWD on endoplasmic reticulum stress and autophagy were evaluated by measuring the mRNA and protein expression levels of endoplasmic reticulum stress markers (PEPK, ATF6, CHOP and caspase-12) and autophagy markers (LC3Ⅱ and Beclin-1) using reverse transcription polymerase chain reaction and the WB method. Furthermore, the ultrastructure of gastric mucosal cells and autophagosome status were observed using transmission electron microscopy. RESULTS: Compared with the model group, the AWD-treated rats exhibited significant improvement in body weight (P < 0.01), reduced protein expression of the intestine epithelial cell-specific markers MUC2, VILLIN, CDX2 and KLF4 (P < 0.01 for all) and increased SOX2 protein expression (P < 0.01). In addition, AWD suppressed the mRNA and protein expression of endoplasmic reticulum stress markers PEPK and ATF6 (P < 0.01 for all) and promoted the mRNA and protein expression of autophagy and apoptosis markers CHOP, caspase-12, LC3Ⅱ and Beclin-1 (P < 0.01 for all). CONCLUSION: Anwei decoction effectively inhibits the further progression of GIM and prevents the occurrence of gastric mucosal carcinogenesis.

Low prevalence of gastric intestinal metaplasia and Helicobacter pylori on surveillance upper endoscopy in Lynch syndrome.

Lynch syndrome (LS) increases the risk of numerous different cancers including gastric cancer. While some current guidelines recommend empiric gastric biopsies be performed during upper gastrointestinal cancer surveillance in Lynch syndrome (LS), the yield of these biopsies and the prevalence of gastric intestinal metaplasia (GIM) and Helicobacter pylori (HP) in LS remains unknown. Herein we analyze 165 consecutive individuals with LS who underwent upper endoscopic surveillance with biopsies of the gastric antrum and body being performed universally in all individuals. Of the study cohort, 6.7% of universally biopsied individuals with LS had GIM and/or HP (5.5% GIM, 3.6% HP). Biopsies of the gastric body did not increase rates of GIM/HP identification compared to antral biopsies alone. GIM was detected on subsequent surveillance in 2.2% of individuals without prior GIM, which may represent either newly developed GIM or GIM that was missed on a prior upper endoscopy due to sampling error. These findings support inclusion of at least baseline gastric antrum biopsies as a routine component of all standard surveillance upper endoscopies performed in LS.

The Clinical Impact and Cost-Effectiveness of Surveillance of Incidentally Detected Gastric Intestinal Metaplasia: A Microsimulation Analysis.

BACKGROUND & AIMS: Gastric intestinal metaplasia (GIM) is associated with a higher risk of noncardia intestinal gastric adenocarcinoma (GA). The aim of this study was to estimate lifetime benefits, complications, and cost-effectiveness of GIM surveillance using esophagogastroduodenoscopy (EGD). METHODS: We developed a semi-Markov microsimulation model of patients with incidentally detected GIM, to compare the effectiveness of EGD surveillance with no surveillance at 10-year, 5-year, 3-year, 2-year, and 1-year intervals. We modeled a simulated cohort of 1,000,000 US individuals aged 50 with incidental GIM. Outcome measures were lifetime GA incidence, mortality, number of EGDs, complications, undiscounted life-years gained, and incremental cost-effectiveness ratio with a willingness-to-pay threshold of $100,000/quality-adjusted life-year (QALY). RESULTS: In the absence of surveillance, the model simulated 32.0 lifetime GA cases and 23.0 lifetime GA deaths per 1000 individuals with GIM, respectively. Among surveilled individuals, simulated lifetime GA incidence (per 1000) decreased with shorter surveillance intervals (10-year to 1-year, 11.2-6.1) as did GA mortality (7.4-3.6). Compared with no surveillance, all modeled surveillance intervals yielded greater life expectancy (87-190 undiscounted life-years gained per 1000); 5-year surveillance provided the greatest number of life-years gained per EGD performed and was the cost-effective strategy ($40,706/QALY). In individuals with risk factors of family history of GA or anatomically extensive, incomplete-type GIM intensified 3-year surveillance was cost-effective (incremental cost-effectiveness ratio $28,156/QALY and $87,020/QALY, respectively). CONCLUSIONS: Using microsimulation modeling, surveillance of incidentally detected GIM every 5 years is associated with reduced GA incidence/mortality and is cost-effective from a health care sector perspective. Real-world studies evaluating the impact of GIM surveillance on GA incidence and mortality in the United States are needed.

Evolving Concepts in Helicobacter pylori Management.

Helicobacter pylori is the most common chronic bacterial infection worldwide and the most significant risk factor for gastric cancer, which remains a leading cause of cancer-related death globally. H pylori and gastric cancer continue to disproportionately impact racial and ethnic minority and immigrant groups in the United States. The approach to H pylori case-finding thus far has relied on opportunistic testing based on symptoms or high-risk indicators, such as racial or ethnic background and family history. However, this approach misses a substantial proportion of individuals infected with H pylori who remain at risk for gastric cancer because most infections remain clinically silent. Moreover, individuals with chronic H pylori infection are at risk for gastric preneoplastic lesions, which are also asymptomatic and only reliably diagnosed using endoscopy and biopsy. Thus, to make a significant impact in gastric cancer prevention, a systematic approach is needed to better identify individuals at highest risk of both H pylori infection and its complications, including gastric preneoplasia and cancer. The approach to H pylori eradication must also be optimized given sharply decreasing rates of successful eradication with commonly used therapies and increasing antimicrobial resistance. With growing acceptance that H pylori should be managed as an infectious disease and the increasing availability of susceptibility testing, we now have the momentum to abandon empirical therapies demonstrated to have inadequate eradication rates. Molecular-based susceptibility profiling facilitates selection of a personalized eradication regimen without necessitating an invasive procedure. An improved approach to H pylori eradication coupled with population-level programs for screening and treatment could be an effective and efficient strategy to prevent gastric cancer, especially in minority and potentially marginalized populations that bear the heaviest burden of H pylori infection and its complications.

Diagnosing and grading gastric atrophy and intestinal metaplasia using semi-supervised deep learning on pathological images: development and validation study.

OBJECTIVE: Patients with gastric atrophy and intestinal metaplasia (IM) were at risk for gastric cancer, necessitating an accurate risk assessment. We aimed to establish and validate a diagnostic approach for gastric biopsy specimens using deep learning and OLGA/OLGIM for individual gastric cancer risk classification. METHODS: In this study, we prospectively enrolled 545 patients suspected of atrophic gastritis during endoscopy from 13 tertiary hospitals between December 22, 2017, to September 25, 2020, with a total of 2725 whole-slide images (WSIs). Patients were randomly divided into a training set (n = 349), an internal validation set (n = 87), and an external validation set (n = 109). Sixty patients from the external validation set were randomly selected and divided into two groups for an observer study, one with the assistance of algorithm results and the other without. We proposed a semi-supervised deep learning algorithm to diagnose and grade IM and atrophy, and we compared it with the assessments of 10 pathologists. The model's performance was evaluated based on the area under the curve (AUC), sensitivity, specificity, and weighted kappa value. RESULTS: The algorithm, named GasMIL, was established and demonstrated encouraging performance in diagnosing IM (AUC 0.884, 95% CI 0.862-0.902) and atrophy (AUC 0.877, 95% CI 0.855-0.897) in the external test set. In the observer study, GasMIL achieved an 80% sensitivity, 85% specificity, a weighted kappa value of 0.61, and an AUC of 0.953, surpassing the performance of all ten pathologists in diagnosing atrophy. Among the 10 pathologists, GasMIL's AUC ranked second in OLGA (0.729, 95% CI 0.625-0.833) and fifth in OLGIM (0.792, 95% CI 0.688-0.896). With the assistance of GasMIL, pathologists demonstrated improved AUC (p = 0.013), sensitivity (p = 0.014), and weighted kappa (p = 0.016) in diagnosing IM, and improved specificity (p = 0.007) in diagnosing atrophy compared to pathologists working alone. CONCLUSION: GasMIL shows the best overall performance in diagnosing IM and atrophy when compared to pathologists, significantly enhancing their diagnostic capabilities.

Association between country of birth and gastric intestinal metaplasia: a retrospective cohort study.

Background: As a precursor to gastric cancer, gastric intestinal metaplasia (GIM) represents a target for surveillance. US-based guidelines recommend surveillance of racial/ethnic minorities and immigrants from high incidence gastric cancer regions, yet there is marked variability in prevalence amongst these subgroups and within groups from high incidence regions. There is a paucity of information regarding country of birth as a risk factor for GIM and we sought to determine the association between country of birth and GIM in an ethnically and racially diverse US population. Methods: This was a retrospective cohort study of persons who underwent esophagogastroduodenoscopy (EGD) with gastric biopsy at University of Miami Hospital between 2011 and 2021. A natural language processing (NLP) algorithm was developed and implemented to extract diagnoses of GIM and Helicobacter pylori (HP) infection from endoscopic pathology reports. Multivariable logistic regression was performed to evaluate risk factors for GIM, accounting for important covariates, including country of birth. Findings: A total of 21,108 persons from 130 varying countries of birth were included in the study. A total of 1699 cases of GIM were identified yielding a prevalence of 8.0% (95% CI: 7.7-8.4%). Multivariable analysis was restricted to countries with at least 100 persons in the cohort, yielding 15 countries with 1208 cases of GIM. Country of birth (p < 0.0001), race/ethnicity (p = 0.026), active HP infection (p < 0.0001), and increasing age (p < 0.0001) were significantly associated with increased odds of GIM. Highest odds for GIM were among persons born in Ecuador (OR 2.34, 95% CI 1.56-3.50), Honduras (OR 2.34, 95% CI 1.65-3.34), and Peru (OR 2.17, 95% CI 1.58-2.99). Interpretation: We demonstrate that country of birth is a key risk factor for GIM. Not all countries that are thought to be in "high-risk" regions are associated with higher rates of GIM, underlining the importance of studying the under-investigated risk factor of country of birth. Guidelines should account for country of birth, in addition to other risk factors, to tailor screening/surveillance appropriately. Funding: Shida Haghighat, MD, MPH is supported by an NIH training grant T32 DK 11667805.

Modified Chaishao Liujunzi Decoction inhibits bile acid-induced gastric intestinal metaplasia: from network prediction to experimental verification.

Modified Chaishao Liujunzi Decoction (MCLD) is a traditional Chinese medicine formula that is used mainly to improve clinical symptoms, alleviate gastric mucosal inflammation, and improve gastric mucosal lesions in patients with gastric intestinal metaplasia (GIM). GIM is considered a precancerous gastric cancer (GC) lesion (PLGC) and exploring effective intervention measures for GIM is of great importance for the prevention of GC. The purpose of this study was to reveal the potential molecular mechanism of MCLD in improving GIM induced by bile acid (BA) using network pharmacology and experimental validation. Through network pharmacology, we speculated that MCLD could act on GIM by driving the epidermal growth factor receptor (EGFR)/PI3K/AKT/mammalian target of rapamycin (mTOR) pathway. After that, we used deoxycholic acid (DCA) to treat GES-1 cells to simulate BA-induced GIM and observed the effects of MCLD treatment. The results indicate that MCLD can significantly inhibit DCA-induced cell proliferation and down-regulate the expression of pro-inflammatory cytokines and intestinal-specific markers. At the same time, MCLD also negatively regulated the expression of genes and proteins of the EGFR/PI3K/AKT/mTOR pathway. Combination with EGFR agonists and inhibitors suggested that MCLD may improve GIM by inhibiting the EGFR/PI3K/AKT/mTOR pathway, which may be related to its inhibition of DCA-induced cell proliferation through this pathway. In conclusion, MCLD may improve BA-induced GIM through the EGFR/PI3K/AKT/mTOR pathway, as predicted by network pharmacology, and is a potential Chinese medicine prescription for the treatment or reversal of GIM.

Intestinal Metaplasia Associated with Symptoms of Dyspepsia.

Background: Peptic ulcer disease (PUD) and Helicobacter pylori (HP) are associated with dyspepsia, but the role of gastric intestinal metaplasia (IM) has not been described. The objective of this study is to examine the association between gastric IM and dyspepsia. Methods: We developed a cohort of consecutive patients referred to gastroenterology between Jan 2019 and July 2020 for dyspepsia and iron deficiency anemia (IDA) and completed an upper endoscopy with biopsies in a safety-net health system. The primary outcome was the prevalence of gastric IM in patients with dyspepsia compared to IDA. Secondary outcomes included prevalence of HP, chronic gastritis (CG) and chronic active gastritis (CAG) in the dyspepsia and IDA groups. A multivariable analysis was performed to assess the independent association between gastric IM and dyspepsia. Results: Compared to the IDA cohort (n = 366), patients with dyspepsia (n = 349) were more likely to be female (65% vs. 47%, p < 0.01), harbor gastric IM (20.3% vs. 14.2%, p = 0.03), and less likely to have CAG (12.0% vs. 26.5%, p < 0.01) or HP (10.9% vs. 21.3%, p < 0.01). After adjusting for pathological findings, race, ethnicity, gender and age, the association strengthened between IM and dyspepsia (adj OR 1.81 from OR 1.54, 95% CI 1.19-2.76, p < 0.01). Conclusions: We observed a significant relationship between the presence of gastric IM and dyspepsia symptoms, which increased after adjusting for confounding factors. Future studies should verify the relationship between IM and dyspepsia, the effect of IM regression, and possible mediators of gastric IM on symptoms.

Goblet cells segmentation from confocal laser endomicroscopy with an improved U-Net.

Gastric intestinal metaplasia (GIM) is regarded as a remarkable precursor for the development of intestinal-type stomach cancer. Goblet cell (GC) segmentation is the crucial step for assessing the degree of GIM by confocal laser endomicroscopy (CLE). However, GC segmentation by hand is difficult, unreliable, and time-consuming. Meanwhile, due to the high resolution and noise interference of CLE images, existing segmentation approaches perform poorly on this task. To tackle those issues, we collected 343 confocal laser endomicroscopy images of 62 patients from a Grade-A tertiary hospital. Each CLE image is manually annotated and then verified three times by skilled medical specialists. Then, U-Net is improved by incorporating the pixel gradient attention mechanism, which focuses on color gradient information around GC and captures color gradient features to direct feature maps in the skip connection layer. At last, the model output vector is used to calculate the possibility map and generate the final segmentation area. Compared with mainstream models, our proposed GC segmentation method from CLE with an improved U-Net (GCSCLE) performs the better segmentation result when tested on our CLE dataset and achieved an IOU of 87.95% and a DICE of 86.64%. Our result shows, the performance of the GCSCLE can be compared with the manual CLE image processing in clinical settings, and it can improve segmentation accuracy and save time and costs.