BackgroundEpstein–Barr virus (EBV)-associated gastric cancer (EBVaGC) has been reported to account for approximately 5–16% of all GCs with good prognosis compared to EBV-negative GC. We evaluated the clinicopathological characteristics of EBVaGC including survival rate in South Korea.MethodsA total of 4,587 patients with GC who underwent EBV in situ hybridization (EBV–ISH) were prospectively enrolled at the Seoul National University Bundang Hospital from 2003 to 2021. Age, sex, smoking status, cancer type and stage, tumor size and location, histological type, molecular features and survival information were analyzed.ResultsA total of 456 patients with GC (9.9%) were positive for EBV. The EBVaGC group displayed a higher proportion of males (P < 0.001), a predominant presence in the proximal stomach (P < 0.001), a higher proportion of undifferentiated cancer (P < 0.001), and a lower cancer stage (P = 0.004) than the EBV-negative group. Cox multivariate analyses revealed age (hazard ratio [HR] = 1.025, P < 0.001), tumor size (HR = 1.109, P < 0.001), and cancer stage (stage2 HR = 4.761, P < 0.001; stage3 HR = 13.286, P < 0.001; stage4 HR = 42.528, P < 0.001) as significant risk factors for GC-specific mortality, whereas EBV positivity was inversely correlated (HR = 0.620, P = 0.022). Furthermore, the EBVaGC group displayed statistically significant survival advantages over the EBV-negative cancer group in terms of both overall (P = 0.021) and GC-specific survival (P = 0.007) on the Kaplan–Meier survival curve. However, this effect was evident only in males.ConclusionsEBVaGC patients showed better prognoses despite their association with proximal location and poorly differentiated histology in male, probably due to the difference in immunity between males and females.

ObjectivePatients 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.MethodsIn 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.ResultsThe 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.ConclusionGasMIL shows the best overall performance in diagnosing IM and atrophy when compared to pathologists, significantly enhancing their diagnostic capabilities.

Given the uncertainties surrounding the associations in previous epidemiological studies, we conducted linear and nonlinear Mendelian randomization (MR) studies to evaluate whether body mass index (BMI) associated with gastric cancer (GC) risk in European and Korean. Genome-wide association study-summary statistics were used from the Pan-UK Biobank, the Genetic Investigation of Anthropometric Traits consortium, the K-CHIP consortium, and BioBank Japan. BMI-associated single nucleotide polymorphisms (SNPs) were used as instrumental variables (IVs) in MR to identify the association between BMI and GC. Both linear and nonlinear MR analyses were performed. Sensitivity analyses were also conducted for individuals below or above a BMI of 24kg/m2. The study used 22 and 55 SNPs as IVs for BMI in European and Korean populations, respectively. Genetically predicted BMI was positively associated with GC risk in the European population (Odds ratio per 1kg/m2 increase; 95% CI = 1.17; 1.01-1.36 using simple median method), but no significant association was observed in the Korean population. However, the nonlinear MR identified a U-shaped association between BMI and GC in the Korean population, with both low and high BMIs associated with increased GC risk. A BMI of 24kg/m2 presented the lowest risk. Sensitivity analyses did not yield any genome-wide significant SNPs. While MR analysis suggests a linear association between BMI and GC in those of European ancestry, nonlinear MR hints at a U-shaped association in Koreans. This suggests the association between BMI and GC risk may vary according to ethnic ancestry.

Gastric cancer often exhibits discrepancies between the gross and pathological tumor boundaries, and the degree of discrepancy may be a tumor characteristic. However, whether these discrepancies influence oncological outcomes remains unclear. The data of patients who underwent total gastrectomy for gastric cancer from 2005 to 2018 were collected. A new parameter, ΔPM, which corresponds to the length of the discrepancy between the gross and pathological proximal boundaries, was calculated and the patients were divided into two groups: patients with long ΔPM and those with short ΔPM. Oncological outcomes were compared between the two groups. A length of 8mm was determined as the cutoff value for long or short ΔPM. Tumor size, growth pattern, pathological type, depth, and esophageal invasion were associated with ΔPM > 8mm. Overall survival of the ΔPM > 8mm group was significantly worse than that of the ΔPM ≤ 8mm group (5-year overall survival: 58% vs 78%; p < 0.0001). Multivariate analysis revealed that ΔPM > 8mm was an independent risk factor for poor survival and peritoneal metastasis. The likelihood ratio test revealed a significant interaction between pT status and ΔPM (p = 0.0007). Circumferential involvement and gross esophageal invasion were poorer survival factors in the ΔPM > 8mm group. ΔPM > 8mm is related to several clinicopathological characteristics and is an independent risk factor for poorer survival and peritoneal metastasis but not local recurrence. ΔPM > 8mm combined with circumferential involvement or esophageal invasion is associated with relatively poor survival outcomes.

Endoscopic submucosal dissection (ESD) is the standard treatment for early gastric cancer in Japan. Pathological evaluation of ESD specimens is considered essential to determine if additional gastrectomy is necessary. Usually, specimens resected by ESD are sliced into 2-3mm wide sections, and each section is examined for depth of tumor and lymphovascular invasion. Nevertheless, in most cases of additional gastrectomy, lymph node metastasis is not present. Given that there are few-studies on how clinical-decisions based on the pathologic-evaluation-method, in particular the specimen cut-width, influence patient outcomes, we retrospectively evaluated whether reducing the number of cuts to one-half or one-third would result in underestimation of the real need for additional surgery. The effect of the actual cut-width on recommended treatment (referral to operation) and patient-outcomes was also assessed. Pathological records of 498 lesions from 439 patients were reviewed and re-evaluated. All pathological descriptions are based on the gastric cancer classification system of the Japanese Gastric Cancer Association, 15th edition. In 5.8% and 8.5% of the total specimens, underdiagnosis of tumor-depth and lymphovascular invasion occurred when the number of sections was reduced to one-half and one-third, respectively. Significantly more submucosal invasions were found in the group in which the cut-with was between 3 and 4mm than in the group in which the cut width was less than 3mm. Evaluation of the appropriate cut-width is important and should be discussed from the standpoint of labor costs and lost opportunities to search for molecular markers in ESD materials.

A gene or variant has pleiotropic effects, and genetic variant identification across multiple phenotypes can provide a comprehensive understanding of biological pathways shared among different diseases or phenotypes. Discovery of genetic loci associated with multiple diseases can simultaneously support general interventions. Several meta-analyses have shown genetic associations with gastric cancer (GC); however, no study has identified associations with other phenotypes using this approach. Here, we applied disease network analysis and gene-based analysis (GBA) to examine genetic variants linked to GC and simultaneously associated with other phenotypes. We conducted a single-nucleotide polymorphism (SNP) level meta-analysis and GBA through a systematic genome-wide association study (GWAS) linked to GC, to integrate published results for the SNP variants and group them into major GC-associated genes. We then performed disease network and expression quantitative trait loci (eQTL) analyses to evaluate cross-phenotype associations and expression levels of GC-related genes. Seven genes (MTX1, GBAP1, MUC1, TRIM46, THBS3, PSCA, and ABO) were associated with GC as well as blood urea nitrogen (BUN), glomerular filtration rate (GFR), and uric acid (UA). In addition, 17 SNPs regulated the expression of genes located on 1q22, 24 SNPs regulated the expression of PSCA on 8q24.3, and rs7849820 regulated the expression of ABO on 9q34.2. Furthermore, rs1057941 and rs2294008 had the highest posterior causal probabilities of being a causal candidate SNP in 1q22, and 8q24.3, respectively. These findings identified seven GC-associated genes exhibiting a cross-association with GFR, BUN, and UA.

BackgroundComputational pathology uses deep learning (DL) to extract biomarkers from routine pathology slides. Large multicentric datasets improve performance, but such datasets are scarce for gastric cancer. This limitation could be overcome by Swarm Learning (SL).MethodsHere, we report the results of a multicentric retrospective study of SL for prediction of molecular biomarkers in gastric cancer. We collected tissue samples with known microsatellite instability (MSI) and Epstein–Barr Virus (EBV) status from four patient cohorts from Switzerland, Germany, the UK and the USA, storing each dataset on a physically separate computer.ResultsOn an external validation cohort, the SL-based classifier reached an area under the receiver operating curve (AUROC) of 0.8092 (± 0.0132) for MSI prediction and 0.8372 (± 0.0179) for EBV prediction. The centralized model, which was trained on all datasets on a single computer, reached a similar performance.ConclusionsOur findings demonstrate the feasibility of SL-based molecular biomarkers in gastric cancer. In the future, SL could be used for collaborative training and, thus, improve the performance of these biomarkers. This may ultimately result in clinical-grade performance and generalizability.

Gastric cancer (GC) is characterized by unique DNA methylation epigenotypes (MEs). However, MEs including adenocarcinomas of the esophagogastric junction (AEG) and background non-neoplastic columnar mucosae (NM) remain to be clarified. We analyzed the genome-wide DNA MEs of AEG, GC, and background NM using the Infinium 450k beadarray, followed by quantitative pyrosequencing validation. Large-scale data from The Cancer Genome Atlas (TCGA) were also reviewed. Unsupervised two-way hierarchical clustering using Infinium data of 21 AEG, 30 GC, and 11 NM revealed four DNA MEs: extremely high-ME (E-HME), high-ME (HME), low-ME (LME), and extremely low-ME (E-LME). Promoter methylation levels were validated by pyrosequencing in 146 samples. Non-inflammatory normal mucosae were clustered into E-LME, whereas gastric or esophagogastric junction mucosae with chronic inflammatory changes caused by either Helicobacter pylori infection or reflux esophagitis were clustered together into LME, suggesting that inflammation status determined DNA MEs regardless of the cause. Three cases of Barrett's-related adenocarcinoma were clustered into HME. Among 94 patients whose tumors could be clustered into one of four MEs, 11 patients with E-LME cancers showed significantly shorter overall survival than that in the other MEs, even with the multivariate Cox regression estimate. TCGA data also showed enrichment of AEG in HME and a poorer prognosis in E-LME. E-LME cases, newly confirmed in this study, form a unique subtype with poor prognosis that is not associated with inflammation-associated elevation of DNA methylation levels. LME could be acquired via chronic inflammation, regardless of the cause, and AEG might preferentially show HME.

BackgroundUbiquitous mitochondrial creatine kinase (uMtCK) transfers high-energy phosphates from mitochondrially generated ATP to creatine to generate phosphocreatine. uMtCK overexpression has been reported in several malignant tumors, however, the clinical significance and impact of uMtCK in gastric cancer (GC) has not been comprehensively studied.MethodsWe first examined uMtCK expression in GC by quantitative real-time PCR and western blot assays. Then the clinicopathological significance of aberrant uMtCK expression was determined by immunohistochemical staining in a GC tissue microarray. Kaplan–Meier analysis was used for survival analysis. The biological functions of uMtCK in GC cells were explored by wound-healing, transwell assays and glucose metabolism assays in vitro as well as a liver metastasis model by spleen injection in nude mice in vivo.ResultsWe verified that the expression of uMtCK was substantially elevated in GC tissues, significantly associating with a poorer prognosis in GC patients, especially for those with advanced stage. In univariate and multivariate analyses, uMtCK expression emerged as an independent prognostic factor for both disease-free survival and overall survival. Functionally, we demonstrated that uMtCK promoted glycolysis in GC cells and facilitated their migration, invasion and liver metastasis in vitro and in vivo. Mechanistically, uMtCK enhanced GC progression in a HK2-dependent glycolysis via acting the JNK-MAPK/JUN signaling pathway.ConclusionsuMtCK could serve as a novel independent prognostic biomarker as well as potential therapeutic target for GC patients, particularly for GC patients with an advanced UICC stage and tumor recurrence.

BackgroundGastric cancer is the fourth leading cause of cancer-related deaths globally. There is a paucity of national studies examining gastric cancer mortality in relation to treatment status. This study evaluated the survival trends in gastric adenocarcinoma and all gastric cancers stratified by treatment in Finland during 1987–2016.MethodsThis population-based, nationwide, retrospective cohort study included all gastric cancer patients registered in the Finnish Cancer Registry and Patient Registry. The survival rates were calculated for 1, 3, and 5 years, stratified by treatment. Prognostic factors were determined using Cox regression.ResultsA total of 18,713 non-cardia gastric adenocarcinoma, and 3617 cardia adenocarcinoma patients were included. Surgical treatment decreased for non-cardia adenocarcinoma and remained constant for cardia adenocarcinoma. In non-cardia adenocarcinoma, the 5-year survival declined from 17% to 16% from 1987–1991 to 2012–2016. In surgically treated patients, survival increased from 29% to 38%, while an increase from 4% to 7% in those undergoing chemotherapy and decrease from 6% to 3% in those not receiving any treatment were observed. In cardia adenocarcinoma, the 5-year survival increased from 10% to 18% in all patients, 16% to 40% in surgical patients, 0% to 5% in patients receiving chemotherapy, and from 5% to 9% in patients receiving no treatment. Earlier calendar periods, older age, male sex, and higher comorbidity were risk factors for poor prognosis.ConclusionsGastric non-cardia adenocarcinoma survival declined, limited to advanced stage patients not receiving any treatment. Gastric cardia cancer survival seems to have improved over time in Finland.Mini abstractThis study evaluated survival trends of gastric cancer in Finland during 1987–2016 and established that the 5-year survival is declining in non-cardia adenocarcinoma but improving in all gastric cancers.