Gastric adenocarcinoma of the fundic gland: A review of clinicopathological characteristics, treatment and prognosis

Kaempferol inhibited invasion and metastasis of gastric cancer cells by targeting AKT/GSK3β pathway based on network pharmacology and molecular docking

This study aims to explore the mechanisms of the inhibitory effect of kaempferol on the invasion and metastasis of gastric cancer (GC) cells through network pharmacology prediction and experimental verification. It identifies core targets via PPI network analysis and finds that kaempferol binds to these targets well. In vitro experiments showed that kaempferol could inhibit the proliferation, colony formation, migration and invasion of GC cells. Western blotting indicated kaempferol may reduce AKT and GSK3β phosphorylation, leading to lower expression of invasion-related genes SRC, MMP9, CXCR4, KDR, and MMP2. Overall, kaempferol may prevent migration and invasion of GC cells via the AKT/GSK3β signaling pathway.

Prognostic prediction of gastric cancer based on H&E findings and machine learning pathomics

AIM

In this research, we aimed to develop a model for the accurate prediction of gastric cancer based on H&E findings combined with machine learning pathomics.

METHODS

Transcriptome data, pathological images, and clinical data from 443 cases were retrieved from TCGA (The Cancer Genome Atlas Program) for survival analysis. The images were segmented using the Otsu algorithm, and features were extracted using the PyRadiomics package. Subsequently, the cases were randomly divided into a training cohort of 165 cases and a validation cohort of 69 cases. Features selected via minimum Redundancy - Maximum Relevance (mRMR)- recursive feature elimination (RFE) screening were used to train a model using the Gradient Boosting Machine (GBM) algorithm. The model's performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC), calibration curves, and decision curves. Additionally, the correlation between the Pathomics score (PS) and immune genes was examined.

RESULTS

In the multivariate analysis, heightened infiltration of activated CD4 memory T cells was strongly associated with improved overall survival (HR = 0.505, 95 % CI = 0.342-0.745, P < 0.001). The pathomic model, exhibiting robust predictive capability, demonstrated impressive AUC values of 0.844 and 0.750 in both study cohorts. The Decision Curve Analysis (DCA) unequivocally underscored the model's exceptional clinical utility. In a subsequent multivariate analysis, heightened infiltration of the PS also emerged as a significant protective factor for overall survival (HR = 0.506, 95 % CI = 0.329-0.777, P = 0.002).

CONCLUSION

The pathomic model based on H&E slides for predicting the infiltration degree of activated CD4 memory T cells, along with integrated bioinformatics analysis elucidating potential molecular mechanisms, offers novel prognostic indicators for the precise stratification and individualized prognosis of gastric cancer patients.

The white ring sign is useful for differentiating between fundic gland polyps and gastric adenocarcinoma of the fundic gland type

Background and study aims Gastric adenocarcinoma of the fundic gland type (GA-FG) is characterized by an elevated lesion with vessel dilation exhibiting branching architecture (DVBA). However, this feature is also found in fundic gland polyps (FGPs), posing a challenge in their differentiation. In this study, we aimed to investigate the clinicopathological features of gastric elevated lesions with DVBA and assess the efficacy of the white ring sign (WRS) as a novel marker for distinguishing between FGPs and GA-FGs. Methods We analyzed 159 gastric elevated lesions without DVBA and 51 gastric elevated lesions with DVBA, further dividing the latter into 39 in the WRS-positive group and 12 in the WRS-negative group. The clinicopathological features, diagnostic accuracy, and inter-rater reliability were analyzed. Results Univariate and multivariate analyses for gastric elevated lesions with DVBA identified the histological type consistent with FGPs and GA-FGs, along with the presence of round pits in the background gastric mucosa, as independent predictors. FGPs were present in 92.3% (36/39) of the WRS-positive group and GA-FGs were observed in 50.0% (6/12) of the WRS-negative group. WRS positivity and negativity exhibited high diagnostic accuracy, with 100% sensitivity, 80.0% specificity, and 94.1% accuracy for FGPs, and 100% sensitivity, 86.7% specificity, and 88.2% accuracy for GA-FGs. Kappa values for WRS between experts and nonexperts were 0.891 and 0.841, respectively, indicating excellent agreement. Conclusions WRS positivity and negativity demonstrate high diagnostic accuracy and inter-rater reliability for FGPs and GA-FGs, respectively, suggesting that WRS is a useful novel marker for distinguishing between FGPs and GA-FGs.

Prognostic Model of D2 Radical Gastrectomy Combined with Neoadjuvant Chemotherapy for Gastric Cancer

Purpose

The AJCC (the American Joint Committee on Cancer) ypTNM (post-neoadjuvant pathologic stage group) staging was established based on patients with lymphadenectomy scope less than D2 and did not include ypT0N0 patients with pathologically complete response (PCR). The purpose of this study was to construct a survival predictive model for gastric cancer patients after neoadjuvant chemotherapy and gastrectomy combined with D2 lymphadenectomy.

Patients and Methods

The multicenter data of 838 gastric cancer patients who received neoadjuvant chemotherapy and gastrectomy combined with D2 lymphadenectomy were analyzed retrospectively. These dual center patients were divided into training (n = 671, the Affiliated Hospital of Qingdao University) and validation (n = 167, Qingdao West Coast New Area Central Hospital) cohorts. Based on training cohort, univariate and multivariable COX regression analyses were performed to select the clinicopathological characteristics significantly correlating with overall survival and construct a nomogram. Based on training and validation cohorts, the distinguishing and calibrating capabilities of nomogram was evaluated by the receiver operating characteristic (ROC) curve, Harrell's concordance index (C-index), decision curve analysis (DCA) curve and calibration curve.

Results

Platelet-to-lymphocyte ratio (PLR), pathologic stage after neoadjuvant treatment: ypT and ypN stage, tumor regression grade (TRG) became independent variables intimately related to the prognosis and was used to construct nomograms of 3/5-year prognosis. The nomograms showed an accuracy in predicting OS (overall survival) rate, with area under the ROC curve (AUC) of 0.818 (95% CI = 0.753~0.883) and C-index of 0.801 (95% CI = 0.744~0.858) in validation cohort. Calibration curves showed satisfactory agreement between nomogram prediction and actual result, and DCA curves indicated the large positive net benefit and excellent clinical usefulness of nomogram.

Conclusion

This study successfully developed a nomogram to predict overall survival of gastric cancer patients after neoadjuvant chemotherapy and gastrectomy combined with D2 lymphadenectomy, which might have excellent predictive performance and clinical application value.

Oxyntic Gland Adenoma in a Patient With Refractory Reflux

A 58-year-old African American male was referred for endoscopic evaluation due to a persistent nine-year history of reflux. Previous endoscopy nine years ago revealed a small hiatal hernia and chronic gastritis caused by Helicobacter pylori (H. pylori), which was treated with triple therapy. During the current endoscopic evaluation, findings consistent with reflux esophagitis were identified, along with the discovery of an incidental 6 mm sessile polyp in the gastric fundus. Pathological examination revealed the presence of an oxyntic gland adenoma (OGA). Otherwise, the stomach was found to be unremarkable endoscopically and histologically. OGA is a rare gastric neoplasm that is primarily observed in Japan, with very few reported cases in North America. Studies have suggested a potential association with antacids, while the role of H. pylori in the development of OGA remains controversial. Our patient's OGA was completely resected during the endoscopy, with no recurrence noted on the three-month follow-up.

Identification of GNG7 as a novel biomarker and potential therapeutic target for gastric cancer via bioinformatic analysis and in vitro experiments

Gastric cancer (GC) is one of the most common malignancies with unfavorable prognoses. The present study aimed to identify novel biomarkers or potential therapeutic targets in GC via bioinformatic analysis and in vitro experiments. The Gene Expression Omnibus and The Cancer Genome Atlas databases were used to screen the differentially expressed genes (DEGs). After protein-protein interaction network construction, both module and prognostic analyses were performed to identify prognosis-related genes in GC. The expression patterns and functions of G protein γ subunit 7 (GNG7) in GC were then visualized in multiple databases and further verified using in vitro experiments. A total of 897 overlapping DEGs were detected and 20 hub genes were identified via systematic analysis. After accessing the prognostic value of the hub genes using the online server Kaplan-Meier plotter, a six-gene prognostic signature was identified, which was also significantly correlated with the process of immune infiltration in GC. The results of open-access database analyses suggested that GNG7 is downregulated in GC; this downregulation was associated with tumor progression. Furthermore, the functional enrichment analysis unveiled that the GNG7-coexpressed genes or gene sets were closely correlated with the proliferation and cell cycle processes of GC cells. Finally, in vitro experiments further confirmed that GNG7 overexpression inhibited GC cell proliferation, colony formation, and cell cycle progression and induced apoptosis. As a tumor suppressor gene, GNG7 suppressed the growth of GC cells via cell cycle blockade and apoptosis induction and thus may be used as a potential biomarker and therapeutic target for GC.

Prognostic value of antitumor drug targets prediction using integrated bioinformatic analysis for immunogenic cell death-related lncRNA model based on stomach adenocarcinoma characteristics and tumor immune microenvironment

Stomach adenocarcinoma (STAD) ranks as the fourth prevalent cause of mortality worldwide due to cancer. The prognosis for those suffering from STAD was bleak. Immunogenic cell death (ICD), a form of induced cellular death that causes an adaptive immune response and has increasing in anticancer treatment. However, it has not been ascertained how ICD-related lncRNAs affect STAD. Using univariate Cox regression and the TCGA database, lncRNAs with prognostic value were identified. Thereafter, we created a prognostic lncRNA-based model using LASSO. Kaplan-Meier assessment, time-dependent receiver operating characteristic (ROC) analyzation, independent prognostic investigation, and nomogram were used to assess model correctness. Additional research included evaluations of the immunological microenvironment, gene set enrichment analyses (GSEA), tumor mutation burdens (TMBs), tumor immune dysfunctions and exclusions (TIDEs), and antitumor compounds IC50 predictions. We found 24 ICD-related lncRNAs with prognostic value via univariate Cox analysis (p < 0.05). Subsequently, a risk model was proposed using five lncRNAs relevant to ICD. The risk signature, correlated with immune cell infiltration, had strong predictive performance. Individuals at low-risk group outlived those at high risk (p < 0.001). An evaluation of the 5-lncRNA risk mode including ROC curves, nomograms, and correction curves confirmed its predictive capability. The findings of functional tests revealed a substantial alteration in immunological conditions and the IC50 sensitivity for the two groups. Using five ICD-related lncRNAs, the authors developed a new risk model for STAD patients that could predict their cumulative overall survival rate and guide their individual treatment.

Identification of Hub Genes Associated With the Development of Stomach Adenocarcinoma by Integrated Bioinformatics Analysis

Objective

This study was conducted in order to gain a better understanding of the molecular mechanisms of stomach adenocarcinoma (STAD), which is necessary to predict the prognosis of STAD and develop novel gene therapy strategies.

Methods

In this study, the gene expression profile of GSE118916 in the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas Program (TCGA) was used to explore the differential co-expression genes of STAD and normal tissues.

Results

A total of 407 STAD samples were collected, consisting of 375 from stomach adenocarcinoma tissues and 32 from normal tissues, as well as RNA-seq count data for 19,600 genes. Forty-two differentially expressed genes were screened by weighted gene co-expression network analysis (WGCNA) and differentially expressed gene analysis. According to the functional annotation analysis of the clusterProfiler R package, these genes were analyzed for GO function enrichment, digestion (biological process), tube bottom material membrane (cell component), and oxidoreductase activity (molecular function). The KEGG pathway was enriched in gastric acid secretion and chemical carcinogenesis. In addition, Cytoscape's cytoHubba plug-in was used to identify seven hub genes (EWSR1, ESR1, CLTC, PCMT1, TP53, HUWE1, and HDAC1) in a protein-protein interaction (PPI) network consisting of 7 nodes and 11 edges. Compared with normal tissues, CLTC and TP53 genes were upregulated in stomach adenocarcinoma (P < 0.05). TP53 was expressed differently in stages II and IV, EWSR1 was expressed differently in stages II and III, and ESR1 was expressed differently in stages I-III. Among the seven hub genes, Kaplan-Meier analysis and TCGG showed that the expression levels of HDAC1 and CLTC were significantly correlated with OS in patients with stomach adenocarcinoma (P < 0.05). GEPIA2 analysis showed that ESR1 expression was closely correlated with OS and DFS in gastric adenocarcinoma (P < 0.05). Then, the expression of the genes and their correlations were revealed by the R2 Platform (http://r2.amc.nl). Finally, we collected 18 pairs of gastric mucosal tissues from normal people and cancer tissues from patients with stomach adenocarcinoma. The expression levels of the above seven hub genes and their relative protein expression were detected by RT-PCR and immunohistochemistry (IHC). The results showed that the gene and protein expression levels in stomach adenocarcinoma tissues were increased than those in the normal group.

Conclusion

In summary, we believe that the identified hub genes were related to the occurrence of stomach adenocarcinoma, especially the expression of ESR1, HDAC1, and CLTC genes, which are related to the prognosis and overall survival of patients and may become the potential for the future diagnosis and treatment of STAD.