Gastric Cancer Model Research Articles

Integrative Analysis Reveals Differential Characteristics of DDR1 Mutant and Wild-type Gastric Cancers and Constructs their Prediction Models.

The molecular typing of gastric cancer by TCGA is significant for the precision treatment of gastric cancer. However, the molecular typing of gastric cancer by TCGA lacks the typing of the rare gene DDR1. Therefore, this study aimed to integrate the analysis to reveal the differential features of DDR1 mutant and wild-type gastric cancers and construct their prediction models. RNAseq data from 375 gastric cancer patients were downloaded from the TCGA database to comprehensively compare the differences between mutant DDR1 and wild-type DDR1 gastric cancers and construct a prognostic model for wild-type DDR1 gastric cancer. First, the mutation rate of DDR1 in gastric cancer was 3.23%. Second, the upregulated genes of mutant DDR1 gastric cancer were different from those of wild-type DDR1 gastric cancer in terms of KEGG and GO enrichment. Next, both mutant DDR1 gastric cancers and wild-type DDR1 gastric cancers were associated with EPIC scores and tumour stemness in macrophages. In addition, mutant DDR1 gastric cancers were associated with the iron death-related genes RPL8, CS, and FANCD2 and the m6A-related gene RBM15, compared with wild-type DDR1 gastric cancers. Finally, the established LASSO regression model confirmed that the survival rate of the high-risk group of wild-- type DDR1 gastric cancer would be lower than that of the low-risk group. This study may provide a new molecular typing method for gastric cancer by comparing the differences between mutant DDR1 and wild-type DDR1 gastric cancer.

Construction and interpretation of machine learning-based prognostic models for survival prediction among intestinal-type and diffuse-type gastric cancer patients

BackgroundGastric cancer is one of the most common malignant tumors worldwide, with high incidence and mortality rates, and it has a complex etiology and complex pathological features. Depending on the tumor type, gastric cancer can be classified as intestinal-type and diffuse-type gastric cancer, each with distinct pathogenic mechanisms and clinical presentations. In recent years, machine learning techniques have been widely applied in the medical field, offering new perspectives for the diagnosis, treatment, and prognosis of gastric cancer patients.MethodsThis study recruited 2158 gastric cancer patients and constructed prognostic prediction models for both intestinal-type and diffuse-type gastric cancer. Clinical pathological data were collected from patients, and machine learning algorithms were used for feature selection and model construction. The performance of the models was validated with training and testing datasets. The Shapley additive explanations (SHAP) values were used to interpret the model predictions and identify the main factors that influence patient survival.ResultsIn the prognostic model for intestinal-type gastric cancer, the gradient boosting decision tree (GBDT) model demonstrated the best performance, with key features including pTNM, CA125, tumor size, CA199, and PALB. Similarly, in the prognostic model for diffuse-type gastric cancer, the GBDT model was utilized, with key features comprising pTNM, Borrmann type IV disease, lymphocyte (LYM), lactate dehydrogenase (LDH), potassium (K), perineural invasion (PNI), tumor size, and whole stomach location. Risk stratification analysis revealed that the prognosis of high-risk patients was significantly worse than that of low-risk patients.ConclusionMachine learning shows great potential in predicting survival outcomes of gastric cancer patients, providing strong support for the development of personalized treatment plans.

A CXCR4 partial agonist improves immunotherapy by targeting polymorphonuclear myeloid-derived suppressor cells and cancer-driven granulopoiesis.

Polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) are pathologically activated neutrophils that potently impair immunotherapy responses. The chemokine receptor CXCR4, a central regulator of hematopoiesis, represents an attractive PMN-MDSC target1. Here, we fused a secreted CXCR4 partial agonist TFF2 to mouse serum albumin (MSA) and demonstrated that TFF2-MSA peptide synergized with anti-PD-1 to induce tumor regression or eradication, inhibited distant metastases, and prolonged survival in multiple gastric cancer (GC) models. Using histidine decarboxylase (Hdc)-GFP transgenic mice to track PMN-MDSC in vivo , we found TFF2-MSA selectively reduced the immunosuppressive Hdc-GFP + CXCR4 hi tumor PMN-MDSCs while preserving proinflammatory neutrophils, thereby boosting CD8 + T cell-mediated anti-tumor response together with anti-PD-1. Furthermore, TFF2-MSA systemically reduced PMN-MDSCs and bone marrow granulopoiesis. In contrast, CXCR4 antagonism plus anti-PD-1 failed to provide a similar therapeutic benefit. In GC patients, expanded PMN-MDSCs containing a prominent CXCR4 + LOX-1 + subset are inversely correlated with the TFF2 level and CD8 + T cells in circulation. Collectively, our studies introduce a strategy of using CXCR4 partial agonism to restore anti-PD-1 sensitivity in GC by targeting PMN-MDSCs and granulopoiesis.

Development and validation of a prediction model for gastric cancer: a single-center prospective study.

This study aimed to develop and validate a novel nomogram for diagnosing gastric cancer (GC). In this prospective analysis, 146 patients of Wenzhou Central Hospital were recruited for a GC group and a benign lesion group and were divided into a training set and an internal validation set in a ratio of 7:3. Clinical and analytical characteristics were collected and analyzed by logistic regression analysis. The performance of the predictive model was evaluated using the receiver operating characteristic curve, calibration curve, and decision curve analysis. There were 5 variables, namely albumin, carcinoembryonic antigen, carbohydrate antigen 125, creatinine, and small proline-rich protein 2A, that were identified as the final parameters for the developed model. In the training and internal validation sets, the area under the curve of the model was 0.968 and 0.979, respectively, showing good diagnostic performance. This study developed and validated a new nomogram based on 5 parameters. This model shows good diagnostic performance in distinguishing GC from benign lesion groups and has certain significance in clinical application.

A cofactor-induced repressive type of transcription factor condensation can be induced by synthetic peptides to suppress tumorigenesis.

Transcriptional factors (TFs) act as key determinants of cell death and survival by differentially modulating gene expression. Here, we identified many TFs, including TEAD4, that form condensates in stressed cells. In contrast to YAP-induced transcription-activating condensates of TEAD4, we found that co-factors such as VGLL4 and RFXANK alternatively induced repressive TEAD4 condensates to trigger cell death upon glucose starvation. Focusing on VGLL4, we demonstrated that heterotypic interactions between TEAD4 and VGLL4 favor the oligomerization and assembly of large TEAD4 condensates with a nonclassical inhibitory function, i.e., causing DNA/chromatin to be aggregated and entangled, which eventually impede gene expression. Based on these findings, we engineered a peptide derived from the TEAD4-binding motif of VGLL4 to selectively induce TEAD4 repressive condensation. This "glue" peptide displayed a strong antitumor effect in genetic and xenograft mouse models of gastric cancer via inhibition of TEAD4-related gene transcription. This new type of repressive TF phase separation exemplifies how cofactors can orchestrate opposite functions of a given TF, and offers potential new antitumor strategies via artificial induction of repressive condensation.

Minimally Invasive Injectable Gel for Local Immunotherapy of Liver and Gastric Cancer.

Local immunotherapy represents a promising solution for preventing tumor recurrence and metastasis post tumor surgical resection by eliminating residue tumor cells as well as eliciting tumor-specific immune responses. Minimally invasive surgery has become a mainstream surgical method worldwide due to its advantages of aesthetics and rapid postoperative recovery. Unfortunately, the currently reported local immunotherapy strategies are mostly designed to be used after open laparotomy, which go against the current surgical philosophy of minimally invasive therapy and is not suitable for clinical translation. Aiming at this problem, a minimally invasive injectable gel (MIGel) is herein reported loaded with immunotherapeutic agents for gastric and liver cancer postoperative treatment. The MIGel is formed by crosslinking between oxidized dextran (ODEX) and 4-arm polyethylene glycol hydroxylamine (4-arm PEG-ONH2) through oxime bonds, which can be injected through a clinic-used minimally invasive drainage tube and adhered tightly to the tissue. The loaded oxaliplatin (OxP) and resiquimod (R848) can be released constantly over two weeks and resulted in over 75% cure rate in orthotopic mouse gastric and liver cancer model. Collectively, a concept of minimally invasive local immunotherapy is proposed and MIGel is designed for local intraperitoneal cancer immunotherapy through minimally invasive surgery, with good clinical translation potential.

Effects of phospholipase D1 inhibitory peptide on the growth and metastasis of gastric cancer cells

Phospholipase D1 (PLD1) contributes to cancer development and progression through its effects on cell proliferation, survival, invasion, metastasis, angiogenesis, drug resistance, and modulation of the tumor microenvironment. Its central role in these processes makes it a promising target for novel cancer treatments aimed at inhibiting its activity and disrupting the signaling pathways it regulates. In this study, we aimed to investigate the effect of PLD1 inhibition on gastric cancer cell growth using a novel peptide inhibitor, TAT-TVTSP. PLD1, which plays a role in cancer progression, catalyzes the conversion of phosphatidylcholine into choline and phosphatidic acid through hydrolysis. To effectively target PLD1 in cells, we engineered TAT-TVTSP by fusing a PLD1-inhibitory peptide (TVTSP) with a cell-penetrating peptide (TAT). We observed that TAT-TVTSP effectively inhibited PLD1 activity in AGS gastric cancer cells. Moreover, TAT-TVTSP significantly inhibited the mammalian target of the rapamycin signaling pathway, including the phosphorylation of key downstream targets such as S6K1, AKT, S473, glycogen synthase kinase-3b, and forkhead box O1. TAT-TVTSP did not induce cell death, but it triggered cell cycle arrest by activating p21 and p27 via AKT phosphorylation. Functional assays revealed that TAT-TVTSP significantly impaired the colony-forming ability of AGS cells, thus inhibiting cell proliferation. Transwell and wound-healing assays revealed that this peptide disrupted the cellular behaviors critical to cancer progression, such as migration and invasion. In vivo, TAT-TVTSP significantly reduced tumor growth in the xenograft model of gastric cancer without any toxicity. Overall, our results suggest that TAT-TVTSP is a novel therapeutic agent for PLD1-mediated cancers.

SUMOylation-induced membrane localization of TRPV1 suppresses proliferation and migration in gastric cancer cells

Gastric cancer (GC) remains a significant health challenge due to its high mortality rate and the limited efficacy of current targeted therapies. A critical barrier in developing more effective treatments is the lack of understanding of specific mechanisms driving GC progression. This study investigates the role of Transient Receptor Potential Vanilloid 1 (TRPV1), a non-selective cation channel known for its high Ca2+ permeability and tumor-suppressive properties in gastrointestinal cancers. Specifically, we explore the impact of SUMOylation—a dynamic and reversible post-translational modification—on TRPV1’s function in GC. We demonstrate that SUMOylation of TRPV1 inhibits cell proliferation and migration in MGC-803 and AGS GC cells. By mutating amino acids near TRPV1’s existing SUMO motif (slKpE), we created a bidirectional SUMO motif (EψKψE) that enhances TRPV1 SUMOylation, resulting in further suppression of GC cell proliferation and migration. In vivo studies support these findings, showing that TRPV1 SUMOylation prevents spontaneous tumorigenesis in a mouse GC model. Further investigation reveals that TRPV1 SUMOylation increases the protein’s membrane expression by inhibiting its interaction with the adaptor-related protein complex 2 mu 1 subunit (AP2M1). This elevated membrane expression leads to increased intracellular Ca2+ influx, activating the AMP-activated protein kinase (AMPK) pathway, which in turn inhibits the proliferation and migration of GC cells.

Identification of a novel prognostic model for gastric cancer utilizing glutamine-related genes

BackgroundGlutamine metabolism presents a promising avenue for cancer prevention and treatment, but the underlying mechanisms in gastric cancer (GC) progression remain elusive. MethodsThe TCGA-STAD and GEO GSE62254 datasets, containing gene expression, clinical information, and survival outcomes of GC, were meticulously examined. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were employed to excavate a key module (MEturquoise), which was used to intersect with glutamine metabolism-related genes (GMRGs) and differentially expressed genes (DEGs) to identify differentially expressed GMRGs (DE-GMRGs). LASSO and Cox Univariate analyses were implemented to determine risk model genes. Correlation of the risk model with clinical parameters, pathways, and tumor immune microenvironments, was analyzed, and its prognostic independence was validated by Cox analyses. Finally, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was performed to validate the expression levels of MYB, LRFN4, LMNB2, and SLC1A5 in GC and para-carcinoma tissue. ResultsThe excavation of 4521 DEGs led to the discovery of the key MEturquoise module, which exhibited robust correlations with GC traits. The intersection analysis identified 42 DE-GMRGs, among which six genes showed consistency. Further LASSO analysis established MYB, LRFN4, LMNB2, and SLC1A5 as pivotal risk model genes. The risk model demonstrated associations with oncogenic and metabolism-related pathways, inversely correlating with responses to immune checkpoint blockade therapies. This risk model, together with “age”, was validated to be an independent prognostic factor for GC. RT-qPCR result indicated that MYB, LRFN4, LMNB2, and SLC1A5 expressions were remarkably up-regulated in GC tissues comparison with para-carcinoma tissue. ConclusionThe present study has generated a novel risk module containing four DE-GMRGs for predicting the prognosis and the response to immune checkpoint blockade treatments for GC. This risk model provides new insights into the involvement of glutamine metabolism in GC, warranting further investigation.

A novel prognostic model based on telomere-related lncRNAs in gastric cancer.

Telomeres are specialized structures at the ends of chromosomes that are important for their protection. Over time, long non-coding RNAs (lncRNAs) have gradually come into the spotlight as essential biomarkers of proliferation, migration, and invasion of human malignant tumors. Nevertheless, the impact of telomere-related lncRNAs (TRLs) in gastric cancer is currently unknown. In the present study, we screen the TRLs and identify a prognostic TRLs signature in gastric cancer. First, telomere-related genes (TRGs) were retrieved from the website, and RNA sequencing (RNA-seq) data and clinical data of stomach adenocarcinoma (STAD) patients were gathered from The Cancer Genome Atlas (TCGA) database. Gastric cancer patients' lncRNAs and overall survival (OS) were found to be related using univariate Cox regression analysis. Next, least absolute shrinkage and selection operator (LASSO) regression analysis and multifactorial Cox regression analysis were used to further screen telomere-related differentially expressed lncRNAs (TRDELs), and finally six lncRNAs were obtained, including LINC01537, CFAP61-AS1, DIRC1, RABGAP1L-IT1, DBH-AS1, and REPIN1-AS1. According to these six TRDELs, a prognostic model for gastric cancer was constructed. The samples were divided into the training group and the testing group at random, and the reliability of prognostic model was validated in both groups and overall samples. In addition, we performed Kaplan-Meier (K-M) survival curve analysis, independent prognostic analysis, and functional enrichment analysis to validate the predictive value and independence of the model, as well as immune cell correlation analysis, clustering analysis, and principal component analysis (PCA) to further explore the relationship between this model and the tumor cells. Finally, we performed the drug sensitivity analysis to identify a few small molecules that may have a therapeutic effect on gastric cancer. Finally, we constructed a prognostic model for gastric cancer consisting of six TRDELs. According to the K-M curve, the prognosis of the low-risk group was noticeably superior than that of the high-risk group. Multivariate Cox regression analysis suggested that risk score was an independent prognostic element. Receiver operating characteristic (ROC) curves, nomogram, and calibration curve indicated that the prognostic model had good predictive ability. Functional enrichment analysis demonstrated major pathways with high- and low-risk groups. Next, both tumor microenvironment (TME) and immune correlation analysis showed discrepancy in the high- and low-risk groups. Through drug sensitivity analysis, we screened four small molecules that might be beneficial for gastric cancer treatment. A prognostic model consisting of these six TRDELs was capable to predict the prognosis of gastric cancer patients.

RETRACTION: The Novel Role of Circular RNA ST3GAL6 on Blocking Gastric Cancer Malignant Behaviours Through Autophagy Regulated by the FOXP2/MET/Mtor Axis.

P. Xu, X. Zhang, J. Cao, J. Yang, Z. Chen, W. Wang, S. Wang, L. Zhang, L. Xie, L. Fang, Y. Xia, Z. Xuan, J. Lv, H. Xu, and Z. Xu, "The Novel Role of Circular RNA ST3GAL6 on Blocking Gastric Cancer Malignant Behaviours Through Autophagy Regulated by the FOXP2/MET/Mtor Axis," Clinical and Translational Medicine 12, no.1 (2022): e707, https://doi.org/10.1002/ctm2.707. The above article, published online on 21 January 2022 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the journal Editor-in-Chief, Xiangdong Wang; the Shanghai Institute of Clinical Bioinformatics; and John Wiley & Sons Australia, Ltd. The retraction has been agreed upon following an investigation into concerns raised by a third party, which revealed inappropriate duplications of image panels within the article (Figures 6H and 7J) and between this article (Figures 2D, 7B, 7K, 8E and 8J) and another article previously published elsewhere by an overlapping group of authors in a different scientific context. The authors were unable to provide a satisfactory explanation and the raw data they supplied could not explain the identified issues. In addition, the cell line SGC-7901 used in this study has been reported as contaminated with HeLa cells, making it a problematic model for gastric cancer [1,2]. Given the extent of the identified issues, the editors have lost confidence in the data presented and the article's conclusions can no longer be considered reliable.

Low-dose apatinib optimizes the vascular normalization and enhances the antitumor effect of PD-1 inhibitor in gastric cancer.

Apatinib is a tyrosine kinase inhibitor that has shown potential in combination with immune checkpoint inhibitors (ICIs) in gastric cancer (GC); however, its role in GC is unclear. This research aims to investigate the effect of low-dose apatinib in GC, and analyze the mechanisms of its underlying action. A mouse model of GC was established, and the experimental mice were divided into different groups for different treatment: group NS (normal saline), group A (low-dose apatinib 50 mg/kg), group B (high-dose apatinib 200 mg/kg), group C [programmed cell death protein 1 (PD-1) inhibitor monotherapy], and group D (PD-1 inhibitor combined with low-dose apatinib). After 14 days of treatment, the tumor and blood samples were collected from all mice for histological and cytokine detection. Compared with the control group, mice in the low-dose apatinib group showed smaller tumor volumes and slower growth. CD31/α-smooth muscle actin (α-SMA) double staining revealed significantly higher coverage of perivascular cells in the low-dose apatinib group by contrast to the control and high-dose apatinib groups, suggesting that low-dose apatinib may alleviate hypoxia. Compared to the high-dose apatinib group, the expression of hypoxia inducible factor 1 alpha (HIF1α) significantly decreased in the low-dose apatinib group. Hematoxylin and eosin (HE) staining results showed a higher proportion of necrotic tumor tissues in the group of mice treated with low-dose apatinib combined with PD-1 inhibitor than in other groups. In addition, this combined treatment significantly reduced the expression of NG2 and HIF1α in mouse tumor tissues, indicating a more normalized vascular density, and also increased the proportion of CD8+ T cells. Low-dose apatinib enhances the antitumor effect of PD-1 inhibitor by normalizing tumor-related blood vessels, alleviating intratumor hypoxia and altering immunosuppressive microenvironment (IM).

Re-analysis of single cell and spatial transcriptomics data reveals B cell landscape in gastric cancer microenvironment and its potential crosstalk with tumor cells for clinical prognosis

BackgroundAt present, immunotherapy has become a powerful treatment for advanced gastric cancer (AGC), but not all patients can benefit from it. According to the latest research, the impact of B cell subpopulations on the immune microenvironment of gastric cancer (GC) is unknown. Exploring whether the interaction between B cells and tumor cells in GC affects the effectiveness of immunotherapy has attracted our interest.MethodsThis study involved the re-analysis of single-cell RNA (scRNA) and spatial transcriptomics (ST) data from publicly available datasets. The focus was on investigating the subpopulations and differentiation trajectories of B cells in the gastric cancer (GC) tumor immune microenvironment (TIME). Spatial transcriptomics (ST) and multiple immunofluorescence (mIF) revealed a clear co-localization pattern between B cells and tumor cells. Multiple immunotherapy datasets were collected to identify unique immunotherapy biomarkers. The unique immunotherapeutic potential of targeting CCL28 was validated through a mouse gastric cancer model. In addition, flow cytometry revealed changes in the tumor immune microenvironment targeting CCL28.ResultsThe re-analysis of ST data from multiple cancer types revealed a co-localization pattern between B cells and tumor cells. A significant number of IgA plasma cells were identified in the GC TIME. Five different tumor-infiltrating B cell subpopulations and two unique B cell differentiation trajectories were characterized, along with seven GC-related states. By analyzing the communication between GC cells and B cells, it was further discovered that tumor cells can influence and recruit plasma cells through CCL28-CCR10 signaling. Additionally, there was a crosstalk between GC cells and B cells. Finally, we identified the LAMA/CD44 signaling axis as a potential prognostic marker for immunotherapy through a large amount of immunotherapy data. We also validated through various animal tumor models that targeting CCL28 can significantly promote CD8+T cell infiltration and function in the TME by regulating B cell and plasma cell functions, and has the ability to synergize immunotherapy.ConclusionThe co-localization and crosstalk between GC cells and B cells significantly affect the efficacy of immunotherapy, and inhibiting the CCL28-CCR10 signal axis is a potential immunotherapy target for GC. Meanwhile, LAMA/CD44 pair may be a potential adverse indicator for immunotherapy and tumor prognosis.

Thirdhand smoke exposure promotes gastric tumor development in mouse and human

The pollution of indoor environments and the consequent health risks associated with thirdhand smoke (THS) are increasingly recognized in recent years. However, the carcinogenic potential of THS and its underlying mechanisms have yet to be thoroughly explored. In this study, we examined the effects of short-term THS exposure on the development of gastric cancer (GC) in vitro and in vivo. In a mouse model of spontaneous GC, CC036, we observed a significant increase in gastric tumor incidence and a decrease in tumor-free survival upon THS exposure as compared to control. RNA sequencing of primary gastric epithelial cells derived from CC036 mice showed that THS exposure increased expression of genes related to the extracellular matrix and cytoskeletal protein structure. We then identified a THS exposure-induced 91-gene expression signature in CC036 and a homologous 84-gene signature in human GC patients that predicted the prognosis, with secreted phosphoprotein 1 (SPP1) and tribbles pseudokinase 3 (TRIB3) emerging as potential targets through which THS may promote gastric carcinogenesis. We also treated human GC cell lines in vitro with media containing various concentrations of THS, which, in some exposure dose range, significantly increased their proliferation, invasion, and migration. We showed that THS exposure could activate the epithelial-mesenchymal transition (EMT) pathway at the transcript and protein level. We conclude that short-term exposure to THS is associated with an increased risk of GC and that activation of the EMT program could be one potential mechanism. Increased understanding of the cancer risk associated with THS exposure will help identify new preventive and therapeutic strategies for tobacco-related disease as well as provide scientific evidence and rationale for policy decisions related to THS pollution control to protect vulnerable subpopulations such as children.

Subtyping of gastric cancer based on basement membrane genes that stratifies the prognosis, immune infiltration and therapeutic response

Gastric cancer (GC) is highly heterogeneous and prone to metastasis, which are obstacles to the effectiveness of treatment. The basement membrane (BM) acts as a barrier to tumor cell invasion and metastasis. It is critical to investigate the relationship between BM status, metastasis, and patient prognosis. In several large cohorts, we investigated BM gene expression-based molecular classification and risk-prognosis models for GC, examined tumor microenvironment (TME) differences among different molecular subtypes, and developed risk models in predicting prognosis, immunotherapy effectiveness, and chemotherapy resistance. Three GC subtypes (BMclusterA/B/C) based on BM gene expression status were discovered. Each of the three GC subtypes has unique immune infiltration and activated oncogenic signals. Moreover, a 6-gene score (BMscore) predictive model was developed. The low BMscore group had a high tumor mutation burden, high immunogenicity, and low RHOJ expression levels, implying that individuals with GC in this category may be more susceptible to immunotherapy and treatment. The EMT subtype showed a considerably higher BMscore than the other subtypes in the Asian Organization for Research on Cancer (ACRG) molecular classification. Endothelial cells, smooth muscle cells, and fibroblasts may be engaged in regulating BM reorganization in GC progression, according to single-cell transcriptome analyses. In conclusion, we defined a novel molecular classification of GC based on BM genes, developed a prognostic risk model, and elucidated the cell subpopulations involved in BM remodeling at the single-cell level. This study has deepened the understanding of the relationship between GC metastasis and BM alterations, achieved prognostic stratification, and guided therapy.

Immunotherapies targeting the oncogenic fusion gene CLDN18-ARHGAP in gastric cancer

The CLDN18-ARHGAP fusion gene is an oncogenic driver newly discovered in gastric cancer. It was detected in 9% (8/87) of gastric cancer patients in our center. An immunogenic peptide specifically targeting CLDN18-ARHGAP fusion gene was generated to induce neoantigen-reactive T cells, which was proved to have specific and robust anti-tumor capacity both in in vitro coculture models and in vivo xenograft gastric cancer models. Apart from the immunogenic potential, CLDN18-ARHGAP fusion gene was also found to contribute to immune suppression by inducing a regulatory T (Treg) cell-enriched microenvironment. Mechanistically, gastric cancer cells with CLDN18-ARHGAP fusion activate PI3K/AKT-mTOR-FAS signaling, which enhances free fatty acid production of gastric cancer cells to favor the survival of Treg cells. Furthermore, PI3K inhibition could effectively reverse Treg cells upregulation to enhance anti-tumor cytotoxicity of neoantigen-reactive T cells in vitro and reduce tumor growth in the xenograft gastric cancer model. Our study identified the CLDN18-ARHGAP fusion gene as a critical source of immunogenic neoepitopes, a key regulator of the tumor immune microenvironment, and immunotherapeutic applications specific to this oncogenic fusion.

Genomic analyses identify 15 susceptibility loci and reveal HDAC2, SOX2-OT, and IGF2BP2 in a naturally-occurring canine model of gastric cancer.

Gastric cancer (GC) is the fifth most common human cancer worldwide, but the genetic etiology is largely unknown. We performed a Bayesian genome-wide association study and selection analyses in a naturally-occurring canine model of GC, the Belgian Tervuren and Sheepdog breeds, to elucidate underlying genetic risk factors. We identified 15 loci with over 90% predictive accuracy for the GC phenotype. Variant filtering revealed germline putative regulatory variants for the EPAS1 (HIF2A) and PTEN genes and a coding variant in CD101. Although closely related to Tervuren and Sheepdogs, Belgian Malinois rarely develop GC. Across-breed analyses uncovered protective haplotypes under selection in Malinois at SOX2-OT and IGF2BP2. Among Tervuren and Sheepdogs, HDAC2 putative regulatory variants were present at comparatively high frequency and were associated with GC. Here, we describe a complex genetic architecture governing GC in a dog model, including genes such as PDZRN3, that have not been associated with human GC.

Gamma-glutamyl transferase secreted by Helicobacter pylori promotes the development of gastric cancer by affecting the energy metabolism and histone methylation status of gastric epithelial cells

BackgroundHelicobacter pylori (H. pylori) infection is critical in the development and occurrence of gastric cancer. H. pylori secretes gamma-glutamyl transferase (GGT), which affects energy metabolism and histone methylation in mesenchymal stem cells. However, its effect on human gastric epithelial cells remains unclear. This study aimed to investigate the effects of GGT on energy metabolism and histone methylation in gastric epithelial cells and determine its role in the development and progression of H. pylori-induced gastric cancer.MethodsA GGT knockout H. pylori strain and mouse gastric cancer model were constructed, and alpha-ketoglutarate (α-KG) was added. The underlying mechanism was investigated using proteomics, immunohistochemistry, Western blotting, and other experimental assays.ResultsH. pylori can colonize the host’s stomach and destroy the gastric epithelium. GGT secreted by H. pylori decreased the concentration of glutamine in the stomach and increased H3K9me3 and H3K27me3 expression, which promoted the proliferation and migration of gastric epithelial cells. Additionally, α-KG reversed this effect. GGT increased the tumorigenic ability of nude mice. GGT, secreted by H. pylori, promoted the expression of ribosomal protein L15 (RPL15), while GGT knockout and supplementation with α-KG and trimethylation inhibitors reduced RPL15 expression and Wnt signaling pathway expression.ConclusionsH. pylori secreted GGT decreased the expression of glutamine and α-KG in gastric epithelial cells, increased the expression of histones H3K9me3 and H3K27me3, and activated the Wnt signaling pathway through RPL15 expression, ultimately changing the biological characteristics of the gastric epithelium and promoting the occurrence of gastric cancer. Altered energy metabolism and histone hypermethylation are important factors involved in this process.Graphical abstract

Impact of body composition parameters, age, and tumor staging on gastric cancer prognosis.

Research studies on gastric cancer have not investigated the combined impact of body composition, age, and tumor staging on gastric cancer prognosis. To address this gap, we used machine learning methods to develop reliable prediction models for gastric cancer. This study included 1,132 gastric cancer patients, with preoperative body composition and clinical parameters recorded, analyzed using Cox regression and machine learning models. The multivariate analysis revealed that several factors were associated with recurrence-free survival (RFS) and overall survival (OS) in gastric cancer. These factors included age (≥65 years), tumor-node-metastasis (TNM) staging, low muscle attenuation (MA), low skeletal muscle index (SMI), and low visceral to subcutaneous adipose tissue area ratios (VSR). The decision tree analysis for RFS identified six subgroups, with the TNM staging I, II combined with high MA subgroup showing the most favorable prognosis and the TNM staging III combined with low MA subgroup exhibiting the poorest prognosis. For OS, the decision tree analysis identified seven subgroups, with the subgroup featuring high MA combined with TNM staging I, II showing the best prognosis and the subgroup with low MA, TNM staging II, III, low SMI, and age ≥65 years associated with the worst prognosis. Cox regression identified key factors associated with gastric cancer prognosis, and decision tree analysis determined prognoses across different risk factor subgroups. Our study highlights that the combined use of these methods can enhance intervention planning and clinical decision-making in gastric cancer.

Paired organoids from primary gastric cancer and lymphatic metastasis are useful for personalized medicine

BackgroundOrganoids are approved by the US FDA as an alternative to animal experiments to guide drug development and for sensitivity screening. Stable organoids models of gastric cancer are desirable for personalized medicine and drug screening.MethodsTumor tissues from a primary cancer of the stomach and metastatic cancer of the lymph node were collected for 3D culture. By long-term culture for over 50 generations in vitro, we obtained stably growing organoid lines. We analyzed short tandem repeats (STRs) and karyotypes of cancer cells, and tumorigenesis of the organoids in nude mice, as well as multi-omics profiles of the organoids. A CCK8 method was used to determine the drugs sensitivity to fluorouracil (5-Fu), platinum and paclitaxel.ResultsPaired organoid lines from primary cancer (SPDO1P) and metastatic lymph node (SPDO1LM) were established with unique STRs and karyotypes. The organoid lines resulted in tumorigenesis in vivo and had clear genetic profiles. Compared to SPDO1P from primary cancer, upregulated genes of SPDO1LM from the metastatic lymph node were enriched in pathways of epithelial-mesenchymal transition and angiogenesis with stronger abilities of cell migration, invasion, and pro-angiogenesis. Based on drug sensitivity analysis, the SOX regimen (5-Fu plus oxaliplatin) was used for chemotherapy with an optimal clinical outcome.ConclusionsThe organoid lines recapitulate the drug sensitivity of the parental tissues. The paired organoid lines present a step-change toward living biobanks for further translational usage.