Molecular analysis of gastric cancer identifies subtypes associated with distinct clinical outcomes

Regulatory mechanism and promising clinical application of exosomal circular RNA in gastric cancer

Gastric cancer (GC) is one of the most common malignancies worldwide and the leading cause of cancer-related deaths. Exosomes are nanoscale extracellular vesicles secreted by a variety of cells and play an important role in cellular communication and epigenetics by transporting bioactive substances in the tumor microenvironment (TME). Circular RNA (circRNA) is a type of non-coding RNA (ncRNA) with a specific structure, which is widely enriched in exosomes and is involved in various pathophysiological processes mediated by exosomes. Exosomal circRNAs play a critical role in the development of GC by regulating epithelial-mesenchymal transition (EMT), angiogenesis, proliferation, invasion, migration, and metastasis of GC. Given the biological characteristics of exosomal circRNAs, they have more significant diagnostic sensitivity and specificity in the clinic and may become biomarkers for GC diagnosis and prognosis. In this review, we briefly describe the biogenesis of exosomes and circRNAs and their biological functions, comprehensively summarize the mechanisms of exosomal circRNAs in the development of GC and chemotherapy resistance, and finally, we discuss the potential clinical application value and challenges of exosomal circRNAs in GC.

LINC01226 promotes gastric cancer progression through enhancing cytoplasm-to-nucleus translocation of STIP1 and stabilizing β-catenin protein

Gastric cancer (GC) remains one of the most common malignances and the leading cause of cancer-related mortality worldwide. Although the critical role of several long non-coding RNAs (lncRNAs) transcribed from several GC-risk loci has been established, we still know little about the biological significance of these lncRNAs at most gene loci and how they play in cell signaling. In the present study, we identified a novel oncogenic lncRNA LINC01226 transcribed from the 1p35.2 GC-risk locus. LINC01226 shows markedly higher expression levels in GC specimens compared with those in normal tissues. High expression of LINC01226 is evidently correlated with worse prognosis of GC cases. In line with these, oncogenic LINC01226 promotes proliferation, migration and metastasis of GC cells ex vivo and in vivo. Importantly, LINC01226 binds to STIP1 protein, leads to disassembly of the STIP1-HSP90 complex, elevates interactions between HSP90 and β-catenin, stabilizes β-catenin protein, activates the Wnt/β-catenin signaling and, thereby, promote GC progression. Together, our findings uncovered a novel layer regulating the Wnt signaling in cancers and uncovers a new epigenetic mode of GC tumorigenesis. These discoveries also shed new light on the importance of functional lncRNAs as innovative therapeutic targets through precisely controlling protein-protein interactions in cancers.

The effects of ARID1A mutation in gastric cancer and its significance for treatment

Gastric cancer (GC) has emerged as a significant issue in public health all worldwide as a result of its high mortality rate and dismal prognosis. AT-rich interactive domain 1 A (ARID1A) is a vital component of the switch/sucrose-non-fermentable (SWI/SNF) chromatin remodeling complex, and ARID1A mutations occur in various tumors, leading to protein loss and decreased expression; it then affects the tumor biological behavior or prognosis. More significantly, ARID1A mutations will likely be biological markers for immune checkpoint blockade (ICB) treatment and selective targeted therapy. To provide theoretical support for future research on the stratification of individuals with gastric cancer with ARID1A as a biomarker to achieve precision therapy, we have focused on the clinical significance, predictive value, underlying mechanisms, and possible treatment strategies for ARID1A mutations in gastric cancer in this review.

Identification and immune landscape analysis of fatty acid metabolism genes related subtypes of gastric cancer

Fatty acid metabolism (FAM) is associated with prognosis and immune microenvironment remodeling in many tumors. It is currently unknown how FAM affects the immunological microenvironment and prognosis of Gastric cancer (GC). Therefore, the current work aims to categorize GC samples based on the expression status of genes involved in FAM and to identify populations that might benefit from immunotherapy. In total, 50 FAM genes associated with overall survival (OS) were determined through univariate Cox proportional hazard regression analysis by mining the public TCGA and GEO databases. The GSE84437 and TCGA-STAD cohort samples were divided into two clusters using the "NMF" R package. According to the survival curve, patients in Cluster-1 showed considerably longer OS than those in Cluster-2. Patients in Cluster-1 exhibited earlier T stages, more intestinal GCs, and were older. MSI molecular subtypes were mainly distributed in Cluster-1, while GS molecular subtypes were distributed primarily in Cluster-2. There were 227 upregulated and 22 down-regulated genes (logFC > 1 or logFC < - 1, FDR < 0.05) in Cluster-2 compared with Cluster-1. One hub module (edges = 64, nodes = 12) was identified with a module score of 11.636 through Cytoscape plug-in MCODE. KEGG and GO analysis showed that the hub genes were associated with the cell cycle and cell division. Different immune cell infiltrates profile, and immune pathway enrichment existed between the subtypes. In conclusion, the current findings showed that practically all immunological checkpoint and immunoregulatory genes were elevated in patients with Cluster-2 GC, indicating that FAM subtypes may be crucial in GC immunotherapy.

Association of genes in hereditary metabolic diseases with diagnosis, prognosis, and treatment outcomes in gastric cancer

Background

Aberrant metabolism is a major hallmark of cancers and hereditary diseases. Genes associated with inborn metabolic errors may also play roles in cancer development. This study evaluated the overall impact of these genes on gastric cancer (GC).

Methods

In total, 162 genes involved in 203 hereditary metabolic diseases were identified in the Human Phenotype Ontology database. Clinical and multi-omic data were acquired from the GC cohort of the Affiliated Hospital of Jiangsu University and other published cohorts. A 4-gene and 32-gene signature was established for diagnosis and prognosis or therapeutic prediction, respectively, and corresponding abnormal metabolism scores (AMscores) were calculated.

Results

The diagnostic AMscore showed high sensitivity (0.88-1.00) and specificity (0.89-1.00) to distinguish between GC and paired normal tissues, with area under the receiver operating characteristic curve (AUC) ranging from 0.911 to 1.000 in four GC cohorts. The prognostic or predictive AMscore was an independent predictor of overall survival (OS) in five GC cohorts and a predictor of the OS and disease-free survival benefit of postoperative chemotherapy or chemoradiotherapy in one GC cohort with such data. The AMscore adversely impacts immune biomarkers, including tumor mutation burden, tumor neoantigen burden, microsatellite instability, programmed death-ligand 1 protein expression, tumor microenvironment score, T cell receptor clonality, and immune cell infiltration detected by multiplex immunofluorescence staining. The AUC of the AMscore for predicting immunotherapy response ranging from 0.780 to 0.964 in four cohorts involving GC, urothelial cancer, melanoma, and lung cancer. The objective response rates in the low and high AMscore subgroups were 78.6% and 3.2%, 40.4% and 7%, 52.6% and 0%, and 72.7% and 0%, respectively (all p<0.001). In cohorts with survival data, a high AMscore was hazardous for OS or progression-free survival, with hazard ratios ranged from 5.79 to 108.59 (all p<0.001). Importantly, the AMscore significantly improved the prediction of current immune biomarkers for both response and survival, thus redefining the advantaged and disadvantaged immunotherapy populations.

Conclusions

Signatures based on genes associated with hereditary metabolic diseases and their corresponding scores could be used to guide the diagnosis and treatment of GC. Therefore, further validation is required.

Genetic landscape and PD-L1 expression in Epstein-Barr virus-associated gastric cancer according to the histological pattern

Epstein-Barr virus (EBV)-associated gastric cancer (EBVaGC) is a distinct molecular subtype of gastric cancer. This study aims to investigate genomic and clinicopathological characteristics of EBVaGC according to the histological pattern. We retrospectively collected 18 specimens of surgically resected EBVaGCs. Whole-exome sequencing was performed for all cases. Moreover, PD-L1 expression and tumor-infiltrating lymphocyte (TIL) percentage were investigated. Among 18 EBVaGCs, 10 cases were of intestinal histology, 3 were of poorly cohesive histology, and the remaining 5 were of gastric carcinoma with lymphoid stroma histology. Whole-exome sequencing revealed that EBVaGCs with intestinal histology harbored pathogenic mutations known to frequently occur in tubular or papillary adenocarcinoma, including TP53, KRAS, FBXW7, MUC6, ERBB2, CTNNB1, and ERBB2 amplifications. One patient with poorly cohesive carcinoma histology harbored a CDH1 mutation. Patients with EBVaGCs with intestinal or poorly cohesive carcinoma histology frequently harbored driver mutations other than PIK3CA, whereas those with EBVaGCs with gastric carcinoma with lymphoid stroma histology lacked other driver mutations. Moreover, the histological pattern of EBVaGCs was significantly associated with the levels of TILs (P = 0.005) and combined positive score (P = 0.027). In conclusion, patients with EBVaGCs with different histological patterns exhibited distinct genetic alteration, PD-L1 expression, and degree of TILs.

Discovery of potent STAT3 inhibitors using structure-based virtual screening, molecular dynamic simulation, and biological evaluation

Introduction

Signal transducer and activator of transcription 3 (STAT3) is ubiquitously hyper-activated in numerous cancers, rendering it an appealing target for therapeutic intervention.

Methods and results

In this study, using structure-based virtual screening complemented by molecular dynamics simulations, we identified ten potential STAT3 inhibitors. The simulations pinpointed compounds 8, 9, and 10 as forming distinct hydrogen bonds with the SH2 domain of STAT3. In vitro cytotoxicity assays highlighted compound 4 as a potent inhibitor of gastric cancer cell proliferation across MGC803, KATO III, and NCI-N87 cell lines. Further cellular assays substantiated the ability of compound 4 to attenuate IL-6-mediated STAT3 phosphorylation at Tyr475. Additionally, oxygen consumption rate assays corroborated compound 4's deleterious effects on mitochondrial function.

Discussion

Collectively, our findings position compound 4 as a promising lead candidate warranting further exploration in the development of anti-gastric cancer therapeutics.

Targeting myeloid checkpoint Siglec-10 reactivates antitumor immunity and improves anti-programmed cell death 1 efficacy in gastric cancer

OBJECTIVE

Immunotherapy has not yielded satisfactory therapeutic responses in gastric cancer (GC). However, targeting myeloid checkpoints holds promise for expanding the potential of immunotherapy. This study aims to evaluate the critical role of Siglec-10+ tumor-associated macrophages (TAMs) in regulating antitumor immunity and to explore the potential of the myeloid checkpoint Siglec-10 as an interventional target.

DESIGN

Siglec-10+ TAMs were assessed based on immunohistochemistry on tumor microarrays and RNA-sequencing data. Flow cytometry, RNA sequencing, and single-cell RNA-sequencing analysis were employed to characterize the phenotypic and transcriptional features of Siglec-10+ TAMs and their impact on CD8+ T cell-mediated antitumor immunity. The effectiveness of Siglec-10 blockade, either alone or in combination with anti-programmed cell death 1 (PD-1), was evaluated using an ex vivo GC tumor fragment platform based on fresh tumor tissues.

RESULTS

Siglec-10 was predominantly expressed on TAMs in GC, and associated with tumor progression. In Zhongshan Hospital cohort, Siglec-10+ TAMs predicted unfavorable prognosis (n=446, p<0.001) and resistance to adjuvant chemotherapy (n=331, p<0.001), which were further validated in exogenous cohorts. In the Samsung Medical Center cohort, Siglec-10+ TAMs demonstrated inferior response to pembrolizumab in GC (n=45, p=0.008). Furthermore, Siglec-10+ TAMs exhibited an immunosuppressive phenotype and hindered T cell-mediated antitumor immune response. Finally, blocking Siglec-10 reinvigorated the antitumor immune response and synergistically enhances anti-PD-1 immunotherapy in an ex vivo GC tumor fragment platform.

CONCLUSIONS

In GC, the myeloid checkpoint Siglec-10 contributes to the regulation of immunosuppressive property of TAMs and promotes the depletion of CD8+ T cells, ultimately facilitating immune evasion. Targeting Siglec-10 represents a potential strategy for immunotherapy in GC.

Gastric cancer peritoneal metastasis related signature predicts prognosis and sensitivity to immunotherapy in gastric cancer

Gastric cancer peritoneal metastases (GCPM) is a leading cause of GC-related death. Early detection of GCPM is critical for improving the prognosis of advanced GC. Differentially expressed genes (DEGs) were identified in the GSE62254 database to distinguish between GCPM and non-GCPM. The gastric cancer peritoneal metastases signature (GCPMs) was developed using DEGs. We analysed the effectiveness of GCPMs as indicators for prognosis, chemotherapy, and immune therapy response in GC patients. Subsequently, we analysed the correlation between GCPMs and immune microenvironment as well as immune escape in GC patients. Random forest model and immunohistochemistry was utilized to identify the crucial genes that can aid in the diagnosis of GCPM. We identified five DEGs and utilized their expression to construct GCPMs. Patients with high GCPMs had a higher likelihood of a poor prognosis, while those with low GCPMs appeared to potentially benefit more from chemotherapy. GCPMs were a dependable marker for predicting the response to immunotherapy. Additionally, GCPMs was found to be significantly linked to stromal score and cancer-associated fibroblasts. SYNPO2 has been identified as the gene with the highest significance in the diagnosis of GCPM. Immunohistochemistry suggests that SYNPO2-positive expression in tumour cells, fibroblasts, inflammatory cell may be associated with promoting peritoneal metastasis in GC. GCPMs have shown to be a promising biomarker for predicting the prognosis and response of GC patients to chemotherapy and immunotherapy. The use of GCPMs for individual tumour evaluation may pave the way for personalized treatment for GC patients in the future.

Comprehensive analysis of anoikis-related genes in prognosis and immune infiltration of gastric cancer based on bulk and single-cell RNA sequencing data

BACKGROUND

Accumulating evidence suggests that anoikis resistance is a key process in cancer cell metastasis, making it an attractive therapeutic target. Therefore, anoikis may become a new treatment for gastric cancer.

METHODS

We used the univariate Cox regression method to screen gastric cancer-related anoikis genes, and a prognostic risk model was established. We analyzed differences between high- and low-risk groups in terms of tumor infiltrating immune cells, gene mutation signatures, and treatment of gastric cancer. Analysis of model associated genes at single-cell resolution was performed.

RESULTS

We filtered to 12 anoikis-related genes and built a prognostic risk model using seven of them, which performed well in multiple datasets. Patients with CCDC178 mutations had a worse prognosis. We also found that patients at low risk were more likely to benefit from chemotherapy and immunotherapy. ERBB2 was found to be highly expressed in epithelial cells and fibroblasts. Our analysis also indicated that gastric cancer samples with high infiltration of iCAFs had a worse prognosis.

CONCLUSION

Seven anoikis-related genes were selected to establish a risk model. The model can be used to predict the prognosis of patients and guide the drug treatment, which provides a new idea for the evaluation and treatment of gastric cancer patients.

Deep sequencing reveals recurrent somatic mutations and distinct molecular subgroups in gastric cancer in Mizo population, North East India

In India, Mizoram has the highest incidence of gastric cancer (GC) which might be associated with environmental factors such as diet, Helicobacter pylori (H.pylori) and Epstein-Barr virus (EBV) infections, and somatic genomic alterations. We performed PCR cum sequencing and fragment analysis for detection of H. pylori/EBV infection and microsatellite Instability (MSI) in GC patients (N = 68). Somatic mutations were identified by targeted and exome sequencing. We found 87% of GC patients infected with H. pylori and or EBV. Pathogenic infections were mostly mutually exclusive with only 16% of coinfection. TP53, MUC6, and ARID1A were significantly mutated. Two molecular subgroups with distinctive mutational profiles were identified: (1) patients harboring mutations in TP53 and (2) patients harboring mutations in RTK/RAS/PI3-K signaling pathway and chromatin-remodeling genes. Therefore, EBV and H. pylori infections and somatic mutations in the genes involved in RTK/RAS/PI3K signaling pathway, chromatin-remodeling, and TP53 might drive GC development and progression in Mizo patients.

Microdissection of cancer-associated fibroblast infiltration subtypes unveils the secreted SERPINE2 contributing to immunosuppressive microenvironment and immuotherapeutic resistance in gastric cancer: A large-scale study integrating bulk and single-cell transcriptome profiling

In the era of immunotherapy, the suboptimal response rate and the development of acquired resistance among the initial beneficiaries continue to present significant challenges across multiple malignancies, including gastric cancer (GC). Considering that the interactions of tumor stroma, especially the cancer-associated fibroblasts (CAFs), with immune and tumor cells, play indispensable roles in tumor progression, tumor microenvironment remodeling and therapeutic responsiveness, in-depth exploration on the roles of CAFs and pivotal mediators of their functions may provide novel clues to increase the effectiveness of current immunotherapeutic drugs and further achieve synergistic antitumor response. Herein, through the consensus clustering of canonical biomarkers, three GC subclasses with different abundance of CAFs were virtually microdissected in four integrated bulk cohorts encompassing 2148 GC patients from 11 independent datasets. An extensive immunogenomic analysis revealed that tumors with high CAFs infiltration were characterized with unfavorable outcomes, aggressive phenotypes, decreased tumor immunogenicity, high risk of immune evasion and thus immunotherapeutic resistance. By leveraging large-scale single-cell transcriptomic profiling, a series of CAF-secreted proteins were identified, among which the SERPINE2 was confirmed to be restrictively enriched in stromal fibroblasts of GC tissues and contribute to promoting a protumor milieu and fostering an immunosuppressive microenvironment via bioinformatics computations and tissue microarray analysis. Moreover, pan-cancer investigations generalized the immunological roles of SERPINE2, especially in pan-gastrointestinal malignancies, with multiple real-world immunotherapy cohorts further confirming its implications on predicting immunotherapeutic efficacy. In conclusion, these findings suggest that the CAF-derived SERPINE2 is a promising immune-oncology target with therapeutic implications to further synergize the immunotherapeutic combinations.

Collagen-related gene expression level predicts the prognosis and immune therapy response

BACKGROUND

Gastric cancer patients responded differently to the same treatment strategy and had various prognoses for the lack of biomarkers to guide the therapy choice.

METHODS

RNA data of a local gastric cancer cohort with 103 patients were processed and used to explore potential treatment guiding factors. Cluster analysis was performed by non-negative matrix factorization. The expression level of collagen-related genes was evaluated by ssGSEA named collagen score (CS). Data from TCGA, ACRG, and an immune therapy cohort were utilized to explore prognosis and efficacy. Prognostic predictive power of CS was assessed using the nomogram.

RESULTS

In our study, local RNA data were processed by cluster analysis, and it was found that cluster 2 contained a worse tumor infiltration status. The GSEA result showed that collagen-related pathways were differentially activated in two clusters. In TCGA and ACRG cohorts, the CS can be used as an independent prognostic factor (TCGA OS: p = 0.018, HR = 3.5; ACRG OS: p = 0.014, HR = 4.88). An immunotherapy cohort showed that the patients with higher CS had a significantly worse ORR (p = 0.0025). The high CS group contained several cell death pathways down-regulated and contained the worse tumor microenvironment. The nomogram demonstrated the survival prediction capability of collagen score.

CONCLUSION

CS was verified as an independent prognostic factor and potentially reflected the therapeutic effect of immunotherapy. The CS could provide a new way to evaluate the clinical prognosis and response information helping develop the collagen-targeted treatment.

Molecular Testing in Stage 4 Stomach Cancer in India: A Single-Centre Experience

Introduction Advanced gastric cancer (GC) has a very poor prognosis, and chemotherapy has been the standard of care. The use of immunotherapy or targeted therapy in the stage 4 setting is dependent on molecular testing of the tumour. There is a paucity of data in the Indian scenario on testing for molecular markers in stage 4 GC. Therefore, in this study, we looked at the prevalence of human epidermal growth factor receptor 2 (HER2/neu) expression/amplification, deficient mismatch repair (d-MMR)/microsatellite instability (MSI) high status, and programmed death ligand 1 (PDL-1) status in stage 4 gastric/gastroesophageal junction (GEJ) adenocarcinoma. Methods A retrospective single-centre observational study was conducted between January 2017 and January 2022 of patients diagnosed with stage 4 GC/GEJ adenocarcinoma. Patient data were collected from stored electronic patient records. Data on stage 4 patients who underwent testing for HER2/neu, mismatch repair (MMR)/MSI, and PDL-1 status were recorded. Treatment received was also noted. Results During the study period, 139 patients were diagnosed with stage 4 GC/GEJ adenocarcinoma. HER2/neu testing was done in 99 stage 4 patients (71.2%), with a positivity rate of 16.16% (n = 16). All patients diagnosed as HER2/neu-positive were treated with trastuzumab. Testing of MMR status was carried out in 91 stage 4 patients (65.4%). d-MMR/MSI high was detected in eight patients (8.8%), of which germline MMR was detected as positive in one patient. Five of these eight patients (62.5%) received immune checkpoint inhibitors. PDL-1 testing was done in 61 of the 139 stage 4 patients (43.9%). Twenty patients (32.7%) had PDL-1 tumour proportion score > 1%/combined positive score > 1. Conclusion Molecular profiling has now become the standard while treating late-stage GC. HER2/neu-positive patients have improved survival due to the use of anti-HER2/neu-targeted therapies. It is important to look at not only PDL-1 but also MMR to identify patients who would be eligible and benefit from immunotherapy.

Advances and key focus areas in gastric cancer immunotherapy: A comprehensive scientometric and clinical trial review (1999-2023)

BACKGROUND

Gastric cancer (GC) is the sixth most common cancer and third leading cause of cancer-related deaths worldwide. Current treatments mainly rely on surgery- and chemotherapy-based systemic; however, the prognosis remains poor for advanced disease. Recent studies have suggested that immunotherapy has significant potential in cancer therapy; thus, GC immunotherapy may improve quality of life and survival for patients with this disease.

AIM

To provide a comprehensive overview of the knowledge structure and research hotspots of GC immunotherapy.

METHODS

We conducted a bibliometric analysis of publications on immunotherapy related to GC in the Web of Science Core Collection database. We analyzed 2013 pub-lications from 1999 to February 1, 2023, using the VOSviewer and CiteSpace software. We assessed publication and citation distributions using the WoS platform and explored research countries, institutions, journals, authors, references, and keywords (co-occurrence, timeline view, and burst analysis). In addition, we examined 228 trials on immunotherapy, 137 on adoptive cell therapy, 274 on immune checkpoint inhibitors (ICIs), and 23 on vaccines from ClinicalTrials.gov and the International Clinical Trials Registry Platform. The Impact Index Per Article for the top ten high-cited papers collected from Reference Citation Analysis (RCA) are presented.

RESULTS

Our bibliometric analysis revealed that the study of immunotherapy in GC has developed rapidly in recent years. China accounted for almost half the publications, followed by the United States. The number of publications in recent years has been growing continuously, and most institutions and authors with the most publications are from China. The main keywords or clusters identified were "tumor microenvironment", "adoptive immunotherapy", "dendritic therapy", and "microsatellite instability".

CONCLUSION

Our analysis of 2013 publications indicated that immunotherapy for GC has led to several new developments in recent years. Considerable progress has been made in vaccinations, immune checkpoint therapy, and adoptive cellular therapy. In particular, ICIs and chimeric antigen receptor T-cells are novel options for the treatment of GC. We suggest that the combination of ICIs, chemotherapy, targeted therapy, and other immunotherapies should be the primary research direction in the future.

Immune perturbation network identifies an EMT subtype with chromosomal instability and tumor immune-desert microenvironment

Most gastric cancer (GC) subtypes are identified through transcriptional profiling overlooking dynamic changes and interactions in gene expression. Based on the background network of global immune genes, we constructed sample-specific edge-perturbation matrices and identified four molecular network subtypes of GC (MNG). MNG-1 displayed the best prognosis and vigorous cell cycle activity. MNG-2 was enriched by immune-hot phenotype with the potential for immunotherapy response. MNG-3 and MNG-4 were identified with epithelial-mesenchymal transition (EMT) peculiarity and worse prognosis, termed EMT subtypes. MNG-3 was characterized by low mutational burden and stromal cells and considered a replica of previous subtypes associated with poor prognosis. Notably, MNG-4 was considered a previously undefined subtype with a dismal prognosis, characterized by chromosomal instability and immune-desert microenvironment. This subtype tended to metastasize and was resistant to respond to immunotherapy. Pharmacogenomics analysis showed three therapeutic agents (NVP-BEZ235, LY2606368, and rutin) were potential interventions for MNG-4.

Current and Emerging Role of Monoclonal Antibody-Based First-Line Treatment in Advanced Gastro-Esophageal and Gastric Cancer

Gastric cancer is the fifth most common malignancy worldwide and one of the main causes of cancer-related death. While surgical treatment is the only curative option for early disease, many have inoperable or advanced disease at diagnosis. Treatment in this case would be a combination of chemotherapy and immunotherapy. Gastro-esophageal (GEJ) and gastric cancer (GC) genetic profiling with current molecular diagnostic techniques has significantly changed the therapeutic landscape in advanced cancers. The identification of key players in GEJ and GC survival and proliferation, such as human epidermal growth factor 2 (HER2), vascular endothelial growth factor (VEGF), and programmed cell death protein 1 (PD-1)/programmed cell death ligand-1 (PD-L1), has allowed for the individualization of advanced cancer treatment and significant improvement in overall survival and progression-free survival of patients. This review comprehensively examines the current and emerging role of monoclonal antibody-based first-line treatments in advanced GEJ and GC. We explore the impact of monoclonal antibodies targeting HER2, VEGF, PD-1/PD-L1, and Claudin 18.2 (CLDN18.2) on the first-line treatment landscape by talking about key clinical trials. This review emphasizes the importance of biomarker testing for optimal treatment selection and provides practical recommendations based on ASCO guidelines.

Gastric Cancer: Molecular Mechanisms, Novel Targets, and Immunotherapies: From Bench to Clinical Therapeutics

Gastric cancer is a global health concern, ranking fifth in cancer diagnoses and fourth in cancer-related deaths worldwide. Despite recent advancements in diagnosis, most cases are detected at advanced stages, resulting in poor outcomes. However, recent breakthroughs in genome analysis have identified biomarkers that hold positive clinical significance for GC treatment. These biomarkers and classifications offer the potential for more precise diagnostic and therapeutic approaches for GC patients. In this review, we explore the classification and molecular pathways in this disease, highlighting potential biomarkers that have emerged in recent studies including targeted therapies and immunotherapies. These advancements provide a promising direction for improving the management of GC.

Predictive Biomarkers for Immunotherapy in Gastric Cancer: Current Status and Emerging Prospects

Gastric cancer presents substantial management challenges, and the advent of immunotherapy has ignited renewed hope among patients. Nevertheless, a significant proportion of patients do not respond to immunotherapy, and adverse events associated with immunotherapy also occur on occasion, underscoring the imperative to identify suitable candidates for treatment. Several biomarkers, including programmed death ligand-1 expression, tumor mutation burden, mismatch repair status, Epstein-Barr Virus infection, circulating tumor DNA, and tumor-infiltrating lymphocytes, have demonstrated potential in predicting the effectiveness of immunotherapy in gastric cancer. However, the quest for the optimal predictive biomarker for gastric cancer immunotherapy remains challenging, as each biomarker carries its own limitations. Recently, multi-omics technologies have emerged as promising platforms for discovering novel biomarkers that may help in selecting gastric cancer patients likely to respond to immunotherapy. The identification of reliable predictive biomarkers for immunotherapy in gastric cancer holds the promise of enhancing patient selection and improving treatment outcomes. In this review, we aim to provide an overview of clinically established biomarkers of immunotherapy in gastric cancer. Additionally, we introduce newly reported biomarkers based on multi-omics studies in the context of gastric cancer immunotherapy, thereby contributing to the ongoing efforts to refine patient stratification and treatment strategies.

CDH1 loss promotes diffuse-type gastric cancer tumorigenesis via epigenetic reprogramming and immune evasion

Diffuse-type gastric adenocarcinoma (DGAC) is a deadly cancer often diagnosed late and resistant to treatment. While hereditary DGAC is linked to CDH1 gene mutations, causing E-Cadherin loss, its role in sporadic DGAC is unclear. We discovered CDH1 inactivation in a subset of DGAC patient tumors. Analyzing single-cell transcriptomes in malignant ascites, we identified two DGAC subtypes: DGAC1 (CDH1 loss) and DGAC2 (lacking immune response). DGAC1 displayed distinct molecular signatures, activated DGAC-related pathways, and an abundance of exhausted T cells in ascites. Genetically engineered murine gastric organoids showed that Cdh1 knock-out (KO), KrasG12D, Trp53 KO (EKP) accelerates tumorigenesis with immune evasion compared to KrasG12D, Trp53 KO (KP). We also identified EZH2 as a key mediator promoting CDH1 loss-associated DGAC tumorigenesis. These findings highlight DGAC's molecular diversity and potential for personalized treatment in CDH1-inactivated patients.

Learning Individual Survival Models from PanCancer Whole Transcriptome Data

PURPOSE

Personalized medicine attempts to predict survival time for each patient, based on their individual tumor molecular profile. We investigate whether our survival learner in combination with a dimension reduction method can produce useful survival estimates for a variety of patients with cancer.

EXPERIMENTAL DESIGN

This article provides a method that learns a model for predicting the survival time for individual patients with cancer from the PanCancer Atlas: given the (16,335 dimensional) gene expression profiles from 10,173 patients, each having one of 33 cancers, this method uses unsupervised nonnegative matrix factorization (NMF) to reexpress the gene expression data for each patient in terms of 100 learned NMF factors. It then feeds these 100 factors into the Multi-Task Logistic Regression (MTLR) learner to produce cancer-specific models for each of 20 cancers (with >50 uncensored instances); this produces "individual survival distributions" (ISD), which provide survival probabilities at each future time for each individual patient, which provides a patient's risk score and estimated survival time.

RESULTS

Our NMF-MTLR concordance indices outperformed the VAECox benchmark by 14.9% overall. We achieved optimal survival prediction using pan-cancer NMF in combination with cancer-specific MTLR models. We provide biological interpretation of the NMF model and clinical implications of ISDs for prognosis and therapeutic response prediction.

CONCLUSIONS

NMF-MTLR provides many benefits over other models: superior model discrimination, superior calibration, meaningful survival time estimates, and accurate probabilistic estimates of survival over time for each individual patient. We advocate for the adoption of these cancer survival models in clinical and research settings.

Definition of a Novel Immunogenic Cell Death-Relevant Gene Signature Associated with Immune Landscape in Gastric Cancer

Immunogenic cell death (ICD) induces anti-tumor immunity and aids in dismantling the immunosuppressive immune microenvironment (TME), which belongs to a type of regulated cell death. The differentiation of gastric cancer (GC) subtypes and the discovery of prognostic biomarkers are crucial for its treatment because GC is a disease that is both highly heterogeneous and aggressive. However, although the induction of ICD in tumor cells is associated with a favorable prognosis, the exact mechanism of its role in GC remains unclear. Transcriptome profiling data and clinical data of GC patients were retrieved from The Cancer Genome Atlas (TCGA) database. Herein, patients were classified with the consensus clustering algorithm, and the associated biological functions and immune microenvironment infiltration were explored based on the expression of ICD-associated genes. A risk score signature consisting of 11 ICD-related genes was established via the least absolute shrinkage and selection operator regression (LASSO) method. We have retrieved similar studies in recent years and compared them with our study using the time-dependent receiver operating characteristic (ROC) curves. Gene set variation analysis (GSVA) and single sample gene set enrichment analysis (ssGSEA) were performed to explore the association between the signature and tumor microenvironment (TME). Two distinct subtypes associated with ICD in GC were identified, each with a different prognosis. The ICD-high expression subtype was associated with higher immune cell infiltration and a better prognosis. The ICD-related gene signature containing 11 genes (CGB5, Z84468.1, APOA5, EPHA8, CLEC18C, TLR7, MUC7, MUC15, CTLA4, CALB2, and UGT2B28), could independently and accurately predict the prognosis of GC. In this study, an ICD-based classification was conducted to assist in the diagnosis and personalized therapy for GC. The ICD-related genes risk score model was established to predict prognosis.

Exploring the molecular characteristics of the malignant potential of gastric adenocarcinoma with enteroblastic differentiation

AIMS

Gastric adenocarcinoma with enteroblastic differentiation (GAED) is a rare subset of alpha-fetoprotein (AFP)-producing carcinomas with poor prognosis. However, the molecular features associated with the malignant potential of GEAD remain partially elucidated.

METHODS AND RESULTS

In this study, the relationship between clinicopathological parameters and aggressive biological behaviour was analysed in 37 patients with GAED. The results showed that GAED tended to infiltrate the deep layer of the gastric wall and possessed more frequent vascular invasion than conventional gastric adenocarcinoma (CGA) (P < 0.001). All distant metastases were observed in the GAED group, not the CGA group (P < 0.001). High HER2 expression was found in nearly 24.32% of the informative cases, and none showed EBV-encoded RNA positivity or deficient mismatch repair. The most frequently mutated gene in GAED was p53. Programmed cell death-ligand 1 (PD-L1) immunostaining revealed 13 patients with a combined positive score (CPS) ≥ 5 (65%, 13 of 20). Thus, based on these molecular markers (immunostaining, in situ hybridisation and mutation analysis), GAED may be classified as a unique subgroup of the chromosomal instability subtype with HER2+ /EBV- /MSS/TP53+ /PD-L1+ . Next-generation sequencing analyses showed that mutations in the TOPI, ELOA and NOTCH3 genes were found only in GAED, and abnormally expressed genes in GAED were significantly enriched in hepatocellular carcinoma-, gland development-, and gastric cancer-related pathways.

CONCLUSION

The HER2+ /EBV- /MSS/TP53+ /PD-L1+ profile and hepatocellular carcinoma-related pathways may be significant in the malignant potential of GAED. In addition to anti-HER2 therapy, immune check-point inhibitors may be an effective treatment option for patients with GAED.

Quantitative Analysis on Molecular Characteristics Evolution of Gastric Cancer Progression and Prognosis

The dynamic changes of key biological characteristics from gastric low-grade intraepithelial neoplasia (LGIN) to high-grade intraepithelial neoplasia (HGIN) to early gastric cancer (EGC) are still unclear, which greatly affect the accurate diagnosis and treatment of EGC and prognosis evaluation of gastric cancer (GC). In this study, bioinformatics methods/tools are applied to quantitatively analyze molecular characteristics evolution of GC progression, and a prognosis model is constructed. This study finds that some dysregulated differentially expressed mRNAs (DEmRNAs) in the LGIN stage may continue to promote the occurrence and development of EGC. Among the LGIN, HGIN, and EGC stages, there are differences and relevance in the transcription expression patterns of DEmRNAs, and the activation related to immune cells is very different. The biological functions continuously changed during the progression from LGIN to HGIN to EGC. The COX model constructed based on the three EGC-related DEmRNAs has GC prognostic risk prediction ability. The evolution of biological characteristics during the development of EGC mined by the authors provides new insight into understanding the molecular mechanism of EGC occurrence and development. The three-gene prognostic risk model provides a new method for assisting GC clinical treatment decisions.

MSI-XGNN: an explainable GNN computational framework integrating transcription- and methylation-level biomarkers for microsatellite instability detection

Microsatellite instability (MSI) is a hypermutator phenotype caused by DNA mismatch repair deficiency. MSI has been reported in various human cancers, particularly colorectal, gastric and endometrial cancers. MSI is a promising biomarker for cancer prognosis and immune checkpoint blockade immunotherapy. Several computational methods have been developed for MSI detection using DNA- or RNA-based approaches based on next-generation sequencing. Epigenetic mechanisms, such as DNA methylation, regulate gene expression and play critical roles in the development and progression of cancer. We here developed MSI-XGNN, a new computational framework for predicting MSI status using bulk RNA-sequencing and DNA methylation data. MSI-XGNN is an explainable deep learning model that combines a graph neural network (GNN) model to extract features from the gene-methylation probe network with a CatBoost model to classify MSI status. MSI-XGNN, which requires tumor-only samples, exhibited comparable performance with two well-known methods that require tumor-normal paired sequencing data, MSIsensor and MANTIS and better performance than several other tools. MSI-XGNN also showed good generalizability on independent validation datasets. MSI-XGNN identified six MSI markers consisting of four methylation probes (EPM2AIP1|MLH1:cg14598950, EPM2AIP1|MLH1:cg27331401, LNP1:cg05428436 and TSC22D2:cg15048832) and two genes (RPL22L1 and MSH4) constituting the optimal feature subset. All six markers were significantly associated with beneficial tumor microenvironment characteristics for immunotherapy, such as tumor mutation burden, neoantigens and immune checkpoint molecules such as programmed cell death-1 and cytotoxic T-lymphocyte antigen-4. Overall, our study provides a powerful and explainable deep learning model for predicting MSI status and identifying MSI markers that can potentially be used for clinical MSI evaluation.

Dynamic single-cell mapping unveils Epstein‒Barr virus-imprinted T-cell exhaustion and on-treatment response

Epstein‒Barr virus (EBV)-associated gastric cancer (GC) manifests an intriguing immunotherapy response. However, the cellular basis for EBV-imprinted tumour immunity and on-treatment response remains undefined. This study aimed to finely characterize the dynamic tumour immune contexture of human EBV (+) GC treated with immunochemotherapy by longitudinal scRNA-seq and paired scTCR/BCR-seq. EBV (+) GC exhibits an inflamed-immune phenotype with increased T-cell and B-cell infiltration. Immunochemotherapy triggers clonal revival and reinvigoration of effector T cells which step to determine treatment response. Typically, an antigen-specific ISG-15+CD8+ T-cell population is highly enriched in EBV (+) GC patients, which represents a transitory exhaustion state. Importantly, baseline intratumoural ISG-15+CD8+ T cells predict immunotherapy responsiveness among GC patients. Re-emerged clonotypes of pre-existing ISG-15+CD8+ T cells could be found after treatment, which gives rise to a CXCL13-expressing effector population in responsive EBV (+) tumours. However, LAG-3 retention may render the ISG-15+CD8+ T cells into a terminal exhaustion state in non-responsive EBV (+) tumours. In accordance, anti-LAG-3 therapy could effectively reduce tumour burden in refractory EBV (+) GC patients. Our results delineate a distinct implication of EBV-imprinted on-treatment T-cell immunity in GC, which could be leveraged to optimize the rational design of precision immunotherapy.

Dual-layer spectral-detector CT for predicting microsatellite instability status and prognosis in locally advanced gastric cancer

OBJECTIVE

To construct and validate a prediction model based on dual-layer detector spectral CT (DLCT) and clinico-radiologic features to predict the microsatellite instability (MSI) status of gastric cancer (GC) and to explore the relationship between the prediction results and patient prognosis.

METHODS

A total of 264 GC patients who underwent preoperative DLCT examination were randomly allocated into the training set (n = 187) and validation set (n = 80). Clinico-radiologic features and DLCT parameters were used to build the clinical and DLCT model through multivariate logistic regression analysis. A combined DLCT parameter (CDLCT) was constructed to predict MSI. A combined prediction model was constructed using multivariate logistic regression analysis by integrating the significant clinico-radiologic features and CDLCT. The Kaplan-Meier survival analysis was used to explore the prognostic significant of the prediction results of the combined model.

RESULTS

In this study, there were 70 (26.52%) MSI-high (MSI-H) GC patients. Tumor location and CT_N staging were independent risk factors for MSI-H. In the validation set, the area under the curve (AUC) of the clinical model and DLCT model for predicting MSI status was 0.721 and 0.837, respectively. The combined model achieved a high prediction efficacy in the validation set, with AUC, sensitivity, and specificity of 0.879, 78.95%, and 75.4%, respectively. Survival analysis demonstrated that the combined model could stratify GC patients according to recurrence-free survival (p = 0.010).

CONCLUSION

The combined model provides an efficient tool for predicting the MSI status of GC noninvasively and tumor recurrence risk stratification after surgery.

CRITICAL RELEVANCE STATEMENT

MSI is an important molecular subtype in gastric cancer (GC). But MSI can only be evaluated using biopsy or postoperative tumor tissues. Our study developed a combined model based on DLCT which could effectively predict MSI preoperatively. Our result also showed that the combined model could stratify patients according to recurrence-free survival. It may be valuable for clinicians in choosing appropriate treatment strategies to avoid tumor recurrence and predicting clinical prognosis in GC.

KEY POINTS

• Tumor location and CT_N staging were independent predictors for MSI-H in GC. • Quantitative DLCT parameters showed potential in predicting MSI status in GC. • The combined model integrating clinico-radiologic features and CDLCT could improve the predictive performance. • The prediction results could stratify the risk of tumor recurrence after surgery.

Transcriptome profiling of patient-derived tumor xenografts suggests novel extracellular matrix-related signatures for gastric cancer prognosis prediction

BACKGROUND

A major obstacle to the development of personalized therapies for gastric cancer (GC) is the prevalent heterogeneity at the intra-tumor, intra-patient, and inter-patient levels. Although the pathological stage and histological subtype diagnosis can approximately predict prognosis, GC heterogeneity is rarely considered. The extracellular matrix (ECM), a major component of the tumor microenvironment (TME), extensively interacts with tumor and immune cells, providing a possible proxy to investigate GC heterogeneity. However, ECM consists of numerous protein components, and there are no suitable models to screen ECM-related genes contributing to tumor growth and prognosis. We constructed patient-derived tumor xenograft (PDTX) models to obtain robust ECM-related transcriptomic signatures to improve GC prognosis prediction and therapy design.

METHODS

One hundred twenty two primary GC tumor tissues were collected to construct PDTX models. The tumorigenesis rate and its relationship with GC prognosis were investigated. Transcriptome profiling was performed for PDTX-originating tumors, and least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied to extract prognostic ECM signatures and establish PDTX tumorigenicity-related gene (PTG) scores. The predictive ability of the PTG score was validated using two independent cohorts. Finally, we combined PTG score, age, and pathological stage information to establish a robust nomogram for GC prognosis prediction.

RESULTS

We found that PDTX tumorigenicity indicated a poor prognosis in patients with GC, even at the same pathological stage. Transcriptome profiling of PDTX-originating GC tissues and corresponding normal controls identified 383 differentially expressed genes, with enrichment of ECM-related genes. A robust prognosis prediction model using the PTG score showed robust performance in two validation cohorts. A high PTG score was associated with elevated M2 polarized macrophage and cancer-associated fibroblast infiltration. Finally, combining the PTG score with age and TNM stage resulted in a more effective prognostic model than age or TNM stage alone.

CONCLUSIONS

We found that ECM-related signatures may contribute to PDTX tumorigenesis and indicate a poor prognosis in GC. A feasible survival prediction model was built based on the PTG score, which was associated with immune cell infiltration. Together with patient ages and pathological TNM stages, PTG score could be a new approach for GC prognosis prediction.

Establishment of a 7-gene expression panel to improve the prognosis classification of gastric cancer patients

Gastric cancer (GC) ranks fifth in incidence and fourth in mortality worldwide. The high death rate in patients with GC requires new biomarkers for improving survival estimation. In this study, we performed a transcriptome-based analysis of five publicly available cohorts to identify genes consistently associated with prognosis in GC. Based on the ROC curve, patients were categorized into high and low-expression groups for each gene using the best cutoff point. Genes associated with survival (AUC > 0.5; univariate and multivariate Cox regressions, p < 0.05) were used to model gene expression-based scores by weighted sum using the pooled Cox β regression coefficients. Cox regression (p < 0.05), AUC > 0.5, sensitivity > 0.5, and specificity > 0.5 were considered to identify the best scores. Gene set enrichment analysis (KEGG, REACTOME, and Gene Ontology databases), as well as microenvironment composition and stromal cell signatures prediction (CIBERSORT, EPIC, xCell, MCP-counter, and quanTIseq web tools) were performed. We found 11 genes related to GC survival in the five independent cohorts. Then, we modeled scores by calculating all possible combinations between these genes. Among the 2,047 scores, we identified a panel based on the expression of seven genes. It was named GES7 and is composed of CCDC91, DYNC1I1, FAM83D, LBH, SLITRK5, WTIP, and NAP1L3 genes. GES7 features were validated in two independent external cohorts. Next, GES7 was found to recategorize patients from AJCC TNM stages into a best-fitted prognostic group. The GES7 was associated with activation of the TGF-β pathway and repression of anticancer immune cells. Finally, we compared the GES7 with 30 previous proposed scores, finding that GES7 is one of the most robust scores. As a result, the GES7 is a reliable gene-expression-based signature to improve the prognosis estimation in GC.

Clinically conserved genomic subtypes of gastric adenocarcinoma

Gastric adenocarcinoma (GAC) is a lethal disease characterized by genomic and clinical heterogeneity. By integrating 8 previously established genomic signatures for GAC subtypes, we identified 6 clinically and molecularly distinct genomic consensus subtypes (CGSs). CGS1 have the poorest prognosis, very high stem cell characteristics, and high IGF1 expression, but low genomic alterations. CGS2 is enriched with canonical epithelial gene expression. CGS3 and CGS4 have high copy number alterations and low immune reactivity. However, CGS3 and CGS4 differ in that CGS3 has high HER2 activation, while CGS4 has high SALL4 and KRAS activation. CGS5 has the high mutation burden and moderately high immune reactivity that are characteristic of microsatellite instable tumors. Most CGS6 tumors are positive for Epstein Barr virus and show extremely high levels of methylation and high immune reactivity. In a systematic analysis of genomic and proteomic data, we estimated the potential response rate of each consensus subtype to standard and experimental treatments such as radiation therapy, targeted therapy, and immunotherapy. Interestingly, CGS3 was significantly associated with a benefit from chemoradiation therapy owing to its high basal level of ferroptosis. In addition, we also identified potential therapeutic targets for each consensus subtype. Thus, the consensus subtypes produced a robust classification and provide for additional characterizations for subtype-based customized interventions.

SEC23A confers ER stress resistance in gastric cancer by forming the ER stress-SEC23A-autophagy negative feedback loop

BACKGROUND

Sec23 homolog A (SEC23A), a core component of coat protein complex II (COPII), has been reported to be involved in several cancers. However, the role of SEC23A in gastric cancer remains unclear.

METHODS

The expression of SEC23A in gastric cancer was analyzed by using qRT-PCR, western blotting and IHC staining. The role of SEC23A in ER stress resistance was explored by functional experiments in vitro and vivo. The occupation of STAT3 on the SEC23A promoter region was verified by luciferase reporter plasmids and CHIP assay. The interaction between SEC23A and ANXA2 was identified by Co-IP and mass spectrometry analysis.

RESULTS

We demonstrated that SEC23A was upregulated in gastric cancer and predicted poor prognosis in patients with gastric cancer. Mechanistically, SEC23A was transcriptional upregulated by ER stress-induced pY705-STAT3. Highly expressed SEC23A promoted autophagy by regulating the cellular localization of ANXA2. The SEC23A-ANXA2-autophay axis, in turn, protected gastric cancer cells from ER stress-induced apoptosis. Furthermore, we identified SEC23A attenuated 5-FU therapeutic effectiveness in gastric cancer cells through autophagy-mediated ER stress relief.

CONCLUSION

We reveal an ER stress-SEC23A-autophagy negative feedback loop that enhances the ability of gastric cancer cells to resist the adverse survival environments. These results identify SEC23A as a promising molecular target for potential therapeutic intervention and prognostic prediction in patients with gastric cancer.

The epigenetic modifier lysine methyltransferase 2C is frequently mutated in gastric remnant carcinoma

Gastric remnant carcinoma (GRC), which occurs in the stomach after partial gastrectomy, is a rare and aggressive form of gastric adenocarcinoma (GAC). Comprehensive profiling of genomic mutations in GRC could provide the basis for elucidating the origin and characteristics of this cancer. Herein, whole-exome sequencing (WES) was performed on 36 matched tumor-normal samples from patients with GRC and identified recurrent mutations in epigenetic modifiers, notably KMT2C, ARID1A, NSD1, and KMT2D, in 61.11% of cases. Mutational signature analysis revealed a low frequency of microsatellite instability (MSI) in GRC, which was further identified by MSIsensor, MSI-polymerase chain reaction, and immunohistochemistry analysis. Comparative analysis demonstrated that GRC had a distinct mutation spectrum compared to that of GAC in The Cancer Genome Atlas samples, with a significantly higher mutation rate of KMT2C. Targeted deep sequencing (Target-seq) of an additional 25 paired tumor-normal samples verified the high mutation frequency (48%) of KMT2C in GRC. KMT2C mutations correlated with poor overall survival in both WES and Target-seq cohorts and were independent prognosticators in GRC. In addition, KMT2C mutations were positively correlated with favorable outcomes in immune checkpoint inhibitor-treated pan-cancer patients and associated with higher intratumoral CD3+ , CD8+ tumor-infiltrating lymphocyte counts, and PD-L1 expression in GRC samples (p = 0.018, 0.092, 0.047, 0.010, and 0.034, respectively). Our dataset provides a platform for information and knowledge mining of the genomic characteristics of GRC and helps to frame new therapeutic approaches for this disease.

Single-cell Profiling Uncovers a Muc4-Expressing Metaplastic Gastric Cell Type Sustained by Helicobacter pylori-driven Inflammation

Mechanisms for Helicobacter pylori (Hp)-driven stomach cancer are not fully understood. In a transgenic mouse model of gastric preneoplasia, concomitant Hp infection and induction of constitutively active KRAS (Hp+KRAS+) alters metaplasia phenotypes and elicits greater inflammation than either perturbation alone. Gastric single-cell RNA sequencing showed that Hp+KRAS+ mice had a large population of metaplastic pit cells that expressed the intestinal mucin Muc4 and the growth factor amphiregulin. Flow cytometry and IHC-based immune profiling revealed that metaplastic pit cells were associated with macrophage and T-cell inflammation. Accordingly, expansion of metaplastic pit cells was prevented by gastric immunosuppression and reversed by antibiotic eradication of Hp. Finally, MUC4 expression was significantly associated with proliferation in human gastric cancer samples. These studies identify an Hp-associated metaplastic pit cell lineage, also found in human gastric cancer tissues, whose expansion is driven by Hp-dependent inflammation.

Significance

Using a mouse model, we have delineated metaplastic pit cells as a precancerous cell type whose expansion requires Hp-driven inflammation. In humans, metaplastic pit cells show enhanced proliferation as well as enrichment in precancer and early cancer tissues, highlighting an early step in the gastric metaplasia to cancer cascade.

A consolidated working classification of gastric cancer for histopathologists (Review)

Gastric cancer (GC) remains a disease with poor prognosis despite increasing availability of more effective targeted treatment. This may be in part due to the difficulty in selecting patients for appropriate treatment. Conventional taxonomic classifications of GC are ill-suited to make full use of recent advances in personalised therapy. In the past decade a number of molecular classifications have been proposed to address this; however, to date, there has been little implementation in the diagnostic routine. The lack of harmonisation between these classifications, the complexity and unavailability of some of the tests required plus the demands on time and resources, all contribute to poor uptake in the diagnostic routine. In the present study, these classifications were reviewed and an inclusive working classification that includes their main points, focuses on prognosis and treatment options and can be delivered using four on-slide tests (in situ hybridization for Epstein-Barr encoding region and immunohistochemistry for mismatch repair, E-cadherin and p53) is proposed. These tests can be performed on paraffin-embedded tissue and could be available in the majority of histopathology laboratories. The proposed classification also includes reflex testing for specific biomarkers relevant to treatment selection.

Comprehensive molecular phenotyping of ARID1A-deficient gastric cancer reveals pervasive epigenomic reprogramming and therapeutic opportunities

OBJECTIVE

Gastric cancer (GC) is a leading cause of cancer mortality, with ARID1A being the second most frequently mutated driver gene in GC. We sought to decipher ARID1A-specific GC regulatory networks and examine therapeutic vulnerabilities arising from ARID1A loss.

DESIGN

Genomic profiling of GC patients including a Singapore cohort (>200 patients) was performed to derive mutational signatures of ARID1A inactivation across molecular subtypes. Single-cell transcriptomic profiles of ARID1A-mutated GCs were analysed to examine tumour microenvironmental changes arising from ARID1A loss. Genome-wide ARID1A binding and chromatin profiles (H3K27ac, H3K4me3, H3K4me1, ATAC-seq) were generated to identify gastric-specific epigenetic landscapes regulated by ARID1A. Distinct cancer hallmarks of ARID1A-mutated GCs were converged at the genomic, single-cell and epigenomic level, and targeted by pharmacological inhibition.

RESULTS

We observed prevalent ARID1A inactivation across GC molecular subtypes, with distinct mutational signatures and linked to a NFKB-driven proinflammatory tumour microenvironment. ARID1A-depletion caused loss of H3K27ac activation signals at ARID1A-occupied distal enhancers, but unexpectedly gain of H3K27ac at ARID1A-occupied promoters in genes such as NFKB1 and NFKB2. Promoter activation in ARID1A-mutated GCs was associated with enhanced gene expression, increased BRD4 binding, and reduced HDAC1 and CTCF occupancy. Combined targeting of promoter activation and tumour inflammation via bromodomain and NFKB inhibitors confirmed therapeutic synergy specific to ARID1A-genomic status.

CONCLUSION

Our results suggest a therapeutic strategy for ARID1A-mutated GCs targeting both tumour-intrinsic (BRD4-assocatiated promoter activation) and extrinsic (NFKB immunomodulation) cancer phenotypes.

Identifying mitophagy-related genes as prognostic biomarkers and therapeutic targets of gastric carcinoma by integrated analysis of single-cell and bulk-RNA sequencing data

Gastric carcinoma (GC) is the fourth leading cause of cancer-related mortality worldwide. Patients with advanced GC tend to have poor prognoses and shortened survival. Finding novel predictive biomarkers for GC prognosis is an urgent need. Mitophagy is the selection degradation of damaged mitochondria to maintain cellular homeostasis, which has been shown to play both pro- and anti-tumor effects. This study combined single-cell sequencing data and transcriptomics to screen mitophagy-related genes (MRGs) associated with GC progression and analyze their clinical values. Reverse transcription-quantitative PCR (RT-qPCR) and immunochemistry (IHC) further verified gene expression profiles. A total of 18 DE-MRGs were identified after taking an intersection of single-cell sequencing data and MRGs. Cells with a higher MRG score were mainly distributed in the epithelial cell cluster. Cell-to-cell communications among epithelial cells with other cell types were significantly upregulated. We established and validated a reliable nomogram model based on DE-MRGs (GABARAPL2 and CDC37) and traditional clinicopathological parameters. GABARAPL2 and CDC37 displayed different immune infiltration states. Given the significant correlation between hub genes and immune checkpoints, targeting MRGs in GC may supplement more benefits to patients who received immunotherapy. In conclusion, GABARAPL2 and CDC37 may be prognostic biomarkers and candidate therapeutic targets of GC.

Impact of programmed death-ligand 1 (PD-L1) positivity on clinical and molecular features of patients with metastatic gastric cancer

BACKGROUND

Programmed death-ligand 1 (PD-L1) is an important screening biomarker to select patients with gastric cancer (GC) for optimized treatment, including immune checkpoint inhibitors (ICI).

METHODS

In this single-institution retrospective cohort study, patients with metastatic GC with available PD-L1 results between October 2019 and September 2021 were identified by reviewing their electronic medical records. Genomic data were obtained from the Samsung Medical Center Clinical Sequencing Platform.

RESULTS

Among the 399 patients, 276 (69%) had a PD-L1 combined positive score (CPS) ≥1, 155 (39%) had a CPS between 1 and 5, and 121 (30%) had a CPS ≥5. Of the 121 patients with CPS ≥5, 28 (23%) had a known etiology for "inflamed tumor," with Epstein-Barr virus (EBV) positivity (N = 11) or high tumor mutational burden (TMB) (N = 17), which included microsatellite instability (MSI) (N = 9). PD-L1 CPS ≥5 was observed in 11/11 (100%) patients with EBV positivity, 9/12 (75%) patients with MSI, and 17/33 (52%) patients with high TMB. For the 108 patients who received ICI therapy, CPS ≥5 was the only predictor significantly associated with survival in multivariable analyses, including TMB, MSI, or EBV. Objective response rate (ORR) was 49% in patients with CPS ≥5, 30% in patients with 1 ≤ CPS <5, and 19% in patients with CPS <1. Among the 31 responders to ICI therapy, 27 (87%) had a CPS of ≥1. Mutations in TET2, IRS2, DOT1L, PTPRT, and LRP1B were associated with a higher ORR (63%-100%), whereas MDC1 mutations were associated with a low ORR (22%).

CONCLUSIONS

PD-L1 expression is an independent and sensitive biomarker for ICI therapy. Considering its significant association with several gene alterations, including PIK3CA mutations and MET amplification, combining ICI therapy with other targeted agents may be a promising therapeutic strategy for GC.

Genomic and evolutionary characteristics of metastatic gastric cancer by routes

BACKGROUND

In gastric cancer (GC) patients, metastatic progression through the lymphatic, hematogenous, peritoneal, and ovarian routes, is the ultimate cause of death. However, the genomic and evolutionary characteristics of metastatic GC have not been widely evaluated.

METHODS

Whole-exome sequencing data were analyzed for 99 primary and paired metastatic gastric cancers from 15 patients who underwent gastrectomy and metastasectomy.

RESULTS

Hematogenous metastatic tumors were associated with increased chromosomal instability and de novo gain/amplification in cancer driver genes, whereas peritoneal/ovarian metastasis was linked to sustained chromosomal stability and de novo somatic mutations in driver genes. The genomic distance of the hematogenous and peritoneal metastatic tumors was found to be closer to the primary tumors than lymph node (LN) metastasis, while ovarian metastasis was closer to LN and peritoneal metastasis than the primary tumor. Two migration patterns for metastatic GCs were identified; branched and diaspora. Both molecular subtypes of the metastatic tumors, rather than the primary tumor, and their migration patterns were related to patient survival.

CONCLUSIONS

Genomic characteristics of metastatic gastric cancer is distinctive by routes and associated with patients' prognosis along with genomic evolution pattenrs, indicating that both primary and metastatic gastric cancers require genomic evaluation.

Epigenetic Modification-Associated Molecular Classification of Gastric Cancer

Epigenetic modification is involved in tumorigenesis and cancer progression. We developed an epigenetic modification-associated molecular classification of gastric cancer (GC) to identify signature genes that accurately predict prognosis and the efficacy of immunotherapy. Least absolute shrinkage and selection operator and multivariate Cox regression analysis were conducted to develop an epigenetic modification-associated molecular classification. We investigated the significance of PIP4P2, an independent prognostic factor of the classification system, in predicting the prognosis and immunotherapy efficacy of patients with GC. The epigenetic modification-associated molecular classification was highly associated with the clinicopathological characteristics of patients and the existing classification of GC. PIP4P2 was highly expressed in GC tissue and tumor-associated macrophages. High PIP4P2 expression in GC tissue-induced tumor progression by activating PI3K/AKT signal transduction had a negative impact on immunotherapy efficacy. High expression of PIP4P2 in macrophages was correlated with poor prognosis in patients with GC. PIP4P2 is an independent unfavorable prognostic factor of epigenetic modification-associated molecular classification, is involved in tumorigenic progression, and is essential for assessing the prognosis and immunotherapy efficacy of GC.

Biomarkers for Predicting Response to Personalized Immunotherapy in Gastric Cancer

Despite advances in diagnostic imaging, surgical techniques, and systemic therapy, gastric cancer (GC) is the third leading cause of cancer-related death worldwide. Unfortunately, molecular heterogeneity and, consequently, acquired resistance in GC are the major causes of failure in the development of biomarker-guided targeted therapies. However, by showing promising survival benefits in some studies, the recent emergence of immunotherapy in GC has had a significant impact on treatment-selectable procedures. Immune checkpoint inhibitors (ICIs), widely indicated in the treatment of several malignancies, target inhibitory receptors on T lymphocytes, including the programmed cell death protein (PD-1)/programmed death-ligand 1 (PD-L1) axis and cytotoxic T-lymphocyte-associated protein 4 (CTLA4), and release effector T-cells from negative feedback signals. In this article, we review currently available predictive biomarkers (including PD-L1, microsatellite instability, Epstein-Barr virus, and tumor mutational burden) that affect the ICI treatment response, focusing on PD-L1 expression. We further briefly describe other potential biomarkers or mechanisms for predicting the response to ICIs in GC. This review may facilitate the expansion of the understanding of biomarkers for predicting the response to ICIs and help select the appropriate therapeutic approaches for patients with GC.

Reduced DEFA5 Expression and STAT3 Activation Underlie the Submucosal Invasion of Early Gastric Cancers

INTRODUCTION

Submucosal invasion is a core hallmark of early gastric cancer (EGC) with poor prognosis. However, the molecular mechanism of the progression from intramucosal gastric cancer (IMGC) to early submucosal-invasive gastric cancer (SMGC) is not fully understood. The objective of this study was to identify genes and pathways involved in the submucosal invasion in EGC using comprehensive gene expression analysis.

METHODS

Gene expression profiling was performed for eight cases of IMGC and eight cases of early SMGC with submucosal invasion ≥500 μm. To validate the findings of gene expression analysis and to examine the gene expression pattern in tissues, immunohistochemical (IHC) staining was performed for 50 cases of IMGC and SMGC each.

RESULTS

Gene expression analysis demonstrated that the expression levels of small intestine-specific genes were significantly decreased in SMGC. Among them, defensin alpha 5 (DEFA5) was the most downregulated gene in SMGC, which was further validated in SMGC tissues by IHC staining. Gene set enrichment analysis showed a strong association between SMGC, the JAK-STAT signaling pathway, and the upregulation of STAT3-activating cytokines. The expression of phosphorylated STAT3 was significant in the nucleus of tumor cells in SMGC tissues but not in areas expressing DEFA5.

CONCLUSION

The results of this study strongly suggest that the downregulation of DEFA5 and the activation of STAT3 play a significant role in the submucosal invasion of EGC.

The Present and Future of Neoadjuvant and Adjuvant Therapy for Locally Advanced Gastric Cancer

Gastric cancer is a highly prevalent and lethal disease worldwide. Given the insidious nature of the presenting symptoms, patients are frequently diagnosed with advanced, unresectable disease. However, many patients will present with locally advanced gastric cancer (LAGC), which is often defined as the primary tumor extending beyond the muscularis propria (cT3-T4) or having nodal metastases (cN+) disease and without distant metastases (cM0). LAGC is typically treated with surgical resection and perioperative chemotherapy. The treatment of LAGC remains a challenge, given the heterogeneity of this disease, and the optimal multimodal treatment regimen may be different for different LAGC subtypes. However, many promising treatments are on the horizon based on knowledge of molecular subtypes and key biomarkers of LAGC, such as microsatellite instability, HER2, Claudin 18.2, FGFR2, and PD-L1. This review will expand upon the discussion of current standard neoadjuvant and adjuvant therapies for LAGC and explore the ongoing and future clinical trials for novel therapies, with information obtained from searches in PubMed and ClinicalTrials.gov.

Evolution of immune and stromal cell states and ecotypes during gastric adenocarcinoma progression

Understanding tumor microenvironment (TME) reprogramming in gastric adenocarcinoma (GAC) progression may uncover novel therapeutic targets. Here, we performed single-cell profiling of precancerous lesions, localized and metastatic GACs, identifying alterations in TME cell states and compositions as GAC progresses. Abundant IgA+ plasma cells exist in the premalignant microenvironment, whereas immunosuppressive myeloid and stromal subsets dominate late-stage GACs. We identified six TME ecotypes (EC1-6). EC1 is exclusive to blood, while EC4, EC5, and EC2 are highly enriched in uninvolved tissues, premalignant lesions, and metastases, respectively. EC3 and EC6, two distinct ecotypes in primary GACs, associate with histopathological and genomic characteristics, and survival outcomes. Extensive stromal remodeling occurs in GAC progression. High SDC2 expression in cancer-associated fibroblasts (CAFs) is linked to aggressive phenotypes and poor survival, and SDC2 overexpression in CAFs contributes to tumor growth. Our study provides a high-resolution GAC TME atlas and underscores potential targets for further investigation.

Predicting response to immunotherapy in gastric cancer via assessing perineural invasion-mediated inflammation in tumor microenvironment

BACKGROUND

The perineural invasion (PNI)-mediated inflammation of the tumor microenvironment (TME) varies among gastric cancer (GC) patients and exhibits a close relationship with prognosis and immunotherapy. Assessing the neuroinflammation of TME is important in predicting the response to immunotherapy in GC patients.

METHODS

Fifteen independent cohorts were enrolled in this study. An inflammatory score was developed and validated in GC. Based on PNI-related prognostic inflammatory signatures, patients were divided into Clusters A and B using unsupervised clustering. The characteristics of clusters and the potential regulatory mechanism of key genes were verified by RT-PCR, western-blot, immunohistochemistry and immunofluorescence in cell and tumor tissue samples.The neuroinflammation infiltration (NII) scoring system was developed based on principal component analysis (PCA) and visualized in a nomogram together with other clinical characteristics.

RESULTS

Inflammatory scores were higher in GC patients with PNI compared with those without PNI (P < 0.001). NII.clusterB patients with PNI had abundant immune cell infiltration in the TME but worse prognosis compared with patients in the NII.clusterA patients with PNI and non-PNI subgroups. Higher immune checkpoint expression was noted in NII.clusterB-PNI. VCAM1 is a specific signature of NII.clusterB-PNI, which regulates PD-L1 expression by affecting the phosphorylation of STAT3 in GC cells. Patients with PNI and high NII scores may benefit from immunotherapy. Patients with low nomogram scores had a better prognosis than those with high nomogram scores.

CONCLUSIONS

Inflammation mediated by PNI is one of the results of tumor-nerve crosstalk, but its impact on the tumor immune microenvironment is complex. Assessing the inflammation features of PNI is a potential method in predicting the response of immunotherapy effectively.

Immune regulation in gastric adenocarcinoma is linked with therapeutic efficacy and improved recovery

Adenocarcinomas are one of the most common histological types of gastric cancer. It has been ranked fifth among common cancers and is the third among death causing cancers worldwide. The high mortality rate among patients with gastric cancer is because of its silent evolution, genetic heterogeneity, high resistance to chemotherapy as well as unavailability of highly effective therapeutic strategy. Until now a number of several treatment strategies have been developed and are being practiced such as surgery, chemotherapy, radio therapy, and immunotherapy, however, further developments are required to improve the treatment responses and reduce the side effects. Therefore, novel personal therapeutic strategies based on immunological responses should be developed by targeting different check points and key immune players. Targeting macrophages and related molecular elements can be useful to achieve these goals. In this minireview, we discuss the available treatment options, molecular underpinnings and immunological regulations associated with gastric adenocarcinoma. We further describe the possible check points and immunological targets that can be used to develop novel therapeutic options.

Assessment of the reliability of MSI status and dMMR proteins deficiency screening on endoscopic biopsy material in esophagus and gastric adenocarcinoma

BACKGROUND

Microsatellite instability (MSI) is a negative predictive factor for neoadjuvant chemotherapy in resectable oesogastric adenocarcinoma and a crucial determinant for immunotherapy. We aimed to evaluate reliability of dMMR/MSI status screening performed on preoperative endoscopic biopsies.

METHODS

Paired pathological samples from biopsies and surgical specimen of oesogastric adenocarcinoma were retrospectively collected between 2009 and 2019. We compared dMMR status obtained by immunohistochemistry (IHC) and MSI status by PCR. dMMR/MSI status on surgical specimen was considered as reference.

RESULTS

PCR and IHC were conclusive on biopsies respectively for 53 (96.4%) and 47 (85.5%) of the 55 patients enrolled. IHC was not contributive for 1 surgical specimen. A third reading of IHC was carried out for 3 biopsies. MSI status was observed in 7 (12.5%) surgical specimens. When analyses were contributive, sensitivity and specificity of biopsies for dMMR/MSI were respectively 85% and 98% for PCR vs. 86% and 98% for IHC. Concordance rate between biopsies and surgical specimen was 96.2% for PCR and 97.8% for IHC.

CONCLUSIONS

Endoscopic biopsies are a suitable source of tissue for dMMR/MSI status determination in oesogastric adenocarcinoma which should be routinely performed at diagnosis to better adapt neoadjuvant treatment.

MINIABSTRACT

By comparison of dMMR phenotype obtained by immunohistochemistry and MSI status by PCR between match-paired samples of oesogastric cancer's endoscopic biopsies and surgical specimen, we observed that biopsies are a suitable source of tissue for dMMR/MSI status determination.

Mutational Signatures in Gastric Cancer and Their Clinical Implications

Gastric cancer is characterised by high inter- and intratumour heterogeneity. The majority of patients are older than 65 years and the global burden of this disease is increasing due to the aging of the population. The disease is usually diagnosed at advanced stages, which is a consequence of nonspecific symptoms. Few improvements have been made at the level of noninvasive molecular diagnosis of sporadic gastric cancer, and therefore the mortality rate remains high. A new field of mutational signatures has emerged in the past decade with advances in the genome sequencing technology. These distinct mutational patterns in the genome, caused by exogenous and endogenous mutational processes, can be associated with tumour aetiology and disease progression, and could provide novel perception on the treatment possibilities. This review assesses the mutational signatures found in gastric cancer and summarises their potential for use in clinical setting as diagnostic or prognostic biomarkers. Associated treatment options and biomarkers already implemented in clinical use are discussed, together with those that are still being explored or are in clinical studies.

KRAS activation in gastric cancer stem-like cells promotes tumor angiogenesis and metastasis

Our previous work showed that KRAS activation in gastric cancer cells leads to activation of an epithelial-to-mesenchymal transition (EMT) program and generation of cancer stem-like cells (CSCs). Here we analyze how this KRAS activation in gastric CSCs promotes tumor angiogenesis and metastasis. Gastric cancer CSCs were found to secrete pro-angiogenic factors such as vascular endothelial growth factor A (VEGF-A), and inhibition of KRAS markedly reduced secretion of these factors. In a genetically engineered mouse model, gastric tumorigenesis was markedly attenuated when both KRAS and VEGF-A signaling were blocked. In orthotropic implant and experimental metastasis models, silencing of KRAS and VEGF-A using shRNA in gastric CSCs abrogated primary tumor formation, lymph node metastasis, and lung metastasis far greater than individual silencing of KRAS or VEGF-A. Analysis of gastric cancer patient samples using RNA sequencing revealed a clear association between high expression of the gastric CSC marker CD44 and expression of both KRAS and VEGF-A, and high CD44 and VEGF-A expression predicted worse overall survival. In conclusion, KRAS activation in gastric CSCs enhances secretion of pro-angiogenic factors and promotes tumor progression and metastasis.

CHSY3 promotes proliferation and migration in gastric cancer and is associated with immune infiltration

BACKGROUND

The glycosyltransferase CHSY3 is a CHSY family member, yet its importance in the context of gastric cancer development remains incompletely understood. The present study was thus developed to explore the mechanistic importance of CHSY3 as a regulator of gastric cancer.

METHODS

Expression of CHSY3 was verified by TCGA, GEO and HPA databases. Kaplan-Meier curve, ROC, univariate cox, multivariate cox, and nomogram models were used to verify the prognostic impact and predictive value of CHSY3. KEGG and GO methods were used to identify signaling pathways associated with CHSY3. TIDE and IPS scores were used to assess the immunotherapeutic value of CHSY3. WGCNA, Cytoscape constructs PPI networks and random forest models to identify key Hub genes. Finally, qRT-PCR and immunohistochemical staining were performed to verify CHSY3 expression in clinical specimens. The ability of CHSY3 to regulate tumor was further assessed by CCK-8 assay and cloning assay, EDU assay, migration assay, invasion assay, and xenograft tumor model analysis.

RESULTS

The expression of CHSY3 was discovered to be abnormally upregulated in GC tissues through TCGA, GEO, and HPA databases, and the expression of CHSY3 was associated with poor prognosis in GC patients. Correlation analysis and Cox regression analysis revealed higher CHSY3 expression in higher T staging, an independent prognostic factor for GC. Moreover, elevated expression of CHSY3 was found to reduce the benefit of immunotherapy as assessed by the TIDE score and IPS score. Then, utilizing WGCNA, the PPI network constructed by Cytoscape, and random forest model, the Hub genes of COL5A2, POSTN, COL1A1, and FN1 associated with immunity were screened. Finally, the expression of CHSY3 in GC tissues was verified by qRT-PCR and immunohistochemical staining. Moreover, the expression of CHSY3 was further demonstrated by in vivo and in vitro experiments to promote the proliferation, migration, and invasive ability of GC.

CONCLUSIONS

The results of this study suggest that CHSY3 is an important regulator of gastric cancer progression, highlighting its promise as a therapeutic target for gastric cancer.

Integrated analysis of the microbiome and transcriptome in stomach adenocarcinoma

We aimed to characterize the stomach adenocarcinoma (STAD) microbiota and its clinical value using an integrated analysis of the microbiome and transcriptome. Microbiome and transcriptome data were downloaded from the Cancer Microbiome Atlas and the Cancer Genome Atlas databases. We identified nine differentially abundant microbial genera, including Helicobacter, Mycobacterium, and Streptococcus, which clustered patients into three subtypes with different survival rates. In total, 74 prognostic genes were screened from 925 feature genes of the subtypes, among which five genes were identified for prognostic model construction, including NTN5, MPV17L, MPLKIP, SIGLEC5, and SPAG16. The prognostic model could stratify patients into different risk groups. The high-risk group was associated with poor overall survival. A nomogram established using the prognostic risk score could accurately predict the 1, 3, and 5 year overall survival probabilities. The high-risk group had a higher proportion of histological grade 3 and recurrence samples. Immune infiltration analysis showed that samples in the high-risk group had a higher abundance of infiltrating neutrophils. The Notch signaling pathway activity showed a significant difference between the high- and low-risk groups. In conclusion, a prognostic model based on five feature genes of microbial subtypes could predict the overall survival for patients with STAD.