Immunotherapy has become an option for the first-line therapy of advanced gastric cancer (GC), with improved survival. Our study aimed to investigate unresectable GC from an imaging perspective combined with clinicopathological variables to identify patients who were most likely to benefit from immunotherapy.

Patients with unresectable GC who were consecutively treated with immunotherapy at two different medical centers of Chinese PLA General Hospital were included and divided into the training and validation cohorts, respectively. A deep learning neural network, using a multimodal ensemble approach based on CT imaging data before immunotherapy, was trained in the training cohort to predict survival, and an internal validation cohort was constructed to select the optimal ensemble model. Data from another cohort were used for external validation. The area under the receiver operating characteristic curve was analyzed to evaluate performance in predicting survival. Detailed clinicopathological data and peripheral blood prior to immunotherapy were collected for each patient. Univariate and multivariable logistic regression analysis of imaging models and clinicopathological variables was also applied to identify the independent predictors of survival. A nomogram based on multivariable logistic regression was constructed.

A total of 79 GC patients in the training cohort and 97 patients in the external validation cohort were enrolled in this study. A multi-model ensemble approach was applied to train a model to predict the 1-year survival of GC patients. Compared to individual models, the ensemble model showed improvement in performance metrics in both the internal and external validation cohorts. There was a significant difference in overall survival (OS) among patients with different imaging models based on the optimum cutoff score of 0.5 (HR = 0.20, 95 % CI: 0.10-0.37, P < 0.001). Multivariate Cox regression analysis revealed that the imaging models, PD-L1 expression, and lung immune prognostic index were independent prognostic factors for OS. We combined these variables and built a nomogram. The calibration curves showed that the C-index of the nomogram was 0.85 and 0.78 in the training and validation cohorts.

The deep learning model in combination with several clinical factors showed predictive value for survival in patients with unresectable GC receiving immunotherapy.

SERPINE1 is a serine protease inhibitor upregulated in various malignancies and pivotal in gastric cancer (GC) metastasis and the tumor microenvironment (TME). This study elucidates the mechanisms by which SERPINE1 mediates anoikis resistance and fosters an immunosuppressive TME in advanced GC. SERPINE1 is highly expressed in GC tissues and metastatic lesions and serves as an independent risk factor for poor prognosis. The transcriptional activation of SERPINE1 by CEBPB triggers the PI3K/AKT and EMT signaling pathway via autocrine mechanisms, enhancing anoikis resistance and metastatic potential in GC cells. Furthermore, SERPINE1 facilitates M2 macrophage polarization by binding to lipoprotein receptor-related protein 1 (LRP1) in a paracrine manner, suppressing CD8+ T-cell infiltration and functionality in the TME. Therapeutic intervention combining SERPINE1 inhibition with PD-1 blockade exhibits synergistic antitumor effects. Clinically, high SERPINE1 expression is associated with an increased risk of recurrence following immune checkpoint inhibitor therapy in patients with advanced GC. These findings suggest that SERPINE1 is a critical driver of GC progression through anoikis resistance and TME remodeling. Hence, SERPINE1 can offer a promising therapeutic target and represent a predictive biomarker for immunotherapy outcomes in GC.

The immune composition of solid tumors is typically inferred from biomarkers, such as histologic and molecular classifications, somatic mutational burden, and PD-L1 expression. However, the extent to which these biomarkers predict the immune landscape in gastric adenocarcinoma-an aggressive cancer often linked to chronic inflammation-remains poorly understood. We leveraged high-dimensional spectral cytometry to generate a comprehensive single-cell immune landscape of tumors, normal tissue, and lymph nodes from patients in the Western Hemisphere with gastric adenocarcinoma. The immune composition of gastric tumors could not be predicted by traditional metrics such as tumor histology, molecular classification, mutational burden, or PD-L1 expression via IHC. Instead, our findings revealed that innate immune surveillance within tumors could be anticipated by the immune profile of the normal gastric mucosa. Additionally, distinct T-cell states in the lymph nodes were linked to the accumulation of activated and memory-like CD8+ tumor-infiltrating lymphocytes. Unbiased reclassification of patients based on tumor-specific immune infiltrate generated four distinct subtypes with varying immune compositions. Tumors with a T cell-dominant immune subtype, which spanned The Cancer Genome Atlas molecular subtypes, were exclusively associated with superior responses to immunotherapy. Parallel analysis of metastatic gastric cancer patients treated with immune checkpoint blockade showed that patients who responded to immunotherapy had a pretreatment tumor composition that corresponded to a T cell-dominant immune subtype from our analysis. Taken together, this work identifies key host-specific factors associated with intratumoral immune composition in gastric cancer and offers an immunological classification system that can effectively identify patients likely to benefit from immune-based therapies.

Gastric cancer (GC) is linked to high morbidity and mortality rates. Approximately two-thirds of GC patients are diagnosed at an advanced or metastatic stage. Conventional treatments for GC, including surgery, radiotherapy, and chemotherapy, offer limited prognostic improvement. Recently, immunotherapy has gained attention for its promising therapeutic effects in various tumors. Immunotherapy functions by activating and regulating the patient's immune cells to target and eliminate tumor cells, thereby reducing the tumor burden in the body. Among immunotherapies, immune checkpoint inhibitors (ICIs) are the most advanced. ICIs disrupt the inhibitory protein-small molecule (PD-L1, CTLA4, VISTA, TIM-3 and LAG3) interactions produced by immune cells, reactivating these cells to recognize and attack tumor cells. However, adverse reactions and resistance to ICIs hinder their further clinical and experimental development. Therefore, a comprehensive understanding of the advancements in ICIs for GC is crucial. This article discusses the latest developments in clinical trials of ICIs for GC and examines combination therapies involving ICIs (targeted therapy, chemotherapy, radiotherapy), alongside ongoing clinical trials. Additionally, the review investigates the tumor immune microenvironment and its role in non-responsiveness to ICIs, highlighting the function of tumor immune cells in ICI efficacy. Finally, the article explores the prospects and limitations of new immunotherapy-related technologies, such as tumor vaccines, nanotechnologies, and emerging therapeutic strategies, aiming to advance research into personalized and optimized immunotherapy for patients with locally advanced gastric cancer.

Immune checkpoint inhibitors (ICIs) represent a groundbreaking advancement in cancer therapy, substantially improving patient survival rates. Our comprehensive research reveals a significant positive correlation between coagulation scores and immune-related gene expression across 30 diverse cancer types. Notably, tumours exhibiting high coagulation scores demonstrated enhanced infiltration of cytotoxic immune cells, including CD8+ T cells, natural killer (NK) cells, and macrophages. Leveraging the TCGA pan-cancer database, we developed the Coagulation.Sig model, a sophisticated predictive framework utilising a coagulation-related genes (CRGs) to forecast immunotherapy outcomes. Through rigorous analysis of ten ICI-treated cohorts, we identified and validated seven critical CRGs: BIRC2, HMGB1, STAT2, IFNAR1, BID, SPATA2, IL33 and IFNG, which form the foundation of our predictive model. Functional analyses revealed that low-risk tumours characterised by higher immune cell populations, particularly CD8+ T cells, demonstrated superior ICI responses. These tumours also exhibited increased mutation rates, elevated neoantigen loads, and greater TCR/BCR diversity. Conversely, high-risk tumours displayed pronounced intratumor heterogeneity (ITH) and elevated NRF2 pathway activity, mechanisms strongly associated with immune evasion. Experimental validation highlighted BIRC2 as a promising therapeutic target. Targeted BIRC2 knockdown, when combined with anti-PD-1 therapy, significantly suppressed tumour growth, enhanced CD8+ T cell infiltration, and amplified IFN-γ and TNF-α secretion in tumour models. Our findings position the Coagulation.Sig model as a novel, comprehensive approach to personalised cancer treatment, with BIRC2 emerging as both a predictive biomarker and a potential therapeutic intervention point.

Leucine-rich repeat containing 25 (LRRC25) is distinguishingly expressed in different tumor types, but the relationship with immune cell infiltration in gastric cancer stills unclear. We analyzed LRRC25 expression using pan-cancer data from The Cancer Genome Atlas and gene data from Gene Expression Omnibus. The clinical significance was further evaluated using gastric cancer tissues derived from clinical trials (no. NCT04208347).

Through bioinformatics analysis of TCGA database and the UCSC Xena database, we found the correlation between LRRC15, gastric cancer, and immune cell infiltration. Further, multiplex immunohistochemistry/immunofluorescence (mIHC/IF), tissue microarray, and image acquisition and quantitative analysis confirmed our theory.

It was discovered that LRRC25 was highly expressed in gastric cancer. Further analysis revealed that the expression of LRRC25 associated with gene sets implicated in immunity, including those in innate immunity, adaptive immunity, and chemokine signaling pathways. The result of (mIHC/IF) suggests a negative relevance between LRRC25 and response of anti-PD-1 treatment and reveals a trend of consistent change on LRRC25 + cells and CD16 expression. We also discovered that LRRC25 expression significantly associated with immune cell infiltration level. In particular, there is a relationship between LRRC25 and the phenotype and function of NK cells.

High LRRC25 expression contributes to immunosuppressive microenvironment by influencing chemokine axis in gastric cancer. LRRC25 may serve as a clinically useful biomarker for predicting neoadjuvant immunotherapeutic response in patients with gastric cancer. LRRC25 can affect the phenotype and function of NK cells.

Analyzing gene expression data from the Cancer Genome Atlas (TCGA) and similar repositories often requires advanced coding skills, creating a barrier for many researchers. To address this challenge, we developed The Cancer Genome Explorer (TCGEx), a user-friendly, web-based platform for conducting sophisticated analyses such as survival modeling, gene set enrichment analysis, unsupervised clustering, and linear regression-based machine learning. TCGEx provides access to preprocessed TCGA data and immune checkpoint inhibition studies while allowing integration of user-uploaded data sets. Using TCGEx, we explore molecular subsets of human melanoma and identify microRNAs associated with intratumoral immunity. These findings are validated with independent clinical trial data on immune checkpoint inhibitors for melanoma and other cancers. In addition, we identify cytokine genes that can be used to predict treatment responses to various immune checkpoint inhibitors prior to treatment. Built on the R/Shiny framework, TCGEx offers customizable features to adapt analyses for diverse research contexts and generate publication-ready visualizations. TCGEx is freely available at https://tcgex.iyte.edu.tr , providing an accessible tool to extract insights from cancer transcriptomics data.

Immune checkpoint inhibitors (ICIs) plus fluorouracil-based chemotherapy (Chemo) have been approved as an initial treatment strategy for metastatic or recurrent human epidermal growth factor receptor 2 (HER2)-negative gastric cancer (GC) or gastroesophageal junction cancer (GEJC). However, since programmed cell death protein-1 (PD-1) or its ligand 1 (PD-L1) inhibitors have just recently been investigated for the treatment of unresectable GC/GEJC, there is ongoing debate regarding their safety and effectiveness for prespecified subgroups. The purpose of this research is to establish a foundation toward stratified decision-making by methodically assessing the merits and drawbacks of PD-1/PD-L1 inhibitors combined with chemo in the clinical utilization of advanced HER2-negative GC/GEJC according to certain prominent large-scale randomized controlled trials (RCTs). In addition, we limitedly explored the favorable short-term efficacy of PD-1/CTLA-4 bispecific antibodies for the above-mentioned tumors.

The researchers retrieved several databases, including PubMed, Embase, Web of Science, ClinicalTrials.gov, and the Cochrane Library, to collect all the relevant literature published since the establishment of the databases until October 30, 2024, and then screened to determine the qualified literature and extracted the relevant information. We only included RCTs for PD-1/PD-L1 inhibitors with or without chemo in advanced GC or GEJC. The primary endpoints were overall survival (OS), progression-free survival (PFS), and objective response rate (ORR). A subgroup analysis for the median overall survival (mOS) was conducted for the following variables: microsatellite instability (MSI) status, PD-L1 expression, combined positive scores (CPS), metastasis status, and primary tumor location. When moderate heterogeneity was found, a random-effect model was applied. The outcome indicators were then statistically analyzed, taking advantage of Review Manager 5.4. Hazard ratio (HR) and risk ratio (RR) were selected as the effect values for statistical analysis.

A total of 7 eligible RCTs and 6537 participants were included in this meta-analysis. Combining PD-1/PD-L1 inhibitors with chemo significantly improved patients' OS compared with chemo alone, especially in the tumor cell PD-L1 expression ≥ 1% [HR = 0.62, 95% CI (0.48, 0.81); a p-value = 0.0004], PD-L1 CPS ≥ 10 [HR = 0.66, 95% CI (0.57, 0.77); a p-value < 0.00001], and MSI-H subgroups [HR = 0.40, 95% CI (0.28, 0.59); a p-value < 0.00001]. Moreover, distinct primary tumor location (GC or GEJC) and the presence of liver metastases could also benefit from the additive or sustained effect of anti-cancer chemo-immunotherapy.

For patients with advanced HER2-negative GC/GEJC, PD-1/PD-L1 inhibitors in combination with chemo have almost demonstrated consistent synergistic anti-tumor benefits to survival outcomes when compared to chemo alone. However, the subgroup analysis in this meta-study revealed that neither PD-L1 expression level nor MSI status could fully predict the efficacy of the dual treatment model but faced a higher possibility of serious treatment-related adverse events (sTRAEs), particularly in the synchronous therapy arm. Therefore, urging the need for more investigations into the development of collaborative prognostic forecasting models for achieving precise stratification, established harmonized testing standards and methods for PD-L1 expression and positivity, optimal CPS threshold for benefits, as well as alternative molecular biomarkers for the reason that certain indicators alone may not discriminate responders clearly. Lastly, dual anti-therapy might be a useful tactic for the population with low PD-L1 expression in the future.

Colorectal cancer (CRC) is the third most common cancer type and one of the leading causes of cancer-related death worldwide. The treatment of advanced metastatic CRC relies on classical chemotherapy combinations (5-fluorouracil, oxaliplatin or irinotecan). However, their use is limited by the emergence of resistance mechanisms, including to oxaliplatin. In this context, we recently showed that the combination of oxaliplatin and ataxia telangiectasia and Rad3-related protein inhibition (VE-822) is synergistic and may have a potential therapeutic effect in metastatic CRC management.

In this study, we investigated the role of the VE-822+oxaliplatin (Vox) combination on the immune response and its potential synergy with an anti-programmed-cell Death receptor-1 (PD-1) antibody. We used cell lines and organoids from metastatic CRC to investigate in vitro Vox efficacy and orthotopic syngeneic mouse models of metastatic CRC to assess the efficacy of Vox+anti-PD-1 antibody and identify the involved immune cells.

The Vox+anti-PD-1 antibody combination completely cured tumor-bearing mice and protected them from a rechallenge. Vox was associated with a reduction of tumor-infiltrated neutrophils, CD206+ macrophages and regulatory T cells. Vox also induced a deep depletion of blood neutrophils. The increased bone marrow granulopoiesis failed to compensate for the Vox-mediated mature neutrophil depletion. Neutrophil depletion using a mouse recombinant anti-Ly6G antibody partially mimicked the Vox effect on the tumor microenvironment, but to a lower extent compared with the Vox+anti-PD-1 antibody combination. Vox, but not neutrophil depletion, led to the emergence of an Ly6C+ PD-1+ CD8+ T-cell population in the blood and spleen of tumor-harboring mice. These cells were proliferating, and expressed IFN-γ, CD62L, CXCR3 and Eomes. Moreover, the proportion of tumor antigen-specific T cells and of CD122+ BCL6+ T cells, which shared phenotypic characteristics with stem-like CD8+ T cells, was increased in treated mice.

Our work strongly suggests that the Vox+anti-PD-1 antibody combination might significantly improve survival in patients with metastatic and treatment-refractory CRC by acting both on cancer cells and CD8+ T cells.

Despite advancements in early detection and treatment, the prognosis and histological types for residual gastric cancer (GC) remains poor.

This case report presents a rare occurrence of residual GC featuring a combination of small cell neuroendocrine carcinoma (SCNEC) and squamous cell carcinoma (SCC) in a 60-year-old male patient. The patient, with a history of Billroth II gastrectomy for duodenal ulcer bleeding, presented with gastrointestinal bleeding. Preoperative computed tomography and positron emission tomography-computed tomography indicated adenocarcinoma with tumor and abdominal lymph node metastasis. The patient underwent laparoscopic total gastrectomy and lymph node dissection for residual GC. Histological examination of the resected tumor confirmed the presence of both SCNEC and SCC. Postoperatively, the patient underwent adjuvant chemotherapy four times. Two years later, the patient was found to occur esophageal cancer and was performed a small bowel stoma and radical esophagectomy.

In this case report, we detail a rare instance of residual GC with mixed SCNEC and SCC, emphasizing the complexity of diagnosis and treatment, and the need for ongoing research.

Metabolic features are crucial in tumor immune interactions, but their relationship with antitumor immune responses is not yet fully understood. This study used Mendelian randomization analysis to identify the causal relationships between blood metabolites and immune cells and to evaluate the effects of metabolic pathways and reactions on antitumor immune responses in various cancers. Levels of 156 metabolites exhibited significant associations with selected immune cells. Metabolic enrichment analysis indicated laurate, propionyl-carnitine, carnitine and l-acetylcarnitine are enriched in fatty acid (FA) metabolism pathways. These enriched pathways are significantly correlated to CD8+ T cell function signatures in tumor environment and favor better prognostic outcomes. Metabolic reactions contributing to better immunotherapy responses were identified and used to establish the immuno-metabolic reaction score (IMRS). IMRS were significantly correlated to CD8+ T cell infiltration levels and CD8+ T cell signature scores in either 10× Visium spatial transcriptomic or RNA-seq samples. Finally, IMRS could significantly predict favorable survival outcomes in different cancer patients treated with immunotherapy. Our study revealed a link between certain metabolites and their related metabolic pathways to tumor immune landscape and immune functions. These results could promote the accurate stratification of patients before treatment and improve the efficacy of immunotherapy.

Recent years, immunotherapy has emerged as a pivotal approach in cancer treatment. However, the response of gastric cancer to immunotherapy exhibits significant heterogeneity. Therefore, the early identification of gastric cancer patients who are likely to benefit from immunotherapy and the discovery of novel therapeutic targets are of critical importance.

We collected data from European Nucleotide Archive (ENA) and Gene Expression Omnibus (GEO) databases. In project PRJEB25780, we performed WGCNA analysis and Lasso regression and chose CXCR2P1 for the subsequent analysis. Then, we compared the expression difference of CXCR2P1 among different groups. Kaplan-Meier curve was used to analyze the prognostic value of CXCR2P1, which was validated by project IMvigor210 and GEO datasets. ESTIMATE and CIBERSORT algorithm were used to evaluate the reshaping effect of CXCR2P1 to immune microenvironment of tumor. Differentially expressed genes (DEG) analysis, enrichGO analysis, Gene Set Enrichment Analysis (GSEA) and co-expression analysis were used to explore the cell biological function and signaling pathway involved in CXCR2P1.

WGCNA identified CXCR2P1 as a hub gene significantly associated with immune response to PD-1 inhibitors in gastric cancer. CXCR2P1 expression was elevated in responders and correlated with better prognosis. Functional analysis revealed its role in reshaping the tumor immune microenvironment by promoting immune cell infiltration, including M1 macrophages, activated CD4+ T cells, and follicular helper T cells. CXCR2P1 enhanced antigen presentation via the MHC-II complex, influenced key immune pathways, such as Toll-like receptor signaling and T-cell activation, which led to the up-regulation of expression of PD-L1. GSEA showed CXCR2P1 were correlated with microRNAs. Through DEG analysis and expression analysis, MIR215 was identified as a potential direct target of CXCR2P1.

High expression of CXCR2P1 is correlated with better response to PD-1 inhibitor. It reshapes the immune microenvironment by increasing immune infiltration and changing the fraction of immune cells. In tumor immune microenvironment, CXCR2P1 can promote inflammation, enhance antigen presentation and activate the PD-1/PD-L1-related signaling pathway, which might be achieved by CXCR2P1-MIR215 axis.

Gastric adenocarcinoma (GAC) imposes a considerable global health burden. Molecular profiling of GAC from the tumor microenvironment perspective through a multi-omics approach is eagerly awaited in order to allow a more precise application of novel therapies in the near future.

To better understand the tumor-immune interface of GAC, we identified an internal cohort of 82 patients that allowed an integrative molecular analysis including mutational profiling by whole-exome sequencing, RNA gene expression of 770 genes associated with immune response, and multiplex protein expression at spatial resolution of 34 immuno-oncology targets at different compartments (tumorous cells and immune cells). Molecular findings were validated in 595 GAC from the TCGA and ACRG external cohorts with available multiomics data. Prediction of response to immunotherapies of the discovered immunophenotypes was assessed in 1039 patients with cancer from external cohorts with available transcriptome data.

Unsupervised clustering by gene expression identified a subgroup of GAC that includes 52% of the tumors, the so-called Inflamed class, characterized by high tumor immunogenicity and cytotoxicity, particularly in the tumor center at protein level, with enrichment of PIK3CA and ARID1A mutations and increased presence of exhausted CD8+ T cells as well as co-inhibitory receptors such as PD1, CTLA4, LAG3, and TIGIT. The remaining 48% of tumors were called non-inflamed based on the observed exclusion of T cell infiltration, with an overexpression of VEGFA and higher presence of TP53 mutations, resulting in a worse clinical outcome. A 10-gene RNA signature was developed for the identification of tumors belonging to these classes, demonstrating in evaluated datasets comparable clinical utility in predicting response to current immunotherapies when tested against other published gene signatures.

Comprehensive immunophenotyping of GAC identifies an inflamed class of tumors that complements previously proposed tumor-based molecular clusters. Such findings may provide the rationale for exploring novel immunotherapeutic approaches for biomarker-enriched populations in order to improve GAC patient's survival.

The formation of immune synapses (ISs) between cytotoxic T cells and tumor cells is crucial for effective tumor elimination. However, the role of ISs in immune evasion and resistance to immune checkpoint blockades (ICBs) remains unclear. We demonstrate that ICAM-1, a key IS molecule activating LFA-1 signaling in T and natural killer (NK) cells, is often expressed at low levels in cancers. The absence of ICAM-1 leads to significant resistance to T and NK cell-mediated anti-tumor immunity. Using a CRISPR screen, we show that ICAM-1 is epigenetically regulated by the DNA methylation pathway involving UHRF1 and DNMT1. Furthermore, we engineer an antibody-based therapeutic agent, "LFA-1 engager," to enhance T cell-mediated anti-tumor immunity by reconstituting LFA-1 signaling. Treatment with LFA-1 engagers substantially enhances immune-mediated cytotoxicity, potentiates anti-tumor immunity, and synergizes with ICB in mouse models of ICAM-1-deficient tumors. Our data provide promising therapeutic strategies for re-engaging immune stimulatory signals in cancer immunotherapy.

In the progression of gastric cancer (GC), various cell types in the tumor microenvironment (TME) exhibit upregulated expression of programmed death ligand 1 (PD-L1), leading to impaired T-cell function and evasion of immune surveillance. Infection with H. pylori and EBV leads to increased PD-L1 expression in various cell types within TME, resulting in immune suppression and facilitating immune escape of GC cells. In the TME, mesenchymal stem cells (MSCs), M1-like tumor-associated macrophages (MI-like TAM), and myeloid-derived suppressor cells (MDSCs) contribute to the upregulation of PD-L1 expression in GC cells. Conversely, mast cells, M2-like tumor-associated macrophages (M2-like TAM), and tumor-associated neutrophils (TANs) exhibit elevated levels of PD-L1 expression in response to the influence of GC cells. Together, these factors collectively contribute to the upregulation of PD-L1 expression in GC. This review aims to provide a comprehensive summary of the cellular expression patterns of PD-L1 in GC and the underlying molecular mechanisms. Understanding the complex regulatory pathways governing PD-L1 expression may offer novel insights for the development of effective immunotherapeutic interventions.

Immune checkpoint blockade (ICB) has revolutionized cancer treatment, but the therapeutic response is highly heterogeneous, which highlights the necessity for developing predictive biomarkers and overcoming ICB resistance. Cancer cell-intrinsic features, especially those that can be dynamically monitored via liquid biopsy, represent a broader scope for biomarker development. In addition, a potential mode of ICB resistance is tumor-intrinsic mechanisms leading to an immunosuppressive tumor microenvironment (TME). However, the underlying interactive network remains elusive, and the generalizable biomarkers and targeting strategies are still lacking. Here, we uncovered the potential of plasma S100 calcium-binding protein A1 (S100A1) for determining ICB efficacy via liquid biopsy of patients with lung cancer. Multiomics and functional studies have suggested that tumor-intrinsic S100A1 expression correlated with an immunologically "cold" TME and resistance to ICB in multiple syngeneic murine tumors and tissue samples from patients with lung cancer. Mechanistic investigations demonstrated that interfering with the tumor-intrinsic S100A1/ubiquitin-specific protease 7/p65/granulocyte-macrophage colony-stimulating factor (GM-CSF) modulatory axis could potentiate an inflamed TME by promoting M1-like macrophage polarization and T cell function. GM-CSF priming was sufficient to enhance the ICB response in tumors with high S100A1 expression in preclinical models. These findings define S100A1 as a potential blood-based biomarker and a novel synergistic target for cancer immunotherapy.

Immunotherapy has surfaced as a promising therapeutic modality for gastric cancer (GC). A comprehensive review of advancements, current status, and research trends in GC immunotherapy is essential to inform future investigative efforts.

To delineate the trends, advancements, and focal points in immunotherapy for GC.

We performed a bibliometric analysis of 2906 articles in English concerning GC immunotherapy published from 2000 to December 20, 2023, indexed in the Web of Science Core Collection. Data analysis and visualization were facilitated by CiteSpace (6.1.6R), VOSviewer v.1.6.17, and GraphPad Prism v8.0.2.

There has been an increase in the annual publication rate of GC immunotherapy research. China leads in publication volume, while the United States demonstrates the highest citation impact. Fudan University is notable for its citation frequency and publication output. Co-citation analysis and keyword frequency revealed and highlighted a focus on GC prognosis, the tumor microenvironment (TME), and integrative immunotherapy with targeted therapy. Emerging research areas include gastroesophageal junction cancer, adoptive immunotherapy, and the role of Treg cell in immunotherapy.

GC immunotherapy research is an expanding field attracting considerable scientific interest. With the clinical adoption of immunotherapy in GC, the primary goals are to enhance treatment efficacy and patient outcomes. Unlike hematological malignancies, GC's solid TME presents distinct immunological challenges that may attenuate the cytotoxic effects of immune cells on cancer cells. For instance, although CAR-T therapy is effective in hematological malignancies, it has underperformed in GC settings. Current research is centered on overcoming immunosuppression within the TME, with a focus on combinations of targeted therapy, adoptive immunotherapy, Treg cell dynamics, and precise prognosis prediction in immunotherapy. Additionally, immunotherapy's role in treating gastroesophageal junction cancer has become a novel research focus.

Helicobacter pylori (H. pylori) infection induces pathological changes via chronic inflammation and virulence factors, thereby increasing the risk of gastric cancer development. Compared with invasive examination methods, H. pylori-related serum indicators are cost-effective and valuable for the early detection of gastric cancer (GC); however, large-scale clinical validation and sufficient understanding of the specific molecular mechanisms involved are lacking. Therefore, a comprehensive review and analysis of recent advances in this field is necessary. In this review, we systematically analyze the relationship between H. pylori and GC and discuss the application of new molecular biomarkers in GC screening. We also summarize the screening potential and application of anti-H. pylori immunoglobulin G and virulence factor-related serum antibodies for identifying GC risk. These indicators provide early warning of infection and enhance screening accuracy. Additionally, we discuss the potential combination of multiple screening indicators for the comprehensive analysis and development of emerging testing methods to improve the accuracy and efficiency of GC screening. Although this review may lack sufficient evidence due to limitations in existing studies, including small sample sizes, regional variations, and inconsistent testing methods, it contributes to advancing personalized precision medicine in high-risk populations and developing GC screening strategies.

Targeting MALT1's paracaspase activity has been explored for B cell lymphoma and solid tumors. While the role of MALT1 in promoting cancer cell proliferation has been investigated, its involvement in immune evasion is unclear. Here we report that MALT1 promotes immune evasion through its paracaspase and death domain. In a paracaspase-dependent manner, MALT1 protects CD274 mRNA from degradation by its cleavage of ROQUIN1 and ROQUIN2. In a death-domain-dependent manner, MALT1 promotes the proliferation and polarization of tumor-associated macrophages to generate an immunosuppressive tumor microenvironment. Targeting MALT1 with antisense oligonucleotides inhibits PD-L1 expression in patient-derived tumor cells and suppresses the proliferation and M2-like polarization of tumor-associated macrophages isolated from patients with cancer. In preclinical models of solid tumors in female mice, treatment with MALT1 antisense oligonucleotides overcomes resistance to immune-checkpoint inhibitors. Together, our study demonstrates that targeting MALT1 is a potential strategy to overcome immune-checkpoint inhibitor resistance.

In less than a decade, immune checkpoint inhibitors (ICIs) have transformed the management of mismatch repair-deficient (dMMR) and microsatellite instability-high (MSI) cancers. However, beyond colorectal cancer (CRC), much of the evidence is mostly derived from non-randomized phase II studies or post-hoc analyses of broader clinical trials. dMMR/MSI tumours represent a specific subgroup of gastro-esophageal adenocarcinomas (GEA), accounting for approximately 9 % of cases, with a higher prevalence in early-stage compared to advanced-stage disease and older female patients. These tumours are predominantly sporadic, often linked to MLH1 promoter methylation, and rarely exhibit HER2 overexpression/ERBB2 amplification or other oncogenic drivers. The treatment landscape for early stage dMMR/MSI GEA is likely to change substantially soon, as ICIs have shown high pathological complete response (pCR) rates in small phase II trials, raising questions on optimisation of neoadjuvant therapy, and paving the way for organ preservation. The standard of treatment for untreated patients with advanced dMMR/MSI GEA is chemotherapy + ICI irrespectively of PDL-1 status. However, the role of chemotherapy-free regimen consisting of CTLA-4 plus PD-1 inhibitors remains undetermined. This review addresses these and other emerging questions, offering expert opinions and insights into the future therapeutic landscape for dMMR/MSI GEA.

Circulating tumor DNA (ctDNA) is nowadays considered a robust source to search for druggable tumoral genetic alterations, and in some specific settings liquid biopsy (LB) is already part of the diagnostics scenario and it has successfully implemented in the everyday practice. Three strengths make LB an extraordinary tool: i) to represent the complex molecular mosaicism that characterizes spatially heterogeneous malignancies; ii) to monitor in real-time the tumoral molecular landscape (i.e. to depict the longitudinal/temporal tumor evolution); iii) to ensure molecular profiling even in those cases in which tissue sampling is not feasible or not adequate. This review provides a snapshot of the current state of the art concerning ctDNA assay utility in gastric cancer (GC), testing its robustness as marker and seeking to understand the reasons for the delay in its application in clinical practice.

Recently, novel molecular targeted therapies have been developed for gastric and esophageal adenocarcinomas. We examined the status of therapeutic target molecules in esophagogastric junction (EGJ) and Barrett's adenocarcinoma.

Tissue microarrays were constructed from 114 cases of non-Barrett's EGJ adenocarcinoma and 30 cases of Barrett's adenocarcinoma. Immunohistochemistry for mismatch repair proteins, PD-L1, HER2, CLDN18, FGFR2b, and EBER-ISH was performed. When HER2 immunohistochemistry was 2 + , gene amplification was examined using in situ hybridization.

EBER positivity, mismatch repair deficiency, PD-L1 combined positive score (CPS) ≥ 1, CLDN18 expression ≥ 75%, FGFR2b expression, and HER2 positivity were observed in 7 (6.1%), 11 (9.6%), 70 (61.4%), 38 (33.3%), 6 (5.3%), and 11 (9.6%) cases of EGJ adenocarcinoma as well as in 0 (0%), 0 (0%), 23 (76.7%), 7 (23.3%), 2 (6.7%), and 6 (20.0%) cases of Barrett's adenocarcinoma, respectively. PD-L1 CPS ≥ 1 cases had longer recurrence-free survival (P = 0.001) and overall survival (P = 0.003) than CPS < 1 cases. Other target molecules were not associated with survival. A total of 93/114 (81.6%) cases of EGJ adenocarcinoma and 26/30 (86.7%) cases of Barrett's adenocarcinomas expressed at least one target molecule.

Most EGJ and Barrett's adenocarcinomas may be eligible for molecular targeted therapy. Appropriate patient stratification based on these molecular tests will be important for precision medicine of the EGJ and Barrett's adenocarcinoma.

In resectable gastric/gastroesophageal junction adenocarcinoma, microsatellite instability-high (MSI-H) confers improved survival, but limited benefit from chemotherapy. Immunotherapy may eliminate the need for chemotherapy or surgery.

INFINITY is a multicenter, multicohort phase II trial (NCT04817826) investigating in cohort 1 the activity and safety of tremelimumab + durvalumab (T300/D) as neoadjuvant treatment of mismatch repair deficient/MSI-H, resectable gastric/gastroesophageal junction adenocarcinoma. Primary endpoint was pathologic complete response (pCR) rate; Secondary endpoints: progression-free survival (PFS), overall survival (OS), quality of life, and translational analyses. In cohort 2, the activity and safety of T300/D was explored as definitive treatment in patients achieving clinical complete response (cCR). Primary endpoint was 2-year cCR rate, and secondary endpoints were PFS, OS, quality of life, gastrectomy-free survival and translational analyses.

In cohort 1, 18 patients were recruited and 15 evaluable. pCR and major pathologic response-pCR were 60% and 80%, respectively. Since pCR rate in T4 tumors was 17%, this subgroup of patients was excluded from enrollment in cohort 2. At 28.1 months median follow-up, 24-month gastric cancer-specific PFS and OS rates were 85% and 92%, respectively. In cohort 2, 18 patients were enrolled and 17 assessable, and 13 had cCR and started non-operative management. At 11.5 months median follow-up, one patient had local regrowth and underwent salvage surgery; 12-month gastrectomy-free survival was 64.2%.

The INFINITY study provided promising activity results of a chemo-free T300/D combination regimen as preoperative treatment in mismatch repair deficient/MSI gastric/gastroesophageal junction adenocarcinoma and the first available feasibility results of a non-operative management strategy in this disease setting, worthy of further validation in larger cohorts.

Currently, immune checkpoint inhibitors (ICIs) have excellent performance in the clinical treatment of advanced gastric cancer (AGC). However, precisely selecting AGC patients who can benefit from immunotherapy is an urgent difficulty. In this study, we investigated the immunoprognostic role of myeloid-to-lymphocyte ratio (M:L) in AGC patients.

We collected information on 268 AGC patients who were hospitalized in the Department of Medical Oncology of PLA General Hospital from December 2014 to May 2021. The patients were divided into low M: L group (< 3.76) and high M:L group (≥ 3.76). Survival differences between different M: L level groups at baseline and after treatment were analyzed by methods such as Kaplan-Meier, Cox or Logistic regression model.

Progression free survival (PFS) (5.8 months vs. 3.4 months, p = 0.001) and overall survival (OS) (14.1 months vs. 9.0 months, p = 0.001) were significantly longer in the low M:L group than in the high M:L group. After analyses of Cox regression modeling it was concluded that M:L was an independent prognostic factor for PFS (HR 1.371 95%CI 1.057-1.777 p = 0.017) and OS (HR 1.352 95%CI 1.003-1.824 p = 0.048), respectively. Subsequent subgroup analyses performed across immunotherapy lines, regimens, PD-1 inhibitor agents, and age groups revealed a poorer prognosis in the high M:L group. Notably, an increase in the value of M:L after treatment significantly increased the risk of poor prognosis.

M:L ≥ 3.76 is associated with poor prognostic outcomes in AGC patients receiving immunotherapy and may be a predictive biomarker of prognosis. This result needs to be confirmed by larger prospective studies.

The expression patterns and functions of Sushi Domain Containing 2 (SUSD2) differ among various malignancies. This research aims to investigate the expression of SUSD2 and the role of the SUSD2+ cancer-associated fibroblasts (CAFs) for immunotherapy in gastric cancer.

The expression of SUSD2 and specific markers (CD4, CD8, PD-1, TIGIT, TIM-3 and CD163) was determined using immunohistochemistry and multiplex immunofluorescence (mIHC) on paraffin sections. Flow cytometry and western blot were used to assess the expression of SUSD2 in fibroblasts from fresh samples. Also, analysis of single-cell and bulk RNA sequencing was employed to confirm the presence and characterize the function of SUSD2+ CAFs. The predictive power of indicators for neoadjuvant immunotherapy was evaluated via ROC curve analysis. Animal experiment was employed to validate the immunosuppressive effect of SUSD2+ CAFs.

SUSD2 is mainly expressed on fibroblasts within the tumors and the high infiltration of SUSD2+ CAFs went together with a poor survival and a more advanced tumor stage. Significantly, the joint use of SUSD2+ CAFs and CD8+ T cells demonstrated a remarkable ability to predict the efficacy of neoadjuvant immunotherapy superior to PD-L1 combined positive score. High SUSD2+ CAFs was correlated with resistance to immunotherapy as well as low CD8+ T infiltration and high exhausted T cell infiltration.

We have identified a novel subset of CAFs that could predict the survival and response to neoadjuvant immunotherapy of patients. The SUSD2+ CAFs have the potential to serve as a predictive biomarker and a promising target for immunotherapy.

The Cancer Genome Atlas (TCGA) classifies gastric cancer (GC) into four molecular subtypes: Epstein-Barr virus-positive, microsatellite instability-high (MSI-H), genomically stable (GS), and chromosomal instability (CIN). This exploratory analysis compared the genomic landscape of late-stage GC from KEYNOTE-059, KEYNOTE-061, and KEYNOTE-062 studies with early-stage GC from TCGA and evaluated the genomic characteristics of late-stage GC in patients of Western and Asian origin.

Using pretreatment tumor samples, bulk DNA was analyzed via whole-exome sequencing (WES; KEYNOTE-059/KEYNOTE-061) and FoundationOneCDx (KEYNOTE-062) to determine TCGA-defined molecular subtypes (only MSI-H is determinable from FoundationOneCDx), genomic alterations, homologous recombination deficiency (HRD), and tumor mutational burden (TMB); gene expression signatures were analyzed using RNA sequencing.

When comparing KEYNOTE-059/061/062 combined WES and FoundationOneCDx data with data from TCGA, the MSI-H subtype prevalence was numerically lower in patients of Western (5% v 22%) and Asian origin (5% v 19%). When comparing KEYNOTE-059/061 WES data with the TCGA data set, the GS subtype prevalence was numerically higher (36% v 21%) in patients of Western or Asian origin. Among subtypes in KEYNOTE-059/061, HRD scores and TMB trended highest in CIN and MSI-H subtypes, respectively. TP53 mutation was the most prevalent genomic characteristic per KEYNOTE-059/061/062 combined analysis in patients of Western or Asian origin. Gene expression signature distributions were generally similar between patients of Western and Asian origin.

Numerical differences in the prevalence of MSI-H and GS subtypes were observed between early-stage and late-stage GC. Genomic characteristics of late-stage GC were generally similar between patients of Western and Asian origin.

The pathogenesis of ovarian cancer (OvCa) involves a complex interplay of genetic, environmental, and hormonal factors. With the in-depth exploration of tumor ecosystem, exosomes can mediate the immunological status of tumor microenvironment (TME). Therefore, we aimed to recognize the tumor-derived exosomes (TEXs) which can distinguish the immune-hot and cold tumors and reflect the immunotherapeutic responses.

A large set of transcriptomic and single-cell RNA-sequencing (scRNA-seq) datasets were downloaded and used to analyze the expression pattern of CD47 and its immuno-correlations in OvCa and multiple epithelial cell carcinomas such as breast cancers. In addition, a pan-gynecological cancer cohort was used to validate the correlation between CD47 and the inflamed TME.

In the current study, we found that CD47 was a TEX signature and had no transcriptional differences among patients with different clinicopathological features. Moreover, CD47 expression was positively correlated with the activation of immunological signaling pathways and enrichment of immune cell subpopulations in OvCa. Furthermore, in breast cancer and gynecological cancers, CD47, specially expressed in tumor cells, also showed favorable ability to distinguish the immune-hot and cold carcinomas. Moreover, in immunotherapy cohorts of breast cancer and other epithelial cell carcinomas, patients with CD47-high phenotype were more sensitive to immunotherapy and tended to achieve remission after treatment. Results from the TMA showed that CD47 was upregulated in tumor tissues and positively correlated with CD8 level.

In conclusion, CD47 is associated with an inflammatory TME, immune-hot tumors, and sensitivity of immunotherapy, highlighting the values of CD47 in identifying immunological traits and an immunotherapeutic response.

Gastric cancer (GC) is recognized for intrinsic heterogeneity, although it is similarly approached in Europe and Latin America (LATAM). The LEGACY project aimed to deepen GC molecular understanding through multi-omics analysis in Europe and LATAM GC samples.

Tumor samples were centrally reviewed for histology, human epidermal growth factor receptor 2 (HER2) expression, and mismatch repair-deficient (dMMR)/microsatellite instability (MSI) status. In addition, we assessed Epstein-Barr virus (EBV) status, programmed death-ligand 1 (PD-L1) combined positive score (CPS), and carried out tissue genomic profiling including tumor mutation burden (TMB) quantification plus targeted transcriptomics for immune microenvironment and cancer cell signaling scores.

In total, 328 GC patients were enrolled. HER2-positive GC and high PD-L1 CPS were more frequent in Europe than in LATAM (9% versus 3% and 15% versus 3%, respectively), whereas EBV was mainly found in LATAM (7%, versus 3% in Europe), and dMMR/MSI tumors were equally distributed (16%). High TMB was enriched in dMMR/MSI and EBV tumors. Mutations in homologous recombination repair (HRR) genes were frequent in both cohorts (24.8% and 14.7% in Europe and LATAM, respectively), and mostly found in dMMR/MSI (63.6%) and intestinal HER2-negative (18.7%) tumors. The prognosis was poor in diffuse HER2-negative GC patients, whose tumors presented an immunosuppressive microenvironment and other distinct pathway activation signatures.

Our findings relate specific molecular alterations of GC tumors from Europe and LATAM to actionable biomarkers for precision cancer therapies. The proposed GC stratification can be implemented in routine care and guide drug development strategies.

Cell-cell interaction (CCI) networks are key to understanding disease progression and treatment response. However, existing methods for inferring these networks often aggregate data across patients or focus on cell-type level interactions, providing a generalized overview but overlooking patient heterogeneity and local network structures. To address this, we introduce "random cell-cell interaction generator" (RaCInG), a model based on random graphs to derive personalized networks leveraging prior knowledge on ligand-receptor interactions and bulk RNA sequencing data. We applied RaCInG to 8,683 cancer patients to extract 643 network features related to the tumor microenvironment and unveiled associations with immune response and subtypes, enabling prediction and explanation of immunotherapy responses. RaCInG demonstrated robustness and showed consistencies with state-of-the-art methods. Our findings highlight RaCInG's potential to elucidate patient-specific network dynamics, offering insights into cancer biology and treatment responses. RaCInG is poised to advance our understanding of complex CCI s in cancer and other biomedical domains.