Gastric cancer (GC) is a molecularly heterogeneous disease with diverse clinical outcomes. Traditional classifications lack predictive accuracy, necessitating alternative molecular subtyping approaches for effective prognosis prediction. The Asian Cancer Research Group (ACRG) molecular subtypes, combined with immune-associated PD-L1 expression, offer a promising framework to predict patient outcomes and potentially guide treatment strategies in GC.

This study retrospectively analyzed 1007 primary GC patients who underwent surgical resection between January 2017 and June 2019 at the Fourth Hospital of Hebei Medical University. Comprehensive immunohistochemical and fluorescent PCR-capillary electrophoresis analyses were conducted to determine ACRG molecular subtypes (microsatellite instability [MSI], microsatellite stability with epithelial-mesenchymal transition [MSS/EMT], MSS/TP53+, and MSS/TP53-) and PD-L1 expression. We assessed the relationship between these classifications and various clinicopathological parameters, including survival outcomes, using Cox regression and Kaplan-Meier analysis.

The ACRG subtypes showed significant associations with clinicopathological features, including tumor invasion depth, Lauren classification, and HER2 status. The MSI subtype (6.7% of cases) was associated with higher PD-L1 positivity and a favorable prognosis, whereas the EMT subtype had the lowest 5-year survival rate (34.55%) and was predominantly linked to diffuse-type histology. PD-L1 positivity correlated with worse survival outcomes, with independent predictive value alongside ACRG subtypes (HR for PD-L1 = 1.759, p = 0.001; HR for ACRG = 5.144, p < 0.001).

The combination of ACRG molecular subtyping and PD-L1 expression serves as an effective predictor of GC prognosis, facilitating tailored clinical decision-making. The ACRG-PD-L1 classification system offers a practical, cost-effective approach for routine clinical application, providing critical insight into GC heterogeneity. Further multicenter studies are needed to validate these findings and explore the impact of ACRG subtypes on therapy responses, particularly in immunotherapy settings.

This case report describes a rare case of bi-phenotypic gastric cancer with two distinct, but clonally related, histological components. The first component, associated with Epstein-Barr virus (EBV) infection, exhibited the morphological features of gastric carcinoma with lymphoid stroma, suggesting that EBV, as an effective immunogenic factor, may trigger a prominent immune response within the tumour microenvironment. The second component, which was EBV-negative, displayed tubular/papillary morphology and features of increased biological aggressiveness, such as high-grade areas and lymphatic invasion. Immunohistochemical and molecular studies confirmed that, despite the differing morphologies and immunophenotypes, both components were clonally related, with the EBV-negative area showing more complex DNA aberrations, reminiscent of chromosomally instable (CIN) lesions. This case describes clonally related EBV-positive and -negative components within a single gastric cancer, contributing to a better understanding of EBV role in tumour heterogeneity and progression and highlights the impact of EBV loss on tumour behaviour.

The mismatch repair (MMR) system plays a crucial role in the maintenance of DNA replication fidelity and genomic stability. The clinical value of the MMR molecular marker as an immunotherapy for advanced solid tumors has been documented. However, this therapy is not effective in some patients. This study aimed to develop an MMR-related molecular prognostic model for identifying appropriate populations of stomach adenocarcinoma (STAD) for better treatment outcome. The MMR genes expression data were downloaded from TCGA and CCLE databases. The expression of four MMR genes, construction of a prognostic risk model, and assessment of immune infiltration in STAD were performed using Xiantao online tool. GEPIA2 was used to explore the association of MMR genes expression with clinical stage and overall survival. The frequency and prognostic value of MMR genes in STAD were conducted on the cBioPortal. The MLH1 co-expression network was established based on the LinkedOmics database. This study found that the expression of MSH2, MSH6 and PMS2 was up-regulated in STAD tissues. Moreover, differential MMR genetic expression levels were not significantly correlated with the clinical stages of STAD. Besides, no significant difference in PFS or OS was observed in STAD patients with or without MMR genetic alteration. Moreover, MLH1 and MSH2 were used to establish a prognostic risk model. The immune infiltration levels of most immune cells were upregulated in the high-risk group with elevated expression of PDCD1 and low TMB score. Finally, we found that MLH1 was an independent predictor of STAD prognosis among the four MMR genes. An MMR-related prognostic model for STAD was constructed based on genes. This model provides a new therapeutic concept for the diagnosis and treatment of STAD.

SH3 domain-binding glutamic acid-rich protein-like 3 (SH3BGRL3) is involved in several human cancers. However, its relationship with gastric cancer (GC) remains elusive. Multiple online bioinformatic tools were used to evaluate the messenger (m)RNA expression levels of SH3BGRL3 in GC using data from The Cancer Genome Atlas and Gene Expression Omnibus databases. Reverse transcription-quantitative PCR and tissue microarray-based immunohistochemistry were performed to assess SH3BGRL3 expression in relation to clinicopathological parameters and outcomes in patients with GC. Significant differentially expressed genes (DEGs) of SH3BGRL3 were enriched and visualized. Furthermore, associations between the expression of SH3BGRL3 and the infiltration of immune cells were explored. SH3BGRL3 exhibited aberrant expression in tumor tissues compared with adjacent normal tissues at the mRNA and protein expression levels, especially in Epstein-Barr virus-negative GC (EBVnGC). Higher SH3BGRL3 expression was significantly associated with increasing tumor-node-metastasis staging, tumor budding, perineural invasion, EGFR expression, and a notably higher preoperative blood glucose concentration in clinical specimens. Multivariate analysis revealed that higher SH3BGRL3 expression was an independent adverse prognostic factor for the overall survival of patients with EBVnGC (hazard ratio, 1.666; P=0.018). Furthermore, the stratified analysis revealed that the SH3BGRL3 phenotype could help to refine prognosis in patients. The C-index of the nomogram was 0.740 when combining SH3BGRL3 with other clinicopathological parameters, which indicated a good model for clinical follow-up decisions. Gene functional enrichment analysis also revealed that the DEGs of SH3BGRL3 were mainly enriched in regulating ATP metabolism, ATP synthesis, oxidative phosphorylation and the electron transport chain in GC. Moreover, a higher SH3BGRL3 expression was significantly positively correlated with the infiltrating macrophages in GC. In conclusion, SH3BGRL3 is upregulated in GC, particularly in EBVnGC. Higher SH3BGRL3 expression is closely associated with hyperglycemia and poor outcomes in patients with EBVnGC, suggesting its potential as a biomarker and prognostic predictor.

The tumor immune microenvironment is increasingly becoming a key consideration in developing treatment regimens for aggressive cancers, with evidence that regulatory T cells (Tregs) attenuate the antitumor response by interrupting cytotoxic T cells (CD8+). Here, we hypothesized the prognostic relevance of the proportions of Tregs (marked by forkhead box protein 3 [FOXP3]) and CD8+ cells in diffuse, non-Epstein-Barr virus (EBV)/non-microsatellite instability (MSI)-high gastroesophageal adenocarcinomas (GEAs), which are clinically characterized as more aggressive, immunologically inactive tumors as compared with their intestinal counterparts. Cell-count ratios of FOXP3+/CD8+ expression were calculated at the intratumoral region and invasive margin discretely on digital images from 303 chemo-naive non-EBV/non-MSI-high esophagogastric junction (EGJ) adenocarcinomas. A significant modifying prognostic effect of tumor histology was observed between 5-year EGJ cancer-specific survival and the FOXP3+/CD8+ ratio at the invasive margin in pStage I-III tumors (p for interaction = 0.022; hazard ratio [HR] = 8.47 and 95% confidence interval [CI], 2.04-35.19 for high ratio [vs. low] for diffuse; HR = 1.57 and 95% CI, 0.88-2.83 for high ratio [vs. low] for intestinal). A high FOXP3+/CD8+ ratio at the invasive margin was associated with RUNX3 methylation (p = 0.035) and poor prognosis in RUNX3-methylated diffuse histological subtype (5-year EGJ cancer-specific survival, 52.3% for high and 100% for low, p = 0.015). Multiomics data from The Cancer Genome Atlas linked CCL28 with RUNX3-suppressed diffuse histological subtypes of non-EBV/non-MSI-high GEA. Our data suggest that a high FOXP3+/CD8+ ratio at the invasive margin might indicate tumor immune escape via CCL28, particularly in the RUNX3-methylated diffuse histological subtype.

A stroma a‑reactive invasion front area (SARIFA) is a new prognostic biomarker in carcinomas. Essentially, SARIFA describes the occurrence of direct contact between at least five tumor cells and adipocytes. This phenomenon is extremely easy and quick to identify, shows an extremely low interobserver variability, and does not require any additional staining as it can be identified on standard HE sections. The prognostic efficiency has now been demonstrated in gastric, colorectal, pancreatic, and prostate carcinoma.

Queiroz et al. showed that the application of cluster methodology for classifying gastric cancer is suitable and efficient within a Brazilian cohort, which is known for its population heterogeneity. The study highlighted the potential utilization of this method within public health services due to its low-cost, presenting a viable means to improve the diagnosis and prognosis of gastric cancer.

Our Brazilian cohort with gastric cancer has a distinct distribution between mutated and normal p53.

New genetic marker-based classifications improve gastric cancer diagnosis accuracy.

Machine learning integration enhances predictive value in gastric cancer diagnosis.

Molecular biomarkers complement clinical decisions, advancing personalized medicine.

Gastric adenocarcinoma remains an aggressive disease with a poor prognosis, as evidenced by a 5-year survival rate of approximately 31%. The histological classifications already proposed do not accurately reflect the high biological heterogeneity of this neoplasm, particularly in diverse populations, and new classification systems using genetic markers have recently been proposed. Following these newly proposed models, we aimed to assess the cluster distribution in a Brazilian cohort. Furthermore, we evaluated whether the inclusion of other clinical and histological parameters could enhance the predictive value.

We used a previously described four-immunohistochemistry/EBER-ISH marker to classify a cohort of 30 Brazilian patients with gastric adenocarcinoma into five different clusters and compared the distribution with other genetically diverse populations. Furthermore, we used artificial intelligence methods to evaluate whether other clinical and pathological parameters could improve the results of the methodology.

Disclosing the genetic variability between populations, we observed a more balanced distribution of the aberrant/normal p53 ratio (0.6) between patients negative for the other markers tested, unlike previous studies with Asian and North American populations. In addition, decision tree analysis reinforced the efficiency of these new classifications, as the stratification accuracy was not altered with or without additional data.

Our study underscores the importance of local research in characterizing diverse populations and highlights the complementary role of molecular biomarkers in personalized medicine for gastric adenocarcinoma, enhancing diagnostic accuracy and potentially improving survival rates.

Gastrointestinal (GI) cancers are highly heterogeneous at multiple levels. Tumor heterogeneity can be captured by molecular profiling, such as genetic, epigenetic, proteomic, and transcriptomic classification. Transcriptomic subtyping has the advantage of combining genetic and epigenetic information, cancer cell-intrinsic properties, and the tumor microenvironment (TME). Unsupervised transcriptomic subtyping systems of different GI malignancies have gained interest because they reveal shared biological features across cancers and bear prognostic and predictive value. Importantly, transcriptomic subtypes accurately reflect complex phenotypic states varying not only per tumor region, but also throughout disease progression, with consequences for clinical management. Here, we discuss methodologies of transcriptomic subtyping, proposed taxonomies for GI malignancies, and the challenges posed to clinical implementation, highlighting opportunities for future transcriptomic profiling efforts to optimize clinical impact.

The Cancer Genome Atlas (TCGA) recognizes four molecular subgroups of gastric cancer: Epstein-Barr virus (EBV) positive, microsatellite instable (MSI), genomically stable (GS), and chromosomal instable (CIN). Since a GS/CIN classifier is lacking, alternative markers such as Lauren's histopathology or CDH1/p53 immunohistochemistry are commonly applied. Here we compared survival of gastric cancer subgroups determined by four methods.

309 EBV negative and microsatellite stable tumors were included from the Dutch D1/D2 trial and assigned to subgroups by: (i) TCGA's specific chromosomal copy number aberrations, (ii) genome instability index (GII), (iii) Lauren's classification, and (iv) CDH1/p53 immunohistochemistry. Subgroups were associated with cancer-related survival (CRS).

Five-year CRS was 42.0% for diffuse and 49.5% for patients with intestinal type tumors, and 57.8% for GS and 41.6% for patients with CIN tumors. Classification by GII or CDH1/p53 IHC did not correlate with CRS. The combination of TCGA and Lauren classifications resulted in four distinct subgroups. Five-year CRS for GS-intestinal (n = 24), GS-diffuse (n = 57), CIN-intestinal (n = 142) and CIN-diffuse (n = 86) was 61.4%, 56.5%, 47.6%, and 31.5%, respectively.

TCGA's GS and CIN subgroups have additional prognostic value to Lauren's classification in resectable gastric cancer. GS-intestinal, GS-diffuse, CIN-intestinal and CIN-diffuse are suggested stratification variables for future studies.

Aims Currently, the clinicopathological characteristics of gastric cancer (GC) with oncogenic NTRK alterations are not well known. Although NTRK fusion has been identified as prevalent in DNA mismatch repair protein deficient (dMMR) colorectal cancer (CRC), the relationship between NTRK alterations and dMMR protein expression in GC has not been previously explored.

Our study comprised 51 cases of EBV(Epstein-barr virus)-associated gastric carcinomas, 94 cases of dMMR GC, 90 cases of gastric adenocarcinoma with hepatoid or enteroblastic differentiation (GAHED) and 256 cases of conventional GC. Furthermore, to investigate the connection between NTRK fusion and dMMR proteins, we collected dMMR tumours of various types, including 21 cases of duodenal adenocarcinomas, 46 endometrioid carcinomas and 82 CRCs. NTRK fusion and amplification were screened in GC and various types of dMMR tumours using fluorescence in situ hybridisation (FISH), while cases positive for FISH translocation underwent next-generation sequencing testing.

Our findings revealed the existence of two cases each of NTRK fusions and NTRK amplifications, which were all enriched in case of GAHED. Additionally, following an analysis of several types of cancers, we discovered that NTRK gene alterations were only present in dMMR CRC.

Our results indicate that NTRK gene alterations are not enriched in GC with dMMR but are specifically enriched in cases of GAHED.

Gastric cancers (GC) are divided into subtypes based on molecular profile: Epstein-Barr virus (EBV)-positive, microsatellite instability (MSI), chromosomal instability (CIN) and genomically stable (GS) tumours. The prognostic impact of this classification is unclear. The aim was to evaluate whether the molecular subtypes determined using in-situ hybridisation (ISH) and immunohistochemistry (IHC) are associated with clinicopathological parameters and prognosis.

The study included 503 GC patients. Based on ISH (EBV) and IHC (MSI and TP53), tumours were divided into EBV-positive, MSI, CIN (EBVneg/MSS/TP53aberrant) and GS (EBVneg/MSS/TP53wild-type) subgroups. Survival analyses with intestinal- and diffuse-type tumours were examined separately. EBV-positive tumours associated with male sex. Both EBV-positive and MSI tumours associated with intestinal type. CIN tumours associated with intestinal-type and positive lymph node status. GS tumours associated with diffuse-type and negative lymph node status. In the total cohort, no significant differences in the 5-year survival were observed. In intestinal tumours, the 5-year survival was better in EBV-positive tumours compared with GS tumours [hazard ratio (HR) = 0.57, 95% confidence interval (CI) = 0.33-0.99]. In diffuse tumours, the 5-year survival was worse in CIN tumours compared with GS tumours (HR = 1.57, 95% CI = 1.14-2.18). In radically resected diffuse tumours, the 5-year survival was worse in MSI tumours compared with GS tumours (HR = 3.26, 95% CI = 1.20-8.82).

The molecular classification is associated with histological type but not prognosis in GC. As the prognostic effects of molecular subtypes in intestinal- and diffuse-type cancers may differ, combining histological and molecular information is recommended for future studies.

Although microsatellite stability/Epithelial-mesenchymal transition (MSS/EMT) subtypes have been reported in multiple cancer prognosis studies, strong confounding factors between MSS/EMT (usually with Lauren's diffuse phenotype) and diffuse gastric cancer (GC) may obscure the independent prognostic value of diffuse GC. Additionally, recent studies suggest a strong correlation between mural stratification based on CT and diffuse GC. This study aims to investigate potential prognostic factors of MSS diffuse GC using mural stratification and to develop a risk assessment model.

This retrospective study included 131 patients with MSS diffuse GC who underwent radical surgery. Univariate and multivariate Cox proportional hazards regression analysis was used to identify model predictors and construct a nomogram for overall survival (OS) and recurrence-free survival (RFS) risks. The model's performance was evaluated using ROC, accuracy, and C-index. Internal validation of the model was conducted using the bootstrap resampling method.

Among 131 cases, 60 cases (45.8%) exhibited grade 2 mural stratification, which correlated with a poorer tumor prognosis and a more invasive phenotype. Furthermore, a nomogram for predicting OS and RFS prognosis was established based on multivariate results (age, extranodal invasion, mural stratification, and/or P53). The nomogram demonstrated excellent performance, with an AUC of 0.859 (95% CI 0.794-0.924) for OS and 0.859 (95% CI 0.789-0.929) for RFS. Internal validation using 1000 bootstrap samples yielded AUC values of 0.845 and 0.846 for OS and RFS, respectively.

Grade 2 mural stratification based on CT imaging revealed a more aggressive invasive phenotype, characterized by increased LN metastasis, higher rates of peritoneal metastasis, and a poorer short-term prognosis. Furthermore, the CT phenotype-based nomogram demonstrates favorable discrimination and calibration, enabling convenient individual short-term prognostic evaluation following resection of MSS diffuse GC.

AT-rich interaction domain 1 (ARID1A) is a pivotal gene with a significant role in gastrointestinal tumors which encodes a protein referred to as BAF250a or SMARCF1, an integral component of the SWI/SNF (SWItch/sucrose non-fermentable) chromatin remodeling complex. This complex is instrumental in regulating gene expression by modifying the structure of chromatin to affect the accessibility of DNA. Mutations in ARID1A have been identified in various gastrointestinal cancers, including colorectal, gastric, and pancreatic cancers. These mutations have the potential to disrupt normal SWI/SNF complex function, resulting in aberrant gene expression and potentially contributing to the initiation and progression of these malignancies. ARID1A mutations are relatively common in gastric cancer, particularly in specific adenocarcinoma subtypes. Moreover, such mutations are more frequently observed in specific molecular subtypes, such as microsatellite stable (MSS) cancers and those with a diffuse histological subtype. Understanding the presence and implications of ARID1A mutations in GC is of paramount importance for tailoring personalized treatment strategies and assessing prognosis, particularly given their potential in predicting patient response to novel treatment strategies including immunotherapy, poly(ADP) ribose polymerase (PARP) inhibitors, mammalian target of rapamycin (mTOR) inhibitors, and enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2) inhibitors.

The availability of more effective biological therapy can improve outcomes of gastric cancer (GC), but most patients do not have access to personalized treatment. GC molecular classification helps identify patients suitable for specific therapies and provides useful prognostic information. To date, only a small number of patients have access to molecular classification. We proposed a working molecular classification that can be delivered using on-slide tests available in most histopathology laboratories. We used eight on-slide tests [in situ hybridization (ISH) for Epstein-Barr virus-encoded small ribonucleic acid (EBER) and immunohistochemistry (IHC) for MutL homolog 1 (MLH1), PMS1 homolog 2 (PMS2), MutS homolog 2 (MSH2), MutS homolog 6 (MSH6), E-cadherin, β-catenin and p53] to classify GC into one of six categories: GC associated with Epstein-Barr virus (GC-EBV), GC mismatch repair deficient (GC-dMMR), GC with epithelial-mesenchymal transition (GC-EMT), GC with chromosomal instability (GC-CIN), GC genomically stable (GC-GS) and GC not otherwise specified (GC-NOS)∕indeterminate. The classification has provision also for current and future on-slide companion diagnostic (CDx) tests necessary to select specific biological therapies and, as proof of principle, in this study we used three CDx tests currently required for the management of GC [human epidermal growth factor receptor 2 (Her2), programmed cell death-ligand 1 (PD-L1) 22C3 and Claudin18.2 (CLDN18.2)]. This paper describes the necessary tissue pathways and laboratory workflow and assesses the feasibility of using this classification prospectively on small endoscopic biopsies of gastric and gastroesophageal junction adenocarcinoma. This work demonstrates that such molecular classification can be implemented in the context of a histopathology diagnostic routine with little impact on turnaround times and laboratory capacity. The widespread adoption of a molecular classification for GC will help refine prognosis and guide the choice of more appropriate biological therapy for these patients.

Esophageal cancer is the eighth most common cancer globally, affecting approximately 570,000 people worldwide and currently ranking sixth among cancer-related mortality (Uhlenhopp et al. in, Clin J Gastroenterol 13:1010-1021, 2020). The prognosis is poor as many patients present with locally incurable or metastatic disease. In spite of advancements in treatment, the overall 5-year survival rates are in the realm of 10% whereas the 5-year post-esophagectomy survival rates are in the realm of 15-40% [2]. The incidence rates vary dramatically worldwide, which can be attributed to demographic and socioeconomic factors. Although the vast majority of esophageal neoplasms arise from the epithelial layer and include squamous cell carcinoma (SCC) and adenocarcinoma (AC), a subset of neuroendocrine and soft tissue tumors can also occur in the esophagus. Several tasks are presented to the surgical pathologist when dealing with esophageal carcinoma that include rendering a diagnosis, classifying the histological type, and assessing prognostic factors. This narrative review aims to evaluate current literature on various esophageal neoplasms and highlight pathological factors that impact clinical decision making and prognosis.

Background and Objectives: Gastric cancer (GC) is one of the most commonly diagnosed cancers and the fourth cause of cancer death worldwide. Personalised treatment improves GC outcomes. A molecular classification is needed to choose the appropriate therapy. A classification that uses on-slide biomarkers and formalin-fixed and paraffin-embedded (FFPE) tissue is preferable to comprehensive genomic analysis. In 2016, Setia and colleagues proposed an on-slide classification; however, this is not in widespread use. We propose a modification of this classification that has six subgroups: GC associated with Epstein-Barr virus (GC EBV+), GC with mismatch-repair deficiency (GC dMMR), GC with epithelial-mesenchymal transformation (GC EMT), GC with chromosomal instability (GC CIN), CG that is genomically stable (GC GS) and GC not otherwise specified (GC NOS). This classification also has a provision for biomarkers for current or emerging targeted therapies (Her2, PD-L1 and Claudin18.2). Here, we assess the implementation and feasibility of this inclusive working classification. Materials and Methods: We constructed a tissue microarray library from a cohort of 79 resection cases from FFPE tissue archives. We used a restricted panel of on-slide markers (EBER, MMR, E-cadherin, beta-catenin and p53), defined their interpretation algorithms and assigned each case to a specific molecular subtype. Results: GC EBV(+) cases were 6%, GC dMMR cases were 20%, GC EMT cases were 14%, GC CIN cases were 23%, GC GS cases were 29%, and GC NOS cases were 8%. Conclusions: This working classification uses markers that are widely available in histopathology and are easy to interpret. A diagnostic subgroup is obtained for 92% of the cases. The proportion of cases in each subgroup is in keeping with other published series. Widescale implementation appears feasible. A study using endoscopic biopsies is warranted.

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.

In this study, we compared programmed death-ligand 1 (PD-L1) expression in primary tissue samples and its soluble form (sPD-L1) concentration in matched preoperative plasma samples from gastric cancer patients to understand the relationship between tissue and plasma PD-L1 expression and to determine its diagnostic and prognostic value.

PD-L1 expression in tissue was assessed by immunohistochemistry and enzyme-linked immunosorbent assay (ELISA), and sPD-L1 concentration in plasma was quantified by ELISA. The levels of the CD274 gene, which encodes for PD-L1 protein, were examined as part of bulk tissue RNA-sequencing analyses. Additionally, we evaluated the association between sPD-L1 levels and various laboratory parameters, disease characteristics, and patient outcomes.

GC patients had significantly higher levels of sPD-L1 in their plasma (71.69 pg/mL) compared to healthy controls (35.34 pg/mL) (p < 0.0001). Moreover, sPD-L1 levels were significantly correlated with tissue PD-L1 protein, CD274 mRNA expression, larger tumor size, advanced tumor stage, and lymph node metastasis. Elevated sPD-L1 levels (> 103.5 ng/mL) were associated with poor overall survival (HR = 2.16, 95%CI 1.15-4.08, p = 0.017). Furthermore, intratumoral neutrophil and dendritic cell levels were directly correlated with plasma sPD-L1 concentration in the GC patients.

sPD-L1 was readily measurable in GC patients, and its level was associated with GC tissue PD-L1 expression, greater inflammatory cell infiltration, disease progression, and survival. Thus, sPD-L1 may be a useful minimally invasive diagnostic and prognostic biomarker in GC patients.

Survival in oesophago-gastric cancer (OGC) is poor due to early diagnostic challenges. Non-invasive risk stratification may identify susceptible patients with pre-malignant or benign disease. Following diagnostic confirmation with endoscopic biopsy, early OGC may be treated sooner. Mucins are transmembrane glycoproteins implicated in OGC with potential use as biomarkers of malignant transformation. This systematic review defines the role of mucins in OGC diagnosis. A literature search of MEDLINE, Web of Science, Embase and Cochrane databases was performed following PRISMA protocols for studies published January 1960-December 2022. Demographic data and data on mucin sampling and analysis methods were extracted. The review included 124 studies (n = 11,386 patients). Gastric adenocarcinoma (GAc) was the commonest OG malignancy (n = 101) followed by oesophageal adenocarcinoma (OAc, n = 24) and squamous cell carcinoma (OSqCc, n = 10). Mucins MUC1, MUC2, MUC5AC and MUC6 were the most frequently implicated. High MUC1 expression correlated with poorer prognosis and metastases in OSqCc. MUC2 expression decreases during progression from healthy mucosa to OAc, causing reduced protection from gastric acid. MUC5AC was upregulated, and MUC6 downregulated in GAc. Mucin expression varies in OGC; changes may be epigenetic or mutational. Profiling upper GI mucin expression in OGC, with pre-malignant, benign and healthy controls may identify potential early diagnostic biomarkers.

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.

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.

With approximately one million diagnosed cases and over 700,000 deaths recorded annually, gastric cancer (GC) is the third most common cause of cancer-related deaths worldwide. GC is a heterogeneous tumor. Thus, optimal management requires biomarkers of prognosis, treatment selection, and treatment response. The Cancer Genome Atlas program sub-classified GC into molecular subtypes, providing a framework for treatment personalization using traditional chemotherapies or biologics. Here, we report a comprehensive study of GC vascular and immune tumor microenvironment (TME)-based on stage and molecular subtypes of the disease and their correlation with outcomes. Using tissues and blood circulating biomarkers and a molecular classification, we identified cancer cell and tumor archetypes, which show that the TME evolves with the disease stage and is a major determinant of prognosis. Moreover, our TME-based subtyping strategy allowed the identification of archetype-specific prognostic biomarkers such as CDH1-mutant GC and circulating IL-6 that provided information beyond and independent of TMN staging, MSI status, and consensus molecular subtyping. The results show that integrating molecular subtyping with TME-specific biomarkers could contribute to improved patient prognostication and may provide a basis for treatment stratification, including for contemporary anti-angiogenesis and immunotherapy approaches.

Evidence suggests that a fraction of new gastric cancer cases may be etiologically associated with Epstein-Barr virus (EBV), a known carcinogenic agent. We aimed to systematically explore the proportion of EBV-positive gastric cancer.

We did a systematic review (PROSPERO CRD42020164473) from January 1990 to August 2021. For each country and geographical region with available data, pooled prevalence and corresponding 95% confidence intervals (CIs) of EBV in gastric tumors were calculated for 3 subtypes of gastric adenocarcinoma (conventional adenocarcinoma, lymphoepithelioma-like gastric carcinoma, and remnant/stump carcinoma). For conventional adenocarcinoma, prevalence ratios (PRs) were presented for sex, Lauren's classification, gastric cancer stage, and anatomical location of the stomach.

In 220 eligible studies including over 68,000 cases of conventional gastric adenocarcinoma, EBV prevalence in tumor cells was 7.5% (95% CI, 6.9%-8.1%) and was higher in men compared with women (PR, 2.1; 95% CI, 1.9-2.4), in diffuse type compared with intestinal type (PR, 1.3; 95% CI, 1.1-1.5), and in the proximal region compared with the distal region (PR, 2.5; 95% CI, 2.0-3.1). There was no difference in EBV prevalence by gastric cancer stage. EBV prevalence was 75.9% (95% CI, 62.8%-85.5%) among lymphoepithelioma-like gastric carcinoma and 26.3% (95% CI, 22.2%-32.0%) among remnant or stump carcinoma.

Assuming a causal association between EBV and gastric cancer, our findings, when applied to the GLOBOCAN 2020 gastric cancer incidence, suggest that primary prevention such as the development of an effective EBV vaccine might prevent 81,000 EBV-associated gastric cancer cases worldwide annually.

Clarification of the prognostic value and relationship of MUC-phenotypes of gastric cancer with clinical and morphological parameters.

Surgical material from 310 patients with a verified diagnosis of gastric cancer was studied. Samples were immunohistochemically stained with antibodies to MUC2, CD10, MUC5AC. The results were compared with clinical and morphological characteristics of gastric cancer and patient survival data.

The MUC-null and MUC-mix groups significantly differ in the prevalence of subtotal/total tumors from the MUC-I group (p=0.022 and p=0.007, respectively), where there are significantly fewer such tumors. Tubular tumors were more common in the MUC-null group compared to the MUC-G (p=0.026) and MUC-mix (p=0.006) groups, and there were fewer cases with the presence of "signet-ring" cells in the MUC-null group (p=0.000). When studying the discohesive histological type, the literature data on smaller tumor sizes and a lower frequency of lymph node metastasis for MUC-G status were not confirmed, but a more frequent proximal localization of MUC-I tumors was found (p=0.003). No statistically significant differences in survival were found in the analysis of the total sample. Differences in survival were found only in discohesive cancers, where the best survival was recorded for the MUC-null group, and the worst for the MUC-mix group (p=0.022). MUC status is not an independent predictor of gastric cancer (HR=1.662, p=0.093).

Between tumors with different MUC statuses, there were differences in localization and belonging to individual histological types. Significant differences in survival were found only for discohesive cancers with MUC-null and MUC-mix statuses. Separation of gastric cancers according to MUC status may have only limited predictive value in selected histological forms of cancer.

Molecular testing for microsatellite instability (MSI) status plays a vital role in the clinical management of gastric cancer (GC). Nevertheless, challenges of routinely applied technology for MSI determination exist. This study aimed to develop and validate a non-invasive imaging biomarker for MSI assessment in GC and explore its prognostic value.

We retrospectively recruited 396 GC patients with pretreatment CT images from a single center and a public database and divided them into an original cohort (n = 356) and an external validation cohort (n = 40). The SMOTE algorithm was used to generate a balanced training cohort (n = 192) and the independent radiomics model, clinical model, and radiomics-clinic combined model were constructed for determining MSI status. The models' discrimination, calibration, clinical usefulness, and prognosis significance were evaluated by AUC, calibration, decision curve analyses, and Kaplan-Meier curve analysis, respectively.

The radiomics-clinic combined model derived from clinical and quantitative CT-based "Radscore" exhibited the best discriminatory abilities of MSI status in all cohorts, with AUCs of 0.836 (95% CI, 0.780-0.893) in the training cohort, 0.834 (95% CI, 0.688-0.981) in the external validation cohort, and 0.750 (95% CI, 0.682-0.819) in the original cohort, respectively. Meanwhile, the combined model demonstrated goodness of fitness, higher clinical net benefits, and significant positive integrated discrimination improvement compared with any independent model. While it showed no significant overall survival- or progression-free survival-based risk stratification ability (p > 0.05).

The radiomics-clinic combined model could be a potential non-invasive biomarker for MSI status in GC, which help clinical decision-making, nevertheless, provided limited prognostic ability.

In gastric cancer (GC), HER2 was the first biomarker for guided therapy registered for clinical use. Considering the recent approvals of immune check-point blockade (ICB) in gastro-oesophageal cancers, testing for mismatch repair deficiency (dMMR), Epstein-Barr virus (EBV) and PD-L1 combined positive score (CPS) is becoming increasingly important. Here we describe a real-world cohort on biomarker assessment in GC patients.

Patients diagnosed with GC between 2017 and 2021 were included. Biomarker results were retrieved from electronic patient files. PD-L1 CPS was determined retrospectively on dMMR and EBV-positive (EBV+) tumours. Data on genomic sequencing were analysed separately.

Of 363 patients identified, 45% had metastatic disease. In 335 patients (92%) at least one biomarker was tested. The prevalence of HER2+, dMMR and EBV+ tumours was 10% (32 of 319), 7% (20 of 294) and 1% (three of 235), respectively. Of the dMMR and EBV+ tumours, 95% had a PD-L1 CPS ≥ 5. Therapeutic strategy was adjusted in 31 of 55 patients and consisted of anti-HER2 therapies as well as ICB in clinical trials. Genomic alterations were found in 44 of 60 tested patients. TP53 (73%) and PIK3CA (20%) mutations were most common, followed by KRAS mutations (11%) and amplifications (11%).

In this real-world cohort, testing for HER2, dMMR and EBV status affected treatment decisions in 56% of the patients. Although most dMMR and EBV+ tumours had a PD-L1 CPS ≥ 5, not all patients with a high probability of treatment response are identified. Based on these results, a stepwise diagnostic strategy is proposed.

Predictive biomarkers are the mainstay of precision medicine. This review summarizes the advancements in tissue-based diagnostic biomarkers for gastric cancer, which is considered the leading cause of cancer-related deaths worldwide. A disease seen in the elderly, it is often diagnosed at an advanced stage, thereby limiting therapeutic options. In Western countries, neoadjuvant/perioperative (radio-)chemotherapy is administered, and adjuvant chemotherapy is administered in the East. The morpho-molecular classification of gastric cancer has opened novel avenues identifying Epstein-Barr-Virus (EBV)-positive, microsatellite instable, genomically stable and chromosomal instable gastric cancers. In chromosomal instable tumors, receptor tyrosine kinases (RKTs) (e.g., EGFR, FGFR2, HER2, and MET) are frequently overexpressed. Gastric cancers such as microsatellite instable and EBV-positive types often express immune checkpoint molecules, such as PD-L1 and VISTA. Genomically stable tumors show alterations in claudin 18.2. Next-generation sequencing is increasingly being used to search for druggable targets in advanced palliative settings. However, most tissue-based biomarkers of gastric cancer carry the risk of a sampling error due to intratumoral heterogeneity, and adequate tissue sampling is of paramount importance.

The first edition of 'A Standardized Pathology Report for Gastric Cancer' was initiated by the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists and published 17 years ago. Since then, significant advances have been made in the pathologic diagnosis, molecular genetics, and management of gastric cancer (GC). To reflect those changes, a committee for publishing a second edition of the report was formed within the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists. This second edition consists of two parts: standard data elements and conditional data elements. The standard data elements contain the basic pathologic findings and items necessary to predict the prognosis of GC patients, and they are adequate for routine surgical pathology service. Other diagnostic and prognostic factors relevant to adjuvant therapy, including molecular biomarkers, are classified as conditional data elements to allow each pathologist to selectively choose items appropriate to the environment in their institution. We trust that the standardized pathology report will be helpful for GC diagnosis and facilitate large-scale multidisciplinary collaborative studies.

The first edition of 'A Standardized Pathology Report for Gastric Cancer' was initiated by the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists and published 17 years ago. Since then, significant advances have been made in the pathologic diagnosis, molecular genetics, and management of gastric cancer (GC). To reflect those changes, a committee for publishing a second edition of the report was formed within the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists. This second edition consists of two parts: standard data elements and conditional data elements. The standard data elements contain the basic pathologic findings and items necessary to predict the prognosis of GC patients, and they are adequate for routine surgical pathology service. Other diagnostic and prognostic factors relevant to adjuvant therapy, including molecular biomarkers, are classified as conditional data elements to allow each pathologist to selectively choose items appropriate to the environment in their institution. We trust that the standardized pathology report will be helpful for GC diagnosis and facilitate large-scale multidisciplinary collaborative studies.

We investigated the impactof microsatellite instability (MSI) and Epstein-Barr virus (EBV) status in gastric cancer (GC), regarding response to perioperative chemotherapy (POPChT), overall survival (OS), and progression-free survival (PFS). We included 137 cases of operated GC, 51 of which were submitted to POPChT. MSI status was determined by multiplex PCR and EBV status by EBV-encoded RNA in situ hybridization. Thirty-seven (27%) cases presented as MSI-high, and seven (5.1%) were EBV+. Concerning tumor regression after POPChT, no differences were observed between the molecular subtypes, but females were more likely to respond (p = 0.062). No significant differences were found in OS or PFS between different subtypes. In multivariate analysis, age (HR 1.02, IC 95% 1.002-1.056, p = 0.033) and positive lymph nodes (HR 1.82, IC 95% 1.034-3.211, p = 0.038) were the only prognostic factors for OS. However, females with MSI-high tumors treated with POPChT demonstrated a significantly increased OS compared to females with MSS tumors (p = 0.031). In conclusion, we found a high proportion of MSI-high cases. MSI and EBV status did not influence OS or PFS either in patients submitted to POPChT or surgery alone. However, superior survival of females with MSI-high tumors suggests that sex disparities and molecular classification may influence treatment options in GC.

Multifocal esophageal squamous cell carcinomas (ESCCs) can be diagnosed as of multicentric origin (MO) or intramural metastasis (IMM). We aimed here to accurately discriminate MO from IMM and explore the tumor immune microenvironment of multifocal ESCCs. Multifocal ESCCs were identified in 333 ESCC patients, and in 145 patients discrimination between MO and IMM was not possible by histopathological examination. Of the 145 patients, tissues of 14 were analyzed by whole-exome sequencing (WES) of 71 different tumor regions, and MO, IMM, and MO/IMM mixed groups were identified in three, ten, and one cases, respectively, based on the similarity of genomic architecture between or among different tumors from one patient. Further phylogenetic analyses revealed complex clonal evolution patterns in IMM cases, and tumor cells disseminated from the primary tumors to IMM tumors were independent of lymph node metastasis. The NanoString-based assay showed that immune cell infiltrates were significantly enriched, and that the immune and proliferation pathways were more activated, in large tumors than in small ones in MO but not IMM cases. Similarly, PD-L1 expression and the density of paratumoral CD8⁺ T cells were higher in large tumors than in small tumors in MO. Taken together, through analysis of the genomic and immune landscapes, our study has comprehensively characterized the heterogeneity and clonal relationship of multifocal ESCCs, which may be helpful in distinguishing MO from IMM, and for interpreting the immunotherapy responses for multifocal ESCC patients. © 2022 The Pathological Society of Great Britain and Ireland.

Gastric cancer (GC) is one of the major causes of cancer deaths worldwide. The disease is seldomly detected early and this limits treatment options. Because of its heterogeneous and complex nature, the disease remains poorly understood. The literature supports the contribution of the gut microbiome in the carcinogenesis and chemoresistance of GC. Drug resistance is the major challenge in GC therapy, occurring as a result of rewired metabolism. Metabolic rewiring stems from recurring genetic and epigenetic factors affecting cell development. The gut microbiome consists of pathogens such as H. pylori, which can foster both epigenetic alterations and mutagenesis on the host genome. Most of the bacteria implicated in GC development are Gram-negative, which makes it challenging to eradicate the disease. Gram-negative bacterium co-infections with viruses such as EBV are known as risk factors for GC. In this review, we discuss the role of microbiome-induced GC carcinogenesis. The disease risk factors associated with the presence of microorganisms and microbial dysbiosis are also discussed. In doing so, we aim to emphasize the critical role of the microbiome on cancer pathological phenotypes, and how microbiomics could serve as a potential breakthrough in determining effective GC therapeutic targets. Additionally, consideration of microbial dysbiosis in the GC classification system might aid in diagnosis and treatment decision-making, taking the specific pathogen/s involved into account.

Gastric cancer has one of the highest incidence rates and is one of the leading causes of cancer-related mortality worldwide. Sequential steps within the carcinogenic process are observed in gastric cancer as well as in pancreatic cancer and colorectal cancer. Kirsten rat sarcoma viral oncogene homolog (KRAS) is the most well-known oncogene and can be constitutively activated by somatic mutations in the gene locus. For over 2 decades, the functions of Kras activation in gastrointestinal (GI) cancers have been studied to elucidate its oncogenic roles during the carcinogenic process. Different approaches have been utilized to generate distinct in vivo models of GI cancer, and a number of mouse models have been established using Kras-inducible systems. In this review, we summarize the genetically engineered mouse models in which Kras is activated with cell-type and/or tissue-type specificity that are utilized for studying carcinogenic processes in gastric cancer as well as pancreatic cancer and colorectal cancer. We also provide a brief description of histological phenotypes and characteristics of those mouse models and the current limitations in the gastric cancer field to be investigated further.

Gastric cancer is a major source of global cancer mortality with limited treatment options and poor patient survival. As our molecular understanding of gastric cancer improves, we are now beginning to recognize that these cancers are a heterogeneous group of diseases with incredibly unique pathogeneses and active oncogenic pathways. It is this molecular diversity and oftentimes lack of common oncogenic driver mutations that bestow the poor treatment responses that oncologists often face when treating gastric cancer. In this review, we will examine the treatments for gastric cancer including up-to-date molecularly targeted therapies and immunotherapies. We will then review the molecular subtypes of gastric cancer to highlight the diversity seen in this disease. We will then shift our discussion to basic science and gastric cancer mouse models as tools to study gastric cancer molecular heterogeneity. Furthermore, we will elaborate on a molecular process termed paligenosis and the cyclical hit model as key events during gastric cancer initiation that impart nondividing mature differentiated cells the ability to re-enter the cell cycle and accumulate disparate genomic mutations during years of chronic inflammation and injury. As our basic science understanding of gastric cancer advances, so too must our translational and clinical efforts. We will end with a discussion regarding single-cell molecular analyses and cancer organoid technologies as future translational avenues to advance our understanding of gastric cancer heterogeneity and to design precision-based gastric cancer treatments. Elucidation of interpatient and intratumor heterogeneity is the only way to advance future cancer prevention, diagnoses and treatment.

Gastric cancer (GC) is one of the most common lethal malignant neoplasms worldwide, with limited treatment options for both locally advanced and/or metastatic conditions, resulting in a dismal prognosis. Although the widely used morphological classifications may be helpful for endoscopic or surgical treatment choices, they are still insufficient to guide precise and/or personalized therapy for individual patients. Recent advances in genomic technology and high-throughput analysis may improve the understanding of molecular pathways associated with GC pathogenesis and aid in the classification of GC at the molecular level. Advances in next-generation sequencing have enabled the identification of several genetic alterations through single experiments. Thus, understanding the driver alterations involved in gastric carcinogenesis has become increasingly important because it can aid in the discovery of potential biomarkers and therapeutic targets. In this article, we review the molecular classifications of GC, focusing on The Cancer Genome Atlas (TCGA) classification. We further describe the currently available biomarker-targeted therapies and potential biomarker-guided therapies. This review will help clinicians by providing an inclusive understanding of the molecular pathology of GC and may assist in selecting the best treatment approaches for patients with GC.

The tumor suppressor gene AT-rich interactive domain 1A (ARID1A) and systemic inflammatory response (SIR) have been reported to be related to the sensitivity to immunotherapy. This study intended to explore the relationship between ARID1A expression and SIR, and to further elucidate the prognostic value of ARID1A expression in gastric cancer (GC).

The mRNA and protein expression of ARID1A were detected in 272 formalin-fixed paraffin-embedded (FFPE) tumor tissues. The data of nine systemic inflammation markers were collected 1 week before gastrectomy. Univariate and multivariate COX analysis were used to screen out independent predictors of GC.

Negative expression of ARID1A protein was related to GC with deficient mismatch repair (dMMR) (p = 0.033), positive programmed cell death-ligand 1 (PD-L1) (p = 0.005) and lower albumin level (p = 0.0064). Low expression of ARID1A mRNA was common in GC with abnormal E-cadherin (p = 0.020) and a higher platelet/lymphocyte ratio (PLR) (p = 0.0391). Multivariate COX analysis showed that the expression of ARID1A protein (p = 0.023), age (p = 0.004), T stage (p = 0.009) and N stage (p = 0.009) were independent predictors of GC. The nomogram established by independent predictors can accurately evaluate the survival risk of patients with GC.

The loss of ARID1A protein expression was associated with the dMMR subtype and high expression of PD-L1 in GC. Negative ARID1A protein and low expression of mRNA were associated with aberrant systemic inflammatory markers. The expression of ARID1A protein had important prognostic significance in GC.

Patients with Epstein-Barr virus-positive gastric cancers or those with microsatellite instability appear to have a favourable prognosis. However, the prognostic value of the chromosomal status (chromosome-stable (CS) versus chromosomal instable (CIN)) remains unclear in gastric cancer.

Gene copy number aberrations (CNAs) were determined in 16 CIN-associated genes in a retrospective study including test and validation cohorts of patients with gastric cancer. Patients were stratified into CS (no CNA), CINlow (1-2 CNAs) or CINhigh (3 or more CNAs). The relationship between chromosomal status, clinicopathological variables, and overall survival (OS) was analysed. The relationship between chromosomal status, p53 expression, and tumour infiltrating immune cells was also assessed and validated externally.

The test and validation cohorts included 206 and 748 patients, respectively. CINlow and CINhigh were seen in 35.0 and 15.0 per cent of patients, respectively, in the test cohort, and 48.5 and 20.7 per cent in the validation cohort. Patients with CINhigh gastric cancer had the poorest OS in the test and validation cohorts. In multivariable analysis, CINlow, CINhigh and pTNM stage III-IV (P < 0.001) were independently associated with poor OS. CIN was associated with high p53 expression and low immune cell infiltration.

CIN may be a potential new prognostic biomarker independent of pTNM stage in gastric cancer. Patients with gastric cancer demonstrating CIN appear to be immunosuppressed, which might represent one of the underlying mechanisms explaining the poor survival and may help guide future therapeutic decisions.