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Gastric cancer (GC) is a malignant tumor with one of the lowest five-year survival rates. Traditional first-line treatment regimens, such as platinum drugs, have limited therapeutic efficacy in treating advanced GC and significant side effects, greatly reducing patient quality of life. In contrast, trastuzumab and other immune checkpoint inhibitors, such as nivolumab and pembrolizumab, have demonstrated consistent and reliable efficacy in treating GC. Here, we discuss the intrinsic characteristics of GC from a molecular perspective and provide a comprehensive review of classification and treatment advances in the disease. Finally, we suggest several strategies based on the intrinsic molecular characteristics of GC to aid in overcoming clinical challenges in the development of precision medicine and improve patient prognosis., (© 2024. The Author(s).)

Background: 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., Background: Our Brazilian cohort with gastric cancer has a distinct distribution between mutated and normal p53., Background: New genetic marker-based classifications improve gastric cancer diagnosis accuracy., Background: Machine learning integration enhances predictive value in gastric cancer diagnosis., Background: Molecular biomarkers complement clinical decisions, advancing personalized medicine., Objective: 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., Methods: 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., Results: 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., Conclusion: 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.

Recent developments have highlighted the critical role that computer-aided diagnosis (CAD) systems play in analyzing whole-slide digital histopathology images for detecting gastric cancer (GC). We present a novel framework for gastric histology classification and segmentation (GHCS) that offers modest yet meaningful improvements over existing CAD models for GC classification and segmentation. Our methodology achieves marginal improvements over conventional deep learning (DL) and machine learning (ML) models by adaptively focusing on pertinent characteristics of images. This contributes significantly to our study, highlighting that the proposed model, which performs well on normalized images, is robust in certain respects, particularly in handling variability and generalizing to different datasets. We anticipate that this robustness will lead to better results across various datasets. An expectation-maximizing Naïve Bayes classifier that uses an updated Gaussian Mixture Model is at the heart of the suggested GHCS framework. The effectiveness of our classifier is demonstrated by experimental validation on two publicly available datasets, which produced exceptional classification accuracies of 98.87% and 97.28% on validation sets and 98.47% and 97.31% on test sets. Our framework shows a slight but consistent improvement over previously existing techniques in gastric histopathology image classification tasks, as demonstrated by comparative analysis. This may be attributed to its ability to capture critical features of gastric histopathology images better. Furthermore, using an improved Fuzzy c-means method, our study produces good results in GC histopathology picture segmentation, outperforming state-of-the-art segmentation models with a Dice coefficient of 65.21% and a Jaccard index of 60.24%. The model's interpretability is complemented by Grad-CAM visualizations, which help understand the decision-making process and increase the model's trustworthiness for end-users, especially clinicians., (© 2024. The Author(s).)

The classification and management of neuroendocrine neoplasms (NENs) arising in the tubular gastrointestinal (GI) tract and pancreas have significantly evolved over the last decades. In the latest WHO classification published in 2022, NENs are separated regardless of their primary origin into two main groups: well-differentiated neuroendocrine tumors (NETs) and poorly differentiated neuroendocrine carcinomas (NECs). The substantial changes in the grading system changed the definition of grade 3 to include high-grade well-differentiated NETs (G3-NETs), and poorly differentiated NECs (-NECs). Although these two subgroups are considered high grades with Ki-67 >20%, they have different genomic profiles, prognosis, and clinical behavior, which critically influence their treatment strategies. The available clinical trial data to guide therapy of these high-grade subgroups are extremely limited, which impacts their management. In this review, we will summarize the current advances in the multidisciplinary approach for the management of high-grade gastroenteropancreatic NENs (GEP-NENs) including G3-NETs and NECs.

Gastric cancer (GC) is a complex and heterogeneous disease with significant phenotypic and genetic variation. Traditional classification systems rely mainly on the evaluation of clinical pathological features and conventional biomarkers and might not capture the diverse clinical processes of individual GCs. The latest discoveries in omics technologies such as next‑generation sequencing, proteomics and metabolomics have provided crucial insights into potential genetic alterations and biological events in GC. Clustering strategies for identifying subtypes of GC might offer new tools for improving GC treatment and clinical trial outcomes by enabling the development of therapies tailored to specific subtypes. However, the feasibility and therapeutic significance of implementing molecular classifications of GC in clinical practice need to addressed. The present review examines the current molecular classifications, delineates the prevailing landscape of clinically relevant molecular features, analyzes their correlations with traditional GC classifications, and discusses potential clinical applications.

Gastric polyps (GPs) are increasingly common. On upper endoscopy, they should be examined with white light and occasionally chromoendoscopy, and their morphology classified according to the Paris classification. Most GPs have a typical endoscopic appearance and can be associated with diseases like Helicobacter pylori infection. Histological examination is necessary for an accurate diagnosis. While most polyps are non-neoplastic and do not require treatment, some carry a risk of malignancy or are already malignant. Therefore, understanding the diagnosis, classification, and management of GPs is crucial for patient prognostication. Our new classification categorizes GPs into "good", "bad", and "ugly" based on their likelihood of becoming malignant. We aim to provide descriptions of the endoscopic appearance, pathology, treatment, and follow-up for different GPs, as well as clinical management flowcharts., Competing Interests: Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article., (©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.)

Background and Aims: 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., Methods and Results: 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)., Conclusions: 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., (© 2024 The Authors. Histopathology published by John Wiley & Sons Ltd.)

Most cancer types have both diffuse and non-diffuse subtypes, which have rather distinct morphologies, namely scattered tiny tumors vs. one solid tumor, and different levels of aggressiveness. However, the causes for forming such distinct subtypes remain largely unknown. Using the diffuse and non-diffuse gastric cancers (GCs) as the illustrative example, we present a computational study based on the transcriptomic data from the TCGA and GEO databases, to address the following questions: (i) What are the key molecular determinants that give rise to the distinct morphologies between diffuse and non-diffuse cancers? (ii) What are the main reasons for diffuse cancers to be generally more aggressive than non-diffuse ones of the same cancer type? (iii) What are the reasons for their distinct immunoactivities? And (iv) why do diffuse cancers on average tend to take place in younger patients? The study is conducted using the framework we have previously developed for elucidation of general drivers cancer formation and development. Our main discoveries are: (a) the level of (poly-) sialic acids deployed on the surface of cancer cells is a significant factor contributing to questions (i) and (ii); (b) poly-sialic acids synthesized by ST8SIA4 are the key to question (iii); and (c) the circulating growth factors specifically needed by the diffuse subtype dictate the answer to question (iv). All these predictions are substantiated by published experimental studies. Our further analyses on breast, prostate, lung, liver, and thyroid cancers reveal that these discoveries generally apply to the diffuse subtypes of these cancer types, hence indicating the generality of our discoveries., Competing Interests: Declaration of competing interest The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Gastric cancer has a high incidence rate, significantly threatening patients' health. Gastric histopathology images can reliably diagnose related diseases. Still, the data volume of histopathology images is too large, making misdiagnosis or missed diagnosis easy. The classification model based on deep learning has made some progress on gastric histopathology images. However, traditional convolutional neural networks (CNNs) generally use pooling operations, which will reduce the spatial resolution of the image, resulting in poor prediction results. The image feature in previous CNN has a poor perception of details. Therefore, we design a dilated CNN with a late fusion strategy (DCNNLFS) for gastric histopathology image classification. The DCNNLFS model utilizes dilated convolutions, enabling it to expand the receptive field. The dilated convolutions can learn the different contextual information by adjusting the dilation rate. The DCNNLFS model uses a late fusion strategy to enhance the classification ability of DCNNLFS. We run related experiments on a gastric histopathology image dataset to verify the excellence of the DCNNLFS model, where the three metrics Precision, Accuracy, and F1-Score are 0.938, 0.935, and 0.959.

Background: The current pathologic N (pN) classification exhibits limitations in the prognostic stratification of patients with pT3-4N0-2M0 gastric cancer (GC). Therefore, this study aimed to develop and validate a new lymph nodal staging method based on the number of examined lymph nodes (ELNs) and lymph node ratio (LNR)., Methods: Data from 7883 patients with pT3-4N0-2M0 GC were collected from the Surveillance, Epidemiology, and End Results (SEER) database and Zhejiang Cancer Provincial Hospital. Optimal cutoff values for ELNs and LNR were determined using X-tile software. Kaplan-Meier methods, Log-rank tests, and Cox regression analyses were employed in this study. Patients were categorized into 3 new pN stages: new pN0 (pN0 with ELNs of >16), new pN1 (pN0 with ELNs of ≤16 or pN1-2 with LNR of ≤0.15), and new pN2 (pN1-2 with LNR of >0.15). The prognostic predictive power of both current and new pN staging was evaluated using the Akaike information criterion (AIC), Bayesian information criterion, concordance index (C-index), and receiver operating characteristic curve., Results: The new pN classification exhibited excellent performance in Kaplan-Meier survival analysis. After adjusting for confounding factors, the new pN staging emerged as an independent prognostic indicator in patients with GC. In the SEER cohort, the new pN staging demonstrated enhanced prognostic prediction accuracy over the American Joint Committee on Cancer pN staging (AIC: 75578.85 vs 75755.06; C-index: 0.642 vs 0.630; P < .001). Similar findings were validated in the Chinese cohort., Conclusion: This study developed and validated an improved pN classification for patients with pT3-4N0-2M0 GC. Surgeons should consider ELNs and LNR when assessing postoperative prognosis in patients with GC., Competing Interests: Declaration of competing interest The authors declare no competing interests., (Copyright © 2024. Published by Elsevier Inc.)

Purpose: The optimal treatment for gastroesophageal junction adenocarcinoma (GEJA) remains controversial. We evaluated the treatment patterns and outcomes of patients with locally advanced GEJA according to the histological type., Materials and Methods: We conducted a single-institution retrospective cohort study of patients with locally advanced GEJA who underwent curative-intent surgical resection between 2010 and 2020. Perioperative therapies as well as clinicopathologic, surgical, and survival data were collected. The results of endoscopy and histopathological examinations were assessed for Siewert and Lauren classifications., Results: Among the 58 patients included in this study, 44 (76%) were clinical stage III, and all received neoadjuvant therapy (72% chemoradiation, 41% chemotherapy, 14% both chemoradiation and chemotherapy). Tumor locations were evenly distributed by Siewert Classification (33% Siewert-I, 40% Siewert-II, and 28% Siewert-III). Esophagogastrectomy (EG) was performed for 47 (81%) patients and total gastrectomy (TG) for 11 (19%) patients. All TG patients received D2 lymphadenectomy compared to 10 (21%) EG patients. Histopathological examination showed the presence of 64% intestinal-type and 36% diffuse-type histology. The frequencies of diffuse-type histology were similar among Siewert groups (37% Siewert-I, 36% Siewert-II, and 33% Siewert-III). Regardless of Siewert type and compared to intestinal-type, diffuse histology was associated with increased intraabdominal recurrence rates (P=0.03) and decreased overall survival (hazard ratio, 2.33; P=0.02). With a median follow-up of 31.2 months, 29 (50%) patients had a recurrence, and the median overall survival was 50.5 months., Conclusions: Present in equal proportions among Siewert types of esophageal and gastric cancer, a diffuse-type histology was associated with high intraabdominal recurrence rates and poor survival. Histopathological evaluation should be considered in addition to anatomic location in the determination of multimodal GEJA treatment strategies., Competing Interests: Dr. Woo is a scientific consultant for Johnson & Johnson Ethicon and serves on the advisory board of Imugene. Dr. Fong is a scientific consultant for Medtronics, Covidien, Xdemics, Vergent Biosciences, Eureka Biologics, and Imugene; receives royalties from Merck and Imugene; has a research study agreement with Imugene; a member of Dr. Fong's family is President and CEO of XDemics. There are no disclosures for the remaining authors., (Copyright © 2024. Korean Gastric Cancer Association.)

Gastric cancers frequently harbor striking histological complexity and diversity between lesions as well as within single lesions, known as inter- and intratumoral heterogeneity, respectively. The latest World Health Organization Classification of Tumors designated more than 30 histological subtypes for gastric epithelial tumors, assigning 12 subtypes for gastric adenocarcinoma (GAD). Meanwhile, recent advances in genome-wide analyses have provided molecular aspects to the histological classification of GAD, and consequently revealed different molecular traits underlying these histological subtypes. Moreover, accumulating knowledge of comprehensive molecular profiles has led to establishing molecular classifications of GAD, which are often associated with clinical biomarkers for therapeutics and prognosis. However, most of our knowledge of GAD molecular profiles is based on inter-tumoral heterogeneity, and the molecular profiles underlying intratumoral heterogeneity are yet to be determined. In this review, recently established molecular classifications of GAD are introduced in the aspect of pathological diagnosis and are discussed in the context of intratumoral heterogeneity., (© 2024 The Authors. Pathology International published by Japanese Society of Pathology and John Wiley & Sons Australia, Ltd.)

Different molecular classifications for gastric cancer (GC) have been proposed based on multi-omics platforms with the long-term goal of improved precision treatment. However, the GC (phospho)proteome remains incompletely characterized, particularly at the level of tyrosine phosphorylation. In addition, previous multiomics-based stratification of patient cohorts has lacked identification of corresponding cell line models and comprehensive validation of broad or subgroup-selective therapeutic targets. To address these knowledge gaps, we applied a reverse approach, undertaking the most comprehensive (phospho)proteomic analysis of GC cell lines to date and cross-validating this using publicly available data. Mass spectrometry (MS)-based (phospho)proteomic and tyrosine phosphorylation datasets were subjected to individual or integrated clustering to identify subgroups that were subsequently characterized in terms of enriched molecular processes and pathways. Significant congruence was detected between cell line proteomic and specific patient-derived transcriptomic subclassifications. Many protein kinases exhibiting 'outlier' expression or phosphorylation in the cell line dataset exhibited genomic aberrations in patient samples and association with poor prognosis, with casein kinase I isoform delta/epsilon (CSNK1D/E) being experimentally validated as potential therapeutic targets. Src family kinases were predicted to be commonly hyperactivated in GC cell lines, consistent with broad sensitivity to the next-generation Src inhibitor eCF506. In addition, phosphoproteomic and integrative clustering segregated the cell lines into two subtypes, with epithelial-mesenchyme transition (EMT) and proliferation-associated processes enriched in one, designated the EMT subtype, and metabolic pathways, cell-cell junctions, and the immune response dominating the features of the other, designated the metabolism subtype. Application of kinase activity prediction algorithms and interrogation of gene dependency and drug sensitivity databases predicted that the mechanistic target of rapamycin kinase (mTOR) and dual specificity mitogen-activated protein kinase kinase 2 (MAP2K2) represented potential therapeutic targets for the EMT and metabolism subtypes, respectively, and this was confirmed using selective inhibitors. Overall, our study provides novel, in-depth insights into GC proteomics, kinomics, and molecular taxonomy and reveals potential therapeutic targets that could provide the basis for precision treatments., (© 2024 The Authors. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

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.

There are differences in the diagnoses of superficial gastric lesions between Japan and other countries. In Japan, superficial gastric lesions are classified as adenoma or cancer. Conversely, outside Japan, the same lesion is classified as low-grade dysplasia (LGD), high-grade dysplasia, or invasive neoplasia. Gastric carcinogenesis occurs mostly de novo , and the adenoma-carcinoma sequence does not appear to be the main pathway of carcinogenesis. Superficial gastric tumors can be roughly divided into the APC mutation type and the TP53 mutation type, which are mutually exclusive. APC -type tumors have low malignancy and develop into LGD, whereas TP53 -type tumors have high malignancy and are considered cancerous even if small. For lesions diagnosed as category 3 or 4 in the Vienna classification, it is desirable to perform complete en bloc resection by endoscopic submucosal dissection followed by staging. If there is lymphovascular or submucosal invasion after mucosal resection, additional surgical treatment of gastrectomy with lymph node dissection is required. In such cases, function-preserving curative gastrectomy guided by sentinel lymph node biopsy may be a good alternative., Competing Interests: Conflict-of-interest statement: The authors declare no conflict of interest related to the publication of this study., (©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.)

Background: Although messenger RNA (mRNA) vaccines have unique advantages against multiple tumors, mRNA vaccine targets in stomach adenocarcinoma (STAD) remain unknown. The potential effectiveness of mRNA vaccines is closely associated with the tumor immune infiltration microenvironment. The present study aimed to identify tumor antigens of STAD as mRNA vaccine targets and systematically determine immune subtypes (ISs) of STAD that might be suitable for immunotherapy., Methods: Gene expression profiles and clinical data of patients with gastric cancer were downloaded from The Cancer Genome Atlas (TCGA; n = 409) and the Gene Expression Omnibus (GEO; n = 433), and genomic data were extracted from cBioPortal. Differential gene expression was analyzed using the limma package, genetic alterations were visualized using maftools, and prognosis was analyzed using ToPP. Correlations between gene expression and immune infiltration were calculated using TIMER software, and potential ISs were identified using ConsensusClusterPlus. Functional enrichment was analyzed in clusterProfiler, and r co-expression networks were analyzed using the weighted gene co-expression network analysis (WGCNA) package in R., Results: Overexpression of the prognostic and highly mutated antigens ADAMTS18, COL10A1, PPEF1, and STRA6 was associated with infiltration by antigen-presenting cells in STAD. Five ISs (IS1-IS5) in STAD with distinct prognoses were developed and validated in TCGA and GEO databases. The tumor mutational burden and molecular and clinical characteristics significantly differed among IS1-IS5. Both IS1 and IS2 were associated with a high mutational burden, massive infiltration by immune cells, especially antigen-presenting cells, and better survival compared with the other subtypes. Both IS4 and IS5 were associated with cold immune infiltration and correlated with advanced pathological stages. We analyzed the immune microenvironments of five subtypes of immune modulators and biomarkers to select suitable populations for mRNA vaccination and established four co-expressed key modules to validate the characteristics of the ISs. Finally, the correlation of these four mRNA vaccine targets with the transcription factors of DC cells, including BATF3, IRF4, IRF8, ZEB2, ID2, KLF4, E2-2, and IKZF1, were explored to reveal the underlying mechanisms., Conclusions: ADAMTS18, COL10A1, PPEF1, and STRA6 are potential mRNA vaccine candidates for STAD. Patients with IS1 and IS2 are suitable populations for mRNA vaccination immunotherapy., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 You, Ouyang, Cai, Chen and Wu.)

Purpose: Current systems of gastric cancer molecular classification include genomic, molecular, and morphological features. Gastric cancer classification based on tissue metabolomics remains lacking. This study aimed to define metabolically distinct gastric cancer subtypes and identify their clinicopathological and molecular characteristics., Experimental Design: Spatial metabolomics by high mass resolution imaging mass spectrometry was performed in 362 patients with gastric cancer. K-means clustering was used to define tumor and stroma-related subtypes based on tissue metabolites. The identified subtypes were linked with clinicopathological characteristics, molecular features, and metabolic signatures. Responses to trastuzumab treatment were investigated across the subtypes by introducing an independent patient cohort with HER2-positive gastric cancer from a multicenter observational study., Results: Three tumor- and three stroma-specific subtypes with distinct tissue metabolite patterns were identified. Tumor-specific subtype T1(HER2+MIB+CD3+) positively correlated with HER2, MIB1, DEFA-1, CD3, CD8, FOXP3, but negatively correlated with MMR. Tumor-specific subtype T2(HER2-MIB-CD3-) negatively correlated with HER2, MIB1, CD3, FOXP3, but positively correlated with MMR. Tumor-specific subtype T3(pEGFR+) positively correlated with pEGFR. Patients with tumor subtype T1(HER2+MIB+CD3+) had elevated nucleotide levels, enhanced DNA metabolism, and a better prognosis than T2(HER2-MIB-CD3-) and T3(pEGFR+). An independent validation cohort confirmed that the T1 subtype benefited from trastuzumab therapy. Stroma-specific subtypes had no association with clinicopathological characteristics, however, linked to distinct metabolic pathways and molecular features., Conclusions: Patient subtypes derived by tissue-based spatial metabolomics are a valuable addition to existing gastric cancer molecular classification systems. Metabolic differences between the subtypes and their associations with molecular features could provide a valuable tool to aid in selecting specific treatment approaches., (©2022 American Association for Cancer Research.)

Background: We aimed to classify metastatic pyloric/antral gastric cancer in terms of macroscopic morphology and metastatic form., Methods: Thirty-eight patients with pyloric/antral gastric cancer were included in the study. Patients were classified according to a combination of Borrmann classification type and metastatic type, and the clinicopathological characteristics of each group were compared., Result: Of the 38 patients, 33 (type II: 9 and type III: 24) (87%) had ulcerative gastric cancer. Ulcerative gastric cancer was classified into four groups: lymphatic only group (L+H-P-), lymphatic + hematogenous group (L+H+P-), disseminated ± lymphatic group (L±H-P+), and lymphatic + hematogenous + disseminated group (L+H+P+). In the L+H-P- group, all patients had bulky lymph nodes and serum levels of both carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) were high; the condition of patients was good, and the therapeutic response was good. In the L+H+P- group, metastases other than liver metastases were rare, and serum CEA levels were high. In the L±H-P+ group, the predominant histological type was signet ring cell carcinoma; both serum CEA and CA19-9 levels were low. Patients in the L+H+P+ group had higher serum CA19-9 levels and were more prone to hematogenous metastasis to various organs; these patients had worse patient status and lower treatment response. Gastric cancer other than ulcerative type was only detected in five patients (type V: 3, type IV: 1, type I: 1)., Conclusion: Classification by a combination of macroscopic and metastatic form in pyloric/antral metastatic gastric cancer might be useful for diagnosis and treatment.

Aims: Fundic gland polyps (FGPs) comprise 66% of all gastric polyps. Although they are usually non-syndromic, they may be associated with various syndromes, including familial adenomatous polyposis (FAP) or gastric adenocarcinoma and proximal polyposis of the stomach (GAPPS). We aimed to evaluate how histological features relate to distinct FGP subtypes., Methods and Results: We performed a retrospective analysis of 118 FGPs from 109 patients for the architecture of fundic glands, microcyst lining, parietal cell hyperplasia and surface foveolar epithelial changes. Age, gender and history of FAP or GAPPS were collected. Based on combinations of histological features, three distinct patterns (A, B and C) of FGPs were delineated and correlated to the aetiologies. Non-syndromic FGPs were well-formed polyps composed of disordered fundic glands with intermediate-sized microcysts typically lined by a mixture of oxyntic and mucin-secreting cells (73%). Parietal cell hyperplasia (80%) and foveolar surface hyperplasia (78%) were common. FAP-associated cases demonstrated small microcysts that were predominantly lined by fundic epithelium (77%), with limited parietal cell hyperplasia (27%); foveolar hyperplasia was uncommon. GAPPS-related polyps were the largest, with prominent, mucin-secreting epithelium-lined microcysts (73%). Hyperproliferative aberrant pits were universally present, whereas parietal cell hyperplasia was uncommon. Pattern A was identified in most non-syndromic FGPs (74%) and in a minority of FAP-related FGPs (26%). The majority (82%) of FAP-related FGPs showed pattern B, but only 18% of non-syndromic FGPs did. Pattern C consisted exclusively of GAPPS-associated polyps., Conclusions: We conclude that, although FGPs share similar histomorphology, subtle differences exist between polyps of different aetiology. In the appropriate clinical setting, the recognition of these variations may help to consider syndromic aetiologies., (© 2022 John Wiley & Sons Ltd.)

Purpose: Risk factors for sporadic GEP-NENs are still not well defined. To identify the main clinical risk factors represents the aim of this study performed by three Italian referral centers for NENs., Methods: We performed a retrospective case-control study including 148 consecutive sporadic GEP-NENs and 210 age- and sex-matched controls. We collected data on clinical features, cancer family history and other potential risk factors., Results: Mean age was 58.3 ± 15.8 years; 50% males, primary site was pancreas (50.7%), followed by ileum (22.3%). The 62.8% and 29.1% of cases were G1 and G2, respectively; the 40% had locally advanced or metastatic disease at diagnosis. Independent risk factors for GEP-NENs were: family history of non-neuroendocrine GEP cancer (OR 2.16, 95% CI 1.31-3.55, p = 0.003), type 2 diabetes mellitus (T2DM) (OR 2.5, 95% CI 1.39-4.51, p = 0.002) and obesity (OR 1.88, 95% CI 1.18-2.99, p = 0.007). In the T2DM subjects, metformin use was a protective factor (OR 0.28, 95% CI 0.08-0.93, p = 0.049). T2DM was also associated with a more advanced (OR 2.39, 95% CI 1.05-5.46, p = 0.035) and progressive disease (OR 2.47, 95% CI 1.08-5.34, p = 0.03). Stratifying cases by primary site, independent risk factors for pancreatic NENs were T2DM (OR 2.57, 95% CI 1.28-5.15, p = 0.008) and obesity (OR 1.98, 95% CI 1.11-3.52, p = 0.020), while for intestinal NENs family history of non-neuroendocrine GEP cancer (OR 2.46, 95% CI 1.38-4.38, p = 0.003) and obesity (OR 1.90, 95% CI 1.08-3.33, p = 0.026)., Conclusion: This study reinforces a role for family history of non-neuroendocrine GEP cancer, T2DM and obesity as independent risk factors for GEP-NENs and suggests a role of metformin as a protective factor in T2DM subjects. If confirmed, these findings could have a significant impact on prevention strategies for GEP-NENs., (© 2021. Italian Society of Endocrinology (SIE).)

Alternatively spliced RNA isoforms are a hallmark of tumors, but their nature, prevalence, and clinical implications in gastric cancer have not been comprehensively characterized. We systematically profiled the splicing landscape of 83 gastric tumors and matched normal mucosa, identifying and experimentally validating eight splicing events that can classify all gastric cancers into three subtypes: epithelial-splicing (EpiS), mesenchymal-splicing (MesS), and hybrid-splicing. These subtypes were associated with distinct molecular signatures and epithelial-mesenchymal transition markers. Subtype-specific splicing events were enriched in motifs for splicing factors RBM24 and ESRP1, which were upregulated in MesS and EpiS tumors, respectively. A simple classifier based only on RNA levels of RBM24 and ESRP1, which can be readily implemented in the clinic, was sufficient to distinguish gastric cancer subtypes and predict patient survival in multiple independent patient cohorts. Overall, this study provides insights into alternative splicing in gastric cancer and the potential clinical utility of splicing-based patient classification., Significance: This study presents a comprehensive analysis of alternative splicing in the context of patient classification, molecular mechanisms, and prognosis in gastric cancer., (©2021 The Authors; Published by the American Association for Cancer Research.)

Aims: This study investigated the relationship between the differentiation of tumour cells into crypts, which is determined by cell differentiation into Paneth and neuroendocrine cells, and tumour infiltration in gastric dysplasia., Methods and Results: The lesions were endoscopically biopsied low-grade dysplasia (LGD), endoscopically resected high-grade dysplasia (HGD) or cancer with submucosal invasion. LGD (n = 32) displayed crypt differentiation across the entire width of the tumour in all cases. Crypt differentiation was identified as a characteristic of tumours with low biological malignancy. HGD (n = 40) included tumours with a mixture of areas with and without crypt differentiation (n = 25) and tumours with crypt differentiation throughout the entire width (n = 15). Of the cancers with submucosal invasion (n = 30), the morphological progression of the HGD area with crypt differentiation, the HGD area without crypt differentiation and invasive cancer without crypt differentiation was confirmed for 23 samples. In two lesions, invasive cancer without crypt differentiation developed from HGD without crypt differentiation throughout the tumour width. In five samples, well-differentiated tubular adenocarcinoma with crypt differentiation developed from HGD with crypt differentiation and invaded with lamina propria-like stroma., Conclusions: Loss of crypt differentiation could be an objective indicator of infiltration in the progression of HGD to invasive cancer. The invasive potential of dysplasia depends upon the presence or absence of crypt differentiation., (© 2021 John Wiley & Sons Ltd.)

Objective: To investigate the correlations between dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) perfusion histogram parameters and vascular endothelial growth factor (VEGF) and epidermal growth factor receptor (EGFR) expressions in advanced gastric cancer (AGC). Methods: This retrospective study included 80 pathologically confirmed patients with AGC who underwent DCE-MRI before surgery from February 2017 to May 2021. The DCE-MRI perfusion histogram parameters were calculated by Omni Kinetics software in four quantitative parameter maps. Immunohistochemical methods were used to detect VEGF and EGFR expressions and calculate the immunohistochemical score. Results: VEGF expression was relatively lower in patients with intestinal-type AGC than those with diffuse-type AGC ( p < 0.05). For VEGF, Receiver operating characteristics (ROC) curve analysis revealed that Quantile 90 of Ktrans, Meanvalue of Kep and Quantile 50 of Ve provided the perfect combination of sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for distinguishing high and low VEGF expression, For EGFR, Skewness of Ktrans, Energy of Kep and Entropy of Vp provided the perfect combination of sensitivity, specificity, PPV and NPV for distinguishing high and low EGFR expression. Ktrans (Quantile 90, Entropy) showed the strongest correlation with VEGF and EGFR in patients with intestinal-type AGC (r = 0.854 and r = 0.627, respectively); Ktrans (Mean value, Entropy) had the strongest correlation with VEGF and EGFR in patients with diffuse-type AGC (r = 0.635 and 0.656, respectively). Conclusion: DCE-MRI perfusion histogram parameters can serve as imaging biomarkers to reflect VEGF and EGFR expressions and estimate their difference in different Lauren classifications of AGC., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Li, Zhao, Wang, Wang, Mao, Liu, Yang, Tao and Lu.)

Background: Gastric carcinoma is a major cause of cancer-related morbidity and mortality worldwide. Gastric neoplasms arise from genetic and epigenetic changes in various genes. Present study evaluates the immunoexpression of PTEN, HER2/neu, and Ki-67 in endoscopic gastric carcinoma biopsies and correlates the expression of these proteins with clinicopathological features., Material and Methods: Adequate endoscopic biopsies of 27 cases of gastric carcinoma were evaluated for World Health Organization (WHO) and Lauren's classification subtypes along with HER2/neu, PTEN, and Ki-67 immunoexpression. HER2/neu immunostaining was scored as proposed in the Trastuzumab for gastric cancer (ToGA) trial while PTEN staining and downregulation were assessed using an immunoreactive score. The cut-off for Ki-67 expression was taken as 90 th percentile of the values in adjacent non-neoplastic tissue. All statistical analysis was done at 5% level of significance with SPSS v22 statistical software., Results: Tubular adenocarcinoma was the commonest WHO histological subtype and 56% of cases were of intestinal type as per Lauren's classification. 55.6% of cases showed a complete loss of PTEN expression in neoplastic tissue. 17 of the 19 cases with adjacent non-neoplastic tissue showed PTEN downregulation in neoplastic tissue. 81.5% of cases had a high Ki-67 index and HER2/neu overexpression was noted in 36% of cases. All the four cases who died had high Ki-67 proliferation indices; 3 patients had loss of PTEN expression and HER2/neu overexpression., Conclusion: We conclude that these immunomarkers can play important role in the behavior of gastric carcinomas and can be targeted for new therapies., Competing Interests: None

Aim: : To assess HER2/neu expressions and correlate with E-cadherin and Serum HER2 level in gastric carcinoma., Method: 31 gastric biopsies and 1 resected specimen were taken in the study with patient details and stained with H and E for histopathological details following Lauren's classification. Immunohistochemistry for HER2 and E-cadherin expression was conducted followed by serum HER2/neu ELISA., Result: Adenocarcinoma with 61% diffuse, 29% intestinal, and 10% other type were observed with predominant HER2 immunoexpression in intestinal-type than in diffuse-type adenocarcinoma. Other observations marked 44% as 3+/positive and 56% as 2+/equivocal in intestinal type while 26% cases as 3+/positive, 69% as 2+/equivocal, and 1% as 1+/negative were observed in diffuse type. The data presented 33% membranous positivity and 67% both membranous + cytoplasmic positivity in intestinal type while 2% showed membranous positivity, 47% both membranous + cytoplasmic, and 42% only cytoplasmic positivity in diffused type. On comparing the localization pattern of HER2 and E-cadherin, 25% of cases showed membranous staining while 50% of cases showed membranous with cytoplasmic staining for both. No cytoplasmic HER2 staining as well as no any staining for E-cadherin was shown by 6% cases., Conclusion: Thus, it can be concluded that cytoplasmic expression of HER2 in gastric adenocarcinoma (mainly diffuse type) may be due to shedding of its extracellular domain, leading to loss of membranous E-cadherin expression on immunohistochemistry. The loss of membranous expression of E-cadherin and increased serum HER2 ELISA were correlated well with these findings., Competing Interests: None

Malignant tumours are traditionally classified according to their organ of origin and whether they are of epithelial (carcinomas) or mesenchymal (sarcomas) origin. By histological appearance the site of origin may often be confirmed. Using same treatment for tumours from the same organ is rational only when there is no principal heterogeneity between the tumours of that organ. Organ tumour heterogeneity is typical for the lungs with small cell and non-small cell tumours, for the kidneys where clear cell renal carcinoma (CCRCC) is the dominating type among other subgroups, and in the stomach with adenocarcinomas of intestinal and diffuse types. In addition, a separate type of neuroendocrine tumours (NETs) is found in most organs. Every cell type able to divide may develop into a tumour, and the different subtypes most often reflect different cell origin. In this article the focus is on the cells of origin in tumours arising in the stomach and kidneys and the close relationship between normal neuroendocrine cells and NETs. Furthermore, that the erythropoietin producing cell may be the cell of origin of CCRCC (a cancer with many similarities to NETs), and that gastric carcinomas of diffuse type may originate from the ECL cell, whereas the endodermal stem cell most probably gives rise to cancers of intestinal type.

Warburg phenomenon refers to the development of unique metabolic patterns during the growth of tumor cells. This study stratified gastric cancer into prognostic metabolic subgroups according to changes in gene expressions related to glycolysis and cholesterol synthesis. The RNA-seq expression data, single nucleotide variants (SNV), short insertions and deletions (InDel) mutation data, copy number variation (CNV) data and clinical follow-up information data of gastric cancer tissues were downloaded from The Cancer Genome Atlas (TCGA) database. ConsensusClusterPlus was used to stratify the metabolic subtypes of gastric cancer. Four metabolic subtypes (Cholesterogenic, Glycolytic, Mixed and Quiescent) of gastric cancer were identified, and patients with cholesterogenic tumors had the longest disease-specific survival (DSS). Genome-wide analysis showed that aberrant amplification of TP53 and MYC in gastric cancer was associated with abnormal cholesterol anabolic metabolism. The mRNA levels of mitochondrial pyruvate carriers 1 and 2 (MPC1/2) differed among the four subtypes. Tumors in the glycolytic group showed a higher PDCD1. A genomic signature based on tumor metabolism of different cancer types was established. This study showed that genes related to glucose and lipid metabolism play an important role in gastric cancer and facilitate a personalized treatment of gastric cancer.

Primary gastric lymphoma (PGL) is a rare clinical entity accounting for the majority of extra-nodal non-Hodgkin lymphoma (EN-NHL). The most common histological subtype is the primary gastric diffuse large B-cell lymphoma (PG-DLBCL) with a media age of 50-60 years old, mostly in male. Pathogenesis is often related to some bacterial infection such as Helicobacter pylori (H. pylori) infection. However, due to various available staging system, there is still no consensus on the staging of PG-DLBCL. The international prognostic index (IPI) is the most valuable used for the stratification of almost all subtype of NHL and as well as for PG-DLBCL. As for treatment strategies, surgery, chemotherapy, radiation therapy and antibiotic therapy in various combinations have been applied in clinical treatment. There are a few well-known prognostic factors and some of them may constitute prognostic models. Due to the increasing incidence of this neoplasm, it is necessary for clinicians to make deep insight of the diagnosis, staging, treatment and prognostic factors of PG-DLBCL., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Background: The correlation between tumor location and lymphatic flow distribution in gastric cancer has been previously reported, and PTD (Proximal - Transitional - Distal) classification was proposed. Our group updated and developed the nPTD classification., Method: We retrospectively studied gastric cancer patients who underwent the dye method sentinel node biopsy from 1993 to 2020. The inclusion criteria were a single lesion type 0 cancer of ≤5 cm in the long axis, clinically node-negative, and invasion within the proper muscle layer pathologically. In this study, the distribution of dyed lymphatic flow was evaluated for each occupied area of the tumor., Results: We included 416 patients in this study. The tumors located in the watershed of the right and left gastroepiploic arteries near greater curvature had extensive lymphatic flow; therefore, a newly circular region with a diameter of 5 cm is set on the watershed of the greater curvature between P and T zone as the 'n' zone. In addition, for cancers located in the lesser P curvature, lymphatic flow to the greater curvature was not observed. Therefore, the P zone was divided into two: the lesser curvature side (PL) and the greater curvature side (PG)., Conclusions: The advantage of the nPTD classification is that it provides not only proper nodal dissection but also adequate function-preserving gastrectomy. If the tumor is localized within the PL, the proximal gastrectomy resection area can be further reduced. In contrast, for cancers located in the 'n' zone, near-total gastrectomy is required because of the extensive lymphatic flow., (© 2021. The Author(s).)

Increasing evidence has demonstrated that lncRNAs are critical regulators in diverse biological processes, but the function of lncRNA in metabolic regulation remains largely unexplored. In this study, we evaluated the association between lncRNA and metabolic pathways and identified metabolism-related lncRNAs. Gastric cancer can be mainly subdivided into 2 clusters based on these metabolism-related lncRNA regulators. Comparative analysis shows that these subtypes are found to be highly consistent with previously identified subtypes based on other omics data. Functional enrichment analysis shows that they are enriched in distinct biological processes. Mutation analysis shows that ABCA13 is a protective factor in subtype C1 but a risk factor in C2. Analysis of chemotherapeutic and immunotherapeutic sensitivity shows that these subtypes tend to display distinct sensitivity to the same chemical drugs. In conclusion, these findings demonstrated the significance of lncRNA in metabolic regulation. These metabolism-related lncRNA regulators can improve our understanding of the underlying mechanism of lncRNAs and advance the research of immunotherapies in the clinical management of gastric cancer., (© 2021. The Author(s).)

Purpose: To assess the clinical indications for, and prognostic impact of surgery after, chemotherapy for type 4 gastric cancer., Methods: The subjects of this retrospective study were 67 patients who received chemotherapy for type 4 gastric cancer. The patients were grouped into those with progressive disease (PD group) and those without PD (non-PD group), according to the tumor response to chemotherapy., Results: Distant metastases developed in 58 patients. With regard to tumor response, there were 16 patients in the PD group and 51 patients in the non-PD group. The prognosis of the PD group patients was significantly poorer than that of the non-PD group patients (p < 0.0001). R0 resection was performed for 21 of 23 patients who underwent surgery after chemotherapy. Multivariate analysis revealed tumor response and surgery as independent prognostic factors (p = 0.0001 and p = 0.0009, respectively). Moreover, multivariate analysis of the surgery group revealed that metastatic nodal status (N0-1 vs. N2-3) and residual tumor status (R0 vs. R1-2) were significant independent prognostic factors (p = 0.0258 and p = 0.0458, respectively)., Conclusion: The findings of this study suggest that surgery after chemotherapy for type 4 gastric cancer may improve the prognosis of responders with N0-1 status, who undergo curative R0 resection., (© 2021. Springer Nature Singapore Pte Ltd.)

Gastric diffuse-type adenocarcinoma represents a disproportionately high percentage of cases of gastric cancers occurring in the young, and its relative incidence seems to be on the rise. Usually it affects the body of the stomach, and it presents shorter duration and worse prognosis compared with the differentiated (intestinal) type adenocarcinoma. The main difficulty encountered in the differential diagnosis of gastric adenocarcinomas occurs with the diffuse-type. As the cancer cells of diffuse-type adenocarcinoma are often single and inconspicuous in a background desmoplaia and inflammation, it can often be mistaken for a wide variety of non-neoplastic lesions including gastritis or reactive endothelial cells seen in granulation tissue. In this study we trained deep learning models to classify gastric diffuse-type adenocarcinoma from WSIs. We evaluated the models on five test sets obtained from distinct sources, achieving receiver operator curve (ROC) area under the curves (AUCs) in the range of 0.95-0.99. The highly promising results demonstrate the potential of AI-based computational pathology for aiding pathologists in their diagnostic workflow system., (© 2021. The Author(s).)

Abstract: In 2018, the eighth edition of the American Joint Committee on Cancer Tumor-Node-Metastasis classification and staging system was implemented. Few reports were made comparing the performance of different editions of the American Joint Committee on Cancer (AJCC) system. Therefore, this study aimed to examine the prognostic predictability from the sixth to the eighth editions of the AJCC staging system for gastric cancer.A total of 414 patients with gastric cancer who underwent surgery at Changhua Christian Hospital from January 2007 to December 2017 were enrolled in the study. To identify the prognostic factors for gastric cancer death, univariate and multivariate analyses were performed. The homogeneity and discrimination abilities of the sixth to eighth editions of the staging system were compared using the likelihood ratio chi-square test, linear trend chi-square test, and Akaike information criterion.The sixth edition of the staging system had the lowest Akaike information criterion value, suggesting a better prognostic stratification than other editions. From the result of the likelihood ratio chi-square test, the T and N staging systems of the seventh and eighth editions had better homogeneity and discriminatory ability than the sixth edition. The eighth edition had better prognostic performance in patients at stage III compared with the seventh edition.The AJCC seventh and eighth editions had improved prognostic predictability of the T and N factors compared with the sixth edition. However, the overall staging performance of the eighth edition is not superior compared to the sixth edition. Further studies with larger sample size should be conducted to compare the performance of different editions of the AJCC staging system for different ethnic populations., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc.)

Importance: Few studies have examined the clinicopathological characteristics and prognoses of patients with hepatoid adenocarcinoma of the stomach (HAS)., Objective: To explore the clinicopathological characteristics and prognoses of patients with HAS and develop a nomogram to predict overall survival (OS)., Design, Setting, and Participants: This prognostic study involved a retrospective analysis of data from 315 patients who received a diagnosis of primary HAS between April 1, 2004, and December 31, 2019, at 14 centers in China., Main Outcomes and Measures: OS and prognostic factors. Patients were randomly assigned to a derivation cohort (n = 220) and a validation cohort (n = 95). A nomogram was developed based on independent prognostic factors identified through a multivariable Cox mixed-effects model., Results: Among 315 patients with HAS (mean [SD] age, 61.9 [10.2] years; 240 men [76.2%]), 137 patients had simple HAS (defined as the presence of histologically contained hepatoid differentiation areas only), and 178 patients had mixed HAS (defined as the presence of hepatoid differentiation areas plus common adenocarcinoma areas). Patients with simple HAS had a higher median preoperative α-fetoprotein level than those with mixed HAS (195.9 ng/mL vs 48.9 ng/mL, respectively; P < .001) and a higher rate of preoperative liver metastasis (23 of 137 patients [16.8%] vs 11 of 178 patients [6.2%]; P = .003). The 3-year OS rates of patients with simple vs mixed HAS were comparable (56.0% vs 60.0%; log-rank P = .98). A multivariable Cox analysis of the derivation cohort found that the presence of perineural invasion (hazard ratio [HR], 2.13; 95% CI, 1.27-3.55; P = .009), preoperative carcinoembryonic antigen levels of 5 ng/mL or greater (HR, 1.72; 95% CI, 1.08-2.74; P = .03), and pathological node category 3b (HR, 3.72; 95% CI, 1.34-10.32; P = .01) were independent risk factors for worse OS. Based on these factors, a nomogram to predict postoperative OS was developed. The concordance indices of the nomogram (derivation cohort: 0.72 [95% CI, 0.66-0.78]; validation cohort: 0.72 [95% CI, 0.63-0.81]; whole cohort: 0.71 [95% CI, 0.66-0.76]) were higher than those derived using the American Joint Committee on Cancer's AJCC Cancer Staging Manual (8th edition) pathological tumor-node-metastasis (pTNM) staging system (derivation cohort: 0.63 [95% CI, 0.57-0.69]; validation cohort: 0.65 [95% CI, 0.56-0.75]; whole cohort: 0.64 [95% CI, 0.59-0.69]) and those derived using a clinical model that included pTNM stage and receipt of adjuvant chemotherapy (derivation cohort: 0.64 [95% CI, 0.58-0.69]; validation cohort: 0.65 [95% CI, 0.56-0.75]; whole cohort: 0.64 [95% CI, 0.59-0.69]). Based on the nomogram cutoff of 10 points, the whole cohort was divided into high-risk and low-risk groups. The 3-year OS rate of patients in the high-risk group was significantly lower than that of patients in the low-risk group (29.7% vs 75.9%, respectively; log-rank P < .001), and the 3-year prognosis of high-risk and low-risk groups could be further distinguished into pTNM stage I to II (33.3% vs 80.2%; exact log-rank P = .15), stage III (34.3% vs 71.3%; log-rank P < .001), and stage IV (15.5% vs 70.3%; log-rank P = .009)., Conclusions and Relevance: This study found that perineural invasion, preoperative carcinoembryonic antigen levels of 5 ng/mL or greater, and pathological node category 3b were independent risk factors associated with worse OS. An individualized nomogram was developed to predict OS among patients with HAS. This nomogram had good prognostic value and may be useful as a supplement to the current American Joint Committee on Cancer TNM staging system.

Introduction: Intestinal metaplasia (IM) is an independent risk factor for gastric cancer (GC). However, the subtypes of IM as a risk factor for GC remain controversial. We performed a systematic review and meta-analysis to evaluate the relationship between IM subtypes and GC risk., Methods: Systematic searches were conducted in PubMed, EMBASE, and the Cochrane Library for published cohort studies of patients with complete IM (type I) or incomplete IM (type II or type III) from inception to May 15, 2021. We extracted relevant data and calculated pooled risk ratios (RRs) and 95% confidence intervals (CIs) comparing the GC risk with IM subtypes., Results: Twelve cohort studies comprising 6,498 individuals were included in the study. Compared with complete IM, the pooled relative risk of GC risk of patients with incomplete IM was 5.16 (95% CI, 3.28-8.12), and the GC risk of type III IM was the highest, with a pooled relative risk of 2.88 (95% CI, 1.37-6.04) compared with that of type II. Compared with complete IM, the pooled relative risk of dysplasia risk in patients with incomplete IM was 3.72 (95% CI, 1.42-9.72), and the dysplasia risk of type III IM was 11.73 (95% CI, 2.08-66.08) compared with that of type I., Discussion: Patients with incomplete IM, especially type III, were at a higher risk of GC and dysplasia than those with complete IM. The current evidence indicates a potential correlation between IM subtypes and GC risk, which may support the use of IM subtypes in GC surveillance., (Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of The American College of Gastroenterology.)

Gastric carcinoma (GC) represents one of the most common and most lethal malignancies worldwide. The histopathological characterization of GC precursor lesions has provided great knowledge about gastric carcinogenesis, with the consequent introduction of effective strategies of primary and secondary prevention. In recent years, a large amount of data about the molecular events in GC development is emerging, flanking the histomorphological descriptions. In this review, we describe the landscape of molecular alterations in gastric pre-invasive lesions with a glance at their potential use in the diagnostic and therapeutic decision-making process.

Background: Gastric adenocarcinoma of fundic-gland type (GA-FG) is a rare variant of gastric neoplasia. However, the etiology, classification, and clinicopathological features of gastric epithelial neoplasm of fundic-gland mucosa lineage (GEN-FGML; generic term of GA-FG related neoplasm) are not fully elucidated. We performed a large, multicenter, retrospective study to establish a new classification and clarify the clinicopathological features of GEN-FGML., Methods: One hundred GEN-FGML lesions in 94 patients were collected from 35 institutions between 2008 and 2019. We designed a new histopathological classification of GEN-FGML using immunohistochemical analysis and analyzed via clinicopathological, immunohistochemical, and genetic evaluation., Results: GEN-FGML was classified into 3 major types; oxyntic gland adenoma (OGA), GA-FG, and gastric adenocarcinoma of fundic-gland mucosa type (GA-FGM). In addition, GA-FGM was classified into 3 subtypes; Type 1 (organized with exposure type), Type 2 (disorganized with exposure type), and Type 3 (disorganized with non-exposure type). OGA and GA-FG demonstrated low-grade epithelial neoplasm, and GA-FGM should be categorized as an aggressive variant of GEN-FGML that demonstrated high-grade epithelial neoplasm (Type 2 > 1, 3). The frequent presence of GNAS mutation was a characteristic genetic feature of GEN-FGML (7/34, 20.6%; OGA 1/3, 33.3%; GA-FG 3/24, 12.5%; GA-FGM 3/7, 42.9%) in mutation analysis using next-generation sequencing., Conclusions: We have established a new histopathological classification of GEN-FGML and propose a new lineage of gastric epithelial neoplasm that harbors recurrent GNAS mutation. This classification will be useful to estimate the malignant potential of GEN-FGML and establish an appropriate standard therapeutic approach., (© 2021. The Author(s).)

Background: Inactivation of TP53, a tumor suppressor gene, is associated with the development of several malignancies, including gastric cancer (GC). The present study aimed to evaluate the correlation between the overexpression of p53 and survival in different Lauren-type GCs., Methods: From May 2003 to December 2019, 3608 GC patients treated endoscopically or surgically at the Seoul National University Bundang Hospital were enrolled for the study. Immunohistochemical staining for p53 was performed on all endoscopic and surgical gastric specimens. Clinicopathologic characteristics with Lauren classification, survival rate, and cancer recurrence were analyzed according to p53 overexpression., Results: Among 3608 GC patients, p53 overexpression was seen in 1334 patients (37%). p53 overexpression was associated with lower depth of invasion (P = 0.026) and Early gastric cancer (P = 0.044) in intestinal-type GC, and with advanced TNM stage (P < 0.001) and Advanced gastric cancer (P < 0.001) in diffuse-type GC. The overall survival (OS) and GC-specific survival (GCSS) were significantly lower in p53 overexpression positive patients. This significance was more pronounced and enhanced in the diffuse-type GC and was absent in the intestinal-type GC. In multivariate analyses, p53 overexpression was associated with poor OS in both subtypes of GC and cancer recurrence in diffuse-type GC. (OS in intestinal-type: adjusted hazard ratio [aHR] = 1.423, P = 0.022; OS in diffuse-type: aHR = 1.401 P = 0.035; cancer recurrence in diffuse-type: aHR = 1.502, P = 0.039)., Conclusion: p53 overexpression was associated with poor prognosis in GC, especially in diffuse-type. In addition, p53 overexpression was associated with early stage disease in intestinal-type GC and with advanced stage disease in diffuse-type GC.

Gastric cancer is a heterogenous disease with different phenotypes, genotypes, and clinical outcomes, including sensitivity to treatments and prognoses. Recent medical advances have enabled the classification of this heterogenous disease into several groups and the consequent analysis of their clinicopathological characteristics. Gastric cancer associated with Epstein-Barr virus (EBV) and microsatellite-unstable tumors are considered to be the two major subtypes as they are clearly defined by well-established methodologies, such as in situ hybridization and polymerase chain reaction-based analyses, respectively. However, discrepancies in the histological diagnosis of gastric neoplasms remain problematic, and international harmonization should be performed to improve our understanding of gastric carcinogenesis. We re-evaluated Japanese cases of early gastric cancer according to the current World Health Organization (WHO) criteria and classified them into genomic subtypes based on microsatellite instability (MSI) and EBV positivity to determine the initial genetic events in gastric carcinogenesis. A total of 113 Japanese early gastric cancers (including low- and high-grade dysplasias) treated with endoscopic resection over 5 years were archived in our hospital. A histological re-evaluation according to the WHO criteria revealed 54 adenocarcinomas, which were divided into 6 EBV-positive (11.1%), 7 MSI-high (MSI-H, 13.0%), and 41 microsatellite stable cases (75.9%). MSI-H adenocarcinoma was confirmed by an immunohistochemistry assay of mismatch repair proteins. Programmed death-ligand 1 immunostaining with two antibodies (E1L3N and SP263) was positive in tumor cells of one MSI-H adenocarcinoma case (1/7, 14.3%). The proportion of stained cells was higher with clone SP263 than with E1L3N. Histologically, EBV-positive carcinomas were poorly differentiated (83.8%), and MSI-H cancers were frequent in well to moderately differentiated adenocarcinoma (85.7%), indicating that the EBV-positive subtype presented with high-grade morphology even when an early lesion. Our study indicates that the WHO criteria are useful for subdividing Japanese early gastric cancers, and this subdivision may be useful for comparative analysis of precursor lesions and early carcinoma., (© 2021 The Authors. The Journal of Pathology: Clinical Research published by The Pathological Society of Great Britain and Ireland & John Wiley & Sons, Ltd.)

Background: Gastric cancer (GC) is a highly heterogeneous tumor with different responses to immunotherapy. Identifying immune subtypes and landscape of GC could improve immunotherapeutic strategies., Methods: Based on the abundance of tumor-infiltrating immune cells in GC patients from The Cancer Genome Atlas, we used unsupervised consensus clustering algorithm to identify robust clusters of patients, and assessed their reproducibility in an independent cohort from Gene Expression Omnibus. We further confirmed the feasibility of our immune subtypes in five independent pan-cancer cohorts. Finally, functional enrichment analyses were provided, and a deep learning model studying the pathological images was constructed to identify the immune subtypes., Results: We identified and validated three reproducible immune subtypes presented with diverse components of tumor-infiltrating immune cells, molecular features, and clinical characteristics. An immune-inflamed subtype 3, with better prognosis and the highest immune score, had the highest abundance of CD8+ T cells, CD4+ T-activated cells, follicular helper T cells, M1 macrophages, and NK cells among three subtypes. By contrast, an immune-excluded subtype 1, with the worst prognosis and the highest stromal score, demonstrated the highest infiltration of CD4+ T resting cells, regulatory T cells, B cells, and dendritic cells, while an immune-desert subtype 2, with an intermediate prognosis and the lowest immune score, demonstrated the highest infiltration of M2 macrophages and mast cells, and the lowest infiltration of M1 macrophages. Besides, higher proportion of EVB and MSI of TCGA molecular subtyping, over expression of CTLA4, PD1, PDL1, and TP53, and low expression of JAK1 were observed in immune subtype 3, which consisted with the results from Gene Set Enrichment Analysis. These subtypes may suggest different immunotherapy strategies. Finally, deep learning can predict the immune subtypes well., Conclusion: This study offers a conceptual frame to better understand the tumor immune microenvironment of GC. Future work is required to estimate its reference value for the design of immune-related studies and immunotherapy selection., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Chen, Sun, Chen, Liu, Chai, Ding, Liu, Feng, Zhou, Shen, Huang and Xu.)

Competing Interests: None

Background: The tumour stroma microenvironment plays an important part in disease progression and its composition can influence treatment response and outcomes. Histological evaluation of tumour stroma is limited by access to tissue, spatial heterogeneity, and temporal evolution. We aimed to develop a radiological signature for non-invasive assessment of tumour stroma and treatment outcomes., Methods: In this multicentre, retrospective study, we analysed CT images and outcome data of 2209 patients with resected gastric cancer from five independent cohorts recruited from two centres (Nanfang Hospital of Southern Medical University [Guangzhou, China] and Sun Yat-sen University Cancer Center [Guangzhou, China]). Patients with histologically confirmed gastric cancer, at least 15 lymph nodes harvested, preoperative abdominal CT available, and complete clinicopathological and follow-up data were eligible for inclusion. Tumour tissue was collected for patients in the training cohort (321 patients), internal validation cohort one (246 patients), and external validation cohort one (128 patients). Four stroma classes were defined according to the protein expression of α-smooth muscle actin and periostin assessed by immunohistochemistry. The primary objective was to predict the histologically based stroma classes by using preoperative CT images. We trained a deep convolutional neural network model using the training cohort and tested the model in the internal and external validation cohort one. We evaluated the model's association with prognosis in the training cohort, two internal, and two external validation cohorts and compared outcomes of patients who received or did not receive adjuvant chemotherapy., Findings: The deep-learning model achieved a high diagnostic accuracy for assessing tumour stroma in both internal validation cohort one (area under the receiver operating characteristic curve [AUC] 0·96-0·98]) and external validation cohort one (AUC 0·89-0·94). The stromal imaging signature was significantly associated with disease-free survival and overall survival in all cohorts (p<0·0001). The predicted stroma classes remained an independent prognostic factor adjusting for clinicopathological variables including tumour size, stage, differentiation, and Lauren histology. In patients with stage II or III disease in predicted stroma classes one and two subgroups, patients who received adjuvant chemotherapy had improved survival compared with those who did not (in those with stage II disease hazard ratio [HR] 0·48 [95% CI 0·29-0·77], p=0·0021; and in those with stage III disease HR 0·70 [0·57-0·85], p=0·00042). However, in the other two subgroups adjuvant chemotherapy was not associated with survival and might even be detrimental in the predicted stroma class 4 subgroup (HR 1·48 [1·08-2·03], p=0·013)., Interpretation: The deep-learning model could allow for accurate and non-invasive evaluation of tumour stroma from CT images in gastric cancer. The radiographical model predicted chemotherapy outcomes and could be used in combination with clinicopathological criteria to refine prognosis and inform treatment decisions of patients with gastric cancer., Funding: None., Competing Interests: Declaration of interests We report no competing interests., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Introduction: Incidence of gastric carcinoma and gastric polyps is on rise all over the world. Chronic atrophic gastritis to intestinal metaplasia progressing to adenocarcinoma has been documented pathway for gastric carcinogenesis. Another pathway for gastric carcinoma is adenoma carcinoma sequence similar to colon cancer., Aim: To study prevalence, endoscopic, and histomorphological features of gastric polyps., Methods and Material: This was retrospective analysis of gastric polyps from 2012 to 2019 in consecutive 10,800 upper gastrointestinal endoscopies. Demographic, endoscopic, and histopathological data were obtained from hospital records. All gastric polyps were classified as per standard histologic criteria. Additional histological features noted were presence of dysplasia, focus of adenoma, or malignancy., Results: The prevalence of gastric polyps was 434 (4%) of 10,800 upper gastrointestinal endoscopies. Majority of polyps were found in the last 4 years (277: 63.8%). Mean age was 55.4 years with male to female ratio 1:1.2. Most of the polyps (94.9%) were less than 1 cm, located in gastric antrum. Multiple polyps were seen in 20.9% cases. On histopathology, fundic gland polyps were most common (147: 33.8%), followed by hyperplastic (128: 29.4%) polyps. Adenomatous polyps were nine (2%); of these, two cases of hyperplastic polyps and one each of fundic gland polyp and benign epithelial polyp showed adenomatous foci., Conclusion: Fundic gland polyps were the most common polyps. With rising incidence of gastric carcinoma, identification of gastric polyps on endoscopy with biopsy can prevent progression to carcinogenesis., Competing Interests: None

Aims: To determine the association of the methylation age (Horvath epigenetic clock) of gastric cancer (GC) tissues with molecular subtypes and patient survival. Materials & methods: Multivariate regression models were used to determine the association of methylation age acceleration (AA) with the clinical and molecular characteristics of 333 GC patients. Results: Relative to the chromosomal instability subtype, the epigenetic AA was 49.8 (95% CI: 42.7-56.9) years for Epstein-Barr virus, 16.1 (10.6-21.6) years for microsatellite instability, and 6.05 (0.1-11.1) years for genomic stability subtype. GC patients with accelerated aging of tumor tissues had better outcomes (adjusted hazard ratio: 3.13; p = 0.03). Differentially methylated probes in patients with accelerated and decelerated methylation aging enriched in pathways including BMP signaling, HMGB1 signaling, STAT3 signaling and human embryonic stem cell pluripotency. Conclusions: Our results highlight the prognostic value of epigenetic AA in GC and suggest that epigenetic AA is also an indicator of molecular subtype in GC.

Gastric cancer (GC) is an aggressive tumor, which is usually diagnosed at an advanced stage and shows high mortality rates. Several GC classifications have been published, based on features such as tumor location, endoscopic features or microscopic architecture. However, TNM stage remains the mainstay of GC management and treatment. In the last years, technical advances have allowed us to investigate the biological heterogeneity of GC and develop new molecular classifications. This knowledge may enhance current classifications, and has the potential to refine GC management and aid in the identification of new molecular targets. In this literature review we have summarized the main findings in epidemiology, screening, classification systems and treatment of GC, focusing on the molecular alterations and new molecular classifications published in the last years., (Copyright © 2020 Sociedad Española de Anatomía Patológica. Publicado por Elsevier España, S.L.U. All rights reserved.)

Objectives: There is a pressing need to develop clinical management pathways for grade 3 (G3) gastroenteropancreatic neuroendocrine neoplasms (GEP NEN)., Methods: We performed a retrospective study on patients with metastatic G3 GEP NEN. The relationship between baseline characteristics and progression-free survival and overall survival was analyzed using the Kaplan-Meier method. Univariate and multivariate analyses were performed using the Cox proportional hazards model., Results: We included 142 patients (74 well-differentiated neuroendocrine tumors [WDNETs], 68 poorly differentiated neuroendocrine carcinomas [PDNECs]). Patients with WDNET had prolonged survival compared with PDNEC (median, 24 vs 15 months, P = 0.0001), which persisted in both pancreatic and nonpancreatic cohorts. Well-differentiated morphology, Ki-67 <50% and positive somatostatin receptor imaging were independently associated with prolonged survival. Of the subgroup treated with first-line platinum-based chemotherapy, response rates were favorable (partial response, 47%; stable disease, 30%); there was no significant difference in response rates nor progression-free survival between WDNET and PDNEC despite significantly prolonged overall survival in the WDNET cohort., Conclusions: Our study corroborates the knowledge of 2 prognostically distinct subgroups within the World Health Organization 2019 G3 GEP NEN population, observed in both pancreatic and nonpancreatic gastrointestinal cohorts. Definitive management pathways are needed to reflect the differences between G3 WDNET and PDNEC., Competing Interests: C.To. reports advisory board and speaker honoraria from Ipsen, Novartis and AAA; outside the submitted work. He has received education grants from Ipsen, Novartis and AAA for the Royal Free NET unit. M.E.C. has received advisory board and speaker honoraria from Ipsen, Novartis, AAA, Lexicon and Pfizer; outside the submitted work. C.Th. reports consulting for Ipsen and Boehringer-Ingelheim and conference travel support from Bayer and Novartis; outside the submitted work. The other authors declare no conflict of interest., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

With the development of genomics, the update of modern imaging technology and the advent of artificial intelligence and big data, the surgical treatment of gastric cancer has gradually stepped into precision medicine. Precision surgery treatment of gastric cancer is based on accurate molecular typing and staging using modern molecular diagnostic technology and imaging, and the formulation of precise and individualized surgical treatment plans, with the concept of minimally invasive and accelerated rehabilitation surgery running through it. For intermediate-stage gastric cancer, we have adopted a comprehensive treatment approach including traditional radiotherapy and chemotherapy, targeted therapy and immunotherapy. Utilize artificial intelligence and big data technology to improve the standardization and interconnectivity of specialty data and realize the transformation of evidence-based medicine. Promoting the standardization, standardization and individualization of gastric cancer surgical treatment, providing patients with precise diagnosis and treatment, and further improving patients' prognosis are the opportunities and challenges in the development of gastric cancer surgery., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

The phenotypical and molecular heterogeneity of gastric cancer has hampered the introduction in clinical practice of a unifying classification of the disease. However, as next generation sequencing (NGS) technologies enhanced the comprehension of the molecular landscape of gastric cancer, novel molecular classification systems have been proposed, allowing the dissection of molecular tumor heterogeneity and paving the way for the development of new targeted therapies. Moreover, the use of NGS analyses in the molecular profiling of formalin-fixed paraffin-embedded (FFPE) specimens will improve patient selection for the enrolment in novel clinical trials. In conclusion, the application of NGS in precision oncology will revolutionize the diagnosis and clinical management in gastric cancer patients., Competing Interests: Declaration of competing interest The authors have no competing interests to declare related to the presented work. MF reports personal fees from Astellas Pharma, GSK, Diaceutics, and Tesaro for consultancy/advisory role and research grants from Astellas Pharma and QED Therapeutics, outside the submitted work., (Copyright © 2021 Elsevier Ltd. All rights reserved.)