Molecular carcinogenesis of gastric cancer: Lauren classification, mucin phenotype expression, and cancer stem cells

Comprehensive analysis of risk factors and nomogram development for predicting hepatic metastasis following radical resection of adenocarcinoma of the esophagogastric junction

BACKGROUND

Adenocarcinoma of the esophagogastric junction (AEG) often presents with subtle early symptoms and delayed diagnosis, frequently resulting in liver metastasis and a poor prognosis. This study aimed to investigate the primary risk factors influencing postoperative liver metastasis in AEG and to develop a simple predictive model to facilitate clinical risk stratification and individualized follow-up strategies.

METHODS

This retrospective study analyzed data from 524 patients with AEG who underwent radical resection, with patients randomly divided into a training group (368 cases) and a validation group (156 cases). Clinical and pathological information was collected, and independent factors significantly associated with postoperative liver metastasis were identified using univariate and multivariate Cox regression analyses. Based on these findings, a nomogram model was constructed to predict the 1-year and 3-year liver metastasis-free survival rates, and the model's predictive performance and clinical utility were evaluated using the C-index, ROC curves, and calibration curves.

RESULTS

Multivariate analysis revealed that thoracoabdominal surgery, higher N stage (N1 and N2/N3), moderate-to-poor differentiation, the presence of vascular tumor thrombus, intestinal type according to Lauren classification, and P53 status were independent risk factors for postoperative liver metastasis. The nomogram model based on these six indicators demonstrated high predictive accuracy in both the training group (C-index = 0.966) and the validation group (C-index = 0.976), with ROC AUCs for both the 1-year and 3-year predictions exceeding 0.96 and favorable calibration curves, confirming the model's strong predictive efficacy.

CONCLUSIONS

The predictive model developed in this study can effectively assess the risk of postoperative liver metastasis in patients with AEG, thereby providing a scientific basis for postoperative monitoring and individualized treatment, with the potential to improve patient outcomes in clinical practice.

Minichromosome maintenance 4 is associated with poor survival and stemness of patients with pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is one of the most well-known cancer types, with a persistently poor 5-year survival rate. We previously reported MCM4 as a molecule associated with cancer stem cells; however, its role in PDAC has not been reported. Therefore, in this study, we aimed to fill this gap in the literature. We analyzed MCM4 expression in 81 PDAC samples using immunohistochemistry (IHC). The functional role of MCM4 in PDAC was investigated using RNA interference in PDAC cell lines. Additionally, a single-cell analysis was conducted by downloading data from six PDAC cases. On IHC, high MCM4 expression was observed in 42 out of 81 (51.9%) PDAC cases. MCM4-positive PDAC was significantly associated with a higher pN grade. Furthermore, high MCM4 expression was linked to a significantly poorer prognosis and was identified as an independent prognostic factor in multivariate analysis. In PDAC cell lines, MCM4 knockdown impairs cell growth and spheroid formation. Single-cell analysis also revealed that MCM4-expressing cells were located upstream of the trajectory, with a cluster showing a correlation with KIFC1, which has been reported to be associated with cancer stemness. These results indicated the significance of MCM4 expression in PDAC and its association with cancer stemness.

Construction and validation of a novel prognostic nomogram for patients with poorly differentiated gastric neuroendocrine neoplasms

BACKGROUND

The prognosis of patients with poorly differentiated gastric neuroendocrine neoplasms (PDGNENs) is dismal and related research is limited.

AIM

To investigate the prognostic factors, and validate a novel prognostic nomogram for PDGNEN patients.

METHODS

We conducted a retrospective study using clinical and pathological data from PDGNEN patients treated at the First Medical Center of the Chinese PLA General Hospital from January 2000 to June 2023. Overall survival (OS) differences were assessed with the Log-rank test and Kaplan-Meier survival curves. Cox regression analysis identified independent risk factors for prognosis. Model performance was evaluated using Harrell's concordance index, receiver operating characteristic analysis, area under the curve, calibration curves, and decision curve analysis (UDC), including the area under the UDC.

RESULTS

The study included 336 patients (227 with neuroendocrine carcinoma and 109 with mixed adenoneuroendocrine carcinoma). The average age was 62.7 years. The cohort comprised 80 (24.7%) patients in stage I, 146 (42.9%) in stage II, 62 (18.1%) in stage III, and 48 (14.3%) in stage IV. Significant differences in OS were observed across tumor-node-metastasis stages (P < 0.001). Multivariate analysis showed age, Ki-67 index, invasion depth, lymph node metastasis, distant metastasis, and platelet-to-lymphocyte ratio as independent risk factors. We developed a nomogram with a concordance index of 0.779 (95% confidence interval: 0.743-0.858). Receiver operating characteristic analysis showed area under the curves for 1-year, 3-year, and 5-year OS predictions of 0.865, 0.850, and 0.890, respectively. The calibration curve demonstrated good agreement with actual outcomes. The area under the UDC for the nomogram vs the 8th American Joint Committee on Cancer tumor-node-metastasis staging system were 0.047 vs 0.027, 0.291 vs 0.179, and 0.376 vs 0.216 for 1-year, 3-year, and 5-year OS, respectively.

CONCLUSION

PDGNENs are predominantly found in older men, often in advanced stages at diagnosis, resulting in poor prognosis. The established nomogram demonstrates strong predictive capability and clinical utility.

Preoperative prediction of the Lauren classification in gastric cancer using automated nnU-Net and radiomics: a multicenter study

OBJECTIVES

To develop and validate a deep learning model based on nnU-Net combined with radiomics to achieve autosegmentation of gastric cancer (GC) and preoperative prediction via the Lauren classification.

METHODS

Patients with a pathological diagnosis of GC were retrospectively enrolled in three medical centers. The nnU-Net autosegmentation model was developed using manually segmented datasets and evaluated by the Dice similarity coefficient (DSC). The CT images were processed by the nnU-Net model to obtain autosegmentation results and extract radiomic features. The least absolute shrinkage and selection operator (LASSO) method selects optimal features for calculating the Radscore and constructing a radiomic model. Clinical characteristics and the Radscore were integrated to construct a combined model. Model performance was evaluated via the receiver operating characteristic (ROC) curve.

RESULTS

A total of 433 GC patients were divided into the training set, internal validation set, external test set-1, and external test set-2. The nnU-Net model achieved a DSC of 0.79 in the test set. The areas under the curve (AUCs) of the internal validation set, external test set-1, and external test set-2 were 0.84, 0.83, and 0.81, respectively, for the radiomic model; and 0.81, 0.81, and 0.82, respectively, for the combined model. The AUCs of the radiomic and combined models showed no statistically significant difference (p > 0.05). The radiomic model was selected as the optimal model.

CONCLUSIONS

The nnU-Net model can efficiently and accurately achieve automatic segmentation of GCs. The radiomic model can preoperatively predict the Lauren classification of GC with high accuracy.

CRITICAL RELEVANCE STATEMENT

This study highlights the potential of nnU-Net combined with radiomics to noninvasively predict the Lauren classification in gastric cancer patients, enhancing personalized treatment strategies and improving patient management.

KEY POINTS

The Lauren classification influences gastric cancer treatment and prognosis. The nnU-Net model reduces doctors' manual segmentation errors and workload. Radiomics models aid in preoperative Lauren classification prediction for patients with gastric cancer.

Identified VCAM1 as prognostic gene in gastric cancer by co-expression network analysis

The diffuse gastric cancer (DGC) is a malignant tumor distinct from intestinal gastric cancer (IGC). This study aims to identify genetic variances and potential diagnostic and therapeutic approaches for diverse types of gastric cancer utilizing an extensive dataset. Data from RNA sequencing and clinical pathological details were acquired from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) dataset. Co-expression gene modules were constructed via Weighted Gene Co-Expression Network Analysis (WGCNA), followed by deciphering gene functions and protein-protein interaction networks within significantly associated modules. In total, analysis was conducted on 56,753 genes from 247 individuals with gastric cancer. Particularly, 621 genes from the green module exhibited strong associations with the Lauren type of gastric cancer. The prominent genes in the green module showed enrichment in processes such as signal transduction, immune response, and the positive regulation of GTPase activity. Noteworthy among these, VCAM1 was identified as the central gene linked to patients' prognosis. Moreover, 72 gastric cancer specimens were collected from The First Affiliated Hospital of University of Science and Technology of China. Immunohistochemical analysis demonstrated a significantly higher expression of VCAM1 in DGC compared to IGC (p = 0.019). Furthermore, it was confirmed that VCAM1 expression serves as a prognostic indicator for patients with DGC (p = 0.002), a correlation not observed in IGC (p = 0.760). In conclusion, this study identifies VCAM1 as a promising diagnostic and prognostic factor, suggesting novel avenues for diagnostic and therapeutic approaches in gastric cancer.

Systematic Characterization of Splicing Dysregulation in Pan Solid Tumor Transcriptome

Splicing dysregulation arising from spliceosomal mutations contributes to disease progression and treatment resistance, mostly in hematologic malignancy. Whereas spliceosomal mutations are less common in solid tumors, splicing disorders are pervasive and proven to promote tumorigenesis. However, there is a lack of systematic understanding of the overall splicing dysregulation patterns and how widespread different patterns occur within or across solid tumor lineage. To address these questions, a computational method called SMNPLS (Sparse Multi-Network Regularized Partial Least Squares) is developed to uncover the pan-cancer splicing dysregulation landscape by extracting joint modular patterns from paired matrices of splicing factors (SFs) expressions and alternative splicing events (ASEs). Six unique patterns illustrated by ASE-SF co-modules are summarized, which involve 1,570 ASEs and altered expression of 170 SFs, covering 40% of TCGA solid tumors. Cross-cancer commonalities of splicing dysregulation are observed among digestive system neoplasms, renal-associated tumors, and urogenital tumors. By contrast, brain tumors demonstrate a distinct splicing pattern with the highest ASE-SF correlation. In addition, some new splicing regulatory relationships are identified that are potentially oncogenic. Overall, the study characterizes the full spectrum of splicing dysregulation patterns, indicating the similarity and specificity of splicing-derived pathogenesis across 31 human solid tumors.

Microbial composition of gastric lesions: differences based on Helicobacter pylori virulence profile

Helicobacter pylori infection is a major risk factor for gastric adenocarcinomas. In the case of the intestinal subtype, chronic gastritis and intestinal metaplasia are well-known sequential steps in carcinogenesis. H. pylori has high genetic diversity that can modulate virulence and pathogenicity in the human host as a cag Pathogenicity Island (cagPAI). However, bacterial gene combinations do not always explain the clinical presentation of the disease, indicating that other factors associated with H. pylori may play a role in the development of gastric disease. In this context, we characterized the microbial composition of patients with chronic gastritis (inactive and active), intestinal metaplasia, and gastric cancer as well as their potential association with H. pylori. To this end, 16 S rRNA metagenomic analysis was performed on gastric mucosa samples from patients with different types of lesions and normal gastric tissues. Our main finding was that H. pylori virulence status can contribute to significant differences in the constitution of the gastric microbiota between the sequential steps of the carcinogenesis cascade. Differential microbiota was observed in inactive and active gastritis dependent of the H. pylori presence and status (p = 0.000575). Pseudomonades, the most abundant order in the gastritis, was associated the presence of non-virulent H. pylori in the active gastritis. Notably, there are indicator genera according to H. pylori status that are poorly associated with diseases and provide additional evidence that the microbiota, in addition to H. pylori, is relevant to gastric carcinogenesis.

The role of cuproptosis in gastric cancer

As a biologically essential transition metal, copper is widely involved in various enzymatic reactions and crucial biological processes in the body. It plays an increasingly important role in maintaining normal cellular metabolism and supporting the growth and development of the human body. As a trace element, copper maintains the dynamic balance of its concentration in body fluids through active homeostatic mechanisms. Both excess and deficiency of copper ions can impair cell function, ultimately leading to cell damage and death. Cuproptosis is a novel form of cell death where copper ions cause cell death by directly binding to the lipoylated components of the citric acid cycle (CAC) in mitochondrial respiration and interfering with the levels of iron-sulfur cluster (Fe-S cluster) proteins, ultimately causing protein toxic stress. Its primary characteristics are Cu2+ concentration dependence and high expression in mitochondrial respiratory cells. Recent research has revealed that, compared to other forms of programmed cell death such as apoptosis, necrosis, and autophagy, cuproptosis has unique morphological and biochemical features. Cuproptosis is associated with the occurrence and development of various diseases, including cancer, neurodegenerative diseases, and cardiovascular diseases. This article focuses on a review of the relevance of cuproptosis in gastric cancer (GC).

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

BACKGROUND

Gastric cancer is one of the most common malignant tumors worldwide, with high incidence and mortality rates, and it has a complex etiology and complex pathological features. Depending on the tumor type, gastric cancer can be classified as intestinal-type and diffuse-type gastric cancer, each with distinct pathogenic mechanisms and clinical presentations. In recent years, machine learning techniques have been widely applied in the medical field, offering new perspectives for the diagnosis, treatment, and prognosis of gastric cancer patients.

METHODS

This study recruited 2158 gastric cancer patients and constructed prognostic prediction models for both intestinal-type and diffuse-type gastric cancer. Clinical pathological data were collected from patients, and machine learning algorithms were used for feature selection and model construction. The performance of the models was validated with training and testing datasets. The Shapley additive explanations (SHAP) values were used to interpret the model predictions and identify the main factors that influence patient survival.

RESULTS

In the prognostic model for intestinal-type gastric cancer, the gradient boosting decision tree (GBDT) model demonstrated the best performance, with key features including pTNM, CA125, tumor size, CA199, and PALB. Similarly, in the prognostic model for diffuse-type gastric cancer, the GBDT model was utilized, with key features comprising pTNM, Borrmann type IV disease, lymphocyte (LYM), lactate dehydrogenase (LDH), potassium (K), perineural invasion (PNI), tumor size, and whole stomach location. Risk stratification analysis revealed that the prognosis of high-risk patients was significantly worse than that of low-risk patients.

CONCLUSION

Machine learning shows great potential in predicting survival outcomes of gastric cancer patients, providing strong support for the development of personalized treatment plans.

Discovering cancer stem-like molecule, nuclear factor I X, using spatial transcriptome in gastric cancer

Gastric cancer (GC) is characterized by significant intratumoral heterogeneity, and stem cells are promising therapeutic targets. Despite advancements in spatial transcriptome analyses, unexplored targets for addressing cancer stemness remain unknown. This study aimed to identify Nuclear Factor IX (NFIX) as a critical regulator of cancer stemness in GC and evaluate its clinicopathological significance and function. Spatial transcriptome analysis of GC was conducted. The correlation between NFIX expression, clinicopathological factors, and prognosis was assessed using immunostaining in 127 GC cases. Functional analyses of cancer cell lines validated these findings. Spatial transcriptome analysis stratified GC tissues based on genetic profiles, identified CSC-like cells, and further refined the classification to identify and highlight the significance of NFIX, as validated by Monocle 3 and CytoTRACE analyses. Knockdown experiments in cancer cell lines have demonstrated the involvement of NFIX in cancer cell proliferation and kinase activity. This study underscores the role of spatial transcriptome analysis in refining GC tissue classification and identifying therapeutic targets, highlighting NFIX as a pivotal factor. NFIX expression is correlated with poor prognosis and drives GC progression, suggesting its potential as a novel therapeutic target for personalized GC therapies.

Altered glycosylation in secreting cells of the gastric glands of aquaporin-4-deficient mice

Aquaporins (AQPs) are important for water transport in the gastrointestinal tract. Changes in their expression and/or localization could cause in disorders and be used as therapeutic targets. Aquaporin-4 (AQP4) is expressed predominantly on the basolateral membrane of the parietal cells in the corpus of the murine gastric glands. Although the secretion of gastric juice is not affected in AQP4-deficient knockout, we evaluated by light microscopy whether the lack of AQP4 affects the glycopatterns of secreting gastric cells. Wild type (WT) and AQP4-deficient knockout mice (KO) were fed a standard diet ad libitum before sacrifice. Segments of stomach corpus were collected, fixed in buffered formalin, and embedded in paraffin wax. Sections, 5-μm thick, were analyzed by histochemical methods (Periodic acid-Schiff, Alcian Blue pH 2.5), and binding of lectins specific to GalNAc (SBA, DBA), Gal (PNA) GlcNAc (WGA, GSAII) mannose and/or glucose (ConA), and fucose (UEA-I, AAA, LTA). Immunohistochemical methods such as anti-Muc6 for neck cells and anti- β- H+/K+-ATPase for parietal cells were also performed. Compared to WT mice, in the mucous cells of KO lower amounts of glycans with galactosyl/galactosaminylated, glycosyl/glycosaminylated, and fucosylated residues were observed; lower fucosylation resulted also in the parietal cells. The observed differences of KO in respect to WT could lead to severer pathological conditions. RESEARCH HIGHLIGHTS: Glycopatterns in gastric glands were compared between wild type (WT) and AQP4-deficient knockout (KO) mice by histochemical and lectin-binding methods. In the mucous cells of KO lower amounts of glycans with galactosyl/galactosaminylated, glycosyl/glycosaminylated and fucosylated residues were observed. In the parietal cells lower fucosylation also resulted. AQP4-deficiency affects glycosylation and could result in altered functionality and pathological conditions.

Impaired Glycosylation of Gastric Mucins Drives Gastric Tumorigenesis and Serves as a Novel Therapeutic Target

BACKGROUND & AIMS

Gastric cancer is often accompanied by a loss of mucin 6 (MUC6), but its pathogenic role in gastric carcinogenesis remains unclear.

METHODS

Muc6 knockout (Muc6-/-) mice and Muc6-dsRED mice were newly generated. Tff1Cre, Golph3-/-, R26-Golgi-mCherry, Hes1flox/flox, Cosmcflox/flox, and A4gnt-/- mice were also used. Histology, DNA and RNA, proteins, and sugar chains were analyzed by whole-exon DNA sequence, RNA sequence, immunohistochemistry, lectin-binding assays, and liquid chromatography-mass spectrometry analysis. Gastric organoids and cell lines were used for in vitro assays and xenograft experiments.

RESULTS

Deletion of Muc6 in mice spontaneously causes pan-gastritis and invasive gastric cancers. Muc6-deficient tumor growth was dependent on mitogen-activated protein kinase activation, mediated by Golgi stress-induced up-regulation of Golgi phosphoprotein 3. Glycomic profiling revealed aberrant expression of mannose-rich N-linked glycans in gastric tumors, detected with banana lectin in association with lack of MUC6 expression. We identified a precursor of clusterin as a binding partner of mannose glycans. Mitogen-activated protein kinase activation, Golgi stress responses, and aberrant mannose expression are found in separate Cosmc- and A4gnt-deficient mouse models that lack normal O-glycosylation. Banana lectin-drug conjugates proved an effective treatment for mannose-rich murine and human gastric cancer.

CONCLUSIONS

We propose that Golgi stress responses and aberrant glycans are important drivers of and promising new therapeutic targets for gastric cancer.

HER-2 positive gastric cancer: Current targeted treatments

Gastric cancer (GC) is highly metastatic and characterized by HER2 amplification. Aberrant HER2 expression drives metastasis, therapy resistance, and tumor recurrence. HER2 amplification contributes to drug resistance by upregulating DNA repair enzymes and drug afflux proteins, reducing drug efficacy. HER2 modulates transcription factors critical for cancer stem cell properties, further impacting drug resistance. HER2 activity is influenced by HER-family ligands, promoting oncogenic signaling. These features point to HER2 as a targetable driver in GC. This review outlines recent advances in HER2-mediated mechanisms and their upstream and downstream signaling pathways in GC. Additionally, it discusses preclinical research investigation that comprehends trastuzumab-sensitizing phytochemicals, chemotherapeutics, and nanoparticles as adjunct therapies. These developments hold promise for improving outcomes and enhancing the management of HER2-positive GC.

Mutations in Helicobacter pylori infected patients with chronic gastritis, intestinal type of gastric cancer and familial gastric cancer

BACKGROUND

Development of sequential changes of mucous leading to gastric cancer and familial cases of gastric cancer of intestinal type is widely connected with Helicobacter pylori infections. In this study we analysed variants of genes involved in cancerogenesis and inflammatory processes of intestines in patients infected with H.pylori. Our goal was to test whether mutations in these genes predestinate to development of gastric cancer, and whether there is a genetic factor that makes it more likely for infections with H.pylori to cause gastric cancer. As infections with H. pylori are relatively common, discovering such genetic predispositions could be used for establishing risk-groups and for planning treatments.

METHODS

Our studies cover analysis of variants in genes involved in cancerogenesis: TP53 (rs11540652, rs587782329, COSM10771), MSH2 (rs193922376), MLH1 (rs63750217), and inflammatory processes of intestine: NOD2 (rs2066847, rs2066842), IL1A (rs1800587) and IL1B (rs1143634) from H.pylori-infected patients.

RESULTS

Mutations were more common in the group of patients with gastric cancer of intestinal type and familial cases of gastric cancer in comparison with patients with chronic gastritis, chronic atrophic gastritis, intestinal metaplasia, dysplasia or gastric cancer (p-value = 0.00824), with the prevalence of p53 mutations in patients with familial gastric cancer vs. patients with other changes of mucosa (p-value = 0.000049). Additionally, gastric cancer patients have mainly genotype TT or CT of the rs2066842 variant of the NOD2 gene.

CONCLUSIONS

The lack of statistically significant changes of other interleukin genes involved in inflammatory processes may suggest the presence of H.pylori infection as a potential trigger for the development of the inflammatory process of the mucosa, leading through microbiota dysbiosis to the development of enteric gastric cancer. Mutations in analysed genes correlated with more severe mucosal changes, with a much more frequent presence of TP53 gene mutations, with a limited presence of other mutations in the familial history of gastric cancer.

RAE1 promotes gastric carcinogenesis and epithelial-mesenchymal transition

AIMS

The purpose of this study was to explore the role of RAE1 in the invasion and metastasis of gastric cancer (GC) cells.

MATERIALS AND METHODS

RAE1 expression in GC cells was determined by reverse-transcription polymerase chain reaction (qRT-PCR) and Western blotting (WB). Cell models featuring RAE1 gene silencing and overexpression were constructed by lentiviral transfection; The proliferation, migration, and invasion ability of cells were detected by cell counting, colony formation assay, would healing assay, and transwell invasion and migration test. WB analysis of ERK/MAPK signaling pathway (ERK1/2, p-ERK1/2, c-Myc) and EMT-related molecules (ZEB1, E-cadherin, N-cadherin, and Vimentin).

RESULTS

The expression level of RAE1 in GC was notably higher than in adjacent tissues. Elevated RAE1 expression correlated with an unfavorable prognosis for GC patients. Knockdown of RAE1, as compared to the control group, resulted in a significant inhibition of proliferation, migration, and invasion abilities in GC cell lines. Furthermore, RAE1 knockdown led to a substantial decrease in the expression of N-cadherin, vimentin, ZEB1, p-ERK1/2, and c-Myc proteins, coupled with a marked increase in E-cadherin expression. The biological effects of RAE1 in GC cells were effectively reversed by the inhibition of the ERK/MAPK signaling pathway using SCH772984. Additionally, RAE1 knockdown demonstrated a suppressive effect on GC tumor size in vivo. Immunohistochemistry (IHC) results revealed significantly lower expression of Ki-67 in RAE1 knockout mice compared to the control group.

CONCLUSIONS

RAE1 promotes GC cell migration and invasion through the ERK/MAPK pathway and is a potential therapeutic target for GC therapy.

BST2 promotes gastric cancer metastasis under the regulation of HOXD9 and PABPC1

Gastric cancer (GC) constitutes substantial cancer mortality worldwide. Several cancer types aberrantly express bone marrow stromal cell antigen 2 (BST2), yet its functional and underlying mechanisms in GC progression remain unknown. In our study, RNA sequencing data revealed that BST2 was transcriptionally activated by homeobox D9 (HOXD9). BST2 was significantly upregulated in GC tissues and promoted epithelial-mesenchymal transition and metastasis of GC. BST2 knockdown reversed HOXD9's oncogenic effect on GC metastasis. Moreover, BST2 messenger RNA stability could be enhanced by poly(A) binding protein cytoplasmic 1 (PABPC1) through the interaction between BST2 3'-UTR and PABPC1 in GC cells. PABPC1 promoted GC metastasis, which BST2 silencing attenuated in vitro and in vivo. In addition, positive correlations among HOXD9, BST2, and PABPC1 were established in clinical samples. Taken together, increased expression of BST2 induced by HOXD9 synergizing with PABPC1 promoted GC cell migration and invasion capacity.

Comprehensive Multiomics Analyses Establish the Optimal Prognostic Model for Resectable Gastric Cancer : Prognosis Prediction for Resectable GC

BACKGROUND

Prognostic models based on multiomics data may provide better predictive capability than those established at the single-omics level. Here we aimed to establish a prognostic model for resectable gastric cancer (GC) with multiomics information involving mutational, copy number, transcriptional, methylation, and clinicopathological alterations.

PATIENTS AND METHODS

The mutational, copy number, transcriptional, methylation data of 268, 265, 226, and 252 patients with stages I-III GC were downloaded from the TCGA database, respectively. Alterations from all omics were characterized, and prognostic models were established at the individual omics level and optimized at the multiomics level. All models were validated with a cohort of 99 patients with stages I-III GC.

RESULTS

TTN, TP53, and MUC16 were among the genes with the highest mutational frequency, while UBR5, ZFHX4, PREX2, and ARID1A exhibited the most prominent copy number variations (CNVs). Upregulated COL10A1, CST1, and HOXC10 and downregulated GAST represented the biggest transcriptional alterations. Aberrant methylation of some well-known genes was revealed, including CLDN18, NDRG4, and SDC2. Many alterations were found to predict the patient prognosis by univariate analysis, while four mutant genes, two CNVs, five transcriptionally altered genes, and seven aberrantly methylated genes were identified as independent risk factors in multivariate analysis. Prognostic models at the single-omics level were established with these alterations, and optimized combination of selected alterations with clinicopathological factors was used to establish a final multiomics model. All single-omics models and the final multiomics model were validated by an independent cohort. The optimal area under the curve (AUC) was 0.73, 0.71, 0.71, and 0.85 for mutational, CNV, transcriptional, and methylation models, respectively. The final multiomics model significantly increased the AUC to 0.92 (P < 0.05).

CONCLUSIONS

Multiomics model exhibited significantly better capability in predicting the prognosis of resectable GC than single-omics models.

Differentially expressed microRNA in prognosis of gastric cancer with Lauren classification

BACKGROUND

Gastric cancer (GC) is one of the most common tumors. There were several classifications of GC recently. The value of Lauren classification in evaluating the prognosis after radical gastrectomy was still unclear and the prognosis of gastric cancer remained relatively poor in the absence of prognostic biomarkers. This study aimed to explore microRNA (miRNA) in the prognosis of GC with different Lauren classification.

METHODS

A retrospective study of 1144 patients was performed in this study. Quantificational reverse transcription-PCR (qRT-PCR) was used to examine the expression of miRNAs. Univariate and multivariate analysis were performed to evaluate prognosis value of Lauren classification.

RESULTS

Total 1144 GC patients were recruited in this cohort, including 302 diffuse type (26.4%), 436 intestinal type (38.1%) and 406 mixed type (35.5%) GC. Multivariate analysis showed that Lauren classification, patients' age, tumor size, tumor infiltrating depth, vascular nerve infiltrating and metastatic lymph nodes ration were significantly correlated with GC patients' OS and DFS. The miR-141-3p, miR-200b-3p and miR-133a-5p were significantly down-regulated in diffuse type compared to intestinal type GC tissues, the miR-105-5p had significant lower expression in diffuse type compared with intestinal type and mixed type GC tissues. As a consequence of univariate analysis, low miR-141-3p in diffuse type GC showed significant worse OS and DFS than high miR-141-3p.

CONCLUSIONS

Lauren classification was an independent prognostic factor in GC. MiR-141-3p was an independent prognostic factor and a promising prognostic biomarker in Lauren classification GC.

Kinesin Family Member B18 Is Related to Gastric Mucin Phenotype and Contributes to Gastric Cancer Progression by Regulating Epithelial-Mesenchymal Transition

INTRODUCTION

Gastric cancer (GC) remains a common health concern worldwide and is the third leading cause of death in Japan. It can be broadly classified into gastric and intestinal mucin phenotypes using immunohistochemistry. We previously reported numerous associations of kinesin family member (KIF) genes and mucin phenotypes with GC. However, no previous studies have reported on the importance of KIF18B in GC using immunostaining. Thus, in this study, we investigated the expression and functions of KIF18B, which is highly expressed in gastric mucin phenotype GC.

METHODS

We performed RNA-seq of gastric and intestinal mucin type GCs, and clinicopathological studies of the KIF18B we found were performed using 96 GC cases. We also performed functional analysis using GC-derived cell lines.

RESULT

RNA-seq showed the upregulation of matrisome-associated genes in gastric mucin phenotype GC and a high expression of KIF18B. KIF18B was detected in 52 of the 96 GC cases (54%) through immunohistochemistry. Low KIF18B expression was significantly associated with poor overall survival (p < 0.01). Other molecules that were significantly associated with KIF18B were MUC5AC and claudin 18; these were also significantly associated with the gastric mucin phenotype. KIF18B small interfering RNA (siRNA)-transfected GC cells showed greater growth and spheroid colony formation than the negative control siRNA-transfected cells. Furthermore, expression of snail family transcriptional repressor 1 and cadherin 2 was significantly increased and that of cadherin 1 was significantly decreased in KIF18B siRNA-transfected GC cells.

CONCLUSION

These findings not only suggest that KIF18B may be a useful prognostic marker, but also provide insight into the pathogenesis of the GC phenotype.

The Genomic Signatures of Linitis Plastica Signal the Entrance into a New Era: Novel Approaches for Diagnosis and Treatment

Linitis Plastica (LP) is a rare and aggressive tumor with a distinctive development pattern, leading to the infiltration of the gastric wall, the thickening of the gastric folds and a "leather bottle appearance". LP is an extremely heterogeneous tumor caused by mutations in oncogenic and tumor suppressive genes, as well as molecular pathways, along with mutations in stromal cells and proteins related to tight junctions. Elucidating the molecular background of tumorigenesis and clarifying the correlation between cancerous cells and stromal cells are crucial steps toward discovering novel diagnostic methods, biomarkers and therapeutic targets/agents. Surgery plays a pivotal role in LP management, serving both as a palliative and curative procedure. In this comprehensive review, we aim to present all recent data on the molecular background of LP and the novel approaches to its management.

Association of CDX2 and mucin expression with chemotherapeutic benefits in patients with stage II/III gastric cancer

BACKGROUND

Better predictors of patients with stage II/III gastric cancer (GC) most likely to benefit from adjuvant chemotherapy are urgently needed. This study aimed to assess the ability of CDX2 and mucin markers to predict prognosis and fluorouracil-based adjuvant chemotherapy benefits.

METHODS

CDX2 and mucin protein expressions were examined by immunohistochemistry and compared with survival and adjuvant chemotherapy benefits in a prospective evaluation cohort of 782 stage II/III GC patients. Then, the main findings were validated in an independent validation cohort (n = 386) and an external mRNA sequencing dataset (ACRG cohort, n = 193).

RESULTS

In the evaluation cohort, CDX2, CD10, MUC2, MUC5AC, and MUC6 expressions were observed in 59.7%, 26.7%, 27.6%, 55.1%, and 57.7% of patients, respectively. However, only the expression of CDX2 was found to be associated with adjuvant chemotherapy benefits. Most importantly, CDX2-negative patients had a poorer prognosis when treated with surgery only, while the prognosis of CDX2-negative and CDX2-positive patients was similar when receiving postoperative adjuvant chemotherapy. Further analysis revealed that patients with CDX2 negative tumors benefited from chemotherapy (5-year overall survival rates: 60.0% with chemotherapy vs. 23.2% with surgery-only, p < 0.001), whereas patients with CDX2 positive tumors did not (pinteraction  = 0.004). Consistent results were obtained in the validation and ACRG cohorts.

CONCLUSIONS

Negative expression of CDX2 is an independent risk factor for survival in stage II/III GC, but subsequent adjuvant chemotherapy is able to compensate for this unfavorable effect. Therefore, active chemotherapy is more urgent for patients with negative CDX2 expression than for patients with positive CDX2 expression.

Sleep Duration and Stress Level in the Risk of Gastric Cancer: A Pooled Analysis of Case-Control Studies in the Stomach Cancer Pooling (StoP) Project

The association between sleep and stress and cancer is underinvestigated. We evaluated these factors in association with gastric cancer (GC). Five case-control studies from the Stomach Cancer Pooling (StoP) Project were included. We calculated the odds ratios (ORs) and the corresponding 95% confidence intervals (CIs) for sleep duration and stress level in association with GC through multiple logistic regression models adjusted for several lifestyle factors. The analysis included 1293 cases and 4439 controls, 215 cardia and 919 noncardia GC, and 353 diffuse and 619 intestinal types. Sleep duration of ≥9 h was associated with GC (OR =1.57, 95% CI = 1.23-2.00) compared to 8 h. This was confirmed when stratifying by subsite (noncardia OR = 1.59, 95% CI = 1.22-2.08, and cardia OR = 1.63, 95% CI = 0.97-2.72) and histological type (diffuse OR = 1.65, 95% CI = 1.14-2.40 and intestinal OR = 1.24, 95% CI = 0.91-1.67). Stress was associated with GC (OR = 1.33, 95% CI = 1.18-1.50, continuous). This relationship was selectively related to noncardia GC (OR = 1.28, 95% 1.12-1.46, continuous). The risk of diffuse (OR = 1.32, 95% CI = 1.11-1.58) and intestinal type (OR = 1.23, 95% CI = 1.07-1.42) were higher when stress was reported. Results for the association between increasing level of stress and GC were heterogeneous by smoking and socioeconomic status (p for heterogeneity = 0.02 and <0.001, respectively). In conclusion, long sleep duration (≥9 h) was associated with GC and its subtype categories. Stress linearly increased the risk of GC and was related to noncardia GC.

Impact of Age at Diagnosis on Clinicopathological Features, Prognosis, and Management of Gastric Cancer: A Retrospective Single-Center Experience from Spain

The impact of age on various aspects of gastric cancer (GC) remains controversial. Clarifying this issue can improve our understanding of the disease, refine risk stratification models, and aid in personalized therapeutic approaches. This study aimed to evaluate the influence of age at diagnosis on the clinicopathological features, prognosis, and management of a specific cohort of Spanish patients with resected GC. The study encompassed 315 patients treated at a single tertiary hospital in Spain, divided into two age-based subgroups: ≤65 years and >65 years. The mean and median ages at diagnosis were 72 and 76 years. Most tumors were diagnosed at pT3 stage (49.2%), and 59.6% of patients had lymph node metastases. 21.3% of cases were diagnosed with GC at age ≤ 65 years. Younger patients showed a significantly higher prevalence of flat, diffuse, high-grade tumors, signet-ring cells, perineural infiltration, D2 lymphadenectomies, and adjuvant therapy. They also exhibited a higher rate of recurrences, but had a significantly longer follow-up. Kaplan-Meier curves indicated no significant prognostic differences based on age. Finally, age did not independently predict overall survival or disease-free survival. Our results suggest that younger patients may require more aggressive treatment due to adverse clinicopathologic features, but the lack of prognostic differences among age groups in our cohort indicates the need for further investigation into the complex interplay between age, clinicopathologic factors, and long-term outcomes in GC.

A novel nomogram and risk stratification system predicting the cancer-specific survival of patients with gastric neuroendocrine carcinoma: a study based on SEER database and external validation

BACKGROUND

Gastric neuroendocrine carcinoma (GNEC) is a rare histology of gastric cancer. The retrospective study was designed to construct and validate a nomogram for predicting the cancer-specific survival (CSS) of postoperative GNEC patients.

METHODS

Data for 28 patients from the Hangzhou TCM Hospital were identified as the external validation cohort. A total of 1493 patients were included in the SEER database and randomly assigned to the training group (1045 patients) and internal validation group (448 patients). The nomogram was constructed using the findings of univariate and multivariate Cox regression studies. The model was evaluated by consistency index (C-index), calibration plots, and clinical net benefit. Finally, the effect between the nomogram and AJCC staging system was compared by net reclassification index (NRI) and integrated discrimination improvement (IDI).

RESULTS

Age, gender, grade, T stage, N stage, metastasis, primary site, tumor size, RNE, and chemotherapy were incorporated in the nomogram. The C-indexes were 0.792 and 0.782 in the training and internal verification sets. The 1-, 3-, and 5-year CSS predicted by the nomogram and actual measurements had good agreement in calibration plots. The 1-, 3-, and 5-year NRI were 0.21, 0.29, and 0.37, respectively. The 1-, 3-, and 5-year IDI values were 0.10, 0.12, and 0.13 (P < 0.001), respectively. In 1-, 3-, and 5-year CSS prediction using DCA curves, the nomogram outperformed the AJCC staging system. The nomogram performed well in both the internal and external validation cohorts.

CONCLUSION

We developed and validated a nomogram to predict 1-, 3-, and 5-year CSS for GNEC patients after surgical resection. This well-performing model could help doctors enhance the treatment plan.

Crafting a Personalized Prognostic Model for Malignant Prostate Cancer Patients Using Risk Gene Signatures Discovered through TCGA-PRAD Mining, Machine Learning, and Single-Cell RNA-Sequencing

BACKGROUND

Prostate cancer is a significant clinical issue, particularly for high Gleason score (GS) malignancy patients. Our study aimed to engineer and validate a risk model based on the profiles of high-GS PCa patients for early identification and the prediction of prognosis.

METHODS

We conducted differential gene expression analysis on patient samples from The Cancer Genome Atlas (TCGA) and enriched our understanding of gene functions. Using the least absolute selection and shrinkage operator (LASSO) regression, we established a risk model and validated it using an independent dataset from the International Cancer Genome Consortium (ICGC). Clinical variables were incorporated into a nomogram to predict overall survival (OS), and machine learning was used to explore the risk factor characteristics' impact on PCa prognosis. Our prognostic model was confirmed using various databases, including single-cell RNA-sequencing datasets (scRNA-seq), the Cancer Cell Line Encyclopedia (CCLE), PCa cell lines, and tumor tissues.

RESULTS

We identified 83 differentially expressed genes (DEGs). Furthermore, WASIR1, KRTAP5-1, TLX1, KIF4A, and IQGAP3 were determined to be significant risk factors for OS and progression-free survival (PFS). Based on these five risk factors, we developed a risk model and nomogram for predicting OS and PFS, with a C-index of 0.823 (95% CI, 0.766-0.881) and a 10-year area under the curve (AUC) value of 0.788 (95% CI, 0.633-0.943). Additionally, the 3-year AUC was 0.759 when validating using ICGC. KRTAP5-1 and WASIR1 were found to be the most influential prognosis factors when using the optimized machine learning model. Finally, the established model was interrelated with immune cell infiltration, and the signals were found to be differentially expressed in PCa cells when using scRNA-seq datasets and tissues.

CONCLUSIONS

We engineered an original and novel prognostic model based on five gene signatures through TCGA and machine learning, providing new insights into the risk of scarification and survival prediction for PCa patients in clinical practice.

De-escalating chemotherapy for stage I-II gastric neuroendocrine carcinoma? A real-world competing risk analysis

BACKGROUND

The role of adjuvant chemotherapy in gastric neuroendocrine neoplasms (GNEC) has not been well clarified yet. The study was designed to investigate the potential effect of adjuvant chemotherapy in stage I-II GNEC patients and construct a predictive nomogram.

METHOD

Stage I-II GNEC patients were included in the Surveillance, Epidemiology, and End Results (SEER) database and divided into chemotherapy and no-chemotherapy groups. We used Kaplan-Meier survival analyses, propensity score matching (PSM), and competing risk analyses. The predictive nomogram was then built and validated.

RESULTS

Four hundred four patients with stage I-II GNEC were enrolled from the SEER database while 28 patients from Hangzhou TCM Hospital were identified as the external validation cohort. After PSM, similar 5-year cancer-specific survival was observed in two groups. The outcomes of competing risk analysis indicated a similar 5-year cumulative incidence of cancer-specific death (CSD) between the two cohorts (35.4% vs. 31.4%, p = 0.731). And there was no significant relation between chemotherapy and CSD in the multivariate competing risks regression analysis (HR, 0.79; 95% CI, 0.48-1.31; p = 0.36). Furthermore, based on the variables from the multivariate analysis, a competing event nomogram was created to assess the 1-, 3-, and 5-year risks of CSD. The 1-, 3-, and 5-year area under the receiver operating characteristic curve (AUC) values were 0.770, 0.759, and 0.671 in the training cohort, 0.809, 0.782, and 0.735 in the internal validation cohort, 0.786, 0.856, and 0.770 in the external validation cohort. Furthermore, calibration curves revealed that the expected and actual probabilities of CSD were relatively consistent.

CONCLUSION

Stage I-II GNEC patients could not benefit from adjuvant chemotherapy after surgery. De-escalation of chemotherapy should be considered for stage I-II GNEC patients. The proposed nomogram exhibited excellent prediction ability.

[Mucins expression in gastric cancer: connection of MUC status with clinical, morphological and prognostic characteristics of the tumor]

OBJECTIVE

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

MATERIAL AND METHODS

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.

RESULTS

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).

CONCLUSION

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.

CD24+CD44+CD54+EpCAM+ gastric cancer stem cells predict tumor progression and metastasis: clinical and experimental evidence

BACKGROUND

Gastric cancer (GC) is a leading cause of cancer-related deaths worldwide. Specific and thorough identification of cancer cell subsets with higher tumorigenicity and chemoresistance, such as cancer stem cells (CSCs), could lead to the development of new and promising therapeutic targets. For better CSC identification, a complete or extended surface marker phenotype is needed to provide increased specificity for new cell targeting approaches. Our goal is to identify and characterize a putative extended phenotype for CSCs derived from patients with GC before treatment, as well as to evaluate its clinical value. In addition, we aim to ensure that cells with this phenotype have stemness and self-renewal capabilities.

METHODS

This is a cohort study including 127 treatment-naïve patients with GC who attended the Instituto Nacional de Cancerología. Multiparametric flow cytometry analysis was performed to determine the extended phenotype of cells derived from gastric biopsies. The tumorigenic capability of cells identified in patients was assessed in a zebrafish model.

RESULTS

CD24+CD44+CD54+EpCAM+ cells were present in all treatment-naïve patients included, with a median abundance of 1.16% (0.57-1.89%). The percentage of CD24+CD44+CD54+EpCAM+ cells was categorized as high or low using 1.19% as the cutoff for the CD24+CD44+CD54+EpCAM+ cell subset. Additionally, a higher TNM stage correlated with a higher percentage of CD24+CD44+CD54+EpCAM+ cells (Rho coefficient 0.369; p < 0.0001). We also demonstrated that a higher percentage of CD24+CD44+CD54+EpCAM+ cells was positively associated with metastasis. The metastatic potential of these cells was confirmed in a zebrafish model. Ultimately, under our conditions, we conclude that CD24+CD44+CD54+EpCAM+ cells are true gastric cancer stem cells (GCSCs).

CONCLUSION

The CD24+CD44+CD54+EpCAM+ cells present in tissue samples from patients are true GCSCs. This extended phenotype results in better and more specific characterization of these highly tumorigenic cells. The relative quantification of CD24+CD44+CD54+EpCAM+ cells has potential clinical value, as these cells are associated with metastatic disease, making their presence an additional prognostic marker and possibly a target for the design of new antineoplastic treatments in the era of precision oncology. Overall, the extended CD24+CD44+CD54+EpCAM+ phenotype of GCSCs could support their isolation for the study of their stemness mechanisms, leading to the identification of better molecular targets for the development of both new therapeutic approaches such as oncoimmunotherapy and new diagnostic and clinical prognostic strategies for GC.

Crizotinib-based proteolysis targeting chimera suppresses gastric cancer by promoting MET degradation

As one of the common malignant cancer types, gastric cancer (GC) is known for late-stage diagnosis and poor prognosis. Overexpression of the receptor tyrosine kinase MET is associated with poor prognosis among patients with advanced stage GC. However, no MET inhibitor has been used for GC treatment. Like other tyrosine kinase inhibitors that fit the "occupancy-driven" model, current MET inhibitors are prone to acquired resistance. The emerging proteolysis targeting chimera (PROTAC) strategy could overcome such limitations through direct degradation of the target proteins. In this study, we successfully transformed the MET-targeted inhibitor crizotinib into a series of PROTACs, recruiting cereblon/cullin 4A E3 ubiquitin ligase to degrade the MET proteins. The optimized lead PROTAC (PRO-6 E) effectively eliminated MET proteins in vitro and in vivo, inhibiting proliferation and motility of MET-positive GC cells. In the MKN-45 xenograft model, PRO-6 E showed pronounced antitumor efficacy with a well-tolerated dosage regimen. These results validated PRO-6 E as the first oral PROTAC for MET-dependent GC.

Comprehensive transcriptomic profiling and mutational landscape of primary gastric linitis plastica

BACKGROUND

Primary gastric linitis plastica (GLP) is a distinct phenotype of gastric cancer with poor survival. Comprehensive molecular profiles and putative therapeutic targets of GLP remain undetermined.

METHODS

We subjected 10 tumor-normal tissue pairs to whole exome sequencing (WES) and whole transcriptome sequencing (WTS). 10 tumor samples were all GLP which involves 100% of the gastric wall macroscopically. TCGA data were compared to generate the top mutated genes and the overexpressed genes in GLP.

RESULTS

Our results reveal that GLP has distinctive genomic and transcriptomic features, dysfunction in the Hippo pathway is likely to be a key step during GLP development. 6 genes were identified as significantly highly mutated genes in GLP, including AOX1, ANKRD36C, CPXM1, PTPN14, RPAP1, and DCDC1). MUC6, as a previously identified gastric cancer driver gene, has a high mutation rate (20%) in GLP. 20% of patients in our GLP cohort had CDH1 mutations, while none had RHOA mutations. GLP exhibits high immunodeficiency and low AMPK pathway activity. Our WTS results showed that 3 PI3K-AKT pathway-related genes (PIK3R2, AKT3, and IGF1) were significantly up-regulated in GLP. Two genes were identified using immunohistochemistry (IHC), IGF2BP3 and MUC16, which specifically expressed in diffuse-type-related gastric cancer cell lines, and its knockdown inhibits PI3K-AKT pathway activity.

CONCLUSIONS

We provide the first integrative genomic and transcriptomic profiles of GLP, which may facilitate its diagnosis, prognosis, and treatment.

Comprehensive Multiomics Analysis Identified IQGAP3 as a Potential Prognostic Marker in Pan-Cancer

Background

IQGAP3 has important function in cancer progression and has become a potential therapeutic target as a transmembrane protein. But its role in tumor immunity and pan-cancer was not systematically investigated. This study evaluated the potential role of IQGAP3 and clinical significance in pan-cancer through combined multiomics analysis.

Methods

From Genotype Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases, transcriptomic datasets were first obtained, and from Gene Expression Omnibus (GEO), expression profiling microarray data were acquired and integrated to systematically assess the expression differences and prognostic relevance of IQGAP3 in pancreatic cancer. Immunohistochemical data were obtained from Human Protein Atlas (HPA) to assess IQGAP3 protein expression differences, and exome data from TCGA were used to analyze IQGAP3 expression in relation to tumor mutational burden (TMB), microsatellite instability (MSI), and mutation. Additionally, we also analyzed the relationship between IQGAP3 expression and immune checkpoints, mismatch repair (MMR), and IQGAP3 relationship with methylation and copy number variation based on expression profiles.

Results

Microsatellite instability (MSI), immune checkpoints, mismatch repair (MMR), and tumor mutational burden (TMB) all closely interacted with IQGAP3 mRNA. In addition, detailed relationships between the immune microenvironment and IQGAP3 mRNA as well as immune cell CD4+ Th2 and myeloid-derived suppressor cells (MDSCs) were determined. Mechanistically, IQGAP3 was involved in cytoskeleton formation, T cell receptor signaling pathways, DNA damage, cell cycle, P53 pathway, Fc gamma R-mediated phagocytosis, and apoptosis.

Conclusion

IQGAP3 could serve as an effective prognostic biomarker for pan-cancer immune-related therapy.

Circular RNA hsa_circ_0002360 Promotes Proliferation and Invasion and Inhibits Oxidative Stress in Gastric Cancer by Sponging miR-629-3p and Regulating the PDLIM4 Expression

Many studies have found that circRNA hsa_0002360 (circ0002360) plays an important role in cancer onset and progression. However, its role in gastric cancer (GC) remains uncertain. Circ0002360 was found to be upregulated in GC cells using QRT-PCR. Furthermore, miR-629-3p, a target miRNA of circ0002360, was the most suppressed miRNA following circ0002360 overexpression. RNA immunoprecipitation (RIP), dual-luciferase reporter analyses, clone formation, transwell, DCFH-DA, and ELISA assays demonstrated that circ0002360-targeted miR-629-3p promotes cell proliferation and migration while inhibiting oxidative stress. GC-related mRNA microarrays from the GEO and TCGA databases, including GSE103236, GSE79973, GSE33429, GSE22804, GSE84437, and TCGA-STAD datasets, were used to find hub biomarkers between normal and gastric cancer samples. WGCNA and uni-Cox analysis were used to identify 27 survival-related risk genes, which were then used to build a risk model for prognosis prediction. Following that, all patients from the GSE84437 and TCGA-STAD datasets with 27 survival-related genes and enough data on survival status and time were randomly assigned to train (n = 433) and test (n = 375) cohorts. Furthermore, ROC and Kaplan-Meier (KM) analyses were used to validate the risk model for both cohorts. randomForest analysis indicated that PDLIM4 was the target gene of miR-629-3p, whose level was increased by circ0002360 but reversed by miR-629-3p mimics. Finally, this study confirmed that circ0002360 sponged miR-629-3p and then upregulated PDLIM4 expression. As a result, circ0002360 may be a useful marker for predicting GC prognosis and an anti-GC treatment target.

Low Expression of miR-491-3p Is Correlated with Lymph Node Metastasis in Gastric Cancer

Objective

MiR-491-3p, as a tumor suppressor miRNA, was found decreased in many solid tissues. In this study, we aim to investigate miR-491-3p expression in gastric cancer with or without lymph node metastasis (LNM).

Methods

GSE173215 dataset from Gene Expression Omnibus (GEO) was used to measure miRNA expression from tissue samples of gastric cancer patients. Moreover, gastric tumor tissues (non-LNM: n = 78; LNM: n = 68) were obtained to detect the miR-491-3p expression. Receiver operating characteristic (ROC) curve and Kaplan–Meier (KM) survival analysis, as well as Cox regression analysis, were performed to reveal the role of miR-491-3p in diagnosis and prognosis of gastric cancer.

Results

According to GSE173215 datasets (t = −11.25, adjust P value = 1.30E-06) and our clinical results (0.390 ± 0.193 vs. 0.562 ± 0.166, P < 0.005), the gastric cancer patients with LNM showed lower miR-491-3p expression than those without LNM, demonstrating a high diagnostic efficiency (sensitivity: 74.36%; specificity: 69.12%). In addition, both LNM and low miR-491-3p expression were correlated with the poor prognosis of gastric cancer. Furthermore, the LNM patient with low expression of miR-491-3p had the worse prognosis, but the non-LNM patient with high expression of miR-491-3p had the best prognosis. MiR-491-3p expression (HR = 0.003, 95%CI: 3.35E-04∼0.028) and LNM (HR = 2.326, 95%CI: 1.046∼5.173) were independent risk factors for gastric cancer.

Conclusion

Downregulated miR-491-3p expression was found in gastric cancer, being a high diagnostic efficiency and an independent risk factor for gastric cancer, especially in those having LNM.

Construction and validation of gastric cancer diagnosis model based on machine learning

Aim: To screen differentially expressed genes related to gastric cancer based on The Cancer Genome Atlas (TCGA) database and construct a gastric cancer diagnosis model by machine learning. Methods: Transcriptional data, genomic data, and clinical information of gastric cancer tissues and non-gastric cancer tissues were downloaded from the TCGA database, and differentially expressed genes of gastric cancer messenger RNA (mRNA) and long non-coding RNA (lncRNA) were screened out. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyzed the differentially expressed genes, and the protein-protein interaction (PPI) of differentially expressed genes was constructed. Core differentially expressed genes were screened by Cytoscape software’s molecular complex detection (MCODE) plug-in. The differential genes of lncRNA were analyzed by univariate Cox regression analysis and lasso regression for further dimension reduction to obtain the core genes. The core genes were screened by machine learning to construct the gastric cancer diagnosis model. The efficiency of the gastric cancer diagnosis model was verified externally by the Gene Expression Omnibus (GEO) database. Results: Finally, 10 genes including long intergenic non-protein coding RNA 1821 (LINC01821), AL138826.1, AC022164.1, adhesion G protein-coupled receptor D1-antisense RNA 1 (ADGRD1-AS1), cyclin B1 (CCNB1), kinesin family member 11 (KIF11), Aurora kinase B (AURKB), cyclin dependent kinase 1 (CDK1), nucleolar and spindle associated protein 1 (NUSAP1), and TTK protein kinase (TTK) were screened as gastric cancer diagnostic model genes. After efficiency analysis, it was found that the random forest algorithm model had the best comprehensive evaluation, with an accuracy of 92% and an area under the curve (AUC) of 0.9722, which was more suitable for building a gastric cancer diagnosis model. The GSE54129 data set was used to verify the gastric cancer diagnosis model with an AUC of 0.904, indicating that the gastric cancer diagnosis model had high accuracy. Conclusions: Machine learning can simplify the bioinformatics analysis process and improve efficiency. The core gene discovered in this study is expected to become a gene chip for the diagnosis of gastric cancer.

Prognostic and Immunological Value of GNB4 in Gastric Cancer by Analyzing TCGA Database

Background

Gastric cancer (GC) represents a universal malignant tumor of the digestive system. Stromal and immune cells belong to two main nontumor components exerting a vital function in the tumor microenvironment.

Methods

Based on TCGA database, this study downloaded clinical information and gene profiles of GC. The ESTIMATE algorithm was adopted for evaluating the score of immune-infiltrating cells. This work employed Sangerbox to explore the differentially denoted genes (DEGs) related to stromal, immunity, and prognosis. Besides, the STRING database was involved in order to detect the association among the proteins. The MCODE module of Cytoscape software was used to screen key genes. Oncomine and GEPIA databases were used, aiming to study the differences in key genes in healthy gastric mucosa and GC. At last, we adopted TISDIB and TIMER databases for analyzing the association of guanine nucleotide binding protein subunit-4 (GNB4) between gastric cancer and tumor immune cells. qRT-PCR was applied for exploring differential GNB4 expression between GC and normal gastric mucosa and investigating the relation of GNB4 with tumor-infiltrating lymphocytes (TILs).

Results

Patients undergoing a great stromal score exhibited worse prognostic outcome, and cases having a low immune score had better prognosis. Overall, altogether 656 genes were upregulated with 5 genes being downregulated, which were matrix immune-related differential genes. Furthermore, 18 genes were screened as hub genes on the basis of the univariate Cox risk model of TCGA database (82 differential genes predicted poor GC survival). Oncomine and GEPIA databases revealed that GNB4 expression in gastric cancer was obviously higher in comparison with that in normal gastric mucosa. The GSEA, TISDIB, and TIMER databases revealed that GNB4 is involved in various tumor signal pathways and immune and metabolic processes. qRT-PCR demonstrated that GNB4 expression in gastric cancer was notably higher in comparison with that in normal gastric mucosa, showing significant association with matrix TILs.

Conclusion

The selected key gene GNB4 is a potential biomarker to guide the immunotherapy of gastric cancer.

The dawn of precision medicine in diffuse-type gastric cancer

Gastric cancer (GC) is one of the most common malignancies worldwide. The histology- and morphology-based Lauren classification of GC has been widely used for over 50 years in clinical practice. The Lauren classification divides GC into intestinal and diffuse types, which have distinct etiology, molecular profiles, and clinicopathological features. Diffuse-type GC (DGC) accounts for approximately 30% of GCs. Tumor cells lack adhesion and infiltrate the stroma as single cells or small subgroups, leading to easy dissemination in the abdominal cavity. Clinically, DGC has aggressive traits with a high risk of recurrence and metastasis, which results in unfavorable prognosis. Although systemic chemotherapy is the main therapeutic approach for recurrent or metastatic GC patients, clinical benefits are limited for patients with DGC. Therefore, it is urgent to develop effective therapeutic strategies for DGC patients. Considerable research studies have characterized the molecular and genomic landscape of DGC, of which tight junction protein claudin-18 isoform 2 (CLDN18.2) and fibroblast growing factors receptor-2 isoform IIIb (FGFR2-IIIb) are the most attractive targets because of their close association with DGC. Recently, the impressive results of two phase II FAST and FIGHT trials demonstrate proof-of-concept, suggesting that anti-CLDN18.2 antibody (zolbetuximab) and FGFR2-IIIb antibody (bemarituzumab) are promising approaches for patients with CLDN18.2-positive and FGFR2-IIIb-positive GC, respectively. In this review, we summarize the clinicopathological features and molecular profiles of DGC and highlight a potential therapeutic target based on the findings of pivotal clinical trials.

The novel lncRNA GPC5-AS1 stabilizes GPC5 mRNA by competitively binding with miR-93/106a to suppress gastric cancer cell proliferation

Long non-coding RNAs (lncRNAs) are of importance in the genesis and progression of gastric cancer (GC). GPC5-AS1 is a novel lncRNA associated with methyl-CpG-binding protein 2 (MeCP2), identified in our previous microarray analysis; however, the role of GPC5-AS1 in GC remains unknown. In the present study, we demonstrate that GPC5-AS1 is downregulated in GC cells and tissues, and this aberrant expression is regulated by MeCP2 through CpG site binding in the promoter region. Importantly, we also demonstrate that GPC5-AS1 overexpression suppresses cell proliferation, colony formation, and cell cycle transition; induces apoptosis in vitro; and inhibits tumorigenicity in vivo. The expression of the controversial gene GPC5 was downregulated in GC tissues, and elevated GPC5 level could inhibit GC cell growth. Mechanistically, we demonstrated that GPC5-AS1 stabilizes GPC5 mRNA by acting as a molecular sponge for miR-93 and miR-106a, thereby reducing GC tumor progression. In conclusion, our results suggest that GPC5-AS1 may play a pivotal role in GC and serve as a potential diagnostic biomarker and a powerful therapeutic target for GC.

DNA methylation of RNA-binding protein for multiple splicing 2 functions as diagnosis biomarker in gastric cancer pathogenesis and its potential clinical significance

Higher methylation levels of RNA-binding protein for multiple splicing 2 (RBPMS2) was reported to be related with unfavorable outcome in gastric cancer (GC). However, molecular function and diagnostic significance of DNA methylation of RBPMS2 remains indistinct. Here we aimed to whether DNA methylation of RBPMS2 acts as a diagnosis biomarker in GC pathogenesis and its potential clinical significance. Western blot and immunochemistry assays were carried out to explore the level of RBPMS2. GC malignancy behaviors were determined by cell counting kit-8, Transwell, flow cytometry analysis and terminal-deoxynucleoitidyl transferase mediated nick end labeling staining. The inflammatory cell infiltration in xenograft model was observed by hematoxylin and eosin staining. CpG Islands was predicted by MethPrimer and the DNA methylation of RBPMS2 was evaluated by methylation-specific polymerase chain reaction. The results showed that RBPMS2 was downregulated in GC specimens. Poor survival rates were associated with low RBPMS2 expression. Overexpression of RBPMS2 inhibited GC growth while facilitated apoptosis in GC cells. In addition, level of DNA methylation of RBPMS2 in GC tissues was increased and DNA methylation of RBPMS2 was strongly associated with tumor invasion, Borrmann classification and TNM stage. We also observed that DNA methylation inhibitors counteracted the role of RBPMS2 in restraining GC development and tumorigenesis. To sum, our data demonstrated that DNA methylation of RBPMS2 was responsible for its downregulation in GC and promoted tumor progression, indicating DNA methylation of RBPMS2 might serve as a valuable potential parameter in GC pathogenesis.

The Clinicopathological Features and Overall Survival of Patients With Gastric Neuroendocrine Carcinoma

OBJECTIVES

Gastric neuroendocrine carcinoma (GNEC) is a class of rare histological subtypes in gastric cancer (GC). This retrospective case-control study aimed to explore the clinicopathological features and overall survival (OS) of patients with GNEC.

METHODS

A large population of GNEC and intestinal-type GC (IGC) patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The 1:1 propensity score matching (PSM) analysis was initiated to adjust the confounders between GNEC and IGC cohorts. Kaplan-Meier (KM) plots with log-rank tests were used to compare the survival differences in GNEC versus IGC. Additionally, Cox proportional hazard regression models were adopted to characterize the prognostic factors relevant to OS of the GNEC patients.

RESULTS

An entity of 4596 patients were collected, including 3943 (85.8%) IGC patients and 653 (14.2%) GNEC patients. The PSM analysis well-balanced all confounders in GNEC versus IGC (all P > .05). The KM plots showed that GNEC had significantly superior OS to IGC both before and after PSM analysis. Before PSM, the median OS was 52 (33.6-70.4) months in GNEC versus 32 (29.3-34.7) months in IGC (P  =  .0015). After PSM, the median OS was 26 (18.3-33.7) months in GNEC versus 21 (17.7-24.3) months in IGC (P  =  .0039). Stratified analysis indicated that GNEC had superior survivals to IGC in early stage patients and those who received surgery. In Cox regression analysis, age ≥ 60, tumor size > 50 mm, stage II-IV, T2, and N3 were independent risk factors for the GNEC patients (hazard ratio [HR]>1, P < .05). By contrast, year 2010 to 2015, female, and surgery were independent protective factors for these patients (HR < 1, P < .05).

CONCLUSIONS

GNEC has unique clinicopathological features quite different from IGC and may have a superior survival to IGC in early stage patients. The prognostic factors identified here may assist the clinicians to more individually treat these patients.

Promotion of gastric tumor initiating cells in a 3D collagen gel culture model via YBX1/SPP1/NF-κB signaling

Background

The high potential for tumor recurrence and chemoresistance is a major challenge of clinical gastric cancer treatment. Increasing evidence suggests that the presence of tumor initiating cells (TICs) is the principal cause of tumor recurrence and chemoresistance. However, the underlying mechanism of TIC development remains controversial.

Methods

To identify novel molecular pathways in gastric cancer, we screened the genomic expression profile of 155 gastric cancer patients from the TCGA database. We then described an improved 3D collagen I gels and tested the effects of collagen on the TIC phenotype of gastric cells using colony formation assay, transwell assay, and nude mouse models. Additionally, cell apoptosis assay was performed to examine the cytotoxicity of 5-fluorine and paclitaxel on gastric cancer cells cultured in 3D collagen I gels.

Results

Elevated expression of type I collagen was observed in tumor tissues from high stage patients (stage T3–T4) when compared to the low stage group (n=10, stage T1–T2). Furthermore, tumor cells seeded in a low concentration of collagen gels acquired TIC-like phenotypes and revealed enhanced resistance to chemotherapeutic agents, which was dependent on an integrin β1 (ITGB1)/Y-box Binding Protein 1 (YBX1)/Secreted Phosphoprotein 1 (SPP1)/NF-κB signaling pathway. Importantly, inhibition of ITGB1/NF-κB signaling efficiently reversed the chemoresistance induced by collagen and promoted anticancer effects in vivo.

Conclusions

Our findings demonstrated that type I collagen promoted TIC-like phenotypes and chemoresistance through ITGB1/YBX1/SPP1/NF-κB pathway, which may provide novel insights into gastric cancer therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02307-x.

Immunotherapy for Peritoneal Metastases from Gastric Cancer: Rationale, Current Practice and Ongoing Trials

Peritoneal metastases from gastric cancer play a key role in the fatal prognosis of the disease. The lack of efficacy of actual therapeutic approaches together with the outcomes achieved with checkpoint inhibitors in gastric cancer compel us to address the current state-of-the-art immunotherapy treatment of peritoneal dissemination. The immunogenicity of the peritoneum has been described to be particularly active at omentum and peritoneal lymph nodes. Also, both innate and acquired immunity seems to be involved at different molecular levels. Recent works show PDL1 expression being less present at the peritoneal level; however, some clinical trials have begun to yield results. For example, the ATTRACTION-2 trial has demonstrated the activity of Nivolumab in heavily pretreated patients even though peritoneal metastases were diagnosed in a 30% of them. Despite positive results in the metastatic setting, peritoneal responses to systemic checkpoint inhibitors remains unclear, therefore, new strategies for intraperitoneal immunotherapy are being proposed for different ongoing clinical trials.

Suppression of CPSF6 Enhances Apoptosis Through Alternative Polyadenylation-Mediated Shortening of the VHL 3'UTR in Gastric Cancer Cells

Alternative polyadenylation (APA) is an important RNA post-transcriptional process, which can generate diverse mRNA isoforms. Increasing evidence shows that APA is involved in cell self-renewal, development, immunity, and cancer. CPSF6 is one of the core proteins of CFIm complex and can modulate the APA process. Although it has been reported to play oncogenic roles in cancer, the underlying mechanisms remain unclear. The aim of the present study was to characterize CPSF6 in human gastric cancer (GC). We observed that CPSF6 was upregulated in GC. Knockdown of CPSF6 inhibited proliferation and enhanced apoptosis of GC cells both in vitro and in vivo. Global APA site profiling analysis revealed that knockdown of CPSF6 induced widespread 3′UTR shortening of genes in GC cells, including VHL. We also found CPSF6 negatively regulated the expression of VHL through APA and VHL short-3′UTR isoform enhanced apoptosis and inhibited cell growth in GC cells. Our data suggested that CPSF6-induced cell proliferation and inhibition of apoptosis were mediated by the preferential usage of poly(A) in VHL. Our data provide insights into the function of CPSF6 and may imply potential therapeutic targets against GC.

HNRNPL Is Identified and Validated as a Prognostic Biomarker Associated with Microsatellite Instability in Human Gastric Cancer

Microsatellite instability (MSI) is emerging as a promising subtype related to immunotherapy in gastric cancer (GC). However, the underlying mechanism between MSI and microsatellite stability (MSS) remains unclear. In this study, we conducted a weighted gene co-expression network analysis and found that the expression of heterogeneous nuclear ribonucleoprotein L (HNRNPL) was significantly increased in MSI GC compared with MSS GC. This finding was further validated in public GC cohorts and commercialized human GC tissue microarray. The significant negative correlation with the expression of mismatch repair protein mutL homolog 1 (MLH1) may be one of the potential mechanisms for the upregulation of HNRNPL expression in MSI GC (R = -0.689, p = 8.59e-11). In addition, HNRNPL expression was markedly upregulated in GC tissues compared with adjacent normal tissues. High HNRNPL expression also predicted a poor prognosis in GC patients. Finally, gene set enrichment analysis revealed that high HNRNPL MSI GC samples were highly positive associated with the biological functions of inflammation and cell proliferation, such as interferon gamma response, MYC targets, E2F targets, and G2/M checkpoints. In conclusion, HNRNPL could be a new MSI-associated prognostic biomarker in GC and could be a new target for the MSI GC treatment.

Integrative omics analysis reveals effective stratification and potential prognosis markers of pan-gastrointestinal cancers

Gastrointestinal (GI) tract cancers are the most common malignant cancers with high mortality rate. Pan-cancer multi-omics data fusion provides a powerful strategy to examine commonalities and differences among various cancer types and benefits for the identification of pan-cancer drug targets. Herein, we conducted an integrative omics analysis on The Cancer Genome Atlas pan-GI samples including six carcinomas and stratified into 9 clusters, i.e. 5 single-type-dominant clusters and 4 mixed clusters, the clustering reveals the molecular features of different subtypes, other than the organ and cell-of-origin classifications. Especially the mixed clusters revealed the homogeneity of pan-GI cancers. We demonstrated that the prognosis differences among pan-GI subtypes based on multi-omics integration are more significant than clustering by single-omics. The potential prognostic markers for pan-GI stratification were identified by proportional hazards model, such as PSCA (for colorectal and stomach cancer) and PPP1CB (for liver and pancreatic cancer), which have prominent prognostic power supported by high concordance index.

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Pan-cancer multi-omics strategy reveals homogeneity and heterogeneity of pan-GI cancers

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Identify 9 iclusters with significantly different survival and molecular features

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Potential prognostic markers have prominent power supported by concordance index

Mutations of key driver genes in gastric cancer metastasis risk: a systematic review and meta-analysis

Objective: Associations between gene mutations and metastasis in gastric cancer (GC) remain contradictory, resulting in the inaccurate estimation of the magnitude of the risk associated with specific genotypes.Methods: In this study, we first screened out four key driver genes (TP53, PIK3CA, APC and ARID1A) by jointly analyzing the mutation levels and searching the literature for genes associated with GC metastasis. We then performed a meta-analysis to demonstrate the relationship between these key driver gene mutations and GC metastasis, including lymphatic and distance metastasis.Results: We found out four key driver genes (TP53, PIK3CA, APC and ARID1A), associated with risk of GC metastasis. The results showed that TP53 (OR 1.39, 95% CI 1.12-1.72) and APC mutations (OR 0.58, 95% CI 0.38-0.89) were associated with lymph node metastasis and distant metastasis in GC. And TP53 mutations (OR 1.65, 95% CI 1.25-2.18) were significantly related to GC metastasis in the Asian population. APC mutations (OR 0.54, 95% CI 0.29-1.00) were also related to GC metastasis in the European and American populations. There was no significant association with GC metastasis in PIK3CA or ARID1A mutations.Expert opinion:Mutations of TP53 and APC play important roles in lymph node metastasis and distant metastasis of GC and may be potential important biomarkers of progression and therapeutic targets. These observations should be further prospectively verified.

Different effects of p53 protein overexpression on the survival of gastric cancer patients according to Lauren histologic classification: a retrospective study

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.

Is there still a place for conventional histopathology in the age of molecular medicine? Laurén classification, inflammatory infiltration and other current topics in gastric cancer diagnosis and prognosis

Gastric cancer (GC) is the fifth most common cancer and the third cause of cancer-related deaths worldwide. In western countries, more than half of GC patients are diagnosed at advanced stages and 5-year survival rates range between 20-30%. The only curative treatment is surgery, and despite recent advances in oncological therapies, GC prognosis is still poor. The main prognostic tool for patient categorization and treatment selection is the TNM classification, but its limitations are being increasingly recognized. Early recurrences may occur in early-stage disease, and patients at the same stage show heterogeneous outcomes. Thus, there is a need to improve GC stratification and to identify new prognostic factors, which may allow us to select drug-susceptible populations, refine patient grouping for clinical trials and discover new therapeutic targets. Molecular classifications have been developed, but they have not been translated to the clinical practice. On the other hand, histological assessment is cheap and widely available, and it is still a mainstay in the era of molecular medicine. Furthermore, histological features are acquiring new roles as reflectors of the genotype-phenotype correlation, and their potential impact on patient management is currently being analyzed. The aim of this literature review is to provide a modern overview of the histological assessment of GC. In this study, we discuss recent topics on the histological diagnosis of GC, focusing on the current role of Laurén classification and the potential value of new histological features in GC, such as inflammatory infiltration and tumor budding.

Molecular Alterations in Gastric Intestinal Metaplasia

Gastric cancer (GC) remains one of the most common causes of mortality worldwide. Intestinal metaplasia (IM) is one of the preneoplastic gastric lesions and is considered an essential predisposing factor in GC development. Here we present a review of recent most relevant papers to summarize major findings on the molecular alterations in gastric IM. The latest progress in novel diagnostic methods allows scientists to identify various types of molecular alterations in IM, such as polymorphisms in various genes, changes in the expression of micro-RNAs and long noncoding RNAs, and altered microbiome profiles. The results have shown that some of these alterations have strong associations with IM and a potential to be used for screening, treatment, and prognostic purposes; however, one of the most important limiting factors is the inhomogeneity of the studies. Therefore, further large-scale studies and clinical trials with standardized methods designed by multicenter consortiums are needed. As of today, various molecular alterations in IM could become a part of personalized medicine in the near future, which would help us deliver a personalized approach for each patient and identify those at risk of progression to GC.

Cooperative participation of epigenomic and genomic alterations in the clinicopathological diversity of gastric adenocarcinomas: significance of cell adhesion and epithelial-mesenchymal transition-related signaling pathways

The present study was conducted to clarify the cooperative significance of epigenomic and genomic abnormalities during gastric carcinogenesis. Using 21 samples of normal control gastric mucosa (C), 109 samples of non-cancerous gastric mucosa (N) and 105 samples of cancerous tissue (T) from 109 patients with primary gastric adenocarcinomas, genome-wide DNA methylation analysis was performed using Infinium assay. Among these samples, 66 paired N and corresponding T samples were subjected to whole-exome and single nucleotide polymorphism array analyses. As had been shown in our previous study, 109 patients were clustered clinicopathologically into least aggressive Cluster A (n = 20), most aggressive Cluster B1 (n = 20) and Cluster B2 (n = 69). Most DNA methylation alterations in each cluster had already occurred even in N samples compared with C samples, and DNA methylation alterations at the precancerous N stage were inherited by the established cancers themselves. Recurrent single nucleotide variants and insertions/deletions resulting in functional disruption of the proteins encoded by the ABCA10, BNC2, CDH1, CTNNB1, SMAD4 and VAV2 genes were specific to Cluster B1, whereas those of the APC, EGFR, ERBB2, ERBB3, MLH1 and MUC6 genes were specific to Cluster A. MetaCore pathway analysis revealed that the epigenomically affected TWIST1 gene and genomically affected CDH1, CTNNB1, MMP9, TLN2, ROCK1 and SMAD4 genes were accumulated in signaling pathways related to cell adhesion, cytoskeleton remodeling and epithelial–mesenchymal transition in Cluster B1. These data indicate that epigenomic alterations at the precancerous stage are important in gastric carcinogenesis and that epigenomic and genomic alterations cooperatively underlie the aggressiveness of gastric adenocarcinomas.