Dissection of gastric cancer heterogeneity for precision oncology

Bioinformatics Analysis of the Expression and Prognostic Significance of Transcription Factor YY1 in Gastric Cancer

BACKGROUND

Emerging evidence indicates that the transcription factor Yin Yang 1 (YY1) plays a critical role in the carcinogenesis and progression of various human malignancies. YY1 is highly expressed in gastric cancer (GC), raising interest in its role in GC.

AIMS

This study aims to analyze the role of YY1 in gastric cancer, investigate its effect on the tumor microenvironment, and assess its potential as a prognostic marker.

METHODS AND RESULTS

Transcriptomic data and clinical information from GC patients were obtained from the TCGA and UCSC databases. YY1 expression was analyzed using the R "limma" package. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed with the online tool clusterProfiler. The relationship between YY1 expression levels and the tumor microenvironment was examined in different risk groups of GC patients. Additionally, YY1-positive staining in 26 clinical GC samples was measured using ImageJ software. Co-expression analysis was used to identify prognostic genes associated with YY1, and a prognostic risk model was built and optimized. Results showed that YY1 was significantly overexpressed in 415 GC (p < 0.001) and was associated with poorer survival outcomes (p = 0.043). GO and KEGG showed that YY1 was involved in key biological processes of the disease. Higher YY1 expression was correlated with lower stromal and immune cell content in the tumor microenvironment. Immunohistochemical staining confirmed YY1 overexpression in GC tissues compared to normal tissues (p = 0.0293). Positive correlations were observed between YY1 and the genes MTA1, TTL15, HNRNPU, WDR20, and PPP4R3A. The prognostic model, which included genes significantly associated with YY1 (risk score AUC = 0.690), predicted patient survival better than other clinical variables.

CONCLUSION

These findings suggest that YY1 plays an important role in the development of GC. Targeting the YY1 pathway may be a potential treatment strategy for GC.

Functions of METTL1/WDR4 and QKI as m7G modification - related enzymes in digestive diseases

N7-methylguanosine (m7G) modification is one of the most prevalent forms of chemical modification in RNA molecules, which plays an important role in biological processes such as RNA stability, translation regulation and ribosome recognition. Methyl-transferation of m7G modification is catalyzed by the enzyme complex of methyltransferase-like 1 (METTL1) and WD repeat domain 4 (WDR4), and Quaking (QKI) recognizes internal m7G methylated mRNA and regulates mRNA translation and stabilization. Recent studies have found that m7G modification - related enzymes are associated with the onset and progression of digestive cancer, such as colorectal cancer, liver cancer, and other digestive diseases such as ulcerative colitis. This review will focus on the latest research progress on the roles of m7G methyltransferase METTL1/WDR4 and recognized enzyme QKI in digestive diseases.

Res@ZIF-90 suppress gastric cancer progression by disturbing mitochondrial homeostasis

BACKGROUND

Gastric cancer (GC) is still a serious threat to human health worldwide. As a natural compound, resveratrol has been proven to have anti-tumor activity, and the nano-delivery carrier has shown its excellent ability to retain and control drug release.

METHODS

Res@ZIF-90 underwent synthesis via a one-pot method and subsequent characterization encompassing Dynamic Light Scattering, Scanning Electron Microscope, Transmission Electron Microscope, and UV-vis absorption spectroscope. The release of resveratrol from Res@ZIF-90 across varied pH environments were delineated employing High Performance Liquid Chromatography. The mitochondrial targeting of Res@ZIF-90 was scrutinized utilizing Fluorescent Inverted Microscopy. The cytotoxic impact of Res@ZIF-90 on HGC-27 cells was evaluated through CCK-8 assay, Live/Dead staining, scratch test, and JC-1 assay. Furthermore, the HGC-27 tumor-bearing mice model was established to explore the anti-tumor effect of Res@ZIF-90.

RESULTS

ZIF-90 can effectively release resveratrol under acidic (pH = 5.5) conditions. In addition, Res@ZIF-90 could be taken up by cells and localized into mitochondria. ZIF-90 has no obvious cytotoxicity at the experimental concentration, while Res@ZIF-90 was more cytotoxic to HGC-27 cells than free resveratrol at the same concentration. Res@ZIF-90 significantly reduced the expressions of PGCS 1α, TFAM, PINK1, and COX IV, which together induced mitochondrial homeostasis disorders and inhibited the tumor growth of HGC-27 tumor-bearing mice in vivo.

CONCLUSIONS

Res@ZIF-90 can inhibit the progression of gastric cancer by targeting the mitochondria of gastric cancer cells and disrupting mitochondrial homeostasis to produce cytotoxic effects. Res@ZIF-90 may be a promising antitumor drug with potential application value.

Combining methylated RNF180 and SFRP2 plasma biomarkers for noninvasive diagnosis of gastric cancer

INTRODUCTION

Gastric cancer (GC) is a common malignant tumor, and early diagnosis significantly improves patient survival rates. This study aimed to investigate the diagnostic value of ring finger protein 180 (RNF180) and secreted frizzled protein 2 (SFRP2) in GC.

MATERIALS & METHODS

A total of 165 healthy individuals, 34 patients with precancerous gastric lesions, and 104 patients with confirmed GC were divided into training and validation sets; methylated RNF180 and SFRP2 were detected in circulating DNA from blood samples. Six models, including those based on logistic regression, Naive Bayes, K-nearest neighbor algorithm, glmnet, neural network, and random forest (RF) were built and validated. Area under the curve (AUC), sensitivity, specificity, positive predictive value, and negative predictive value were determined.

RESULTS

In the training set, the RF model with RNF180 and SFRP2 (R + S) had an AUC of 0.839 (95 % CI: 0.727-0.951), sensitivity of 60.3 %, and specificity of 85.5 % for diagnosing GC. The RF model with R + S+ Tumor markers had an AUC of 0.849 (95 % CI: 0.717-0.981), sensitivity of 62.8 %, and specificity of 87.1 %. In the validation set, the RF model with R + S had an AUC of 0.844 (95 % CI: 0.774-0.923), sensitivity of 87.8 %, and specificity of 69.2 %. The RF model with R + S + Tumor markers had an AUC of 0.858 (95 % CI: 0.781-0.939), sensitivity of 85.4 %, and specificity of 76.9 %.

CONCLUSION

Our results suggest that RNF180 and SFRP2 could serve as diagnostic biomarkers for GC when using the RF model.

Role of molecular imaging in prognosis, diagnosis, and treatment of gastrointestinal cancers: An update on new therapeutic methods

One of the leading causes of cancer-related death is gastrointestinal cancer, which has a significant morbidity and mortality rate. Although preoperative risk assessment is essential for directing patient care, its biological behavior cannot be accurately predicted by conventional imaging investigations. Potential pathophysiological information in anatomical imaging that cannot be visually identified can now be converted into high-dimensional quantitative image features thanks to the developing discipline of molecular imaging. In order to enable molecular tissue profile in vivo, molecular imaging has most recently been utilized to phenotype the expression of single receptors and targets of biological therapy. It is expected that molecular imaging will become increasingly important in the near future, driven by the expanding range of biological therapies for cancer. With this live molecular fingerprinting, molecular imaging can be utilized to drive expression-tailored customized therapy. The technical aspects of molecular imaging are first briefly discussed in this review, followed by an examination of the most recent research on the diagnosis, prognosis, and potential future clinical methods of molecular imaging for GI tract malignancies.

GCclassifier: An R package for the prediction of molecular subtypes of gastric cancer

Gastric cancer (GC) is one of the most commonly diagnosed malignancies, threatening millions of lives worldwide each year. Importantly, GC is a heterogeneous disease, posing a significant challenge to the selection of patients for more optimized therapy. Over the last decades, extensive community effort has been spent on dissecting the heterogeneity of GC, leading to the identification of distinct molecular subtypes that are clinically relevant. However, so far, no tool is publicly available for GC subtype prediction, hindering the research into GC subtype-specific biological mechanisms, the design of novel targeted agents, and potential clinical applications. To address the unmet need, we developed an R package GCclassifier for predicting GC molecular subtypes based on gene expression profiles. To facilitate the use by non-bioinformaticians, we also provide an interactive, user-friendly web server implementing the major functionalities of GCclassifier. The predictive performance of GCclassifier was demonstrated using case studies on multiple independent datasets.

Nucleic Acid Amplification Circuit-Based Hydrogel (NACH) Assay for One-Step Detection of Metastatic Gastric Cancer-Derived Exosomal miRNA

Gastric cancer (GC) is recognized as the fifth most prevalent malignant tumor worldwide. It is characterized by diverse clinical symptoms, treatment responses, and prognoses. In GC prognosis, the promotion of epithelial-mesenchymal transition (EMT) fosters cancer cell invasion and metastasis, thereby triggering the dissemination of tumor cells. This study proposes a nucleic acid amplification circuit-based hydrogel (NACH) assay for identifying exosomal miRNA derived from metastatic GC. The NACH assay employs the rolling circle amplification method and targets miRNA-21, a tumor-related oncogene, and miRNA-99a, which promotes EMT. Specific amplification probes for each target are immobilized within the hydrogel, enabling a streamlined, one-step amplification reaction. The NACH assay exhibits a detection limit of 1 fm for miRNA-21 and miRNA-99a, thereby enabling rapid and highly sensitive on-site detection. Performance evaluation using exosomal miRNA extracted from cell culture media, mouse plasma, and human plasma revealed fluorescence intensity patterns similar to those obtained in qRT-PCR. Furthermore, deploying a custom-developed portable fluorometer for the NACH assay allows for diagnostic performance assessment and point-of-care testing using clinical samples from GC patients. These findings emphasize the potential of the NACH assay to be used as a robust tool for the genetic diagnosis of GC based on exosome detection.

Deciphering the Landscape of GATA-Mediated Transcriptional Regulation in Gastric Cancer

Gastric cancer (GC) is an asymptomatic malignancy in early stages, with an invasive and cost-ineffective diagnostic toolbox that contributes to severe global mortality rates on an annual basis. Ectopic expression of the lineage survival transcription factors (LS-TFs) GATA4 and 6 promotes stomach oncogenesis. However, LS-TFs also govern important physiological roles, hindering their direct therapeutic targeting. Therefore, their downstream target genes are particularly interesting for developing cancer-specific molecular biomarkers or therapeutic agents. In this work, we couple inducible knockdown systems with chromatin immunoprecipitation and RNA-seq to thoroughly detect and characterize direct targets of GATA-mediated transcriptional regulation in gastric cancer cells. Our experimental and computational strategy provides evidence that both factors regulate the expression of several coding and non-coding RNAs that in turn mediate for their cancer-promoting phenotypes, including but not limited to cell cycle, apoptosis, ferroptosis, and oxidative stress response. Finally, the diagnostic and prognostic potential of four metagene signatures consisting of selected GATA4/6 target transcripts is evaluated in a multi-cancer panel of ~7000 biopsies from nineteen tumor types, revealing elevated specificity for gastrointestinal tumors. In conclusion, our integrated strategy uncovers the landscape of GATA-mediated coding and non-coding transcriptional regulation, providing insights regarding their molecular and clinical function in gastric cancer.

Prognostic Influence of Galectin-1 in Gastric Adenocarcinoma

Galectin-1 (Gal-1), a member of the human lectin family, has garnered attention for its association with aggressive behavior in human tumors, prompting research into the development of targeted drugs. This study aims to assess the staining pattern and prognostic significance of Gal-1 immunohistochemical expression in a homogeneous cohort of Western patients with gastric cancer (GC). A total of 149 cases were included and tissue microarrays were constructed. Stromal Gal-1 expression was observed to some extent in most tumors, displaying a cytoplasmic pattern. Cases with stromal Gal-1 overexpression showed significantly more necrosis, lymphovascular invasion, advanced pTNM stages, recurrences, and cancer-related deaths. Epithelial Gal-1 expression was present in 63.8% of the cases, primarily exhibiting a cytoplasmic pattern, and its overexpression was significantly associated with lymphovascular invasion, peritumoral lymphocytic infiltration, and tumor-related death. Kaplan/Meier curves for cancer-specific survival (CSS) revealed a significantly worse prognosis for patients with tumors exhibiting stromal or epithelial Gal-1 overexpression. Furthermore, stromal Gal-1 expression stratified stage III patients into distinct prognostic subgroups. In a multivariable analysis, increased stromal Gal-1 expression emerged as an independent prognostic factor for CSS. These findings underscore the prognostic relevance of Gal-1 and suggest its potential as a target for drug development in Western patients with GC.

Potential therapeutic targets of gastric cancer explored under endogenous network modeling of clinical data

Improvement in the survival rate of gastric cancer, a prevalent global malignancy and the leading cause of cancer-related mortality calls for more avenues in molecular therapy. This work aims to comprehend drug resistance and explore multiple-drug combinations for enhanced therapeutic treatment. An endogenous network modeling clinic data with core gastric cancer molecules, functional modules, and pathways is constructed, which is then transformed into dynamics equations for in-silicon studies. Principal component analysis, hierarchical clustering, and K-means clustering are utilized to map the attractor domains of the stochastic model to the normal and pathological phenotypes identified from the clinical data. The analyses demonstrate gastric cancer as a cluster of stable states emerging within the stochastic dynamics and elucidate the cause of resistance to anti-VEGF monotherapy in cancer treatment as the limitation of the single pathway in preventing cancer progression. The feasibility of multiple objectives of therapy targeting specified molecules and/or pathways is explored. This study verifies the rationality of the platform of endogenous network modeling, which contributes to the development of cross-functional multi-target combinations in clinical trials.

Management of Microsatellite Instability High (MSI-H) Gastroesophageal Adenocarcinoma

BACKGROUND

Gastroesophageal cancer is a major cause of cancer-related mortality worldwide. Treatment of both early stage and advanced disease remains highly reliant on cytotoxic chemotherapy. About 4-24% of gastroesophageal cancers are microsatellite instability high (MSI-H). The MSI-H subtype is associated with favorable prognosis, resistance to cytotoxic chemotherapy, and sensitivity to immune checkpoint inhibitors (ICI). Recent studies have demonstrated promising activity of ICIs in the MSI-H subtype, resulting in fundamental changes in the management of MSI-H gastroesophageal adenocarcinoma.

PURPOSE

In this review, we discuss the prevalence, characteristics, prognosis, and management of MSI-H gastroesophageal adenocarcinoma, with a focus on recent and ongoing studies that have changed the landscape of treatment for the MSI-H subtype. We also discuss current challenges in the management of resectable and advanced MSI-H gastroesophageal cancer, including the need for more accurate biomarkers of response to ICI therapy.

Molecular classification and intratumoral heterogeneity of gastric adenocarcinoma

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.

Proteome-based molecular subtyping and therapeutic target prediction in gastric cancer

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.

Expression of the Folate Receptor Proteins FOLR1 and FOLR2 in Correlation With Clinicopathological Variables of Gastric Cancer

INTRODUCTION

Gastric cancer (GC) remains a leading cause of cancer-related mortality worldwide, owing to its aggressive nature and poor prognosis. The role of folate receptors, particularly folate receptor 1 (FOLR1) and folate receptor 2 (FOLR2), in cancer has been increasingly recognized due to their overexpression in various malignancies including gastric cancer, and its potential implications in cancer progression, treatment resistance and as therapeutic targets.

OBJECTIVE

To evaluate the expression patterns of FOLR1 and FOLR2 in GC patients' tissue and blood specimens and to correlate these patterns with clinicopathological variables.

METHODS

A total of 58 gastric cancer patients were enrolled at the Regional Cancer Centre (RCC) from March 2017 to March 2020. Immunohistochemical analysis was performed to examine the expression of FOLR1 and FOLR2 in formalin-fixed paraffin-embedded (FFPE) tissue samples. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to analyze FOLR1 and FOLR2 expression in blood samples. Statistical analyses were conducted using chi-square tests, independent T-tests, and Kaplan-Meier survival analysis.

RESULTS

FOLR1 and FOLR2 were overexpressed in 82.76% and 70.69% of gastric cancer tissues, respectively. High expression levels of FOLR1 were significantly associated with the diffuse type of gastric cancer (p<0.005). qRT-PCR showed significant overexpression of FOLR1 in gastric cancer blood samples compared to control samples, with a median fold change of approximately 14.18 times. Conversely, FOLR2 was significantly underexpressed in gastric cancer samples, with a fold change of 0.30. However, no significant correlation was found between FOLR2 expression and the clinicopathological features. The overall survival analysis did not show a significant difference in survival rates based on the expression levels of FOLR1 and FOLR2.

CONCLUSIONS

This study highlights the differential expression patterns of FOLR1 and FOLR2 in gastric cancer and underscores the complexity of their roles in cancer biology. While FOLR1 shows potential as a biomarker for gastric cancer due to its overexpression, further studies are needed to fully elucidate the therapeutic and prognostic implications of folate receptors in gastric cancer.

Metabolic heterogeneity affects trastuzumab response and survival in HER2-positive advanced gastric cancer

BACKGROUND

Trastuzumab is the only first-line treatment targeted against the human epidermal growth factor receptor 2 (HER2) approved for patients with HER2-positive advanced gastric cancer. The impact of metabolic heterogeneity on trastuzumab treatment efficacy remains unclear.

METHODS

Spatial metabolomics via high mass resolution imaging mass spectrometry was performed in pretherapeutic biopsies of patients with HER2-positive advanced gastric cancer in a prospective multicentre observational study. The mass spectra, representing the metabolic heterogeneity within tumour areas, were grouped by K-means clustering algorithm. Simpson's diversity index was applied to compare the metabolic heterogeneity level of individual patients.

RESULTS

Clustering analysis revealed metabolic heterogeneity in HER2-positive gastric cancer patients and uncovered nine tumour subpopulations. High metabolic heterogeneity was shown as a factor indicating sensitivity to trastuzumab (p = 0.008) and favourable prognosis at trend level. Two of the nine tumour subpopulations associated with favourable prognosis and trastuzumab sensitivity, and one subpopulation associated with poor prognosis and trastuzumab resistance.

CONCLUSIONS

This work revealed that tumour metabolic heterogeneity associated with prognosis and trastuzumab response based on tissue metabolomics of HER2-positive gastric cancer. Tumour metabolic subpopulations may provide an association with trastuzumab therapy efficacy.

CLINICAL TRIAL REGISTRATION

The patient cohort was conducted from a multicentre observational study (VARIANZ;NCT02305043).

Targeting cell surface glucose-regulated protein 94 in gastric cancer with an anti-GRP94 human monoclonal antibody

Gastric cancer (GC), a leading cause of cancer-related mortality, remains a significant challenge despite recent therapeutic advancements. In this study, we explore the potential of targeting cell surface glucose-regulated protein 94 (GRP94) with antibodies as a novel therapeutic approach for GC. Our comprehensive analysis of GRP94 expression across various cancer types, with a specific focus on GC, revealed a substantial overexpression of GRP94, highlighting its potential as a promising target. Through in vitro and in vivo efficacy assessments, as well as toxicological analyses, we found that K101.1, a fully human monoclonal antibody designed to specifically target cell surface GRP94, effectively inhibits GC growth and angiogenesis without causing in vivo toxicity. Furthermore, our findings indicate that K101.1 promotes the internalization and concurrent downregulation of cell surface GRP94 on GC cells. In conclusion, our study suggests that cell surface GRP94 may be a potential therapeutic target in GC, and that antibody-based targeting of cell surface GRP94 may be an effective strategy for inhibiting GRP94-mediated GC growth and angiogenesis. [BMB Reports 2024; 57(4): 188-193].

A Review on Anaplastic Lymphoma Kinase (ALK) Rearrangements and Mutations: Implications for Gastric Carcinogenesis and Target Therapy

Gastric adenocarcinoma is a complex disease with diverse genetic modifications, including Anaplastic Lymphoma Kinase (ALK) gene changes. The ALK gene is located on chromosome 2p23 and encodes a receptor tyrosine kinase that plays a crucial role in embryonic development and cellular differentiation. ALK alterations can result from gene fusion, mutation, amplification, or overexpression in gastric adenocarcinoma. Fusion occurs when the ALK gene fuses with another gene, resulting in a chimeric protein with constitutive kinase activity and promoting oncogenesis. ALK mutations are less common but can also result in the activation of ALK signaling pathways. Targeted therapies for ALK variations in gastric adenocarcinoma have been developed, including ALK inhibitors that have shown promising results in pre-clinical studies. Future studies are needed to elucidate the ALK role in gastric cancer and to identify predictive biomarkers to improve patient selection for targeted therapy. Overall, ALK alterations are a relevant biomarker for gastric adenocarcinoma treatment and targeted therapies for ALK may improve patients' overall survival.

Pretreatment controlling nutritional status (CONUT) score and carcinoembryonic antigen level provide tumor progression and prognostic information in gastric cancer: A retrospective study

This study explores the role of combining the controlling nutritional status (CONUT) score and the carcinoembryonic antigen (CEA) level on predicting tumor stage and prognosis in gastric cancer (GC) patients. A total of 682 GC patients were included in this retrospective study. CONUT scores and CEA levels were combined to establish a new scoring system: CONUT-CEA score. cutoff values for distinguishing patients between stage IV and non-stage IV were established by receiver operating characteristic curves. cutoff values for predicting prognosis were determined by maximum χ2 method. The CONUT and CEA cutoff values for discriminating stage IV patients from non-stage IV patients were 2.0 and 5.58 ng/mL, respectively. Logistic regression model demonstrated that high CONUT-CEA score was related to advanced tumor stage. Among non-stage IV patients, CONUT and CEA cutoff values of 2.0 and 9.50 ng/mL predicted overall survival (OS), respectively. The Cox proportional risk model revealed that high CONUT-CEA score was notable related to decreased OS (2 vs 0: hazard ratios (HR) = 2.358, 95% confidence intervals (CI) = 1.412-3.940, P = .001) and decreased disease-free survival (2 vs 0: HR = 1.980, 95% CI = 1.072-3.656, P = .003). The CONUT-CEA score may be a good biomarker for predicting tumor stage and prognosis in GC patients.

LncRNA MIR200CHG inhibits EMT in gastric cancer by stabilizing miR-200c from target-directed miRNA degradation

Gastric cancer (GC) is a heterogeneous disease, threatening millions of lives worldwide, yet the functional roles of long non-coding RNAs (lncRNAs) in different GC subtypes remain poorly characterized. Microsatellite stable (MSS)/epithelial-mesenchymal transition (EMT) GC is the most aggressive subtype associated with a poor prognosis. Here, we apply integrated network analysis to uncover lncRNA heterogeneity between GC subtypes, and identify MIR200CHG as a master regulator mediating EMT specifically in MSS/EMT GC. The expression of MIR200CHG is silenced in MSS/EMT GC by promoter hypermethylation, associated with poor prognosis. MIR200CHG reverses the mesenchymal identity of GC cells in vitro and inhibits metastasis in vivo. Mechanistically, MIR200CHG not only facilitates the biogenesis of its intronic miRNAs miR-200c and miR-141, but also protects miR-200c from target-directed miRNA degradation (TDMD) through direct binding to miR-200c. Our studies reveal a landscape of a subtype-specific lncRNA regulatory network, providing clinically relevant biological insights towards MSS/EMT GC.

Prognostic role of the number of resected and negative lymph nodes in Spanish patients with gastric cancer

INTRODUCTION

Lymph node (LN) involvement is one of the most critical prognostic factors in resected gastric cancer (GC). Some analyses, mainly conducted in Asian populations, have found that patients with a higher number of total lymph nodes (NTLN) and/or negative lymph nodes (NNLN) have a better prognosis, although other authors have failed to confirm these results.

MATERIALS AND METHODS

Retrospective study including all patients with GC resected in a tertiary hospital in Spain between 2001 and 2019 (n = 315). Clinicopathological features were collected and patients were categorized according to the NTLN and the NNLN. Statistical analyses were performed.

RESULTS

Mean NNLN was 17. The NNLN was significantly related to multiple clinicopathological variables, including recurrence and tumor-related death. The classification based on the NNLN (N1: ≥16, N2: 8-15, N3: ≤7) effectively stratified the entire cohort into three distinct prognostic groups and maintained its prognostic value within both the pN0 and pN+ patient subsets. Furthermore, it was an independent prognostic indicator for both overall and disease-free survival. Conversely, the mean NTLN was 21.9. Patients with ≤16 LN retrieved exhibited distinct clinicopathological features compared to those with >16 LN, but no significant differences were observed in terms of recurrence or disease-associated death. The application of alternative cut-off points for NTLN (10, 20, 25, 30, and 40) showed no prognostic significance.

CONCLUSIONS

In Spanish patients with resected GC the NNLN hold prognostic significance, while the NTLN does not appear to be prognostically significant. Incorporating the NNLN into GC staging may enhance the accuracy of the TNM system.

Concordance between microsatellite instability testing and immunohistochemistry for mismatch repair proteins and efficient screening of mismatch repair deficient gastric cancer

Microsatellite instability (MSI) testing, an established technique that has gained prominence in recent years for its predictive potential regarding the efficacy of immune checkpoint inhibitors, is used to evaluate DNA mismatch repair (MMR) deficiency (dMMR). As with other methods, the immunohistochemistry (IHC) of MMR proteins is also widely adopted. Although both techniques have been validated, their concordance rate remains unknown, particularly regarding non-colorectal cancer. Therefore, the aim of the present study was to explore and elucidate their concordance in the context of gastric cancer (GC). A total of 489 surgically resected primary GC tissues were analyzed to compare the results yielded by the MSI test and those from IHC. Of 488 GC cases, 56 (11.5%) exhibited a loss of MMR proteins, whereas 52 (10.7%) were classified as high-frequency MSI (MSI-H). The concordance rate between these two categories was 99.2%. The microsatellite markers BAT26 and MONO27 demonstrated 100% sensitivity and 99.5% specificity in detecting dMMR GC. In addition, histopathological analysis revealed that MSI-H was more prevalent in GCs exhibiting coexisting Tub2 and Por1 subtypes. However, four discordant cases were observed. All four cases were microsatellite-stable cases but exhibited loss of MLH1 protein expression with hypermethylation of the MLH1 promoter. The results of the present study highlight that while there is a strong concordance between MSI and IHC testing results for determining dMMR status, IHC testing may offer superior efficacy in detecting dMMR.

Prognostic Value of T-Cell Density in the Tumor Center and Outer Margins in Gastric Cancer

Tumor-infiltrating lymphocytes are associated with the survival of gastric cancer patients. T-cell densities in the tumor and its periphery were previously identified as prognostic T-cell markers for resectable gastric cancer. Immunohistochemistry for 5 T-cell markers, CD3, CD45RO, CD8, FOXP3, and granzyme B was performed on serial sections of N = 251 surgical resection specimens of patients treated with surgery only in the D1/D2 trial. Positive T cells were digitally quantified into tiles of 0.25 mm2 across 3 regions: the tumor center (TC), the inner invasive margin, and the outer invasive margin (OIM). A classification and regression tree model was employed to identify the optimal combination of median T-cell densities per region with cancer-specific survival (CSS) as the outcome. All statistical tests were 2-sided. CD8OIM was identified as the most dominant prognostic factor, followed by FOXP3TC, resulting in a decision tree containing 3 prognostically distinct subgroups with high (Hi) or low (Lo) density of the markers: CD8OIMHi, CD8OIMLo/FOXP3TCHi, and CD8OIMLo/FOXP3TCLo. In a multivariable Cox regression analysis, which included pathological T and N stages, Lauren histologic types, EBV status, microsatellite instability, and type of surgery, the immune subgroups were independent predictors for CSS. CSS was lower for CD8OIMLo/FOXP3TCHi (HR: 5.02; 95% CI: 2.03-12.42) and for CD8OIMLo/FOXP3TCLo (HR: 7.99; 95% CI: 3.22-19.86), compared with CD8OIMHi (P < .0001). The location and density of both CD8+ and FOXP3+ T cells in resectable gastric cancer are independently associated with survival. The combination of CD8OIM and FOXP3TC T-cell densities is a promising stratification factor that should be validated in independent studies.

Active ingredients Isorhamnetin of Croci Srigma inhibit stomach adenocarcinomas progression by MAPK/mTOR signaling pathway

Gastric cancer (GC) remains the third leading cause of cancer-related mortality in the world, and ninety-five percent of GC are stomach adenocarcinomas (STAD). The active ingredients of Croci Stigma, such as Isorhamnetin, Crocin, Crocetin and Kaempferol, all have antitumor activity. However, their chemical and pharmacological profiles remain to be elusive. In this study, network pharmacology was used to characterize the action mechanism of Croci Stigma. All compounds were obtained from the traditional Chinese medicine systems pharmacology (TCMSP) database, and active ingredients were selected by their oral bioavailability and drug-likeness index. The targets of Croci Stigma active ingredients were obtained from the traditional Chinese medicine integrated database (TCMID), whereas the related genes of STAD were obtained from DisGeNET platform. Cytoscape was used to undertake visual analyses of the Drug Ingredients-Gene Symbols-Disease (I-G-D) network, and 2 core genes including MAPK14, ERBB3 were obtained, which are the predicted targets of isorhamnetin (IH) and quercetin, respectively. Data analysis from TCGA platform showed that MAPK14 and ERBB3 all upregulated in STAD patients, but only the effect of MAPK14 expression on STAD patients' survival was significant. Molecular docking showed that IH might affect the function of MAPK14 protein, and then the underlying action mechanisms of IH on STAD were experimentally validated using human gastric cancer cell line, HGC-27 cells. The results showed that IH can inhibit cell proliferation, migration, clonal formation, and arrest cell cycle, but promote the apoptosis of HGC-27 cells. qRT-PCR data demonstrated that IH downregulated the MAPK14 mRNA expression and EMT related genes. WB results showed that IH regulates MAPK/mTOR signaling pathway. These findings suggest that IH has the therapeutic potential for the treatment of STAD.

Mining proteomics data to extract post-translational modifications associated with gastric cancer

Gastric cancers are highly heterogeneous, deep-seated tumours associated with late diagnosis and poor prognosis. Post-translational modifications (PTMs) of proteins are known to be well-associated with oncogenesis and metastasis in most cancers. Several enzymes which drive PTMs have also been used as theranostics in cancers of the breast, ovary, prostate and bladder. However, there is limited data on PTMs in gastric cancers. Considering that experimental protocols for simultaneous analysis of multiple PTMs are being explored, a data-driven approach involving reanalysis of mass spectrometry-derived data is useful in cataloguing altered PTMs. We subjected publicly available mass spectrometry data on gastric cancer to an iterative searching strategy for fetching PTMs including phosphorylation, acetylation, citrullination, methylation and crotonylation. These PTMs were catalogued and further analyzed for their functional enrichment through motif analysis. This value-added approach delivered identification of 21,710 unique modification sites on 16,364 modified peptides. Interestingly, we observed 278 peptides corresponding to 184 proteins to be differentially abundant. Using bioinformatics approaches, we observed that majority of these altered PTMs/proteins belonged to cytoskeletal and extracellular matrix proteins, which are known to be perturbed in gastric cancer. The dataset derived by this mutiPTM investigation can provide leads to further investigate the potential role of altered PTMs in gastric cancer management.

A novel immunohistochemical score predicts the postoperative prognosis of gastric cancer patients

BACKGROUND AND AIM

Immunohistochemistry indicators are increasingly being used to predict the survival prognosis of cancer patients after surgery. This study aimed to combine some markers to establish an immunohistochemical score (MSI-P53-Ki-67[MPK]) and stratify postoperative patients with gastric cancer according to the score.

METHODS

We used 245 patients who underwent surgery at one center as the training cohort and 111 patients from another center as the validation cohort. All patients were treated between January 2012 and June 2018. The training cohort was screened for prognostic factors, and MPK scores were established using univariate and multifactorial COX risk proportional models. Patients were prognostically stratified according to the MPK score after gastrectomy for gastric cancer. Overall survival (OS) and recurrence-free survival (RFS) rates were compared among low-, intermediate-, and high-risk groups using the Kaplan-Meier method, and survival curves were plotted. Finally, the MPK score was validated using the validation cohort.

RESULTS

In the training group, there were statistically significant differences in OS and RFS in the low, medium, and high-risk groups (P < 0.001). Thirty patients were in the high-risk group (12.2%). The median survival times of the three groups were 64.0, 44.0, and 23.0, respectively, and median times to recurrence were 54.0, 35.0, and 16.0 months, respectively. In the validation group, the prognosis in the three risk groups remained significantly different (P < 0.001).

CONCLUSIONS

The novel MPK score could effectively predict the postoperative OS and RFS of gastric cancer patients, risk-stratify postoperative patients, and identify postoperative high-risk patients for refined management.

Tumour infiltrating lymphocytes and survival after adjuvant chemotherapy in patients with gastric cancer: post-hoc analysis of the CLASSIC trial

BACKGROUND

Only a subset of gastric cancer (GC) patients with stage II-III benefits from chemotherapy after surgery. Tumour infiltrating lymphocytes per area (TIL density) has been suggested as a potential predictive biomarker of chemotherapy benefit.

METHODS

We quantified TIL density in digital images of haematoxylin-eosin (HE) stained tissue using deep learning in 307 GC patients of the Yonsei Cancer Center (YCC) (193 surgery+adjuvant chemotherapy [S + C], 114 surgery alone [S]) and 629 CLASSIC trial GC patients (325 S + C and 304 S). The relationship between TIL density, disease-free survival (DFS) and clinicopathological variables was analysed.

RESULTS

YCC S patients and CLASSIC S patients with high TIL density had longer DFS than S patients with low TIL density (P = 0.007 and P = 0.013, respectively). Furthermore, CLASSIC patients with low TIL density had longer DFS if treated with S + C compared to S (P = 0.003). No significant relationship of TIL density with other clinicopathological variables was found.

CONCLUSION

This is the first study to suggest TIL density automatically quantified in routine HE stained tissue sections as a novel, clinically useful biomarker to identify stage II-III GC patients deriving benefit from adjuvant chemotherapy. Validation of our results in a prospective study is warranted.

Mucin-Phenotype and Expression of the Protein V-Set and Immunoglobulin Domain Containing 1 (VSIG1): New Insights into Gastric Carcinogenesis

In gastric cancer (GC), intestinal metaplasia (IM) is a common precursor lesion, but its relationship to the MUC2/MUC5AC/CDX2 axis is not completely understood. Although V-set and immunoglobulin domain containing 1 (VSIG1) is supposed to be a specific marker for gastric mucosa and GC, respectively, no data about its relationship with IM or mucin phenotype have been published. The aim of our study was to explore the possible linkage between IM and these four molecules. The clinicopathological features of 60 randomly selected GCs were examined in association with VSIG1, MUC2, MUC5AC and CDX2. Two online database platforms were also used to establish the transcription factors (TFs) network involved in MUC2/MUC5AC/CDX2 cascade. IM was more frequently encountered in females (11/16 cases) and in patients below 60 years old (10/16 cases). Poorly differentiated (G3) carcinomas tended to show a loss of CDX2 (27/33 cases) but not of MUC2 and MUC5AC. MUC5AC and CDX2 were lost in parallel with the depth of invasion of the pT4 stage (28/35 and 29/35 cases), while an advanced Dukes-MAC-like stage was only correlated with CDX2 and VSIG1 loss (20/37 and 30/37 cases). VSIG1 was directly correlated with MUC5AC (p = 0.04) as an indicator of gastric phenotype. MUC2-negative cases showed a propensity towards lymphatic invasion (37/40 cases) and distant metastases, while CDX2-negative cases tended to associate with hematogenous dissemination (30/40 cases). Regarding the molecular network, only 3 of the 19 TFs involved in this carcinogenic cascade (SP1, RELA, NFKB1) interacted with all targeted genes. In GC, VSIG1 can be considered an indicator of gastric phenotype carcinomas, where carcinogenesis is mainly driven by MUC5AC. Although infrequently encountered in GC, CDX2 positivity might indicate a locally advanced stage and risk for vascular invasion, especially in tumors developed against the background of IM. The loss of VSIG1 indicates a risk for lymph node metastases.

Network-Based and Machine-Learning Approaches Identify Diagnostic and Prognostic Models for EMT-Type Gastric Tumors

The microsatellite stable/epithelial-mesenchymal transition (MSS/EMT) subtype of gastric cancer represents a highly aggressive class of tumors associated with low rates of survival and considerably high probabilities of recurrence. In the era of precision medicine, the accurate and prompt diagnosis of tumors of this subtype is of vital importance. In this study, we used Weighted Gene Co-expression Network Analysis (WGCNA) to identify a differentially expressed co-expression module of mRNAs in EMT-type gastric tumors. Using network analysis and linear discriminant analysis, we identified mRNA motifs and microRNA-based models with strong prognostic and diagnostic relevance: three models comprised of (i) the microRNAs miR-199a-5p and miR-141-3p, (ii) EVC/EVC2/GLI3, and (iii) PDE2A/GUCY1A1/GUCY1B1 gene expression profiles distinguish EMT-type tumors from other gastric tumors with high accuracy (Area Under the Receiver Operating Characteristic Curve (AUC) = 0.995, AUC = 0.9742, and AUC = 0.9717; respectively). Additionally, the DMD/ITGA1/CAV1 motif was identified as the top motif with consistent relevance to prognosis (hazard ratio > 3). Molecular functions of the members of the identified models highlight the central roles of MAPK, Hh, and cGMP/cAMP signaling in the pathology of the EMT subtype of gastric cancer and underscore their potential utility in precision therapeutic approaches.

MiR-200/183 family-mediated module biomarker for gastric cancer progression: an AI-assisted bioinformatics method with experimental functional survey

BACKGROUND

Gastric cancer (GC) is a major cancer burden throughout the world with a high mortality rate. The performance of current predictive and prognostic factors is still limited. Integrated analysis is required for accurate cancer progression predictive biomarker and prognostic biomarkers that help to guide therapy.

METHODS

An AI-assisted bioinformatics method that combines transcriptomic data and microRNA regulations were used to identify a key miRNA-mediated network module in GC progression. To reveal the module's function, we performed the gene expression analysis in 20 clinical samples by qRT-PCR, prognosis analysis by multi-variable Cox regression model, progression prediction by support vector machine, and in vitro studies to elaborate the roles in GC cells migration and invasion.

RESULTS

A robust microRNA regulated network module was identified to characterize GC progression, which consisted of seven miR-200/183 family members, five mRNAs and two long non-coding RNAs H19 and CLLU1. Their expression patterns and expression correlation patterns were consistent in public dataset and our cohort. Our findings suggest a two-fold biological potential of the module: GC patients with high-risk score exhibited a poor prognosis (p-value < 0.05) and the model achieved AUCs of 0.90 to predict GC progression in our cohort. In vitro cellular analyses shown that the module could influence the invasion and migration of GC cells.

CONCLUSIONS

Our strategy which combines AI-assisted bioinformatics method with experimental and clinical validation suggested that the miR-200/183 family-mediated network module as a "pluripotent module", which could be potential marker for GC progression.

Regulatory enhancer profiling of mesenchymal-type gastric cancer reveals subtype-specific epigenomic landscapes and targetable vulnerabilities

OBJECTIVE

Gastric cancer (GC) comprises multiple molecular subtypes. Recent studies have highlighted mesenchymal-subtype GC (Mes-GC) as a clinically aggressive subtype with few treatment options. Combining multiple studies, we derived and applied a consensus Mes-GC classifier to define the Mes-GC enhancer landscape revealing disease vulnerabilities.

DESIGN

Transcriptomic profiles of ~1000 primary GCs and cell lines were analysed to derive a consensus Mes-GC classifier. Clinical and genomic associations were performed across >1200 patients with GC. Genome-wide epigenomic profiles (H3K27ac, H3K4me1 and assay for transposase-accessible chromatin with sequencing (ATAC-seq)) of 49 primary GCs and GC cell lines were generated to identify Mes-GC-specific enhancer landscapes. Upstream regulators and downstream targets of Mes-GC enhancers were interrogated using chromatin immunoprecipitation followed by sequencing (ChIP-seq), RNA sequencing, CRISPR/Cas9 editing, functional assays and pharmacological inhibition.

RESULTS

We identified and validated a 993-gene cancer-cell intrinsic Mes-GC classifier applicable to retrospective cohorts or prospective single samples. Multicohort analysis of Mes-GCs confirmed associations with poor patient survival, therapy resistance and few targetable genomic alterations. Analysis of enhancer profiles revealed a distinctive Mes-GC epigenomic landscape, with TEAD1 as a master regulator of Mes-GC enhancers and Mes-GCs exhibiting preferential sensitivity to TEAD1 pharmacological inhibition. Analysis of Mes-GC super-enhancers also highlighted NUAK1 kinase as a downstream target, with synergistic effects observed between NUAK1 inhibition and cisplatin treatment.

CONCLUSION

Our results establish a consensus Mes-GC classifier applicable to multiple transcriptomic scenarios. Mes-GCs exhibit a distinct epigenomic landscape, and TEAD1 inhibition and combinatorial NUAK1 inhibition/cisplatin may represent potential targetable options.

Bioinformatics Prediction and Machine Learning on Gene Expression Data Identifies Novel Gene Candidates in Gastric Cancer

Gastric cancer (GC) is one of the five most common cancers in the world and unfortunately has a high mortality rate. To date, the pathogenesis and disease genes of GC are unclear, so the need for new diagnostic and prognostic strategies for GC is undeniable. Despite particular findings in this regard, a holistic approach encompassing molecular data from different biological levels for GC has been lacking. To translate Big Data into system-level biomarkers, in this study, we integrated three different GC gene expression data with three different biological networks for the first time and captured biologically significant (i.e., reporter) transcripts, hub proteins, transcription factors, and receptor molecules of GC. We analyzed the revealed biomolecules with independent RNA-seq data for their diagnostic and prognostic capabilities. While this holistic approach uncovered biomolecules already associated with GC, it also revealed novel system biomarker candidates for GC. Classification performances of novel candidate biomarkers with machine learning approaches were investigated. With this study, AES, CEBPZ, GRK6, HPGDS, SKIL, and SP3 were identified for the first time as diagnostic and/or prognostic biomarker candidates for GC. Consequently, we have provided valuable data for further experimental and clinical efforts that may be useful for the diagnosis and/or prognosis of GC.

V-set and immunoglobulin domain containing 1 (VSIG1) as an emerging target for epithelial-mesenchymal transition of gastric cancer

V-set and Immunoglobulin domain containing 1 (VSIG1) is a cell–cell adhesion molecule which role in the genesis and evolution of gastric cancer (GC) is not understood. Only three Medline-indexed papers have focused on the role of VSIG1 in GC. The clinicopathological features of 94 GCs were examined in association with immunohistochemical (IHC) patterns of VSIG1, E-cadherin, and β-catenin which were assessed in the tumor core (central) vs. invasive edge. Cases were classified depending on the VSIG1 expression: membrane/membrane in both core and invasive front; null/negative staining in both core and invasive front; and cases with translocational patterns: membrane core/cytoplasmic buds and cytoplasmic core/null buds. Most of the tumors showed null pattern (n = 54). Cases with translocational patterns (n = 20) were GCs with a high lymph node ratio value (≥ 0.26) and advanced Dukes-MAC-like stage. Of the 20 total cases, 9 showed membrane-to-nuclear translocation of β-catenin and loss of E-cadherin, as indicators of epithelial–mesenchymal transition. All cases with membrane/membrane pattern (n = 20) involved the distal stomach. The poorest overall survival was registered in patients with subcellular translocation of VSIG1, compared to those with either membrane/membrane or null patterns (p = 0.002). In GC, VSIG1 acts as an adhesion membrane protein but its membrane-cytoplasmic translocation can be an indicator of epithelial–mesenchymal transition due to cytoplasmic VSIG1-mediated activation of canonical Wnt/β-catenin signaling pathway.

Detection of a novel panel of 24 genes with high frequencies of mutation in gastric cancer based on next-generation sequencing

BACKGROUND

Gastric cancer is a leading cause of cancer-related mortality worldwide. Many somatic mutations have been identified based on next-generation sequencing; they likely play a vital role in cancer treatment selection. However, next-generation sequencing has not been widely used to diagnose and treat gastric cancer in the clinic.

AIM

To test the mutant gene frequency as a guide for molecular diagnosis and personalized therapy in gastric cancer by use of next-generation sequencing.

METHODS

We constructed a panel of 24 mutant genes to detect somatic nucleotide variations and copy number variations based on a next-generation sequencing technique. Our custom panel included high-mutation frequency cancer driver and tumour suppressor genes. Mutated genes were also analyzed using the cBioPortal database. The clinical annotation of important variant mutation sites was evaluated in the ClinVar database. We searched for candidate drugs for targeted therapy and immunotherapy from the OncoKB database.

RESULTS

In our study, the top 16 frequently mutated genes were TP53(58%), ERBB2(28%), BRCA2 (23%), NF1 (19%), PIK3CA (14%), ATR (14%), MSH2 (12%), FBXW7 (12%), BMPR1A (12%), ERBB3 (11%), ATM (9%), FGFR2 (8%), MET (8%), PTEN (6%), CHD4 (6%), and KRAS (5%). TP53 is a commonly mutated gene in gastric cancer and has a similar frequency to that in the cBioPortal database. 33 gastric cancer patients (51.6%) with microsatellite stability and eight patients (12.5%) with microsatellite instability-high were investigated. Enrichment analyses demonstrated that high-frequency mutated genes had transmembrane receptor protein kinase activity. We discovered that BRCA2, PIK3CA, and FGFR2 gene mutations represent promising biomarkers in gastric cancer.

CONCLUSION

We developed a powerful panel of 24 genes with high frequencies of mutation that could detect common somatic mutations. The observed mutations provide potential targets for the clinical treatment of gastric cancer.

Synchronous gallbladder metastasis originating from residual gastric cancer: a case report and the review of literature

BACKGROUND

Gastric cancer rarely metastasizes to the gallbladder. Furthermore, there has never been a case report of simultaneous gallbladder metastasis from residual gastric cancer. Here, we report a case of synchronous gallbladder metastasis originating from a residual gastric cancer.

CASE PRESENTATION

A 67-year-old man underwent a follow-up upper endoscopy 18 months after a partial gastrectomy for gastric cancer; an ulcerative lesion was found in the remnant stomach at the gastrojejunal anastomosis. A biopsy revealed gastric signet-ring cell carcinoma (SRCC). A full-body examination revealed no abnormalities other than gallstones in the gallbladder. With a diagnosis of residual gastric cancer (cT2N0M0 cStage I), the patient underwent open total gastrectomy and cholecystectomy. Macroscopic findings of the resected specimen revealed thickening of the gallbladder wall; however, no obvious neoplastic lesions were found on the mucosal surface of the gallbladder. The pathological findings showed that the SRCC had invaded the submucosa of the gastrojejunostomy site with a high degree of lymphatic invasion and lymph node metastases. SRCCs were also found in the lymphatic vessels of the gallbladder wall. These findings suggested the possibility of gallbladder metastasis through lymphatic vessels. The patient and his family members refused postoperative chemotherapy. Ten months after the operation, the patient experienced respiratory failure due to lymphangitis carcinomatosa and died.

CONCLUSIONS

At present, it is difficult to determine whether resection of the gallbladder contributes to an improved prognosis of gastric cancer patients. However, reports in such cases demonstrate that gallbladder metastasis could be a poor predictor of prognosis for gastric cancer.

Multicellular Modelling of Difficult-to-Treat Gastrointestinal Cancers: Current Possibilities and Challenges

Cancers affecting the gastrointestinal system are highly prevalent and their incidence is still increasing. Among them, gastric and pancreatic cancers have a dismal prognosis (survival of 5–20%) and are defined as difficult-to-treat cancers. This reflects the urge for novel therapeutic targets and aims for personalised therapies. As a prerequisite for identifying targets and test therapeutic interventions, the development of well-established, translational and reliable preclinical research models is instrumental. This review discusses the development, advantages and limitations of both patient-derived organoids (PDO) and patient-derived xenografts (PDX) for gastric and pancreatic ductal adenocarcinoma (PDAC). First and next generation multicellular PDO/PDX models are believed to faithfully generate a patient-specific avatar in a preclinical setting, opening novel therapeutic directions for these difficult-to-treat cancers. Excitingly, future opportunities such as PDO co-cultures with immune or stromal cells, organoid-on-a-chip models and humanised PDXs are the basis of a completely new area, offering close-to-human models. These tools can be exploited to understand cancer heterogeneity, which is indispensable to pave the way towards more tumour-specific therapies and, with that, better survival for patients.

In-Vivo Induced CAR-T Cell for the Potential Breakthrough to Overcome the Barriers of Current CAR-T Cell Therapy

Chimeric antigen receptor T cell (CAR-T cell) therapy has shown impressive success in the treatment of hematological malignancies, but the systemic toxicity and complex manufacturing process of current autologous CAR-T cell therapy hinder its broader applications. Universal CAR-T cells have been developed to simplify the production process through isolation and editing of allogeneic T cells from healthy persons, but the allogeneic CAR-T cells have recently encountered safety concerns, and clinical trials have been halted by the FDA. Thus, there is an urgent need to seek new ways to overcome the barriers of current CAR-T cell therapy. In-vivo CAR-T cells induced by nanocarriers loaded with CAR-genes and gene-editing tools have shown efficiency for regressing leukemia and reducing systemic toxicity in a mouse model. The in-situ programming of autologous T-cells avoids the safety concerns of allogeneic T cells, and the manufacture of nanocarriers can be easily standardized. Therefore, the in-vivo induced CAR-T cells can potentially overcome the abovementioned limitations of current CAR-T cell therapy. Here, we provide a review on CAR structures, gene-editing tools, and gene delivery techniques applied in immunotherapy to help design and develop new in-vivo induced CAR-T cells.

Depiction of Aging-Based Molecular Phenotypes With Diverse Clinical Prognosis and Immunological Features in Gastric Cancer

Objective

Aging acts as a dominating risk factor for human cancers. Herein, we systematically dissected the features of transcriptional aging-relevant genes in gastric cancer from multiple perspectives.

Methods

Based on the transcriptome profiling of prognostic aging-relevant genes, patients with gastric cancer in The Cancer Genome Atlas (TCGA) stomach adenocarcinoma (TCGA-STAD) cohort were clustered with a consensus clustering algorithm. Mutational landscape and chemotherapeutic responses were analyzed and immunological features (immunomodulators, immune checkpoint molecules, cancer immunity cycle, and tumor-infiltrating immune cells) were systematically evaluated across gastric cancer. Weighted gene co-expression network (WGCNA) was conducted for screening aging molecular phenotype-relevant genes, and key genes were identified with Molecular Complex Detection (MCODE) analyses. Expressions of key genes were examined in 20 paired tumors and controls with RT-qPCR and Western blotting. Proliferation and apoptosis were investigated in two gastric cancer cells under MYL9 deficiency.

Results

Three aging-based molecular phenotypes (namely, C1, C2, and C3) were conducted in gastric cancer. Phenotype C1 presented the most prominent survival advantage and highest mutational frequencies. Phenotype C2 indicated low responses to sorafenib and gefitinib, while C3 indicated low responses to vinorelbine and gemcitabine. Additionally, phenotype C2 was characterized by enhanced immune and stromal activation and an inflamed tumor microenvironment. Seven aging molecular phenotype-relevant key genes (ACTA2, CALD1, LMOD1, MYH11, MYL9, MYLK, and TAGLN) were identified, which were specifically upregulated in tumors and in relation to dismal prognosis. Among them, MYL9 deficiency reduced proliferation and enhanced apoptosis in gastric cancer cells.

Conclusion

Collectively, aging-based molecular subtypes may offer more individualized therapy recommendations and prognosis assessment for patients in distinct subtypes.

Identifying novel therapeutic targets in gastric cancer using genome-wide CRISPR-Cas9 screening

Genome-scale CRISPR-Cas9 screening technology is a powerful tool to systematically identify genes essential for cancer cell survival. Herein, TKOv3, a genome-scale CRISPR-Cas9 knock-out library, was screened in the gastric cancer (GC) cells, and relevant validation experiments were performed. We obtained 854 essential genes for the AGS cell line, and 184 were novel essential genes. After knocking down essential genes: SPC25, DHX37, ABCE1, SNRPB, TOP3A, RUVBL1, CIT, TACC3 and MTBP, cell viability and proliferation were significantly decreased. Then, we analysed the detected essential genes at different time points and proved more characteristic genes might appear with the extension of selection. After progressive selection using a series of open datasets, 41 essential genes were identified as potential drug targets. Among them, methyltransferase 1 (METTL1) was over expressed in GC tissues. High METTL1 expression was associated with poor prognosis among 3 of 6 GC cohorts. Furthermore, GC cells growth was significantly inhibited after the down-regulation of METTL1 in vitro and in vivo. Function analysis revealed that METTL1 might play a role in the cell cycle through AKT/STAT3 pathways. In conclusion, compared with existing genome-scale screenings, we obtained 184 novel essential genes. Among them, METTL1 was validated as a potential therapeutic target of GC.

The seen and the unseen: Molecular classification and image based-analysis of gastrointestinal cancers

Gastrointestinal cancers account for 22.5% of cancer related deaths worldwide and represent circa 20% of all cancers. In the last decades, we have witnessed a shift from histology-based to molecular-based classifications using genomic, epigenomic, and transcriptomic data. The molecular based classification revealed new prognostic markers and may aid the therapy selection. Because of the high-costs to perform a molecular classification, in recent years immunohistochemistry-based surrogate classification were developed which permit the stratification of patients, and in parallel multiple groups developed hematoxylin and eosin whole slide image analysis for sub-classifying these entities. Hence, we are witnessing a return to an image-based classification with the purpose to infer hidden information from routine histology images that would permit to detect the patients that respond to specific therapies and would be able to predict their outcome. In this review paper, we will discuss the current histological, molecular, and immunohistochemical classifications of the most common gastrointestinal cancers, gastric adenocarcinoma, and colorectal adenocarcinoma, and will present key aspects for developing a new artificial intelligence aided image-based classification of these malignancies.

Molecular classification of gastric cancer predicts survival in patients undergoing radical gastrectomy based on project HOPE

BACKGROUND

Gastric cancer (GC) has been classified based on molecular profiling like The Cancer Genome Atlas (TCGA) and Asian Cancer Research Group (ACRG), and attempts have been made to establish therapeutic strategies based on these classifications. However, it is difficult to predict the survival according to these classifications especially in radically resected patients. We aimed to establish a new molecular classification of GC which predicts the survival in patients undergoing radical gastrectomy.

METHODS

The present study included 499 Japanese patients with advanced GC undergoing radical (R0/R1) gastrectomy. Whole-exome sequencing, panel sequencing, and gene expression profiling were conducted (High-tech Omics-based Patient Evaluation [Project HOPE]). We classified patients according to TCGA and ACRG subtypes, and evaluated the clinicopathologic features and survival. Then, we attempted to classify patients according to their molecular profiles associated with biological features and survival (HOPE classification).

RESULTS

TCGA and ACRG classifications failed to predict the survival. In HOPE classification, hypermutated (HMT) tumors were selected first as a distinctive feature, and T-cell-inflamed expression signature-high (TCI) tumors were then extracted. Finally, the remaining tumors were divided by the epithelial-mesenchymal transition (EMT) expression signature. HOPE classification significantly predicted the disease-specific and overall survival (p < 0.001 and 0.020, respectively). HMT + TCI showed the best survival, while EMT-high showed the worst survival. The HOPE classification was successfully validated in the TCGA cohort.

CONCLUSIONS

We established a new molecular classification of gastric cancer that predicts the survival in patients undergoing radical surgery.

Metabolomics study identified bile acids as potential biomarkers for gastric cancer: A case control study

Gastric cancer (GC) is a common lethal malignancy worldwide. Gastroscopy is an effective screening technique for decreasing mortality. However, there are still limited useful non-invasive markers for early detection of GC. Bile acids are important molecules for the modulation of energy metabolism. With an in-depth targeted method for accurate quantitation of 80 bile acids (BAs), we aimed to find potential biomarkers for the early screening of GC. A cohort with 280 participants was enrolled, including 113 GC, 22 benign gastric lesions (BGL) and 145 healthy controls. Potential markers were identified using a random forest machine algorithm in the discovery cohort (n=180), then validated in an internal validation cohort (n=78) and a group with 22 BGL. The results represented significant alterations in the circulating BA pool between GC and the controls. BAs also exhibited significant correlations with various clinical traits. Then, we developed a diagnostic panel that comprised six BAs or ratios for GC detection. The panel showed high accuracy for the diagnosis of GC with AUC of 1 (95%CI: 1.00-1.00) and 0.98 (95%CI: 0.93-1.00) in the discovery and validation cohort, respectively. This 6-BAs panel was also able to identify early GC with AUC of 1 (95%CI: 0.999-1.00) and 0.94 (95%CI: 0.83-1.00) in the discovery and validation cohort, respectively. Meanwhile, this panel achieved a good differential diagnosis between GC and BGL and the AUC was 0.873 (95%CI: 0.812-0.934). The alternations of serum bile acids are characteristic metabolic features of GC. Bile acids could be promising biomarkers for the early diagnosis of GC.

Development and Validation of a Novel Prognosis Prediction Model for Patients With Stomach Adenocarcinoma

Background: Stomach adenocarcinoma (STAD) is a significant global health problem. It is urgent to identify reliable predictors and establish a potential prognostic model.

Methods: RNA-sequencing expression data of patients with STAD were downloaded from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database. Gene expression profiling and survival analysis were performed to investigate differentially expressed genes (DEGs) with significant clinical prognosis value. Overall survival (OS) analysis and univariable and multivariable Cox regression analyses were performed to establish the prognostic model. Protein–protein interaction (PPI) network, functional enrichment analysis, and differential expression investigation were also performed to further explore the potential mechanism of the prognostic genes in STAD. Finally, nomogram establishment was undertaken by performing multivariate Cox regression analysis, and calibration plots were generated to validate the nomogram.

Results: A total of 229 overlapping DEGs were identified. Following Kaplan–Meier survival analysis and univariate and multivariate Cox regression analysis, 11 genes significantly associated with prognosis were screened and five of these genes, including COL10A1, MFAP2, CTHRC1, P4HA3, and FAP, were used to establish the risk model. The results showed that patients with high-risk scores have a poor prognosis, compared with those with low-risk scores (p = 0.0025 for the training dataset and p = 0.045 for the validation dataset). Subsequently, a nomogram (including TNM stage, age, gender, histologic grade, and risk score) was created. In addition, differential expression and immunohistochemistry stain of the five core genes in STAD and normal tissues were verified.

Conclusion: We develop a prognostic-related model based on five core genes, which may serve as an independent risk factor for survival prediction in patients with STAD.

Long non-coding RNAs: Biogenesis, functions, and clinical significance in gastric cancer

Gastric cancer (GC) is one of the most prevalent malignant tumor types and the third leading cause of cancer-related death worldwide. Its morbidity and mortality are very high due to a lack of understanding about its pathogenesis and the slow development of novel therapeutic strategies. Long non-coding RNAs (lncRNAs) are a class of non-coding RNAs with a length of more than 200 nt. They play crucial roles in a wide spectrum of physiological and pathological processes by regulating the expression of genes involved in proliferation, differentiation, apoptosis, cell cycle, invasion, metastasis, DNA damage, and carcinogenesis. The aberrant expression of lncRNAs has been found in various cancer types. A growing amount of evidence demonstrates that lncRNAs are involved in many aspects of GC pathogenesis, including its occurrence, metastasis, and recurrence, indicating their potential role as novel biomarkers in the diagnosis, prognosis, and therapeutic targets of GC. This review systematically summarizes the biogenesis, biological properties, and functions of lncRNAs and highlights their critical role and clinical significance in GC. This information may contribute to the development of better diagnostics and treatments for GC.

Histological and mutational profile of diffuse gastric cancer: current knowledge and future challenges

Gastric cancer (GC) pathogenesis is complex and heterogeneous, reflecting morphological, molecular and genetic diversity. Diffuse gastric cancer (DGC) and intestinal gastric cancer (IGC) are the major histological types. GC may be sporadic or hereditary; sporadic GC is related to environmental and genetic low-risk factors and hereditary GC is caused by inherited high-risk mutations, so far identified only for the diffuse histotype. DGC phenotypic heterogeneity challenges the current understanding of molecular mechanisms underlying carcinogenesis. The definition of a DGC-specific mutational profile remains controversial, possibly reflecting the heterogeneity of DGC-related histological subtypes [signet-ring cell carcinoma (SRCC) and poorly cohesive carcinoma not otherwise specified (PCC-NOS)]. Indeed, DGC and DGC-related subtypes may present specific mutational profiles underlying the particularly aggressive behaviour and dismal prognosis of DGC vs IGC and PCC-NOS vs SRCC. In this systematic review, we revised the histological presentations, molecular classifications and approved therapies for gastric cancer, with a focus on DGC. We then analysed results from the most relevant studies, reporting mutational analysis data specifying mutational frequencies, and their relationship with DGC and IGC histological types, and with specific DGC subtypes (SRCC and PCC-NOS). We aimed at identifying histology-associated mutational profiles with an emphasis in DGC and its subtypes (DGC vs IGC; sporadic vs hereditary DGC; and SRCC vs PCC-NOS). We further used these mutational profiles to identify the most commonly affected molecular pathways and biological functions, and explored the clinical trials directed specifically to patients with DGC. This systematic analysis is expected to expose a DGC-specific molecular profile and shed light into potential targets for therapeutic intervention, which are currently missing.

MiR-148a-3p targets CEMIP to suppress the genesis of gastric cancer cells

BACKGROUND

Gastric cancer is the sixth common malignancy worldwide. Dysregulation of Cell Migration Inducing Hyaluronidase 1 (CEMIP) gene and microRNA-148a -3p (miR-148a-3p) expressions has been found in gastric cancer genesis. However, the underlying molecular mechanism in gastric cancer needs further investigation.

METHODS

The expression of gastric cancer tissues' and cells' CEMIP and miR-148a-3p were examined by RT-qPCR. The interaction between miR-148a-3p and CEMIP was verified by luciferase activity detection. Cell viability, proliferation, adhesion, and apoptosis in gastric cancer GTL-16 and AGS cells were analyzed by CCK8, BrdU, cell adhesion, and FITC assay.

RESULTS

CEMIP expression was significantly elevated, but the miR-148a-3p level was downregulated in gastric cancer tissues and cell lines. Overexpression of CEMIP accelerated cell viability, proliferation, and adhesion, but attenuated cell apoptosis of gastric cancer cells. In addition, upregulation of miR-148a-3p repressed the development of gastric cancer in vitro. Moreover, miR-148a-3p suppressed gastric cancer tumorigenesis by inhibiting the expression of CEMIP.

CONCLUSION

The study clarified that miR-148a-3p suppressed gastric cancer tumorigenesis by inhibiting CEMIP, which may be effective targets for the clinical treatment of gastric cancer.

PD-1 inhibition in patient derived tissue cultures of human gastric and gastroesophageal adenocarcinoma

Emerging immunotherapies quest for better patient stratification in cancer treatment decisions. Moderate response rates of PD-1 inhibition in gastric and esophagogastric junction cancers urge for meaningful human model systems that allow for investigating immune responses ex vivo. Here, the standardized patient-derived tissue culture (PDTC) model was applied to investigate tumor response to the PD-1 inhibitor Nivolumab and the CD3/CD28 t-lymphocyte activator ImmunoCult^TM. Resident t-lymphocytes, tumor proliferation and apoptosis, as well as bulk gene expression data were analyzed after 72 h of PD-1 inhibition either as monotherapy or combined with Oxaliplatin or ImmunoCult^TM. Individual responses to PD-1 inhibition were found ex vivo and combination with chemotherapy or t-lymphocyte activation led to enhanced antitumoral effects in PDTCs. T-lymphocyte activation as well as the addition of pre-cultured peripheral blood mononuclear cells improved PDTC for studying t-lymphocyte and tumor cell communication. These data support the potential of PDTC to investigate immunotherapy ex vivo in gastric and esophagogastric junction cancer.

Deep Learning for Automatic Subclassification of Gastric Carcinoma Using Whole-Slide Histopathology Images

Histomorphologic types of gastric cancer (GC) have significant prognostic values that should be considered during treatment planning. Because the thorough quantitative review of a tissue slide is a laborious task for pathologists, deep learning (DL) can be a useful tool to support pathologic workflow. In the present study, a fully automated approach was applied to distinguish differentiated/undifferentiated and non-mucinous/mucinous tumor types in GC tissue whole-slide images from The Cancer Genome Atlas (TCGA) stomach adenocarcinoma dataset (TCGA-STAD). By classifying small patches of tissue images into differentiated/undifferentiated and non-mucinous/mucinous tumor tissues, the relative proportion of GC tissue subtypes can be easily quantified. Furthermore, the distribution of different tissue subtypes can be clearly visualized. The patch-level areas under the curves for the receiver operating characteristic curves for the differentiated/undifferentiated and non-mucinous/mucinous classifiers were 0.932 and 0.979, respectively. We also validated the classifiers on our own GC datasets and confirmed that the generalizability of the classifiers is excellent. The results indicate that the DL-based tissue classifier could be a useful tool for the quantitative analysis of cancer tissue slides. By combining DL-based classifiers for various molecular and morphologic variations in tissue slides, the heterogeneity of tumor tissues can be unveiled more efficiently.

Immune-Related Nine-MicroRNA Signature for Predicting the Prognosis of Gastric Cancer

Recent findings have demonstrated the superiority and utility of microRNAs (miRNAs) as new biomarkers for cancer diagnosis, therapy, and prognosis. In this study, to explore the prognostic value of immune-related miRNAs in gastric cancer (GC), we analyzed the miRNA-expression profiles of 389 patients with GC, using data deposited in The Cancer Genome Atlas database. Using a forward- and backward-variable selection and multivariate Cox regression analyses model, we identified a nine-miRNA signature (the “ImmiRSig,” consisting of miR-125b-5p, miR-99a-3p, miR-145-3p, miR-328-3p, miR-133a-5p, miR-1292-5p, miR-675-3p, miR-92b-5p, and miR-942-3p) in the training cohort that enabled the division of patients into high- and low-risk groups with significantly different survival rates. The ImmiRSig was successfully validated with an independent test cohort of 193 GC patients. Univariate and multivariate Cox regression analyses indicated that the ImmiRSig would serve as an independent prognostic factor after adjusting for other clinical covariates. Pending further prospective validation, the identified ImmiRSig appears to have significant clinical importance in terms of improving outcome predictions and guiding personalized treatment for patients with GC. Finally, significant associations between the ImmiRSig and the half-maximal inhibitory concentrations of chemotherapeutic agents were observed, suggesting that ImmiRSig may predict the clinical efficacy of chemotherapy.

Clinical Significance of Composition Changes in T-cell Subpopulations After Chemotherapy in Patients With Gastric Cancer

BACKGROUND/AIM

New therapeutic agents and prognostic biomarkers for gastric cancer are needed. We analyzed the composition of peripheral blood T-cell subpopulations in response to chemotherapy in patients with gastric cancer.

PATIENTS AND METHODS

Peripheral blood samples were collected from patients diagnosed with gastric cancer before and after chemotherapy (FOLFOX; oxaliplatin, 5-fluorouracil, and leucovorin). Peripheral blood mononuclear cells were isolated. Patients were divided into responder (n=5) and non-responder groups (n=2) based on their chemotherapy outcomes.

RESULTS

Non-responders showed lower numbers of CD4+/total cells and CD8+/total cells after chemotherapy compared to the responder group, but the difference was not significant (p=0.905, p=0.095). Naïve T, central memory T, effector memory T and effector T-cell counts differed in both groups after chemotherapy.

CONCLUSION

Changes in peripheral T-cell subpopulations after chemotherapy were confirmed in patients with gastric cancer, which may be a prognostic predictor and development of therapeutic agents.