Molecular analysis of gastric cancer identifies subtypes associated with distinct clinical outcomes

Neoadjuvant and/or adjuvant chemotherapy for gastric cancer patients with microsatellite instability or deficient mismatch repair: a systematic review and meta-analysis study protocol

INTRODUCTION

Whether gastric cancer (GC) patients with deficient mismatch repair or microsatellite instability-high (dMMR/MSI-H) benefit from perioperative (neoadjuvant and/or adjuvant) chemotherapy is controversial. This protocol delineates the planned scope and methods for a systematic review and meta-analysis that aims to compare the efficacy of perioperative chemotherapy with surgery alone in resectable dMMR/MSI-H GC patients.

METHODS AND ANALYSIS

This study protocol is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols-P guideline. PubMed, Embase, Cochrane (CENTRAL), and the Web of Science databases will be searched, supplemented by a secondary screening of relevant records. Both randomised controlled trials and non-randomised studies will be included in this study. The primary and secondary outcomes under scrutiny will be overall survival, disease-free survival and progression-free survival. Two reviewers will independently screen studies, extract data and assess the risk of bias. We will analyse different treatment settings (eg, neoadjuvant or adjuvant or combined as perioperative chemotherapies) separately and conduct sensitivity analyses.

ETHICS AND DISSEMINATION

No ethics approval is required for this systematic review and meta-analysis, as no individual patient data will be collected. The findings of our study will be published in a peer-reviewed journal.

PROSPERO REGISTRATION NUMBER

CRD42023494276.

Integrated clinical and genomic models using machine-learning methods to predict the efficacy of paclitaxel-based chemotherapy in patients with advanced gastric cancer

BACKGROUND

Paclitaxel is commonly used as a second-line therapy for advanced gastric cancer (AGC). The decision to proceed with second-line chemotherapy and select an appropriate regimen is critical for vulnerable patients with AGC progressing after first-line chemotherapy. However, no predictive biomarkers exist to identify patients with AGC who would benefit from paclitaxel-based chemotherapy.

METHODS

This study included 288 patients with AGC receiving second-line paclitaxel-based chemotherapy between 2017 and 2022 as part of the K-MASTER project, a nationwide government-funded precision medicine initiative. The data included clinical (age [young-onset vs. others], sex, histology [intestinal vs. diffuse type], prior trastuzumab use, duration of first-line chemotherapy), and genomic factors (pathogenic or likely pathogenic variants). Data were randomly divided into training and validation sets (0.8:0.2). Four machine learning (ML) methods, namely random forest (RF), logistic regression (LR), artificial neural network (ANN), and ANN with genetic embedding (ANN with GE), were used to develop the prediction model and validated in the validation sets.

RESULTS

The median patient age was 64 years (range 25-91), and 65.6% of those were male. A total of 288 patients were divided into the training (n = 230) and validation (n = 58) sets. No significant differences existed in baseline characteristics between the training and validation sets. In the training set, the areas under the ROC curves (AUROC) for predicting better progression-free survival (PFS) with paclitaxel-based chemotherapy were 0.499, 0.679, 0.618, and 0.732 in the RF, LR, ANN, and ANN with GE models, respectively. The ANN with the GE model that achieved the highest AUROC recorded accuracy, sensitivity, specificity, and F1-score performance of 0.458, 0.912, 0.724, and 0.579, respectively. In the validation set, the ANN with GE model predicted that paclitaxel-sensitive patients had significantly longer PFS (median PFS 7.59 vs. 2.07 months, P = 0.020) and overall survival (OS) (median OS 14.70 vs. 7.50 months, P = 0.008). The LR model predicted that paclitaxel-sensitive patients showed a trend for longer PFS (median PFS 6.48 vs. 2.33 months, P = 0.078) and OS (median OS 12.20 vs. 8.61 months, P = 0.099).

CONCLUSIONS

These ML models, integrated with clinical and genomic factors, offer the possibility to help identify patients with AGC who may benefit from paclitaxel chemotherapy.

Success rate of current human-derived gastric cancer organoids establishment and influencing factors: A systematic review and meta-analysis

BACKGROUND

Human-derived gastric cancer organoids (GCOs) are widely used in gastric cancer research; however, the culture success rate is generally low.

AIM

To explore the potential influencing factors, and the literature on successful culture rates of GCOs was reviewed using meta-analysis.

METHODS

PubMed, Web of Science, and EMBASE were searched for studies. Two trained researchers selected the studies and extracted data. STATA 17.0 software was used for meta-analysis of the incidence of each outcome event. The adjusted Methodological Index for Non-Randomized Studies scale was used to assess the quality of the included studies. Funnel plots and Egger's test were used to detect publication bias. Subgroup analyses were conducted for sex, tissue source, histological classification, and the pathological tumor-node-metastasis (pTNM) cancer staging system.

RESULTS

Eight studies with a pooled success rate of 66.6% were included. GCOs derived from women and men had success rates of 67% and 46.7%, respectively. GCOs from surgery or biopsy/endoscopic submucosal dissection showed success rates of 70.9% and 53.7%, respectively. GCOs of poorly-differentiated, moderately-differentiated and signet-ring cell cancer showed success rates of 64.6%, 31%, and 32.7%, respectively. GCOs with pTNM stages I-II and III-IV showed success rates of 38.3% and 65.2%, respectively. Y-27632 and non-Y-27632 use showed success rates of 58.2% and 70%, respectively. GCOs generated with collagenase were more successful than those constructed with Liberase TH and TrypLE (72.1% vs 71%, respectively). EDTA digestion showed a 50% lower success rate than other methods (P = 0.04).

CONCLUSION

GCO establishment rate is low and varies by sex, tissue source, histological type, and pTNM stage. Omitting Y-27632, and using Liberase TH, TrypLE, or collagenase yields greater success than EDTA.

FAM120A deficiency improves resistance to cisplatin in gastric cancer by promoting ferroptosis

The occurrence of chemoresistance is an inescapable obstacle affecting the clinical efficacy of cisplatin in gastric cancer (GC). Exploring the regulatory mechanism of cisplatin resistance will help to provide potential effective targets for improving the prognosis of gastric cancer patients. Here, we find that FAM120A is upregulated in GC tissues and higher in cisplatin-resistant GC tissues, and its high expression is positively correlated with the poor outcome of GC patients. Functional studies indicate that FAM120A confers chemoresistance to GC cells by inhibiting ferroptosis. Mechanically, METTL3-induced m6A modification and YTHDC1-induced stability of FAM120A mRNA enhance FAM120A expression. FAM120A inhibits ferroptosis by binding SLC7A11 mRNA and enhancing its stability. FAM120A deficiency enhances cisplatin sensitivity by promoting ferroptosis in vivo. These results reveal the function of FAM120A in chemotherapy tolerance and targeting FAM120A is an effective strategy to alleviate cisplatin resistance in GC.

A retrospective study: exploring the optimal patient population for adjuvant chemotherapy after D2 gastrectomy

BACKGROUND

Adjuvant chemotherapy (CT) constitutes the primary approach for treating resectable advanced gastric cancer (GC). However, the effectiveness of postoperative CT can differ across various patient groups. This retrospective study aimed to examine how variances in clinical and pathologic factors affect postoperative CT.

METHODS

This study enrolled 2060 patients with GC who underwent curative gastrectomy at Zhejiang Cancer Hospital between January 2008 and December 2017, with 1277 receiving postoperative CT. This study used Kaplan-Meier to determine the effect of clinical and pathology factors on CT benefits. In addition, univariate and multivariate Cox regression analyses were used to identify independent prognosis risk factors.

RESULTS

Both univariate and multivariate analyses demonstrated that the absence of postoperative CT is an independent factor associated with a poor prognosis in patients with GC. The Kaplan-Meier univariate analysis revealed that specific subgroups, including males, those with a normal body mass index (BMI), the elderly, individuals with gastric adenocarcinoma, cases of nerve invasion by the tumor, vascular invasion by the tumor, tumor size ≥ 5 cm, and Tumor, Node, Metastasis (TNM) stage III, exhibited improved treatment outcomes with the administration of postoperative CT. The creation of nomograms using Cox regression and the rms package holds significant clinical relevance.

CONCLUSION

Postoperative CT is advantageous for prolonging the survival of advanced patients undergoing D2 gastrectomy, particularly in male patients, the elderly, individuals with a normal BMI score, those diagnosed with gastric adenocarcinoma, cases, in which the tumor invades nerves or blood vessels, patients with a tumor size of ≥5 cm, and those with a TNM stage of III, as it results in improved treatment outcomes within these subgroups.

Precision Oncology in Gastrointestinal and Colorectal Cancer Surgery

Precision medicine is used to treat gastrointestinal malignancies including esophageal, gastric, small bowel, colorectal, and pancreatic cancers. Cutting-edge assays to detect and treat these cancers are active areas of research and will soon become standard of care. Colorectal cancer is a prime example of precision oncology as disease site is no longer the final determinate of treatment. Here, the authors describe how leveraging an understanding of tumor biology translates to individualized patient care using evidence-based practices.

A radiomics signature derived from CT imaging to predict MSI status and immunotherapy outcomes in gastric cancer: a multi-cohort study

BACKGROUND

Accurate microsatellite instability (MSI) testing is essential for identifying gastric cancer (GC) patients eligible for immunotherapy. We aimed to develop and validate a CT-based radiomics signature to predict MSI and immunotherapy outcomes in GC.

METHODS

This retrospective multicohort study included a total of 457 GC patients from two independent medical centers in China and The Cancer Imaging Archive (TCIA) databases. The primary cohort (n = 201, center 1, 2017-2022), was used for signature development via Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression analysis. Two independent immunotherapy cohorts, one from center 1 (n = 184, 2018-2021) and another from center 2 (n = 43, 2020-2021), were utilized to assess the signature's association with immunotherapy response and survival. Diagnostic efficiency was evaluated using the area under the receiver operating characteristic curve (AUC), and survival outcomes were analyzed via the Kaplan-Meier method. The TCIA cohort (n = 29) was included to evaluate the immune infiltration landscape of the radiomics signature subgroups using both CT images and mRNA sequencing data.

RESULTS

Nine radiomics features were identified for signature development, exhibiting excellent discriminative performance in both the training (AUC: 0.851, 95%CI: 0.782, 0.919) and validation cohorts (AUC: 0.816, 95%CI: 0.706, 0.926). The radscore, calculated using the signature, demonstrated strong predictive abilities for objective response in immunotherapy cohorts (AUC: 0.734, 95%CI: 0.662, 0.806; AUC: 0.724, 95%CI: 0.572, 0.877). Additionally, the radscore showed a significant association with PFS and OS, with GC patients with a low radscore experiencing a significant survival benefit from immunotherapy. Immune infiltration analysis revealed significantly higher levels of CD8 + T cells, activated CD4 + B cells, and TNFRSF18 expression in the low radscore group, while the high radscore group exhibited higher levels of T cells regulatory and HHLA2 expression.

CONCLUSION

This study developed a robust radiomics signature with the potential to serve as a non-invasive biomarker for GC's MSI status and immunotherapy response, demonstrating notable links to post-immunotherapy PFS and OS. Additionally, distinct immune profiles were observed between low and high radscore groups, highlighting their potential clinical implications.

E-cadherin loss drives diffuse-type gastric tumorigenesis via EZH2-mediated reprogramming

Diffuse-type gastric adenocarcinoma (DGAC) is a deadly cancer often diagnosed late and resistant to treatment. While hereditary DGAC is linked to CDH1 mutations, the role of CDH1/E-cadherin inactivation in sporadic DGAC tumorigenesis remains elusive. We discovered CDH1 inactivation in a subset of DGAC patient tumors. Analyzing single-cell transcriptomes in malignant ascites, we identified two DGAC subtypes: DGAC1 (CDH1 loss) and DGAC2 (lacking immune response). DGAC1 displayed distinct molecular signatures, activated DGAC-related pathways, and an abundance of exhausted T cells in ascites. Genetically engineered murine gastric organoids showed that Cdh1 knock-out (KO), KrasG12D, Trp53 KO (EKP) accelerates tumorigenesis with immune evasion compared with KrasG12D, Trp53 KO (KP). We also identified EZH2 as a key mediator promoting CDH1 loss-associated DGAC tumorigenesis. These findings highlight DGAC's molecular diversity and potential for personalized treatment in CDH1-inactivated patients.

Complete and rapid response with the combination of immunotherapy and chemotherapy in a young adult patient with microsatellite instability-high metastatic gastric cancer

ABSTRACT

Gastric cancer (GC) is an aggressive malignancy; 5.0% of GC patients are diagnosed before the age of 40. These patients are more aggressive and advanced stage at the diagnosis. Microsatellite instability-high (MSI-H) status is usually seen in relatively older patients. We report a 31-year-old male patient presenting with an intra-abdominal mass and spleen lesions that radiologically mimic a gastrointestinal stromal tumor (GIST). He underwent surgery. Histological examination revealed poorly differentiated adenocarcinoma starting from the deep gastric mucosa. After surgery, rapidly progressive disease was observed. The patient with MSI-H and combined positive score (CPS) of 65% was treated with a combination of immunotherapy and chemotherapy; complete response was observed in approximately 3 months. This is a very rare GC case in young adult age with MSI-H status and responds to treatment in a short time. Predictive markers for immunotherapy efficacy are still being discussed; this case supports the predictive role of high CPS score and MSI-H phenotype in demonstrating treatment efficacy.

Immune Landscape of Epstein-Barr Virus-Associated Gastric Cancer: Analysis From a Western Academic Institution

INTRODUCTION

Epstein-Barr virus-associated gastric cancer (EBVaGC) may be a meaningful biomarker for potential benefit from immunotherapy. Further investigation is needed to characterize the immune landscape of EBVaGC. We assessed our institutional frequency of surgically treated EBVaGC and analyzed the immunologic biomarker profile and tumor-infiltrating lymphocyte (TIL) phenotypes of a series of EBVaGC compared to non-EBVaGC cases.

METHODS

Available tissue samples from all patients with biopsy-confirmed gastric adenocarcinoma who underwent resection with curative intent from 2012 to 2020 at our institution were collected. In situ hybridization was used to assess EBV status; multiplex immunohistochemistry was performed to assess mismatch repair status, Programmed Death-Ligand 1 (PD-L1) expression, and phenotypic characterization of TILs.

RESULTS

Sixty-eight samples were included in this study. EBVaGC was present in 3/68 (4%) patients. Among all patients, 27/68 (40%) had positive PD-L1 expression; two of three (67%) EBVaGC patients exhibited positive PD-L1 expression. Compared to non-EBVaGC, EBV-positive tumors showed 5-fold to 10-fold higher density of TILs in both tumor and stroma and substantially elevated CD8+ T cell to Tregulatory cell ratio. The memory subtypes of CD8+ and CD4+ T cells were upregulated in EBVaGC tumors and stromal tissue compared to non-EBVaGC.

CONCLUSIONS

The incidence of surgically resected EBVaGC at our center was 4%. EBVaGC tumors harbor elevated levels of TILs, including memory subtypes, within both tumor and tumor-related stroma. Robust TIL presence and upregulated PD-L1 positivity in EBVaGC may portend promising responses to immunotherapy agents. Further investigation into routine EBV testing and TIL phenotype of patients with gastric cancer to predict response to immunotherapy may be warranted.

Implementing an integrated molecular classification for gastric cancer from endoscopic biopsies using on-slide tests

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

Targeting HER2 in Gastroesophageal Adenocarcinoma: Molecular Features and Updates in Clinical Practice

Gastroesophageal adenocarcinoma (GEA) is one of the principal causes of death related to cancer globally. Human epidermal growth factor receptor 2 (HER2) is a tyrosine kinase receptor which is found to be overexpressed or amplified in approximately 20% of GEA cases. In GEA, the identification of HER2-positive status is crucial to activate a specific anti-HER2 targeted therapy. The landmark ToGA trial demonstrated the superiority of adding trastuzumab to platinum-based chemotherapy, becoming the first-line standard of treatment. However, unlike breast cancer, the efficacy of other anti-HER2 drugs, such as lapatinib, pertuzumab, and T-DM1, has failed to improve outcomes in advanced and locally advanced resectable GEA. Recently, the combination of trastuzumab with pembrolizumab, along with chemotherapy, and the development of trastuzumab deruxtecan, with its specific bystander activity, demonstrated improved outcomes, renewing attention in the treatment of this disease. This review will summarise historical and emerging therapies for the treatment of HER2-positive GEA, with a section dedicated to the HER2 molecular pathway and the use of novel blood biomarkers, such as circulating tumour DNA and circulating tumour cells, which may be helpful in the future to guide treatment decisions.

Feature-specific quantile normalization and feature-specific mean-variance normalization deliver robust bi-directional classification and feature selection performance between microarray and RNAseq data

BACKGROUND

Cross-platform normalization seeks to minimize technological bias between microarray and RNAseq whole-transcriptome data. Incorporating multiple gene expression platforms permits external validation of experimental findings, and augments training sets for machine learning models. Here, we compare the performance of Feature Specific Quantile Normalization (FSQN) to a previously used but unvalidated and uncharacterized method we label as Feature Specific Mean Variance Normalization (FSMVN). We evaluate the performance of these methods for bidirectional normalization in the context of nested feature selection.

RESULTS

FSQN and FSMVN provided clinically equivalent bidirectional model performance with and without feature selection for colon CMS and breast PAM50 classification. Using principal component analysis, we determine that these methods eliminate batch effects related to technological platforms. Without feature selection, no statistical difference was identified between the performance of FSQN and FSMVN of cross-platform data compared to within-platform distributions. Under optimal feature selection conditions, balanced accuracy was FSQN and FSMVN were statistically equivalent to the within-platform distribution performance in multivariable linear regression analysis. FSQN and FSMVN also provided similar performance to within-platform distributions as the number of selected genes used to create models decreases.

CONCLUSIONS

In the context of generating supervised machine learning classifiers for molecular subtypes, FSQN and FSMVN are equally effective. Under optimal modeling conditions, FSQN and FSMVN provide equivalent model accuracy performance on cross-platform normalization data compared to within-platform data. Using cross-platform data should still be approached with caution as subtle performance differences may exist depending on the classification problem, training, and testing distributions.

Liquid biopsy for gastric cancer: Techniques, applications, and future directions

After the study of circulating tumor cells in blood through liquid biopsy (LB), this technique has evolved to encompass the analysis of multiple materials originating from the tumor, such as nucleic acids, extracellular vesicles, tumor-educated platelets, and other metabolites. Additionally, research has extended to include the examination of samples other than blood or plasma, such as saliva, gastric juice, urine, or stool. LB techniques are diverse, intricate, and variable. They must be highly sensitive, and pre-analytical, patient, and tumor-related factors significantly influence the detection threshold, diagnostic method selection, and potential results. Consequently, the implementation of LB in clinical practice still faces several challenges. The potential applications of LB range from early cancer detection to guiding targeted therapy or immunotherapy in both early and advanced cancer cases, monitoring treatment response, early identification of relapses, or assessing patient risk. On the other hand, gastric cancer (GC) is a disease often diagnosed at advanced stages. Despite recent advances in molecular understanding, the currently available treatment options have not substantially improved the prognosis for many of these patients. The application of LB in GC could be highly valuable as a non-invasive method for early diagnosis and for enhancing the management and outcomes of these patients. In this comprehensive review, from a pathologist's perspective, we provide an overview of the main options available in LB, delve into the fundamental principles of the most studied techniques, explore the potential utility of LB application in the context of GC, and address the obstacles that need to be overcome in the future to make this innovative technique a game-changer in cancer diagnosis and treatment within clinical practice.

The viral etiology of EBV-associated gastric cancers contributes to their unique pathology, clinical outcomes, treatment responses and immune landscape

Epstein-Barr virus (EBV) is a pathogen known to cause a number of malignancies, often taking years for them to develop after primary infection. EBV-associated gastric cancer (EBVaGC) is one such malignancy, and is an immunologically, molecularly and pathologically distinct entity from EBV-negative gastric cancer (EBVnGC). In comparison with EBVnGCs, EBVaGCs overexpress a number of immune regulatory genes to help form an immunosuppressive tumor microenvironment (TME), have improved prognosis, and overall have an "immune-hot" phenotype. This review provides an overview of the histopathology, clinical features and clinical outcomes of EBVaGCs. We also summarize the differences between the TMEs of EBVaGCs and EBVnGCs, which includes significant differences in cell composition and immune infiltration. A list of available EBVaGC and EBVnGC gene expression datasets and computational tools are also provided within this review. Finally, an overview is provided of the various chemo- and immuno-therapeutics available in treating gastric cancers (GCs), with a focus on EBVaGCs.

Integrated analysis of disulfidptosis-related immune genes signature to boost the efficacy of prognostic prediction in gastric cancer

BACKGROUND

Gastric cancer (GC) remains a malignant tumor with high morbidity and mortality, accounting for approximately 1,080,000 diagnosed cases and 770,000 deaths worldwide annually. Disulfidptosis, characterized by the stress-induced abnormal accumulation of disulfide, is a recently identified form of programmed cell death. Substantial studies have demonstrated the significant influence of immune clearance on tumor progression. Therefore, we aimed to explore the intrinsic correlations between disulfidptosis and immune-related genes (IRGs) in GC, as well as the potential value of disulfidptosis-related immune genes (DRIGs) as biomarkers.

METHODS

This study incorporated the single-cell RNA sequencing (scRNA-seq) dataset GSE183904 and transcriptome RNA sequencing of GC from the TCGA database. Disulfidptosis-related genes (DRGs) and IRGs were derived from the representative literature on both cell disulfidptosis and immunity. The expression and distribution of DRGs were investigated at the single-cell level in different GC cell types. Pearson correlation analysis was used to identify the IRGs closely related to disulfidptosis. The prognostic signature of DRIGs was established using Cox and LASSO analyses. We then analyzed and evaluated the differences in long-term prognosis, Gene Set Enrichment Analysis (GSEA), immune infiltration, mutation profile, CD274 expression, and response to chemotherapeutic drugs between the two groups. A tissue array containing 63 paired GC specimens was used to verify the expression of 4 DRIGs and disulfidptosis regulator SLC7A11 through immunohistochemistry staining.

RESULTS

The scRNA-seq analysis found that SLC7A11, SLC3A2, RPN1 and NCKAP1 were enriched in specific cell types and closely related to immune infiltration. Four DIRGs (GLA, HIF-1α, VPS35 and CDC37) were successfully identified to establish a signature to potently predict the survival time of GC patients. Patients with high risk scores generally experienced worse prognoses and exhibited greater resistant to classical chemotherapy drugs. Furthermore, the expression of GLA, HIF-1α, VPS35, CDC37 and SLC7A11 were elevated in GC tissues. A high expression of GLA, HIF-1α, VPS35 or CDC37 was associated with more advanced clinical stage of GC and increased SLC7A11 expression.

CONCLUSION

Current study first highlights the potential value of DRIGs as biomarkers in GC. We successfully constructed a robust model incorporating four DRIGs to accurately predict the survival time and clinicopathological characteristics of GC patients.

Cancer-associated fibroblasts: protagonists of the tumor microenvironment in gastric cancer

Enhanced knowledge of the interaction of cancer cells with their environment elucidated the critical role of tumor microenvironment in tumor progression and chemoresistance. Cancer-associated fibroblasts act as the protagonists of the tumor microenvironment, fostering the metastasis, stemness, and chemoresistance of cancer cells and attenuating the anti-cancer immune responses. Gastric cancer is one of the most aggressive cancers in the clinic, refractory to anti-cancer therapies. Growing evidence indicates that cancer-associated fibroblasts are the most prominent risk factors for a poor tumor immune microenvironment and dismal prognosis in gastric cancer. Therefore, targeting cancer-associated fibroblasts may be central to surpassing resistance to conventional chemotherapeutics, molecular-targeted agents, and immunotherapies, improving survival in gastric cancer. However, the heterogeneity in cancer-associated fibroblasts may complicate the development of cancer-associated fibroblast targeting approaches. Although single-cell sequencing studies started dissecting the heterogeneity of cancer-associated fibroblasts, the research community should still answer these questions: "What makes a cancer-associated fibroblast protumorigenic?"; "How do the intracellular signaling and the secretome of different cancer-associated fibroblast subpopulations differ from each other?"; and "Which cancer-associated fibroblast subtypes predominate specific cancer types?". Unveiling these questions can pave the way for discovering efficient cancer-associated fibroblast targeting strategies. Here, we review current knowledge and perspectives on these questions, focusing on how CAFs induce aggressiveness and therapy resistance in gastric cancer. We also review potential therapeutic approaches to prevent the development and activation of cancer-associated fibroblasts via inhibition of CAF inducers and CAF markers in cancer.

Gastric Cancer in the Era of Epigenetics

Gastric cancer (GC) remains a significant contributor to cancer-related mortality. Novel high-throughput techniques have enlightened the epigenetic mechanisms governing gene-expression regulation. Epigenetic characteristics contribute to molecular taxonomy and give rise to cancer-specific epigenetic patterns. Helicobacter pylori (Hp) infection has an impact on aberrant DNA methylation either through its pathogenic CagA protein or by inducing chronic inflammation. The hypomethylation of specific repetitive elements generates an epigenetic field effect early in tumorigenesis. Epstein-Barr virus (EBV) infection triggers DNA methylation by dysregulating DNA methyltransferases (DNMT) enzyme activity, while persistent Hp-EBV co-infection leads to aggressive tumor behavior. Distinct histone modifications are also responsible for oncogene upregulation and tumor-suppressor gene silencing in gastric carcinomas. While histone methylation and acetylation processes have been extensively studied, other less prevalent alterations contribute to the development and migration of gastric cancer via a complex network of interactions. Enzymes, such as Nicotinamide N-methyltransferase (NNMT), which is involved in tumor's metabolic reprogramming, interact with methyltransferases and modify gene expression. Non-coding RNA molecules, including long non-coding RNAs, circular RNAs, and miRNAs serve as epigenetic regulators contributing to GC development, metastasis, poor outcomes and therapy resistance. Serum RNA molecules hold the potential to serve as non-invasive biomarkers for diagnostic, prognostic or therapeutic applications. Gastric fluids represent a valuable source to identify potential biomarkers with diagnostic use in terms of liquid biopsy. Ongoing clinical trials are currently evaluating the efficacy of next-generation epigenetic drugs, displaying promising outcomes. Various approaches including multiple miRNA inhibitors or targeted nanoparticles carrying epigenetic drugs are being designed to enhance existing treatment efficacy and overcome treatment resistance.

Development and validation of a deep learning model for predicting postoperative survival of patients with gastric cancer

BACKGROUND

Deep learning (DL), a specialized form of machine learning (ML), is valuable for forecasting survival in various diseases. Its clinical applicability in real-world patients with gastric cancer (GC) has yet to be extensively validated.

METHODS

A combined cohort of 11,414 GC patients from the Surveillance, Epidemiology and End Results (SEER) database and 2,846 patients from a Chinese dataset were utilized. The internal validation of different algorithms, including DL model, traditional ML models, and American Joint Committee on Cancer (AJCC) stage model, was conducted by training and testing sets on the SEER database, followed by external validation on the Chinese dataset. The performance of the algorithms was assessed using the area under the receiver operating characteristic curve, decision curve, and calibration curve.

RESULTS

DL model demonstrated superior performance in terms of the area under the curve (AUC) at 1, 3, and, 5 years post-surgery across both datasets, surpassing other ML models and AJCC stage model, with AUCs of 0.77, 0.80, and 0.82 in the SEER dataset and 0.77, 0.76, and 0.75 in the Chinese dataset, respectively. Furthermore, decision curve analysis revealed that the DL model yielded greater net gains at 3 years than other ML models and AJCC stage model, and calibration plots at 3 years indicated a favorable level of consistency between the ML and actual observations during external validation.

CONCLUSIONS

DL-based model was established to accurately predict the survival rate of postoperative patients with GC.

Helicobacter pylori and immunotherapy for gastrointestinal cancer

Helicobacter pylori infection is associated with the risk of gastrointestinal (GI) cancers; however, its impact on immunotherapy for GI cancers remains uncertain. In this study, we included 10,122 patients who underwent 13C-urea breath tests. Among 636 patients with Epstein-Barr virus-negative microsatellite-stable gastric cancer (GC) who were treated with anti-PD-1/PD-L1 therapy, H. pylori-positive patients exhibited significantly longer immune-related progression-free survival (irPFS) compared with H. pylori-negative patients (6.97 months versus 5.03 months, p < 0.001, hazard ratio [HR] 0.76, 95% confidence interval [CI] 0.62-0.95, p = 0.015). Moreover, the H. pylori-positive group demonstrated a trend of 4 months longer median immune-related overall survival (irOS) than the H. pylori-negative group. H. pylori-positive GC displayed higher densities of PD-L1+ cells and nonexhausted CD8+ T cells, indicative of a "hot" tumor microenvironment. Transcriptomic analysis revealed that H. pylori-positive GC shared molecular characteristics similar to those of immunotherapy-sensitive GC. However, H. pylori-positive patients with DNA mismatch repair-deficient (dMMR)/microsatellite instability-high (MSI-H) colorectal adenocarcinoma and esophageal squamous cell carcinoma (ESCC) had shorter irPFS compared with H. pylori-negative patients (16.13 months versus not reached, p = 0.042, HR 2.26, 95% CI 1.13-4.50, p = 0.021 and 5.57 months versus 6.97 months, p = 0.029, HR 1.59, 95% CI 1.14-2.23, p = 0.006, respectively). The difference in irOS between H. pylori-positive and -negative patients had the same trend as that between dMMR/MSI-H colorectal adenocarcinoma and ESCC patients. We also identified a trend of shorter irPFS and irOS in H. pylori-positive liver cancer and pancreatic cancer patients. In summary, our findings supported that H. pylori infection is a beneficial factor for GC immunotherapy by shaping hot tumor microenvironments. However, in dMMR/MSI-H colorectal adenocarcinoma and ESCC patients, H. pylori adversely affects the efficacy of immunotherapy.

New clinical trial design in precision medicine: discovery, development and direction

In the era of precision medicine, it has been increasingly recognized that individuals with a certain disease are complex and different from each other. Due to the underestimation of the significant heterogeneity across participants in traditional "one-size-fits-all" trials, patient-centered trials that could provide optimal therapy customization to individuals with specific biomarkers were developed including the basket, umbrella, and platform trial designs under the master protocol framework. In recent years, the successive FDA approval of indications based on biomarker-guided master protocol designs has demonstrated that these new clinical trials are ushering in tremendous opportunities. Despite the rapid increase in the number of basket, umbrella, and platform trials, the current clinical and research understanding of these new trial designs, as compared with traditional trial designs, remains limited. The majority of the research focuses on methodologies, and there is a lack of in-depth insight concerning the underlying biological logic of these new clinical trial designs. Therefore, we provide this comprehensive review of the discovery and development of basket, umbrella, and platform trials and their underlying logic from the perspective of precision medicine. Meanwhile, we discuss future directions on the potential development of these new clinical design in view of the "Precision Pro", "Dynamic Precision", and "Intelligent Precision". This review would assist trial-related researchers to enhance the innovation and feasibility of clinical trial designs by expounding the underlying logic, which be essential to accelerate the progression of precision medicine.

Tutorial on survival modeling with applications to omics data

MOTIVATION

Identification of genomic, molecular and clinical markers prognostic of patient survival is important for developing personalized disease prevention, diagnostic and treatment approaches. Modern omics technologies have made it possible to investigate the prognostic impact of markers at multiple molecular levels, including genomics, epigenomics, transcriptomics, proteomics and metabolomics, and how these potential risk factors complement clinical characterization of patient outcomes for survival prognosis. However, the massive sizes of the omics datasets, along with their correlation structures, pose challenges for studying relationships between the molecular information and patients' survival outcomes.

RESULTS

We present a general workflow for survival analysis that is applicable to high-dimensional omics data as inputs when identifying survival-associated features and validating survival models. In particular, we focus on the commonly used Cox-type penalized regressions and hierarchical Bayesian models for feature selection in survival analysis, which are especially useful for high-dimensional data, but the framework is applicable more generally.

AVAILABILITY AND IMPLEMENTATION

A step-by-step R tutorial using The Cancer Genome Atlas survival and omics data for the execution and evaluation of survival models has been made available at https://ocbe-uio.github.io/survomics.

Clinical outcome and molecular landscape of patients with ARID1A-loss gastric cancer

Chromatin remodelers are commonly altered in human cancer. The mutation of AT-rich interactive domain 1A (ARID1A) in gastric cancer (GC), a component of the SWI/SNF chromatin remodeling complex, was proven associated with treatment response in our previous study. However, ARID1A loss of function was caused not only by mutations but also copy number deletions. The clinicopathologic, genomic, and immunophenotypic correlates of ARID1A loss is largely uncharacterized in GC. Here, 819 patients with clinicopathological information and sequencing data or formalin-fixed paraffin-embedded tissues from four cohorts, Zhongshan Hospital (ZSHS) cohort (n = 375), The Cancer Genome Atlas (TCGA) cohort (n = 371), Samsung Medical Center (SMC) cohort (n = 53), and ZSHS immunotherapy cohort (n = 20), were enrolled. ARID1A loss was defined by genome sequencing or deficient ARID1A expression by immunohistochemistry. We found that ARID1A mutation and copy number deletion were enriched in GC with microsatellite instability (MSI) and chromosomal-instability (CIN), respectively. In the TCGA and ZSHS cohorts, only CIN GC with ARID1A loss could benefit from fluorouracil-based adjuvant chemotherapy. In the SMC and ZSHS immunotherapy cohorts, ARID1A loss exhibited a tendency of superior responsiveness and indicated favorable overall survival after anti-PD-1 immunotherapy. ARID1A-loss tumors demonstrated elevated mutation burden, neoantigen load, and interferon gamma pathway activation. Moreover, in CIN GC, ARID1A loss was correlated with higher homologous recombination deficiency. ARID1A loss defines a distinct subtype of GC characterized by high levels of genome instability, neoantigen formation, and immune activation. These tumors show sensitivity to both chemotherapy and anti-PD-1 immunotherapy. This study provides valuable insights for precision treatment strategies in GC.

Identification of Potential Genomic Alterations Using Pan-Cancer Cell-Free DNA Next-Generation Sequencing in Patients With Gastric Cancer

Background

Molecular cancer profiling may lead to appropriate trials for molecularly targeted therapies. Cell-free DNA (cfDNA) is a promising diagnostic and/or prognostic biomarker in gastric cancer (GC). We characterized somatic genomic alterations in cfDNA of patients with GC.

Methods

Medical records and cfDNA data of 81 patients diagnosed as having GC were reviewed. Forty-nine and 32 patients were tested using the Oncomine Pan-Cancer Cell-Free Assay on the Ion Torrent platform and AlphaLiquid 100 kit on the Illumina platform, respectively.

Results

Tier I or II alterations were detected in 64.2% (52/81) of patients. Biomarkers for potential targeted therapy were detected in 55.6% of patients (45/81), and clinical trials are underway. ERBB2 amplification is actionable and was detected in 4.9% of patients (4/81). Among biomarkers showing potential for possible targeted therapy, TP53 mutation (38.3%, 35 variants in 31 patients, 31/81) and FGFR2 amplification (6.2%, 5/81) were detected the most.

Conclusions

Next-generation sequencing of cfDNA is a promising technique for the molecular profiling of GC. Evidence suggests that cfDNA analysis can provide accurate and reliable information on somatic genomic alterations in patients with GC, potentially replacing tissue biopsy as a diagnostic and prognostic tool. Through cfDNA analysis for molecular profiling, it may be possible to translate the molecular classification into therapeutic targets and predictive biomarkers, leading to personalized treatment options for patients with GC in the future.

Comparative analysis of ARID1A mutations with mRNA levels and protein expression in gastric carcinoma

The ARID1A gene is pivotal in chromatin remodeling and genomic integrity and is frequently mutated in various cancer types. ARID1A mutation is the second most frequently mutated tumor suppressor gene and has been suggested as a predictor of immunotherapeutic responsiveness in gastric carcinoma (GC). Despite its significance, the relationship among ARID1A somatic mutations, RNA expression levels, and protein expression remains unclear, particularly in GC. For this purpose, we performed comparative study in two cohorts. Cohort 1 used next-generation sequencing (NGS) to identify 112 GC cases with ARID1A mutations. These cases were compared with ARID1A immunohistochemistry (IHC) results. Cohort 2 employed microarray gene expression data to assess ARID1A RNA levels and compare them with ARID1A IHC results. In Cohort 1, 38.4% of ARID1A-mutated GC exhibited a complete loss of ARID1A protein when assessed by IHC, whereas the remaining 61.6% displayed intact ARID1A. Discordance between NGS and IHC results was not associated with specific mutation sites, variant classifications, or variant allele frequencies. In Cohort 2, 24.1% of the patients demonstrated a loss of ARID1A protein, and there was no significant difference in mRNA levels between the ARID1A protein-intact and -loss groups. Our study revealed a substantial discrepancy between ARID1A mutations detected using NGS and protein expression assessed using IHC in GC. Moreover, ARID1A mRNA expression levels did not correlate well with protein expression. These findings highlighted the complexity of ARID1A expression in GC.

Sex-dependent different clinicopathological characterization of Epstein-Barr virus-associated gastric carcinoma: a large-scale study

BACKGROUND

Epstein-Barr virus (EBV)-associated gastric cancer (EBVaGC) has been reported to account for approximately 5-16% of all GCs with good prognosis compared to EBV-negative GC. We evaluated the clinicopathological characteristics of EBVaGC including survival rate in South Korea.

METHODS

A total of 4,587 patients with GC who underwent EBV in situ hybridization (EBV-ISH) were prospectively enrolled at the Seoul National University Bundang Hospital from 2003 to 2021. Age, sex, smoking status, cancer type and stage, tumor size and location, histological type, molecular features and survival information were analyzed.

RESULTS

A total of 456 patients with GC (9.9%) were positive for EBV. The EBVaGC group displayed a higher proportion of males (P < 0.001), a predominant presence in the proximal stomach (P < 0.001), a higher proportion of undifferentiated cancer (P < 0.001), and a lower cancer stage (P = 0.004) than the EBV-negative group. Cox multivariate analyses revealed age (hazard ratio [HR] = 1.025, P < 0.001), tumor size (HR = 1.109, P < 0.001), and cancer stage (stage2 HR = 4.761, P < 0.001; stage3 HR = 13.286, P < 0.001; stage4 HR = 42.528, P < 0.001) as significant risk factors for GC-specific mortality, whereas EBV positivity was inversely correlated (HR = 0.620, P = 0.022). Furthermore, the EBVaGC group displayed statistically significant survival advantages over the EBV-negative cancer group in terms of both overall (P = 0.021) and GC-specific survival (P = 0.007) on the Kaplan-Meier survival curve. However, this effect was evident only in males.

CONCLUSIONS

EBVaGC patients showed better prognoses despite their association with proximal location and poorly differentiated histology in male, probably due to the difference in immunity between males and females.

Predictive and prognostic biomarkers in gastrointestinal tract tumours

Tumours of the gastrointestinal tract represent nearly a quarter of all newly diagnosed tumours diagnosed in 2019. Various treatment modalities for gastrointestinal cancers exist, some of which may be guided by biomarkers. Biomarkers act as gauges of either normal or pathogenic processes or responses to an exposure or intervention. They come in many forms. This review explores established and potential molecular/immunohistochemical (IHC) predictive and prognostic biomarkers of the gastrointestinal tract.

Immunotherapy in Esophagogastric Cancer: Treatment Landscape, Challenges, and New Directions

BACKGROUND

Cancers of the upper gastrointestinal tract represent a lethal disease entity comprising the esophagus, gastroesophageal junction, and stomach. The backbone of therapy in esophagogastric cancers has predominantly been chemotherapy-based. However, over the last decade, with the debut of immune checkpoint inhibitors, sophisticated molecular testing, and a more comprehensive understanding of the tumor microenvironment, immunotherapy has been incorporated into the treatment of localized and advanced esophagogastric cancers with promising results.

PURPOSE

This study aimed to review the unique tumor microenvironment and role of immunotherapy in esophagogastric cancers.

METHODS

We conducted a systematic review of clinical and translational research for immunotherapy in esophagogastric cancers.

RESULTS

This article will explore the unique tumor microenvironment in gastroesophageal cancers, the role of immunotherapy in localized and advanced disease, challenges in management, and new therapeutic approaches in clinical trials.

CONCLUSION

With further exploration into targeted therapy and immunotherapy, we anticipate the emergence of novel treatments that will improve survival and quality of life in patients with esophagogastric cancers.

Esophageal adenocarcinoma heterogeneity in clinicopathology and prognosis: A single center longitudinal study of 146 cases over a 20-year period

Recent genomic studies suggest that esophageal adenocarcinoma (EAC) is not homogeneous and can be divided into true (tEAC) and probable (pEAC) groups. We compared clinicopathologic and prognostic features between the two groups of EAC. Based on endoscopic, radiologic, surgical, and pathologic reports, tumors with epicenters beyond 2 cm of the gastroesophageal junction (GEJ) were assigned to the tEAC group (N = 63), while epicenters within 2 cm of, but not crossing the GEJ, were allocated to the pEAC group (N = 83). All 146 consecutive patients were male (age: median 70 years, range: 51-88) and White-predominant (98.6 %). There was no significant difference in gastroesophageal reflux disease, obesity, comorbidity, and the prevalence of Barrett's esophagus, and cases diagnosed during endoscopic surveillance. However, compared to the pEAC group, the tEAC group had significantly more cases with hiatal hernia (P = 0.003); their tumors were significantly smaller in size (P = 0.007), more frequently with tubular/papillary adenocarcinoma (P = 0.001), had fewer cases with poorly cohesive carcinoma (P = 0.018), and demonstrated better prognosis in stage I disease (P = 0.012); 5-year overall survival (34.9 months) was significantly longer (versus 16.8 months in pEACs) (P = 0.043). Compared to the patients without resection, the patients treated with endoscopic or surgical resection showed significantly better outcomes, irrespective of stages. We concluded that EACs were heterogeneous with two distinct tEAC and pEAC groups in clinicopathology and prognosis; resection remained the better option for improved outcomes. CONDENSED ABSTRACT: Esophageal adenocarcinoma can be divided into true or probable groups with distinct clinicopathology and better prognosis in the former than in the latter. we showed that resection remained the better option for improved outcomes.

Mutational landscape of TP53 and CDH1 in gastric cancer

In this editorial we comment on an article published in a recent issue of the World J Gastrointest Surg. A common gene mutation in gastric cancer (GC) is the TP53 mutation. As a tumor suppressor gene, TP53 is implicated in more than half of all tumor occurrences. TP53 gene mutations in GC tissue may be related with clinical pathological aspects. The TP53 mutation arose late in the progression of GC and aided in the final switch to malignancy. CDH1 encodes E-cadherin, which is involved in cell-to-cell adhesion, epithelial structure maintenance, cell polarity, differentiation, and intracellular signaling pathway modulation. CDH1 mutations and functional loss can result in diffuse GC, and CDH1 mutations can serve as independent prognostic indicators for poor prognosis. GC patients can benefit from genetic counseling and testing for CDH1 mutations. Demethylation therapy may assist to postpone the onset and progression of GC. The investigation of TP53 and CDH1 gene mutations in GC allows for the investigation of the relationship between these two gene mutations, as well as providing some basis for evaluating the prognosis of GC patients.

Molecular Classifications in Gastric Cancer: A Call for Interdisciplinary Collaboration

Gastric cancer (GC) is a heterogeneous disease, often diagnosed at advanced stages, with a 5-year survival rate of approximately 20%. Despite notable technological advancements in cancer research over the past decades, their impact on GC management and outcomes has been limited. Numerous molecular alterations have been identified in GC, leading to various molecular classifications, such as those developed by The Cancer Genome Atlas (TCGA) and the Asian Cancer Research Group (ACRG). Other authors have proposed alternative perspectives, including immune, proteomic, or epigenetic-based classifications. However, molecular stratification has not yet transitioned into clinical practice for GC, and little attention has been paid to alternative molecular classifications. In this review, we explore diverse molecular classifications in GC from a practical point of view, emphasizing their relationships with clinicopathological factors, prognosis, and therapeutic approaches. We have focused on classifications beyond those of TCGA and the ACRG, which have been less extensively reviewed previously. Additionally, we discuss the challenges that must be overcome to ensure their impact on patient treatment and prognosis. This review aims to serve as a practical framework to understand the molecular landscape of GC, facilitate the development of consensus molecular categories, and guide the design of innovative molecular studies in the field.

Development of a CD8+ T cell associated signature for predicting the prognosis and immunological characteristics of gastric cancer by integrating single-cell and bulk RNA-sequencing

The universally poor clinical outcome makes gastric cancer (GC) still a significant public health threat, the main goal of our research is to develop a prognostic signature that can forecast the outcomes and immunological characteristics of GC via integrating single-cell and bulk RNA-sequencing. The CD8+ T cell feature genes were screened out by exploring single-cell RNA-sequencing (scRNA-seq) profiles retrieved from the TISCH2 database. Then, Cox and LASSO regressions were exploited for constructing a prognostic model in TCGA cohort based on these CD8+ T cell feature genes. Survival analysis was conducted to investigate the predictive capability of the signature for the clinical outcome of GC patients in TCGA and GEO cohorts. Additionally, we further examined the correlations between the risk signature and tumor immunotherapeutic response from the perspectives of immune infiltration, tumor mutation burden (TMB), immune checkpoint biomarker (ICB) expression, tumor microenvironment (TME), microsatellite instability (MSI), TIDE, and TCIA scores. In total, 703 CD8+ T cell feature genes were identified, eight of which were selected for constructing a prognostic signature. GC patients who possess high-risk score had significantly poorer survival outcomes than those who possess low-risk score in TCGA and GEO cohorts. Immune infiltration analysis proved that the risk score was negatively connected with the infiltration abundance of CD8+ T cells. Then, our findings demonstrated that GC patients in the high-risk subgroup possess a higher proportion of MSI-L/MSS, lower immune checkpoint biomarker expression, lower TMB, higher TIDE scores and lower TCIA scores compared to those in the low-risk subgroup. What's more, immunotherapy cohort analysis confirmed that patients who possess high-risk score are not sensitive to anti-cancer immunotherapy. Our study developed a reliable prognostic signature for GC that was significantly correlated with the immune landscape and immunotherapeutic responsiveness. The risk signature may guide clinicians to adopt more accurate and personalized treatment strategies for GC patients.

DeepRisk network: an AI-based tool for digital pathology signature and treatment responsiveness of gastric cancer using whole-slide images

BACKGROUND

Digital histopathology provides valuable information for clinical decision-making. We hypothesized that a deep risk network (DeepRisk) based on digital pathology signature (DPS) derived from whole-slide images could improve the prognostic value of the tumor, node, and metastasis (TNM) staging system and offer chemotherapeutic benefits for gastric cancer (GC).

METHODS

DeepRisk is a multi-scale, attention-based learning model developed on 1120 GCs in the Zhongshan dataset and validated with two external datasets. Then, we assessed its association with prognosis and treatment response. The multi-omics analysis and multiplex Immunohistochemistry were conducted to evaluate the potential pathogenesis and spatial immune contexture underlying DPS.

RESULTS

Multivariate analysis indicated that the DPS was an independent prognosticator with a better C-index (0.84 for overall survival and 0.71 for disease-free survival). Patients with low-DPS after neoadjuvant chemotherapy responded favorably to treatment. Spatial analysis indicated that exhausted immune clusters and increased infiltration of CD11b+CD11c+ immune cells were present at the invasive margin of high-DPS group. Multi-omics data from the Cancer Genome Atlas-Stomach adenocarcinoma (TCGA-STAD) hint at the relevance of DPS to myeloid derived suppressor cells infiltration and immune suppression.

CONCLUSION

DeepRisk network is a reliable tool that enhances prognostic value of TNM staging and aid in precise treatment, providing insights into the underlying pathogenic mechanisms.

Potential crosstalk between SPP1 + TAMs and CD8 + exhausted T cells promotes an immunosuppressive environment in gastric metastatic cancer

BACKGROUND

Immunotherapy brings new hope to patients with advanced gastric cancer. However, liver metastases can reduce the efficacy of immunotherapy in patients. Tumor-associated macrophages (TAMs) may be the cause of this reduction in efficacy. SPP1 + TAMs are considered to have immunosuppressive properties. We aimed to investigate the involvement of SPP1 + TAMs in the metastasis of gastric cancer.

METHODS

The single-cell transcriptome was combined with batched BULK datasets for analysis. Animal models were used to verify the analysis results.

RESULTS

We reveal the interaction of SPP1 + TAMs with CD8 + exhausted T cells in metastatic cancer. Among these interactions, GDF15-TGFBR2 may play a key immunosuppressive role. We constructed an LR score to quantify interactions based on ligands and receptors. The LR score is highly correlated with various immune features and clinical molecular subtypes. The LR score may also guide the prediction of the efficacy of immunotherapy and prognosis.

CONCLUSIONS

The crosstalk between SPP1 + TAMs and CD8 + exhausted T cells plays a key immunosuppressive role in the gastric metastatic cancer microenvironment.

Exploration of radionuclide labeling of a novel scFv-Fc fusion protein targeting CLDN18.2 for tumor diagnosis and treatment

PURPOSE

Claudin 18.2 (CLDN18.2), due to its highly selective expression in tumor cells, has made breakthrough progress in clinical research and is expected to be integrated into routine tumor diagnosis and treatment.

METHODS

In this research, we obtained an scFv-Fc fusion protein (SF106) targeting CLDN18.2 through hybridoma technology. The scFv-Fc fusion protein was labeled with radioactive isotopes (124I and 177Lu) to generate the radio-probes. The targeting and specificity of the radio-probes were tested in cellular models, and its diagnostic and therapeutic potential was further evaluated in tumor-bearing models.

RESULTS

The molecular probes [124I]I-SF106 and [177Lu]Lu-DOTA-SF106 possess high radiochemical purity (RCP, 98.18 ± 0.93 % and 97.05 ± 1.1 %) and exhibit good stability in phosphate buffer saline and 5 % human serum albumin (92.44 ± 4.68 % and 91.03 ± 2.42 % at 120 h). [124I]I-SF106 uptake in cells expressing CLDN18.2 was well targeted and specific, and the dissociation constant was 17.74 nM [124I]I-SF106 micro-PET imaging showed that the maximum standardized uptake value (SUVmax) was significantly higher than CLDN18.2-negative tumors (1.83 ± 0.02 vs. 1.23 ± 0.04, p < 0.001). The maximum uptake was attained in tumors expressing CLDN18.2 at 48 h after injection. [124I]I-SF106 and [177Lu]Lu-DOTA-SF106 dosimetric study showed that the effective dose in humans complies with the medical safety standards required for their clinical application. The results of treatment experiments showed that 3 MBq of [177Lu]Lu-DOTA-SF106 in CLDN18.2-expressing tumor-bearing mice could significantly inhibit tumor growth.

CONCLUSION

These results indicate that radionuclide-labeled scFv-Fc molecular probes ([124I]I-SF106 and [177Lu]Lu-DOTA-SF106) provide a new possibility for the diagnosis and treatment of CLDN18.2-positive cancer patients in clinical practice.

Individual Survival Distributions Generated by Multi-Task Logistic Regression Yield a New Perspective on Molecular and Clinical Prognostic Factors in Gastric Adenocarcinoma

Recent advances in our understanding of gastric cancer biology have prompted a shift towards more personalized therapy. However, results are based on population-based survival analyses, which evaluate the average survival effects of entire treatment groups or single prognostic variables. This study uses a personalized survival modelling approach called individual survival distributions (ISDs) with the multi-task logistic regression (MTLR) model to provide novel insight into personalized survival in gastric adenocarcinoma. We performed a pooled analysis using 1043 patients from a previously characterized database annotated with molecular subtypes from the Cancer Genome Atlas, Asian Cancer Research Group, and tumour microenvironment (TME) score. The MTLR model achieved a 5-fold cross-validated concordance index of 72.1 ± 3.3%. This model found that the TME score and chemotherapy had similar survival effects over the entire study time. The TME score provided the greatest survival benefit beyond a 5-year follow-up. Stage III and Stage IV disease contributed the greatest negative effect on survival. The MTLR model weights were significantly correlated with the Cox model coefficients (Pearson coefficient = 0.86, p < 0.0001). We illustrate how ISDs can accurately predict the survival time for each patient, which is especially relevant in cases of molecular subtype heterogeneity. This study provides evidence that the TME score is principally associated with long-term survival in gastric adenocarcinoma. Additional external validation and investigation into the clinical utility of this ISD model in gastric cancer is an area of future research.

Tubulointerstitial nephritis antigen-like 1 from cancer-associated fibroblasts contribute to the progression of diffuse-type gastric cancers through the interaction with integrin β1

BACKGROUND

Tumor cells of diffuse-type gastric cancer (DGC) are discohesive and infiltrate into the stroma as single cells or small subgroups, so the stroma significantly impacts DGC progression. Cancer-associated fibroblasts (CAFs) are major components of the tumor stroma. Here, we identified CAF-specific secreted molecules and investigated the mechanism underlying CAF-induced DGC progression.

METHODS

We conducted transcriptome analysis for paired normal fibroblast (NF)-CAF isolated from DGC patient tissues and proteomics for conditioned media (CM) of fibroblasts. The effects of fibroblasts on cancer cells were examined by transwell migration and soft agar assays, western blotting, and in vivo. We confirmed the effect of blocking tubulointerstitial nephritis antigen-like 1 (TINAGL1) in CAFs using siRNA or shRNA. We evaluated the expression of TINAGL1 protein in frozen tissues of DGC and paired normal stomach and mRNA in formalin-fixed, paraffin-embedded (FFPE) tissue using RNA in-situ hybridization (RNA-ISH).

RESULTS

CAFs more highly expressed TINAGL1 than NFs. The co-culture of CAFs increased migration and tumorigenesis of DGC. Moreover, CAFs enhanced the phosphorylation of focal adhesion kinase (FAK) and mesenchymal marker expression in DGC cells. In an animal study, DGC tumors co-injected with CAFs showed aggressive phenotypes, including lymph node metastasis. However, increased phosphorylation of FAK and migration were reduced by blocking TINAGL1 in CAFs. In the tissues of DGC patients, TINAGL1 was higher in cancer than paired normal tissues and detected with collagen type I alpha 1 chain (COL1A1) in the same spot. Furthermore, high TINAGL1 expression was significantly correlated with poor prognosis in several public databases and our patient cohort diagnosed with DGC.

CONCLUSIONS

These results indicate that TINAGL1 secreted by CAFs induces phosphorylation of FAK in DGC cells and promotes tumor progression. Thus, targeting TINAGL1 in CAFs can be a novel therapeutic strategy for DGC.

Expression patterns of E2Fs identify tumor microenvironment features in human gastric cancer

Objective

E2F transcription factors are associated with tumor development, but their underlying mechanisms in gastric cancer (GC) remain unclear. This study explored whether E2Fs determine the prognosis or immune and therapy responses of GC patients.

Methods

E2F regulation patterns from The Cancer Genome Atlas (TCGA) were systematically investigated and E2F patterns were correlated with the characteristics of cellular infiltration in the tumor microenvironment (TME). A principal component analysis was used to construct an E2F scoring model based on prognosis-related differential genes to quantify the E2F regulation of a single tumor. This scoring model was then tested in patient cohorts to predict effects of immunotherapy.

Results

Based on the expression profiles of E2F transcription factors in GC, two different regulatory patterns of E2F were identified. TME and survival differences emerged between the two clusters. Lower survival rates in the Cluster2 group were attributed to limited immune function due to stromal activation. The E2F scoring model was then constructed based on the E2F-related prognostic genes. Evidence supported the E2F score as an independent and effective prognostic factor and predictor of immunotherapy response. A gene-set analysis correlated E2F score with the characteristics of immune cell infiltration within the TME. The immunotherapy cohort database showed that patients with a higher E2F score demonstrated better survival and immune responses.

Conclusions

This study found that differences in GC prognosis might be related to the E2F patterns in the TME. The E2F scoring system developed in this study has practical value as a predictor of survival and treatment response in GC patients.

Identification of a lipid homeostasis-related gene signature for predicting prognosis, immunity, and chemotherapeutic effect in patients with gastric cancer

Gastric cancer (GC) is one of the most common and deadliest cancers worldwide. Lipid homeostasis is essential for tumour development because lipid metabolism is one of the most important metabolic reprogramming pathways within tumours. Elucidating the mechanism of lipid homeostasis in GC might significantly improve treatment strategies and patient prognosis. GSE62254 was applied to construct a lipid homeostasis-related gene signature score (HGSscore) by multiple bioinformatic algorithms including weighted gene coexpression network analysis (WGCNA) and LASSO-Cox regression. A nomogram based on HGSscore and relevant clinical characteristics was constructed to predict the survival of patients with GC. TIMER and xCell were used to evaluate immune and stromal cell infiltration in the tumour microenvironment. Correlations between lipid homeostasis-related genes and chemotherapeutic efficacy were analysed in GSCAlite. RT‒qPCR and cell viability assays were applied to verify the findings in this study. HGSscore was constructed based on eighteen lipid homeostasis-related genes that were selected by WGCNA and LASSO-Cox regression. HGSscore was strongly associated with advanced TNM stage and showed satisfactory value in predicting GC prognosis in three independent cohorts. Furthermore, we found that HGSscore was associated with the tumour mutation burden (TMB) and immune/stromal cell infiltration, which are related to GC prognosis, indicating that lipid homeostasis impacts the formation of the tumour microenvironment (TME). With respect to the GSCAlite platform, PLOD2 and TGFB2 were shown to be positively related to chemotherapeutic resistance, while SLC10A7 was a favourable factor for chemotherapy efficacy. Cell viability assays showed that disrupted lipid homeostasis could attenuate GC cell viability. Moreover, RT‒qPCR revealed that lipid homeostasis could influence expression of specific genes. We identified a lipid homeostasis-related gene signature that correlated with survival, clinical characteristics, the TME, and chemotherapeutic efficacy in GC patients. This research provides a new perspective for improving prognosis and guiding individualized chemotherapy for patients with GC.

Clinical and Genetic Characteristics of Early and Advanced Gastric Cancer

Gastric cancer (GC) persists as the fourth most prevalent cause of global cancer-related mortality, presenting a challenge due to the scarcity of available therapeutic strategies. Precision medicine is crucial not only in the treatment but also in the management of GC. We performed gene panel sequencing with Oncomine focus assay comprising 52 cancer-associated genes and MSI analysis in 100 case-matched gastric cancer cases. A comprehensive analysis of clinical and genetic characteristics was conducted on these genetic results and clinicopathological findings. Upon comparison of clinicopathological characteristics, significant differences between early gastric cancer (EGC) and advanced gastric cancer (AGC) were observed in tumor location (p = 0.003), Lauren classification (p = 0.015), T stage (p = 0.000), and N stage (p = 0.015). The six most frequently mutated genes were PIK3CA (29%, 10/35), ERBB2 (17%, 6/35), KRAS (14%, 5/35), ALK (6%, 2/35), ESR1 (6%, 2/35), and FGFR3 (6%, 2/35). Regarding genetic variation, there was a tendency for the N stage to be higher in GC patients with mutated genes (p = 0.014). The frequency of mutations in GC patients was statistically significantly higher in AGC (n = 24) compared to EGC (n = 11) (odds ratio, 2.792; 95% confidence interval, 1.113 to 7.007; p = 0.026). Six of the ten GC patients carrying mutated genes and exhibiting MSI were classified into intestinal-type and undifferentiated GC, with the location of the tumor being in the lower-third. Among these patients, five harbored mutated PIK3CA, while the remaining patient had a mutation in ALK. Conclusions: AGC patients more frequently exhibited alterations of PIK3CA, KRAS, and ERBB2 as somatic oncogenic drivers, and displayed a higher prevalence of cumulative genetic events, including increased rates of PIK3CA mutations, enhanced detection of immunotherapy biomarkers, and mutations of the ESR1 gene.

Mechanisms of cellular crosstalk in the gastric tumor microenvironment are mediated by YAP1 and STAT3

Deregulation of the Hippo pathway is a driver for cancer progression and treatment resistance. In the context of gastric cancer, YAP1 is a biomarker for poor patient prognosis. Although genomic tumor profiling provides information of Hippo pathway activation, the present study demonstrates that inhibition of Yap1 activity has anti-tumor effects in gastric tumors driven by oncogenic mutations and inflammatory cytokines. We show that Yap1 is a key regulator of cell metabolism, proliferation, and immune responses in normal and neoplastic gastric epithelium. We propose that the Hippo pathway is targetable across gastric cancer subtypes and its therapeutic benefits are likely to be mediated by both cancer cell-intrinsic and -extrinsic mechanisms.

Immunosuppressive MFAP2+ cancer associated fibroblasts conferred unfavorable prognosis and therapeutic resistance in gastric cancer

PURPOSE

To explore the predictive merit of MFAP2+ cancer associated fibroblasts (CAFs) infiltration for clinical outcomes and adjuvant chemotherapy or immunotherapy responsiveness in gastric cancer (GC).

METHODS

In this study, several independent cohorts were included respectively to dissect the relationship of clinical outcomes, therapeutic responses and tumor microenvironment with different MFAP2+ CAFs infiltration. Drug sensitivity analysis was conducted to predict the relationship between MFAP2+ CAFs infiltration and targeted drug response. Kaplan-Meier curves and the log-rank test were used to compare clinical outcomes of patients with different MFAP2+ CAFs infiltration.

RESULTS

High MFAP2+ CAFs infiltration yielded inferior prognosis in terms of overall survival, progress free survival and recurrence free survival in GC. Patients with low MFAP2+ CAFs infiltration were more likely to gain benefit from adjuvant therapy. Moreover, low MFAP2+ CAFs infiltration could predict a promising response to immunotherapy in GC patients. MFAP2+ CAFs with immunosuppressive features were highly relevant to immune evasive contexture characterized by the dysfunction of CD8+ T cells. We found that MFAP2+ CAFs communicated with T cells, B cells and Macrophages through releasing macrophage migration inhibitor factor (MIF), which further suggested that MFAP2+ CAFs might promote therapeutic resistance through regulating T cells dysfunction and M2 macrophages polarization.

CONCLUSION

Immunosuppressive MFAP2+ CAFs constructed an immune evasive tumor microenvironment characterized by incapacitated immune effector cells, consequently predicting inferior clinical outcomes and response on adjuvant therapy and immunotherapy in patients with GC. The potential of immunosuppressive MFAP2+ CAFs as a therapeutic target for GC deserved thoroughly exploration.

Stroma AReactive Invasion Front Areas (SARIFA) improves prognostic risk stratification of perioperative chemotherapy treated oesophagogastric cancer patients from the MAGIC and the ST03 trial

BACKGROUND

Tumour-associated fat cells without desmoplastic stroma reaction at the invasion front (Stroma AReactive Invasion Front Areas (SARIFA)) is a prognostic biomarker in gastric and colon cancer. The clinical utility of the SARIFA status in oesophagogastric cancer patients treated with perioperative chemotherapy is currently unknown.

METHODS

The SARIFA status was determined in tissue sections from patients recruited into the MAGIC (n = 292) or ST03 (n = 693) trials treated with surgery alone (S, MAGIC) or perioperative chemotherapy (MAGIC, ST03). The relationship between SARIFA status, clinicopathological factors, overall survival (OS) and treatment was analysed.

RESULTS

The SARIFA status was positive in 42% MAGIC trial S patients, 28% MAGIC and 48% ST03 patients after pre-operative chemotherapy. SARIFA status was related to OS in MAGIC trial S patients and was an independent prognostic biomarker in ST03 trial patients (HR 1.974, 95% CI 1.555-2.507, p < 0.001). ST03 patients with lymph node metastasis (ypN + ) and SARIFA-positive tumours had poorer OS than patients with ypN+ and SARIFA-negative tumours (plogrank < 0.001).

CONCLUSIONS

The SARIFA status has clinical utility as prognostic biomarker in oesophagogastric cancer patients irrespective of treatment modality. Whilst underlying biological mechanisms warrant further investigation, the SARIFA status might be used to identify new drug targets, potentially enabling repurposing of existing drugs targeting lipid metabolism.

Claudin-18.2 testing and its impact in the therapeutic management of patients with gastric and gastroesophageal adenocarcinomas: A literature review with expert opinion

Claudin-18.2 (CLDN18.2) is a member of the tight junction protein family and is a highly selective biomarker with frequent abnormal expression during the occurrence and development of various primary malignant tumors, including gastric cancer (GC) and esophago-gastric junction adenocarcinomas (EGJA). For these reasons, CLDN18.2 has been investigated as a therapeutic target for GC/EGJA malignancies. Recently, zolbetuximab has been proposed as a new standard of care for patients with CLDN18.2-positive, HER2-negative, locally advanced and metastatic GC/EGJA. The use of CLDN18 IHC assays to select patients who might benefit from anti-CLDN18.2 therapy is currently entering clinical practice. In this setting, pathologists play a central role in therapeutic decision-making. Accurate biomarker assessment is essential to ensure the best therapeutic option for patients. In the present review, we provide a comprehensive overview of available evidence on CLDN18.2 testing and its impact on the therapeutic management of patients with GC/EGJA, as well as some practical suggestions for CLDN18.2 staining interpretation and potential pitfalls in the real-world setting.

Leveraging synthetic lethality to uncover potential therapeutic target in gastric cancer

Since trastuzumab was approved in 2012 for the first-line treatment of gastric cancer (GC), no significant advancement in GC targeted therapies has occurred. Synthetic lethality refers to the concept that simultaneous dysfunction of a pair of genes results in a lethal effect on cells, while the loss of an individual gene does not cause this effect. Through exploiting synthetic lethality, novel targeted therapies can be developed for the individualized treatment of GC. In this study, we proposed a computational strategy named Gastric cancer Specific Synthetic Lethality inference (GSSL) to identify synthetic lethal interactions in GC. GSSL analysis was used to infer probable synthetic lethality in GC using four accessible clinical datasets. In addition, prediction results were confirmed by experiments. GSSL analysis identified a total of 34 candidate synthetic lethal pairs, which included 33 unique targets. Among the synthetic lethal gene pairs, TP53-CHEK1 was selected for further experimental validation. Both computational and experimental results indicated that inhibiting CHEK1 could be a potential therapeutic strategy for GC patients with TP53 mutation. Meanwhile, in vitro experimental validation of two novel synthetic lethal pairs TP53-AURKB and ARID1A-EP300 further proved the universality and reliability of GSSL. Collectively, GSSL has been shown to be a reliable and feasible method for comprehensive analysis of inferring synthetic lethal interactions of GC, which may offer novel insight into the precision medicine and individualized treatment of GC.

Blockade of V-domain immunoglobulin suppressor of T-cell activation reprograms tumour-associated macrophages and improves efficacy of PD-1 inhibitor in gastric cancer

BACKGROUND AND AIMS

In gastric cancer, the response rate of programmed cell death protein-1 (PD-1) inhibitor is far from satisfactory, indicating additional nonredundant pathways might hamper antitumour immunity. V-domain immunoglobulin suppressor of T-cell activation (VISTA) has been reported in several malignancies as a novel immune-checkpoint. Nevertheless, the role of VISTA in gastric cancer still remains obscure. Our purpose is to explore the clinical significance and potential mechanism of VISTA in affecting gastric cancer patients' survival and immunotherapeutic responsiveness.

METHODS

Our study recruited eight independent cohorts with a total of 1403 gastric cancer patients. Immunohistochemistry, multiplex immunofluorescence, flow cytometry or intracellular flow cytometry, quantitative polymerase chain reaction, western blotting, fluorescence-activated cell sorting, magnetic-activated cell sorting, smart-seq2, in vitro cell co-culture and ex vivo tumour inhibition assays were applied to investigate the clinical significance and potential mechanism of VISTA in gastric cancer.

RESULTS

VISTA was predominantly expressed on tumour-associated macrophages (TAMs), and indicated poor clinical outcomes and inferior immunotherapeutic responsiveness. VISTA+ TAMs showed a mixed phenotype. Co-culture of TAMs and CD8+ T cells indicated that VISTA+ TAMs attenuated effective function of CD8+ T cells. Blockade of VISTA reprogrammed TAMs to a proinflammatory phenotype, reactivated CD8+ T cells and promoted apoptosis of tumour cells. Moreover, blockade of VISTA could also enhance the efficacy of PD-1 inhibitor, suggesting that blockade of VISTA might synergise with PD-1 inhibitor in gastric cancer.

CONCLUSIONS

Our data revealed that VISTA was an immune-checkpoint associated with immunotherapeutic resistance. Blockade of VISTA reprogrammed TAMs, promoted T-cell-mediated antitumour immunity, and enhanced efficacy of PD-1 inhibitor, which might have implications in the treatment of gastric cancer.

Somatic mouse models of gastric cancer reveal genotype-specific features of metastatic disease

Metastatic gastric carcinoma is a highly lethal cancer that responds poorly to conventional and molecularly targeted therapies. Despite its clinical relevance, the mechanisms underlying the behavior and therapeutic response of this disease are poorly understood owing, in part, to a paucity of tractable models. Here we developed methods to somatically introduce different oncogenic lesions directly into the murine gastric epithelium. Genotypic configurations observed in patients produced metastatic gastric cancers that recapitulated the histological, molecular and clinical features of all nonviral molecular subtypes of the human disease. Applying this platform to both wild-type and immunodeficient mice revealed previously unappreciated links between the genotype, organotropism and immune surveillance of metastatic cells, which produced distinct patterns of metastasis that were mirrored in patients. Our results establish a highly portable platform for generating autochthonous cancer models with flexible genotypes and host backgrounds, which can unravel mechanisms of gastric tumorigenesis or test new therapeutic concepts.

Immunoneoadjuvant therapy with immune checkpoint inhibitors of gastric cancer: an emerging exemplification : Immunoneoadjuvant therapy of gastric cancer

Advances in immune checkpoint inhibitors (ICIs) have enabled more effective treatment for individuals with various types of solid tumors. Given the improved survival benefit and acceptable safety profile of ICIs in advanced gastric cancer, there is plenty of interest in the use of ICIs in the neoadjuvant setting with curative intent. Theoretically, immunoneoadjuvant with ICIs could boost the levels of endogenous tumor antigen present in the tumor to enhance T-cell priming and further enhance systemic immunity. This systemic immune response may improve the detection and elimination of the disseminated micrometastatic tumors beyond the resected tumor, which are sources of postsurgical relapse. Numerous clinical studies have begun to explore the application of ICIs in neoadjuvant treatment of gastric cancer. This article reviews the progress in the use of ICI monotherapy and in combination with alternative therapies for the treatment of gastric cancer to aid in the development of gastric cancer immunoneoadjuvant therapy and improve the overall therapeutic benefit.

Comprehensive Analysis on Prognostic Signature Based on T Cell-Mediated Tumor Killing Related Genes in Gastric Cancer

Although immunotherapy is a valuable treatment for gastric cancer (GC), identifying the patients who would benefit most from this approach presents a challenge. In this study, GC patients were divided into two subtypes by consensus clustering according to T cell-mediated tumor killing related genes (TTKRGs), and there were significant differences in tumor-infiltrating immune cells, signaling pathways, and gene expression of immunomodulators and inhibitory immune checkpoints between the two subtypes. Then, we developed an individualized signature based on TTKRGs, and its clinical and predictive value in GC patients for chemotherapeutic and immunotherapeutic responses was assessed. We confirmed the expression levels of signature genes in GC tumor tissue using quantitative real-time polymerase chain reaction (qRT-PCR). Additionally, to improve the accuracy of GC prognosis predictions, we established a nomogram. We further identified some compounds as sensitive drugs targeting GC risk groups. The signature showed significant predictive ability across RNA-seq, microarray, and qRT-PCR cohorts, which could assist in predicting survival, immunotherapeutic and chemotherapeutic outcomes in GC patients.