Gastric Cancer最新文献

Background: Elastic laminal invasion (ELI), defined as tumor invasion beyond the peritoneal elastic lamina, may affect gastric cancer (GC) prognosis, though limited data exist on this relationship.

Methods: We retrospectively reviewed representative pathological slides from 396 patients with pT3 or pT4a GC who underwent curative resection to assess the association between ELI and relapse-free survival (RFS) and overall survival (OS).

Results: The 5-year RFS of pT3 GC with negative ELI was 85.9%, which was better than the 55.9% of that of ELI-positive pT3 (P < 0.001) or pT4a (51.3%) GC (P < 0.001). Similarly, the 5-year OS of ELI-negative pT3 GC was 90.4%, while the corresponding values for ELI-positive pT3 and pT4a were 67.0% (P < 0.001) and 63.6% (P < 0.001), respectively. Multivariate analysis revealed that the most significant prognostic factors for RFS were pT factors (i.e., pT3 with ELI/pT4), tumor size (≥ 80 mm), and nodal metastasis. We subdivided our cohort of patients with pathological stage II (pT3N0, pT3N1) GC into ELI-negative and ELI-positive subgroups, and found that the ELI-negative ones had better RFS percentages than those who were ELI-positive or stage III (P = 0.002 and P < 0.001, respectively).

Conclusions: ELI-positive pT3 GC has a worse prognosis than its ELI-negative counterpart, comparable to that of pT4a. These findings suggest a need to revisit the pT grading system in GC.

Background: Trastuzumab resistance in HER2-positive cancers remains a significant clinical challenge with limited therapeutic options. Although the tumor-promoting role of the Yes-associated protein (YAP) pathway is well established, its role in trastuzumab resistance remains unclear.

Methods: We established four trastuzumab-resistant (HR) cell lines (NCI-N87HR, SNU216HR, SNU2670HR, and SNU2773HR) from HER2-positive gastric cancer and biliary tract cancer cell lines. YAP pathway activation was assessed using Phospho-RTK arrays, bulk RNA-Seq, and immunofluorescence. Antitumor effects of YAP targeting were evaluated with MTT assays, cell-cycle analysis, migration assays, RT-qPCR, ELISA, and xenograft models of SNU-2773 and SNU-2773HR cells. Immune modulation by YAP was studied through co-culture experiments with human PBMCs and cancer cells, followed by flow cytometry analysis of immune markers.

Results: Upregulation and activation of the YAP/TAZ pathway were observed in HR cells, indicated by elevated ROR2 levels and nuclear translocation of YAP. This activation, driven by YAP/TEAD-dependent Wnt5a expression, suggests a positive-feedback mechanism that amplifies YAP activity. Elevated YAP and TEAD levels were observed in patient tumor tissues during disease progression following HER2-targeted therapies. Targeting YAP disrupted its oncogenic effects and restored sensitivity to trastuzumab, increased activation of CD4⁺ and CD8⁺ T cells in PBMCs, likely via PD-L1 downregulation and enhanced immunogenic cell death. Verteporfin, a YAP-TEAD inhibitor, effectively reduced tumor growth and increased apoptosis in mouse models bearing HR tumors.

Conclusions: Targeting the ROR2-YAP/TEAD axis presents a promising therapeutic approach to overcome trastuzumab resistance in HER2-positive cancers, offering a potential strategy for enhancing treatment efficacy and improving clinical outcomes.

Background: Although H. pylori is the most important risk factor for gastric cancer, the role of anti-H. pylori antibody titers in gastric carcinogenesis has not been investigated outside Asia. We aimed to analyze the relationship between H. pylori antibody titers and the risk of gastric precancerous lesions in a Caucasian population.

Methods: We analyzed the GISTAR pilot study data on participants from Latvia with available anti-H. pylori IgG antibody serology and histopathological information. Participants were classified into four groups according to antibody titer: low-negative (LN), high-negative (HN), low-positive (LP), and high-positive (HP). Odds ratios (ORs) for atrophic gastritis among the 4 groups were compared using logistic regression.

Results: Among a total of 1725 individuals, 970 with available histopathological information were included. A total of 738 individuals (76.1%) had histologically diagnosed atrophic gastritis. Risk of histological atrophic gastritis for each group compared to LN was as follows: HN (OR, 1.52; 95% confidence interval (CI) 0.85-2.72), LP (OR 2.04; 95% CI 1.25-3.32), and HP (OR, 2.47; 95% CI 1.50-4.07). Antibody titer as a continuous variable showed a positive relationship with histological atrophic gastritis (OR 1.09 per 10 EIU; 95% CI 1.04-1.14). The positive relationship was clearer among those aged ≥ 50 years.

Conclusions: Anti-H. pylori antibody titer was positively related to the risk of atrophic gastritis in a middle-aged Caucasian population, suggesting its potential complementary role in gastric cancer risk stratification in a European setting where upper endoscopic examination is less routinely available.

Background: Although genome-wide promoter CpG island hypermethylation of Epstein-Barr virus-associated gastric carcinoma (EBV GC) is well known, ZNF793 is rarely methylated in EBV GC but is frequently methylated in other molecular subtypes of GC, including microsatellite instability-high GC. Based on the hypothesis that ZNF793 may be important for cell survival and stemness in EBV GC, the oncogenic role of ZNF793 was investigated.

Methods: ZNF793 expression was knocked out and then restored in EBV and non-EBV GC cell lines, and its effects on cell proliferation, cell migration, cell invasion, tumor sphere formation, and xenograft tumor formation were assessed.

Results: ZNF793 knockout significantly suppressed the migration, invasion, proliferation, and stemness in GC cells with ZNF793 expression. Additionally, ZNF793 knockout significantly inhibited tumor growth in a xenograft tumor model.

Conclusions: These results suggest that ZNF793 plays an oncogenic role in not only EBV GC but also other subtypes of GC and may be a potential therapeutic target.

A 73-year-old male patient presented with anemia and was diagnosed with unresectable advanced gastric cancer with distant lymph node metastases. The biopsy specimen showed a poorly differentiated adenocarcinoma. Immunohistochemistry was negative for human epidermal growth factor receptor 2, positive for claudin- 18, and revealed a preserved mismatch repair status. A regimen of capecitabine, oxaliplatin, and zolbetuximab was chosen as the primary chemotherapy regimen. On day 2, the patient started complaining of nausea and decreased appetite, and his symptoms gradually worsened. Esophagogastroduodenoscopy performed on day 11 revealed an erythematous and edematous mucosa with white secretions throughout the stomach. A histopathological examination revealed epithalaxia at the surface and severe inflammatory cell infiltration in the lamina propria. These endoscopic and histological findings indicated zolbetuximab-related gastritis. His symptoms improved three weeks after the discontinuation of chemotherapy. Endoscopic and pathological improvements of the gastritis were confirmed three months after the discontinuation of zolbetuximab. This report describes the first case of prolonged severe gastrointestinal symptoms with severe gastritis caused by zolbetuximab, as demonstrated by endoscopic and histopathological evidence.

Background: Accurate diagnosis of ESD specimens is crucial for managing early gastric cancer. Identifying tumor areas in serially sectioned ESD specimens requires experience and is time-consuming. This study aimed to develop and evaluate a deep learning model for diagnosing ESD specimens.

Methods: Whole-slide images of 366 ESD specimens of adenocarcinoma were analyzed, with 2257 annotated regions of interest (tumor and muscularis mucosa) and 83,839 patch images. The development set was divided into training and internal validation sets. Tissue segmentation performance was evaluated using the internal validation set. A detection algorithm for tumor and submucosal invasion at the whole-slide image level was developed, and its performance was evaluated using a test set.

Results: The model achieved Dice coefficients of 0.85 and 0.79 for segmentation of tumor and muscularis mucosa, respectively. In the test set, the diagnostic performance of tumor detection, measured by the AUROC, was 0.995, with a specificity of 1.000 and a sensitivity of 0.947. For detecting submucosal invasion, the model achieved an AUROC of 0.981, with a specificity of 0.956 and a sensitivity of 0.907. Pathologists' performance in diagnosing ESD specimens was evaluated with and without assistance from the deep learning model, and the model significantly reduced the mean diagnosis time (747 s without assistance vs. 478 s with assistance, P < 0.001).

Conclusion: The deep learning model demonstrated satisfactory performance in tissue segmentation and high accuracy in detecting tumors and submucosal invasion. This model can potentially serve as a screening tool in the histopathological diagnosis of ESD specimens.

Background: We developed and evaluated a skeletal muscle deep-learning (SMDL) model using skeletal muscle computed tomography (CT) imaging to predict the survival of patients with gastric cancer (GC).

Methods: This multicenter retrospective study included patients who underwent curative resection of GC between April 2008 and December 2020. Preoperative CT images at the third lumbar vertebra were used to develop a Transformer-based SMDL model for predicting recurrence-free survival (RFS) and disease-specific survival (DSS). The predictive performance of the SMDL model was assessed using the area under the curve (AUC) and benchmarked against both alternative artificial intelligence models and conventional body composition parameters. The association between the model score and survival was assessed using Cox regression analysis. An integrated model combining SMDL signature with clinical variables was constructed, and its discrimination and fairness were evaluated.

Results: A total of 1242, 311, and 94 patients were assigned to the training, internal, and external validation cohorts, respectively. The Transformer-based SMDL model yielded AUCs of 0.791-0.943 for predicting RFS and DSS across all three cohorts and significantly outperformed other models and body composition parameters. The model score was a strong independent prognostic factor for survival. Incorporating the SMDL signature into the clinical model resulted in better prognostic prediction performance. The false-negative and false-positive rates of the integrated model were similar across sex and age subgroups, indicating robust fairness.

Conclusions: The Transformer-based SMDL model could accurately predict survival of GC and identify patients at high risk of recurrence or death, thereby assisting clinical decision-making.

Background: Temporal and spatial molecular heterogeneity contributes to resistance to targeted and immune therapies in gastric and esophagogastric junction carcinoma (G/EGJ). This study evaluates differences in biomarker expression between primary G/EGJ and paired peritoneal metastases (PM).

Methods: We analyzed 74 cases of primary G/EGJ and paired PM using immunohistochemistry for HER2, PD-L1, Claudin18 (CLDN18), DNA mismatch repair (MMR) proteins, p53, E-cadherin, and in situ hybridization for EBER. Biomarker concordance between primary and metastatic tumors was assessed.

Results: Primary G/EGJ were predominantly poorly cohesive (45.9%) or mixed-type (37.8%). Regarding predictive biomarkers, low rates of HER2 overexpression (5.4%), MMR deficiency (4.1%), and EBER positivity (1.4%) were observed, while PD-L1 CPS ≥ 1 occurred in 79.7% of cases and CLDN18 positivity was observed in 31.1% of cases. Concordance was perfect for MMR and EBER, while PD-L1 showed the highest discordance (32.4%). HER2 had a low discordance rate (2.7%). CLDN18 exhibited good concordance (86.5%) and showed consistent positivity in PD-L1- and HER2-negative primary tumors (28.6%).

Conclusion: G/EGJ with PM show distinct molecular features and spatial heterogeneity, with MMR, EBER, and HER2 demonstrating strong concordance, while PD-L1 showed greater variability. As for novel biomarkers, CLDN18.2 shows substantial concordance between primary G/EGJ and PM and could be a promising target in HER2/PD-L1-negative G/EGJ with PM.

Background: Epstein-Barr virus (EBV) positivity is a potential predictive biomarker for immune checkpoint inhibitors (ICIs) in gastric cancer patients, but its value in first-line ICI-based chemotherapy remains unclear. This study aimed to evaluate the predictive value of EBV positivity in patients treated with first-line nivolumab plus chemotherapy.

Methods: This single-center study included advanced gastric cancer patients treated with first-line nivolumab plus chemotherapy (n = 293). Patients with EBV positivity treated with chemotherapy alone (n = 12) served as the control group. EBV positivity was confirmed by in situ hybridization.

Results: Among patients treated with nivolumab plus chemotherapy, 18 (6.1%) had EBV-positive tumors, and these were associated with high PD-L1 combined positive score (CPS) expression levels. Progression-free survival (PFS) and overall survival (OS) tended to be more favorable in those with EBV-positive tumors. Multivariate analysis of patients treated with nivolumab-chemotherapy revealed that EBV positivity, combined with PD-L1 CPS ≥ 5, was an independent factor for PFS. In patients with EBV-positive tumors, nivolumab-chemotherapy was associated with significantly favorable PFS and OS compared to chemotherapy alone. Similar results were observed in the subgroup with PD-L1 CPS ≥ 5. However, survival outcomes did not differ between patients treated with nivolumab plus chemotherapy versus chemotherapy alone in the subgroup with PD-L1 CPS < 5.

Conclusion: EBV positivity predicts favorable survival outcomes in patients with gastric cancer treated with nivolumab plus chemotherapy. The benefit of nivolumab plus chemotherapy over chemotherapy alone for patients with EBV positivity appears to be associated with high PD-L1 expression levels.

Background: Bemarituzumab, a monoclonal antibody targeting fibroblast growth factor receptor 2b (FGFR2b), is under evaluation in phase 3 trials of gastric cancer (GC) trials. However, data on the characteristics, prognostic significance, and heterogenous expression patterns of FGFR2b overexpression in GC remain limited. Therefore, this study aims to investigate the clinicopathologic characteristics and survival outcomes of FGFR2b-positive GC, along with the expression concordance across biopsy, surgical, and metastatic specimens.

Methods: This retrospective study included 466 patients with stages I-IV GC. Biopsy-surgical and primary-metastatic specimen pairs were available for 163 and 135 patients, respectively. FGFR2b overexpression was defined as moderate-to-strong membranous and/or cytoplasmic expression in ≥ 10% of tumor cells. FGFR2 amplification was evaluated using chromogenic in situ hybridization.

Results: FGFR2b overexpression was observed in 4.1% of patients, with 14/341 surgical specimens (4.1%), 3/284 gastric biopsies (1.1%), and 4/135 metastatic specimens (3.0%). FGFR2b overexpression correlated with deeper invasion and perineural invasion in resectable GC. However, it did not influence survival outcomes in resectable or metastatic GC. Among 163 biopsy-surgical pairs, FGFR2b overexpression was observed in only one pair (0.6%). Similarly, among 135 paired primary-metastatic specimens, FGFR2b overexpression was observed in one (0.7%). FGFR2 gene amplification occurred in 16/17 (94.1%) cases with FGFR2b overexpression.

Conclusion: Significant intratumoral and intrapatient heterogeneity is observed in FGFR2b overexpression. Given this variability in expression levels, a single endoscopic biopsy may not accurately assess FGFR2b overexpression. The FGFR2b positivity rate in gastric cancers was 4.1%, likely due to the substantial heterogeneity in its expression.