e15693 Background: Proton pump inhibitors (PPIs) are frequently prescribed to patients with gastric cancer for gastroesophageal reflux disease (GERD), ulcer prophylaxis, and symptom control. Emerging evidence suggests that PPIs may adversely affect immune checkpoint inhibitor (ICI) efficacy by disrupting gut microbiota composition, a factor increasingly recognized as a determinant of the antitumor immune response. We evaluated the association between concomitant PPI use and overall survival (OS) in a real-world cohort of patients receiving first-line ICI therapy. Methods: We performed a retrospective study using TriNetX. Adult patients with gastric adenocarcinoma who initiated nivolumab- or pembrolizumab-based first-line treatment between 2016 and 2024 were identified. Patients were classified as active PPI users if they had documented PPI prescription/administration (omeprazole, pantoprazole, esomeprazole, lansoprazole) within 30 days before or after ICI initiation, and non-users otherwise. Cohorts were 1:1 propensity score-matched for age, sex, PPI indication, comorbidities, baseline corticosteroid use, and prior Helicobacter pylori infection. OS was analyzed using Kaplan–Meier and Cox proportional hazards models. Sensitivity analyses exclude patients with recent GI bleeding and restricted exposure to sustained PPI use (> 60 days). Results: Following propensity score matching, 4,372 patients were included (2,186 PPI users and 2,186 non-users). Baseline characteristics were well balanced between cohorts (mean age 64.1 years; 38% female; GERD prevalence 41%; peptic ulcer disease 18%). At a median follow-up of 20.3 months, active PPI use was associated with significantly worse overall survival compared with non-use. Median OS was 11.2 months in PPI users versus 14.9 months in non-users (log-rank p < 0.001). Concomitant PPI exposure was independently associated with inferior OS (HR 1.27, 95% CI 1.16–1.39). Subgroup analyses demonstrated consistent findings across: ICI agents such as nivolumab (HR 1.25) and pembrolizumab (HR 1.29), presence of GERD, HR 1.22 in documented GERD, and absence of ulcer disease: HR 1.31 in patients without prior peptic ulcer disease. Sensitivity analyses yielded similar effect estimates, supporting the robustness of the findings. Conclusions: In this large real-world cohort of patients with gastric adenocarcinoma treated with first-line immunotherapy, concomitant PPI use was associated with significantly worse overall survival, even after rigorous adjustment for PPI indications and comorbidity burden. These findings support the microbiome hypothesis, suggesting that acid-suppressive therapy may impair the effectiveness of immunotherapy. Careful evaluation of the need for PPIs and prospective studies incorporating microbiome-directed interventions are warranted.

Sensitivity analyses: correlates of potentially clinically significant sleep difficulties (≥5/10) among adult patients with cancer in uni- and multivariable logistic regression models, limited to patients ± 90 days from diagnosis (N = 15,023).

BACKGROUND:Drug-induced liver injury poses a diagnostic challenge in oncology patients, especially those on immune checkpoint inhibitors, because symptoms often overlap with immune-mediated hepatitis. The increasing use of social media has led people to self-administer veterinary anthelmintics like fenbendazole for cancer, often at high doses and without medical guidance, despite limited data on safety or effectiveness. CASE SUMMARY:We report a case of a 47-year-old woman with metastatic colon cancer on nivolumab/relatlimab who developed severe hepatocellular liver injury after increasing her self-administered dose of fenbendazole. A detailed medical and temporal history, supported by a Roussel Uclaf Causality Assessment Method score of 8 (probable), identified fenbendazole as the most likely cause. Rapid biochemical improvement occurred after stopping the drug, with safe reintroduction of immunotherapy and no recurrence of liver injury. CONCLUSION:This case emphasizes the importance of thorough medication history-taking and structured causality assessment to distinguish between unregulated drug-induced liver injury and immune-related adverse events in cancer care. The use of social media to promote alternative therapies necessitates proactive patient counseling due to significant liver risks, and careful diagnostic evaluation can prevent unnecessary immunosuppression or treatment delays.

3661 Background: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are increasingly prescribed for diabetes and obesity and exert pleiotropic metabolic and anti-inflammatory effects. While prior studies have focused on their role in cancer prevention, limited data exist regarding their impact on cancer treatment outcomes. We evaluated the association between concomitant GLP-1 RA use and overall survival (OS) in patients with colorectal cancer (CRC) receiving standard first-line chemotherapy. Methods: Using the Blue Diamond Global Collaborative Network, adult patients with CRC initiating first-line FOLFOX or FOLFIRI between 2015 and 2024 were identified. Patients were classified as GLP-1 RA users if they received a GLP-1 RA (e.g., semaglutide, liraglutide, dulaglutide) within 90 days before or after chemotherapy initiation, and non-users otherwise. Cohorts were 1:1 propensity score matched for age, sex, BMI, diabetes status, line of therapy, comorbidities, and baseline corticosteroid use. The primary endpoint was OS. Kaplan–Meier methods and Cox proportional hazards models were used for analysis. Results: After matching, 4,824 patients were included (2,412 per cohort). Baseline characteristics were well balanced (mean age 61.8 years; 46% female; mean BMI 31.2 kg/m²; 58% with diabetes). At a median follow-up of 24.6 months, patients receiving concomitant GLP-1 RAs demonstrated significantly improved overall survival compared with non-users. Median OS was 28.4 months among GLP-1 RA users versus 23.6 months among non-users (log-rank p <0.001). GLP-1 RA use was independently associated with improved OS (HR 0.82, 95% CI 0.76–0.89). Regarding safety outcomes, GLP-1 RA users experienced a lower incidence of neutropenia (18.9% vs 23.7%; RR 0.80, p =0.002) and reduced chemotherapy-induced neuropathy (14.2% vs 18.6%; RR 0.76, p =0.004). Subgroup analyses demonstrated consistent OS benefit across chemotherapy backbone: FOLFOX (HR 0.81) and FOLFIRI (HR 0.84), and the most pronounced effect in patients with BMI ≥30 kg/m². Sensitivity analyses restricting sustained GLP-1 RA exposure (>6 months) yielded similar results. Conclusions: In this large real-world cohort of patients with colorectal cancer, concomitant GLP-1 receptor agonist use was associated with improved overall survival and reduced chemotherapy-related toxicity. These findings suggest a potential adjunctive therapeutic role for GLP-1 RAs during active cancer treatment, potentially mediated through metabolic stabilization, reduced systemic inflammation, and improved treatment tolerance. Prospective studies are warranted to confirm these observations.

BACKGROUND:The poor prognosis of cholangiocarcinoma (CCA) is largely driven by rapid, asymptomatic disease progression, which usually results in a late diagnosis in the absence of established screening strategies. An early, cost-effective, and universally applicable risk assessment strategy would therefore be valuable. METHODS:We developed machine learning (ML) models on prospective, multimodal data from 487,495 UK Biobank (UKB) participants, of whom 649 developed CCA during follow-up. Data from England (80%) were utilised for ML development via five-fold cross-validation, and then all models were tested on withheld data from Scotland, Wales, and Newcastle (20%). Iterative ablation studies reduced inputs from >150 features across demographic data, lifestyle, health records, blood parameters, genomics, and metabolomics to models built on five and ten routinely available clinical parameters. These were externally validated in the Penn Medicine Biobank (PMBB; n = 2638; 28 CCA), All of Us Research Program (AOU; n = 330,433; 362 CCA), Japan Medical Data Centre Claims Database (JMDC; n = 8,425,522; 723 CCA) and TriNetX (n = 728,886; 1592 CCA). FINDINGS:We show that ML models integrating biliary-disease associated health records and Gamma glutamyltransferase can stratify risk of future CCA. Evaluation on the UKB test set as well as three independent cohorts revealed robust performance and generalisability across ethnicities. We achieved AUROCs of 0.71 [95% CI: 0.703-0.711], 0.77 [95% CI: 0.764-0.778 ], 0.796 [95% CI: 0.795-0.798] and 0.8 [95% CI: 0.794-0.805] for UKB, PMBB, AOU, and JMDC respectively, with respective AUPRCs of 0.014 [95% CI: 0.009-0.018], 0.042 [95% CI: 0.037-0.048], 0.038 [95% CI: 0.033-0.042] and 0.001 [95% CI: 0.001-0.001]. In AOU, application of the Youden J-optimised threshold yielded a number needed to screen of 79. Separate models for intra- and extrahepatic CCA did not improve performance. In line with the pathophysiology, performance declined for longer intervals between assessment and event. A group-level analysis in the TriNetX cohort revealed hazard ratios of up to 82.5 [95% CI: 26.4-257.96]. We provide extensive interpretability results and release all source codes used to develop the presented models. INTERPRETATION:We provide a comprehensive framework for early CCA risk stratification in the general population, identifying key predictors, and demonstrating the potential of data-driven models in personalised screening for hepatobiliary cancer. FUNDING:German Cancer Aid (grant #70115730), Junior Principal Investigator Fellowship programme of RWTH Aachen Excellence strategy.

Sensitivity analyses: correlates of severe sleep difficulties (≥7/10) among adult patients with cancer in uni- and multivariable logistic regression models (N = 20,416).

The Cancer Moonshot Program aims to reduce cancer mortality by 50% within 25 years through innovation in early detection, precision medicine and novel therapies. However, achieving this goal requires an equal emphasis on supportive oncology, which addresses symptom management, psychosocial needs, and quality of life. Despite its proven benefits, supportive care remains underfunded and often delayed in cancer treatment. This editorial highlights ongoing initiatives within the Moonshot framework, such as the integration of early palliative care and the expansion of telehealth services. Challenges, including provider awareness and reimbursement barriers, must be addressed to ensure equitable, patient-centred cancer care.

Gastrointestinal (GI) cancers are among the most common malignancies worldwide and impose a substantial symptom burden from diagnosis through survivorship. Despite advances in systemic therapies and surgical approaches, patients continue to experience undertreated symptoms, psychosocial distress, financial toxicity, and fragmented supportive care. This review examines how artificial intelligence (AI) may help transform GI supportive oncology from a reactive, episodic model to a proactive, continuous, and personalized approach. AI applications in GI supportive oncology are advancing along two related domains: (1) AI-enabled patient-reported outcome (PRO) tools, including real-time symptom monitoring, unsupervised symptom clustering, and AI-enhanced triage pathways; and (2) tumor-aware supportive care, including AI-driven radiomics for sarcopenia detection and multimodal prognostic models that inform supportive care needs. Systematic electronic PRO monitoring has been associated with improved survival and reduced acute care utilization, while AI-automated CT sarcopenia detection identifies muscle wasting that routine clinical documentation often misses. Important implementation challenges remain, including the black-box problem, algorithmic bias, privacy concerns, the digital divide, and regulatory uncertainty. Precision supportive oncology, integrating PRO-based symptom intelligence with imaging-derived risk stratification, has the potential to improve GI cancer care by making it more anticipatory and patient-centered. This review proposes a two-lane framework consisting of PRO-driven symptom intelligence and tumor-aware supportive care, unified by principles of privacy, explainability, and equity. Responsible adoption will require prospective validation, equitable design, and clinically interpretable systems.

A recent study by Zhu SS et al evaluated the prognostic value of the systemic immune-inflammation index and serum lactoferrin in older patients with colon cancer. While this work highlights the potential role of inflammation-based biomarkers in predicting survival, several methodological and analytical concerns limitations constrain its clinical applicability. These include a small sample size, a single-center observational design, a short follow-up duration, incomplete adjustment for confounding variables, and reliance on cut-off thresholds derived from receiver operating characteristic analyses, which increases the risk of overfitting. Moreover, the reported predictive accuracy was moderate, yet the findings were presented as clinically decisive, warranting caution in interpretation. Future studies should aim for multicenter, prospective cohorts with larger sample sizes, longer follow-up periods, and the integration of established prognostic indices and molecular biomarkers. Incorporating rigorous statistical validation and exploring biomarker dynamics over time would strengthen external validity. Addressing these issues could advance the development of reliable, inflammation-based prognostic tools and support individualized treatment strategies for elderly colon cancer patients.

Characteristics independently associated with greater odds of clinically significant sleep difficulties (≥5/10) among adult patients with cancer (N = 20,416) in a multivariable logistic regression model. *, age 80+; **, none; ***, none/mild; ****, 4–6 times a week or more; *****, breast.

11160 Background: Gut microbiota composition plays a critical role in mediating response to immune checkpoint inhibitors (ICIs). Antibiotic exposure has been associated with impaired ICI efficacy across tumor types; however, data specific to esophagogastric cancers remain limited. We evaluated the association between peritreatment antibiotic exposure and overall survival (OS) among patients with advanced esophagogastric cancer receiving ICIs in routine clinical practice. Methods: We conducted a retrospective cohort study using the TriNetX Global Collaborative Network. Adult patients with advanced or metastatic esophageal or gastric adenocarcinoma who received nivolumab- or pembrolizumab-based therapy between 2016 and 2024 were identified. Patients were categorized as antibiotic-exposed (receipt of systemic antibiotics within 60 days before or after ICI initiation) and non-exposed (no documented antibiotic exposure during the same period). Cohorts were 1:1 propensity score matched for age, sex, cancer subtype, Charlson comorbidity index, infection-related diagnoses, baseline corticosteroid use, and hospitalization within 30 days prior to ICI initiation. The primary endpoint was OS. Kaplan–Meier and Cox proportional hazards models were used for analysis. Sensitivity analyses evaluated the timing and duration of antibiotic exposure. Results: After matching, 3,024 patients were included (1,512 per cohort). Baseline characteristics were well balanced (mean age 63.7 years; 34% female; median Charlson comorbidity index 5). At a median follow-up of 19.8 months, antibiotic exposure was associated with significantly worse overall survival compared with non-exposure. Median OS was 10.6 months in antibiotic-exposed patients versus 14.3 months in non-exposed patients (log-rank p < 0.001). Antibiotic exposure was independently associated with inferior OS (HR 1.34, 95% CI 1.22–1.47). The negative association was most pronounced among patients with broad-spectrum antibiotic exposure (HR 1.41) and among those with antibiotic exposure within 30 days prior to ICI initiation (HR 1.38). Findings remained robust in sensitivity analyses excluding patients with documented sepsis or prolonged hospitalization. Conclusions: In this large real-world cohort of patients with esophagogastric cancer treated with ICIs, peritreatment antibiotic exposure was associated with significantly worse overall survival. These findings further support the role of the gut microbiome in modulating immunotherapy response and underscore the importance of judicious antibiotic use during ICI therapy.

Magnetic resonance imaging (MRI)-based habitat imaging is a promising non-invasive approach for assessing intratumoral heterogeneity and predicting responses to transarterial chemoembolization (TACE) in hepatocellular carcinoma. A recent multicenter study by Lv et al published in the World Journal of Gastroenterology combined MRI-derived habitat features with clinical data to develop a predictive model that achieved area under the curve values of 0.97, 0.91, and 0.93 across different cohorts, outperforming single-modality models. The ecological diversity index from Gaussian mixture model clustering offers a new measure of tumor ecosystem complexity. However, there are methodological concerns, including potential information leakage, confounding factors from mixed TACE methods, misclassification of modified Response Evaluation Criteria in Solid Tumors outcomes due to imaging variability, and limited inter-site radiomics harmonization. The low transportability of the standalone clinical model (area under the curve values = 0.54, accuracy = 0.41) underscores significant variability across centers. Future efforts should focus on prospective validation with standardized imaging, integration of multiparametric MRI, multi-lesion modeling, radiogenomic correlation studies, and decision-impact trials to assess whether model-guided patient selection can improve survival outcomes. Addressing these challenges is essential to establishing habitat imaging as a reliable tool for personalized TACE in hepatocellular carcinoma.

Gastric cancer (GC) has remained one of the leading causes of cancer-related deaths globally. The development of noninvasive biomarkers in cancer diagnosis and treatment has gained substantial traction in recent years. Recent evidence highlights hypercoagulation as a promising prognostic biomarker, particularly in locally advanced GC (LAGC) who underwent radical resection after neoadjuvant immunochemotherapy (NICT). A recent study by Li et al showed that hypercoagulation is a valuable prognostic indicator for patients with LAGC who have undergone radical resection following NICT. While the study addresses an important clinical issue and provides insightful findings, the present study offered valuable insights; the applicability of these findings was constrained by the retrospective design, the focus on a single center, and the small sample size of the existing studies. Additionally, vital confounders, such as preoperative comorbidities and systemic inflammation, are inadequately addressed. Future studies should focus on prospective multicenter trials, incorporating advanced predictive models such as machine learning algorithms to integrate coagulation markers with other clinical variables for personalized risk stratification. In addition, we are required to validate findings to examine the biological mechanisms correlating hypercoagulation to tumor progression. Integrating machine learning, comprehensive biomarker panels, and real-world data would allow the researchers to have personalized risk stratification, improve predictive accuracy, and optimize clinical decision-making. Finally, A multidisciplinary approach, including lifestyle interventions and imaging modalities, is essential to improve outcomes among patients with GC.