Pamela L. Kunz

Introduction: MET (c‐MET) is a receptor tyrosine kinase implicated in numerous cancers, including pancreatic neuroendocrine tumours (pNETs), by promoting cell proliferation, survival, invasion and angiogenesis. Recognizing its oncogenic potential, there is significant interest in MET‐targeted therapies for malignancies like pNETs, which often develop treatment resistance. Immunohistochemistry (IHC) has become a practical method for detecting MET overexpression in cancers. This study evaluates MET expression in pNETs by IHC and assesses its correlation with prognostic variables and survival outcomes. Methods and results: Tissue microarrays containing well‐differentiated neuroendocrine tumours from the gastrointestinal tract were analysed. The study included 125 pNET cores from 112 patients after application of inclusion criteria. MET expression was determined using the H‐score system. Different variables were assessed for H‐score distribution and cross‐tables. Survival analyses were conducted based on progression‐free survival and overall survival. Positive MET expression was found in 83.5% of cases. Higher MET H‐scores were seen in patients with lymphovascular invasion (LVI), distant metastases and higher tumour grade ( P < 0.05). When assessing different variables for higher MET H‐scores, a significant association emerged at the 150‐cut‐off‐point for LVI, perineural invasion, radiological evidence of progression and overall survival. For survival analysis, at a MET H‐score threshold of 200, high MET expression was significantly associated with shorter progression‐free survival (mean 8.7 versus 13.4 years, P < 0.05) and overall survival (mean 3.6 versus 7.7 years, P < 0.05). Conclusion: Elevated MET expression is linked to adverse histopathological features and worse clinical outcomes in pNET. Standardizing MET IHC evaluation is critical as anti‐MET therapies develop, and identifying patients likely to benefit from these treatments remains essential.

Summary: This commentary on a cohort study of patients with uncommon DPYD variants resulting in increased toxicities highlights the importance of expanding the current DPYD testing profile, the limitations of current testing, and the critical need to consider patients of African ancestry who can carry rare yet extremely toxic DPYD variants. See related article by Nguyen-Hoang et al., p. XX .

PURPOSE: To assess the generalizability of cancer clinical trials by comparing trial enrollment with baseline cancer populations across three National Cancer Institute (NCI)–designated cancer centers and to identify institutional barriers and best practices. METHODS: We conducted a retrospective analysis (2020-2024) of three NCI-designated Comprehensive Cancer Centers using Epic electronic health records and Clinical Trial Management Systems. Baseline cancer populations were compared with enrolled patients across solid tumors and hematologic malignancies by age, race/ethnicity, language, geography, and insurance status. We additionally evaluated the impact of an automated clinical trial prescreening tool implemented at Yale Cancer Center on enrollment demographics. RESULTS: Among 311,186 patients with solid tumor and 62,988 with hematology malignancies, non–English-speaking and Medicaid-insured populations were consistently underrepresented. Vanderbilt-Ingram Cancer Center enrolled the largest cohorts (12,053 solid tumor; 2,214 hematology) and demonstrated strong rural representation (23.2% enrolled v 17.8% baseline in solid tumors) but limited enrollment of non-English speakers (0.7% v 2.3% baseline in hematology). Mays Cancer Center at UT Health San Antonio achieved the highest racial/ethnic (68.5% v 57.5% baseline) and Medicaid-insured representation (28.3% v 10.4% baseline) in hematology despite smaller volumes. Yale Cancer Center maintained strong enrollment of older adults but underrepresented young adults; implementation of automated prescreening increased young adult consent (1.2%-5.2%) and minority participation (18.2%-23.8%) in solid tumors. CONCLUSION: Persistent enrollment disparities—particularly among non–English-speaking and Medicaid populations—were observed across institutions, alongside distinct institutional strengths. Technology-enabled interventions and cross-institutional knowledge sharing targeting language, socioeconomic, and geographic barriers are critical to improving equitable trial participation in precision oncology.

PURPOSE: Women occupy a minority of academic leadership positions despite increasing representation in the physician workforce. Similarly, women remain underrepresented as academic conference presenters, an important factor for career advancement. We examined whether there were gender disparities in opportunities to present original research at the ASCO Annual Meeting. METHODS: We retrospectively reviewed oral original research, educational, and discussant presentations at the ASCO Annual Meetings from 2018 to 2021. Presenters were identified as first author, senior author, or ASCO-appointed (chair, discussant, or speaker). Presenter-identified gender was unavailable; binary gender was determined by presenter name, pronouns, video files, and institutional websites. Presenter gender distributions were summarized descriptively by nominal levels for each third variable with corresponding odds ratios (ORs) for each nominal level. Common ORs were estimated for each third variable if the Breslow-Day test was not significant, with no adjustments for P values. RESULTS: We reviewed 4,267 video presentations, divided into original research (n = 2,079) and ASCO-appointed (n = 2,188). Women represented 37% of first authors (OR, 0.68 [95% CI, 0.60 to 0.76]) and 28% of senior authors (OR, 0.44 [95% CI, 0.39 to 0.50]), compared with 47% of ASCO-appointed presenters. Women were significantly more likely to have an ASCO-appointed role than a first or senior author role, even after adjusting for conference year, session type, session area, academic rank, and geographic region. CONCLUSION: Gender disparities persist in opportunities to present original research at the ASCO Annual Meeting. Women were less likely to present research as first or senior author and were more likely to have an educational or discussant role. As high-profile original research can elevate careers, examining factors contributing to this disparity may suggest approaches to address gender leadership gaps in oncology.

PURPOSE: Cancer clinical trial enrollment remains critically low at 5%-7% of adult patients despite exponential growth in available trials. Manual patient-trial matching represents a fundamental bottleneck, whereas current artificial intelligence (AI) and machine learning patient-trial matching systems lack data standardization and compatibility across health systems. We developed and validated a semiautomated clinical trial patient matching (CTPM) tool to improve recruitment efficiency and scalability. METHODS: We created a hybrid rules–based and natural language processing (NLP)–based pipeline that automatically screens patients using structured and unstructured electronic health record data standardized to the Observational Medical Outcomes Partnership (OMOP) common data model. CTPM performance was first evaluated on one metastatic colorectal cancer (CRC) trial by comparing CTPM accuracy and efficiency to manual chart review. Following the single-trial validation, we then implemented the system across 29 clinical trials spanning multiple cancer specialties and phases. RESULTS: For the single CRC trial, CTPM achieved 94% retrospective and 88% prospective accuracy, matching gold standard clinical chart review with 100% sensitivity. Implementation reduced chart review workload 10-fold and screening time by 41% (3.1 to 1.8 minutes per chart) for those patients who did undergo review. Since September 2022, the system has screened 98,348 patients across 29 trials, identifying 825 eligible candidates and facilitating 117 patient enrollments with 9%-37% consent rates. CONCLUSION: This AI and NLP tool demonstrates improved efficiency in clinical trial recruitment by enabling research teams to focus on qualified candidates rather than exhaustive chart reviews. The OMOP-based framework supports scalability across health systems, with potential to address enrollment challenges that limit patient access to clinical trials.

ASCO Guidelines provide recommendations with comprehensive review and analyses of the relevant literature for each recommendation, following the guideline development process as outlined in the ASCO Guidelines Methodology Manual . ASCO Guidelines follow the ASCO Conflict of Interest Policy for Clinical Practice Guidelines . Clinical Practice Guidelines and other guidance (“Guidance”) provided by ASCO is not a comprehensive or definitive guide to treatment options. It is intended for voluntary use by clinicians and should be used in conjunction with independent professional judgment. Guidance may not be applicable to all patients, interventions, diseases or stages of diseases. Guidance is based on review and analysis of relevant literature and is not intended as a statement of the standard of care. ASCO does not endorse third-party drugs, devices, services, or therapies and assumes no responsibility for any harm arising from or related to the use of this information. See complete disclaimer in Appendix 1 and 2 (online only) for more. PURPOSE: To develop a clinical practice guideline and recommendations for symptom management of patients with well-differentiated grade 1 to grade 3 metastatic gastroenteropancreatic neuroendocrine tumors. METHODS: ASCO convened an Expert Panel to develop a clinical practice guideline by reviewing the literature for relevant guidelines, systematic reviews, randomized controlled trials (RCTs), and observational studies to develop recommendations for clinical practice. RESULTS: The literature review identified eight guidelines, 19 systematic reviews, and three RCTs that informed the development of guideline recommendations. RECOMMENDATIONS: Recommendations are included for carcinoid syndrome, carcinoid heart disease and carcinoid crisis, and functional pancreatic neuroendocrine tumor syndromes. Recommendations are provided for surgical management, liver-directed therapy, and systemic therapy options, as well as palliative care. Limited guidance is provided for sequencing of interventions. Additional information is available at www.asco.org/gastrointestinal-cancer-guidelines .

PURPOSE: Gastric cancer (GC) in the United States is often diagnosed at a distant stage, resulting in poor survival. Despite this, no systematic early detection programs exist. This study focuses on gastric adenocarcinoma (GA), the most common and aggressive GC subtype, across seven states with large Asian and Hispanic populations—groups at elevated risk. We examined noncardia GA incidence, stage at diagnosis, survival outcomes, and hazard ratios (HRs) to identify geographic and racial disparities and inform targeted prevention strategies. METHODS: Using SEER 22 data, we analyzed GA cases diagnosed from 2010 to 2019 in seven states: California, New York, New Jersey, Texas, Connecticut, Georgia, and New Mexico. Cases were categorized by tumor location, stage, and race/ethnicity. Median survival, 5-year survival rates, and adjusted HRs were estimated. RESULTS: GA was predominantly diagnosed at the distant stage (cardia: 37.9%, noncardia: 39.1%), with consistently poor survival. For noncardia GA, 5-year survival at the localized and regional stages ranged from 46.2% to 73.9% and 23.7% to 40.3%, respectively; distant-stage survival ranged from 2.2% to 5.9%, with a median survival of 4.6 to 7.1 months. Compared with California, New York and New Jersey showed better survival at earlier stages, while Texas and New Mexico fared worse. Racial disparities were evident: non-Hispanic Black patients had the poorest survival, and non-Hispanic Asians had the best. CONCLUSION: This study highlights striking racial and geographic disparities in GA outcomes. The 5-year survival rate for GA was 26%—substantially lower than the 36% rate typically cited for GC overall. These findings underscore the need for risk-informed screening and early detection efforts, particularly in underserved and high-risk populations.