Citations

Abstract Purpose: Isocitrate dehydrogenase (IDH) 1/2–isoform inhibitors have clinical efficacy in IDH1/IDH2-mutated neoplasms. However, primary resistance and secondary resistance limit their therapeutic potential. LY3410738, an oral, brain-penetrant, dual IDH1/IDH2-mutated isoform-selective inhibitor, was designed to overcome resistance. Patients and Methods: This global, multicenter, open-label, phase I study of patients with IDH-mutant solid tumors evaluated LY3410738 as monotherapy (dose escalation) for advanced solid tumors in combination with cisplatin–gemcitabine (CISGEM) for newly diagnosed cholangiocarcinoma or with durvalumab for relapsed/refractory cholangiocarcinoma (dose expansion; NCT04521686). Primary objectives were the maximum tolerated dose, recommended phase II dose, and preliminary antitumor activity. Safety, pharmacokinetics, inhibition of D-2-hydroxyglutarate, and ctDNA were assessed. Results: Overall, 119 patients received LY3410738 alone (N = 94) or in combination with CISGEM (N = 19) or durvalumab (N = 6). No dose-limiting toxicities were observed; the maximum tolerated dose was not determined. Common adverse events included nausea, vomiting, and decreased appetite. Overall response rates of 5.2% and 11.1% and disease control rates of 56.9% and 63.0% were observed for patients with relapsed/refractory IDH1- or IDH2-mutant cholangiocarcinoma or IDH1-mutant glioma, respectively. D-2-hydroxyglutarate normalization was rapid and durable. In dose-expansion cohorts, combination treatments were tolerable, with one dose-limiting toxicity in the durvalumab cohort. LY3410738 plus CISGEM demonstrated a response rate of 42.1%, a median duration of response of 8.1 months, and a median progression-free survival of 10.2 months for patients with newly diagnosed IDH-mutant cholangiocarcinoma. Conclusions: LY3410738 demonstrated largely cytostatic antitumor activity in IDH1- or IDH2-mutated cholangiocarcinoma and IDH1-mutated gliomas. LY3410738 plus CISGEM exhibited favorable antitumor activity in patients with treatment-naïve IDH-mutated cholangiocarcinoma, warranting further exploration as a treatment strategy.

Objective To establish a framework for validating candidate biomarkers of cerebral small vessel diseases (SVD) associated with cognitive impairment and characterize individuals enrolled by the MarkVCID2 consortium under this framework. Methods Participants age 60 to 90 years were enrolled across 17 MarkVCID2 sites. Recruitment was targeted to enrich in cognitive symptoms (mild dementia, mild cognitive impairment, subjective cognitive decline), defined risk factors (diabetes mellitus, advanced hypertension), and Black/African American, White, and Hispanic/Latino subgroups. Enrolled participants underwent baseline visits that included cognitive testing, multimodal magnetic resonance imaging (MRI), and biofluid collection. Provisional risk for SVD‐related cognitive decline was estimated primarily by baseline cognitive symptoms plus SVD risk factors. Adjudicated risk status was estimated by cognitive symptoms plus presence of moderate‐to‐severe white matter hyperintensities, microbleeds, or lacunes on baseline MRI. Results MarkVCID2 enrolled 1883 individuals age 73.4 ± 7.5 years, 65.0% female, 24.2% Hispanic, and 27.1% non‐Hispanic Black. Among enrollees, 44.8% were provisionally designated high‐risk. After baseline MRI, 48.5% were categorized as adjudicated high‐risk status, with substantial recategorization both from low‐ to high‐risk (primarily because of MRI lesions without SVD risk factors) and high‐ to low‐risk (primarily suspected cognitive impairment at screening not confirmed by baseline testing). Interpretation MarkVCID2 baseline data indicate successful enrollment of diverse individuals enriched in factors associated with SVD‐related cognitive decline. Changes over 3 years of longitudinal follow‐up will be analyzed to validate the candidate biomarkers for 2 projected contexts of use: subject selection (identifying likelihood of future SVD progression) and study outcome (efficiently measuring SVD progression). ANN NEUROL 2026;99:449–458

Abstract Objective Gastrointestinal (GI) symptoms are common in systemic mastocytosis (SM). We hereby report the clinicopathologic and molecular features of GI mastocytosis. Methods The study includes 104 patients with suspected SM. Of 258 GI biopsy ­specimens, 33 (20 patients, 19%) were mastocytosis-positive, with 19 (16 patients) initially missed. Results Tryptase (n = 29) was weakly positive/negative in two-thirds of the mastocytosis-positive GI biopsy specimens. Additional immunohistochemistry (n = 23) showed positive mast cell expression for CD30 (n = 2), CD123 (n = 7), and PD-L1 (n = 12), as well as increased PD-1–positive cells (n = 4). Sixty patients had positive bone marrow (BM) for SM (SM-BM+), including 19 with positive GI biopsy specimens (SM-GI+). Almost all (43/44) SM-BM– patients were SM-GI–. The SM-GI vs SM-BM status showed high positive predictive value (95%) and specificity (98%). Patients with SM with mastocytosis-positive vs mastocytosis-negative GI biopsy specimens had higher serum tryptase levels (P = .04). KIT D816V mutation was detected in 7 of 13 and 12 of 13 mastocytosis-positive GI biopsy specimens using allele-specific polymerase chain reaction and droplet digital polymerase chain reaction (ddPCR), respectively. Conclusions GI mastocytosis is highly predictive of SM in BM; however, most SM-BM+ patients are SM-GI–. The SM-BM– patients are very unlikely to be SM-GI+. Because GI neoplastic mast cells are often tryptase negative, diagnostic evaluation should include CD117 and CD25 immunohistochemistry, as well as KIT D816V mutation analysis by ddPCR as needed.

ABSTRACT Survival prediction models in essential thrombocythemia (ET) include the International Prognostic Scoring System (IPSET) and the more recently introduced triple‐A (AAA) prognostic score. The latter enlists age and absolute neutrophil (ANC) and lymphocyte (ALC) counts as risk variables. In the current study, a Mayo Clinic discovery cohort of 658 patients with ET was used to identify AAA‐independent risk variables. Accordingly, multivariable analysis‐derived HRs (95% CI) were 15.7 (8.4–29.5) for age > 70 years (8 points); 4.2 (2.3–7.5) for age 50 to 70 years (2 points); 1.8 (1.2–2.5) for ANC ≥ 8 × 10 9 /L (1 point); 1.4 (1.03–1.9) for ALC < 1.7 × 10 9 /L (1 point); 1.8 (1.2–2.6) for absolute monocyte count (AMC) ≥ 0.5 × 10 9 /L (1 point); 1.8 (1.2–2.3) for male sex (1 point); 1.8 (1.3–2.4) for arterial hypertension (1 point); and 1.6 (1.2–2.3) for arterial thrombosis (1 point). HR‐weighted scoring enabled a 4‐tiered risk classification: ultra‐low (0–1 points; N = 94; median survival 42.7 years), low (2–4 points; N = 297; 23 years), intermediate (5 points; N = 66; 17.3 years), and high (6–14 points; N = 201; 10.8 years). Time‐dependent predictive performance at 20/25 years favored AAA + (AUC 0.92/0.91) vs. AAA (0.86/0.86) vs. IPSET (0.81/0.84). The AAA + risk model was subsequently validated by two external cohorts from Israel ( N = 5968) and Italy ( N = 682). In the cohort from Israel, disease‐specific mortality was assessed by comparing observed survival to an age‐ and sex‐matched reference population, which suggested near‐normal life expectancy in ultra‐low risk patients. The current study highlights host‐related factors as the primary determinants of longevity in ET and provides a composite risk score (AAA + ) that is based on complete blood count‐derived parameters and host‐related factors. Predictive performance of the new model was shown to be superior to that of IPSET and AAA.

Abstract Purpose To describe the creation and clinical deployment of an integrated stand‐alone hybrid automated chart review platform that is comprised of a database, oncology information system (OIS) interfaces, and a user interface (UI). Methods A consensus checklist was developed to homogenize the practices of clinical physics staff and physics residents for all plan types. Critical review of the single checklist's items led to the creation of a new concept, the “plan attribute,” which permits specialization of the final checklist based on the characteristics of a particular plan. Only relevant and applicable tests are automatically populated to form a plan checklist based on plan attributes. Each populated checklist in this hybrid automation platform includes elements of full automation, steps or functions that use automation to augment a human input or effort, as well as steps completed by humans. Logging and categorizing of deficiencies found during the chart check was also implemented. Results Chart check data was analyzed for an over 4‐year time span starting from the clinical deployment of the tool in October 2020. This analysis included a total of 427 073 tests spread among 7882 initial chart checks. The recorded deficiencies at three triage levels showed 7116 minor errors, 679 major errors, and 71 plan rejections. The plan rejection level is the highest chart deficiency, which required the plan to be rejected and sent back for serious remediation and/or new plan generation. Conclusion This report describes the successful development and implementation of a hybrid‐automated chart checking program. The software leverages modern database and software design to improve the per case performance and experience of a multi‐user group. Chart check database permits high‐level review and improvement in all aspects of plan check and user performance.