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Importance Total pancreatectomy (TP) is indicated for advanced pancreatic cancer or multifocal tumors. Furthermore, TP may be performed to avoid the risk of pancreatic fistula in selected patients to improve the perioperative risk profile. Objective To define reference values for TP based on a low-risk cohort treated at expert centers. Design, Setting, and Participants This multicenter study analyzed outcomes from patients undergoing primary TP for malignant or benign lesions from 25 international expert centers from January 2017 to November 2023. Low-risk patients undergoing TP (LR-TP) were without vascular resections or significant comorbidities. Exposures TP. Main Outcomes and Measures Twenty reference values were derived from the 75th or the 25th percentile of the median values of all centers. Outcomes of LR-TP were compared with a cohort of TP with vascular resection, TP due to high-risk pancreatic anastomosis, and the benchmark values for low-risk pancreatoduodenectomy. Results Of 994 patients, 333 (33.5%; median [IQR] age, 66 [58-72] years; 171 male [51.4%]) qualified as the LR-TP cohort. Reference values included blood loss (≤1000 mL), major complications (≤37%), 3-month postoperative mortality (<6%), and retrieved lymph nodes (≥29). Compared with TP with vascular resections, reference cutoffs were not met for major complications (51% vs LR-TP ≤37%) and 90-day mortality (11% vs LR-TP ≤6%). For TP due to high-risk anastomosis, failure to rescue rate (38% vs ≤6%) and 90-day mortality (11% vs LR-TP ≤6%) were not met. Compared with pancreatoduodenectomy, reference values for postoperative mortality were 3 times higher for LR-TP (≤2% vs ≤6%) and less for resected lymph nodes (≥16 vs ≥29). Conclusions and Relevance This case-control study provided global reference values for TP, indicating significantly higher postoperative morbidity and mortality compared with pancreatoduodenectomy. Perioperative morbidity of TP was especially increased in patients with vascular resections. These reference values can serve for quality control of pancreatic surgery.

Abstract BACKGROUND While most meningiomas are classified as low-grade tumors with indolent behavior, a subset is characterized by a more aggressive clinical course and patients undergo repeated resections and courses of radiation. Once these therapies fail, prognosis is poor and progression-free survival (PFS) rates at 6 months (PFS-6) are estimated to only be 43.6% for WHO grade 1 and 38% for WHO grade 2/3 meningiomas. Effective medical therapies are limited. Somatostatin receptor 2 (SSTR2) is expressed in a majority of meningiomas and represents a suitable treatment target. [177Lu]Lu-DOTA-TATE (177Lu-Dotatate) is an SSTR2-targeted radioligand therapy, established as standard of care in the treatment of certain neuroendocrine tumors. Two ongoing non-randomized studies of 177Lu-Dotatate in meningiomas have reported encouraging efficacy compared to historical benchmarks. METHODS/STUDY DESIGN The MOMENTUM-1 study (RTOG 3523, NCT#06955169) is a multicenter, randomized, open-label study of 177Lu-Dotatate in adult patients with progressive intracranial WHO grade 1-3 meningiomas. Up to 130 eligible subjects are randomized in a 2:1 fashion to 177Lu-Dotatate at 7.4 GBq (200 mCi) every 4 weeks for 4 (+2 optional) doses or standard of care (SOC) medical therapy as defined by the protocol and deemed appropriate by the local investigator. Treatment responses are assessed by gadolinium-enhanced MRI brain and [68Ga]Ga-DOTA-TATE (68Ga-Dotatate) PET imaging. At time of progression, cross-over from the SOC to the interventional treatment arm is allowed. The primary endpoint is PFS. Secondary endpoints include PFS-6, OS-12, OS, response assessments (ORR, DCR), safety/tolerability, and patient-reported outcomes. RESULTS/CONCLUSION MOMENTUM-1 is a multicenter, randomized, open-label, phase II study of 177Lu-Dotatate in adult patients with progressive WHO grade 1-3 meningioma. This clinical trial is expected to start enrolling patients in the United States in the third quarter of 2025. Details on study design, eligibility criteria for subject enrollment and study site eligibility criteria will be presented.

Abstract Computer vision now enables deep learning models to link histopathologic features to molecular features in a quantitative manner not previously achievable by human pathologists. However, human interpretability is often limited. We trained a deep neural network to predict gene expression from digital whole slide images (WSIs) using 848 central nervous system (CNS) tumors with paired WSI and RNA-sequencing data. We used inferred RNA expression levels as a surrogate for protein expression of the CNS tumor lineage markers GFAP, OLIG2, and SSTR2, as well as the proliferation marker MKI67 (Ki67). We established thresholds for categorizing the inferred expression levels as positive or negative based on levels observed in cross-validation testing in select tumor types to approximate routine clinical interpretation of immunohistochemical (IHC) staining. We tested the sensitivity and specificity of our ‘virtual’ IHC on an independent, multi-institutional cohort of over 2,000 CNS tumors with objective diagnostic labels derived from DNA methylation-based tumor classification. As a dichotomous variable, inferred GFAP expression showed a sensitivity of 74% and a specificity of 99% as a glial marker in a cohort of gliomas and meningiomas. In the same cohort, OLIG2 showed a sensitivity of 75% and a specificity of 97% as a glial marker, while SSTR2 showed a sensitivity of 83% and a specificity of 97% as a marker of meningioma. In a cohort of ependymomas and gliomas, virtual IHC for OLIG2 showed a sensitivity of 75% and a specificity of 82% in distinguishing ependymomas from gliomas. Finally, in a cohort of gliomas, inferred expression of MKI67 demonstrated a trend consistent with what would be expected by actual IHC, with increasing MKI67 expression with increasing tumor grade. Our model provides the basis for a human interpretable and clinically applicable deep neural network to aid human pathologists in the diagnosis and grading of CNS tumors.

Abstract Molecular testing has become critical components in the diagnostic classification of the central nervous system (CNS) tumors. However, these methods require substantial resources, limiting accessibility for many patients. Recent advances in artificial intelligence (AI) and computer vision empower deep learning models to infer molecular features from histopathology images, which may often be more readily available than molecular testing, to classify CNS tumors. We trained pan-CNS tumor models to predict DNA methylation and gene expression from whole-slide images (WSIs). These molecular predictions were then used in a hierarchical machine learning framework, termed Neuropath-AI, to predict nine broad tumor families and 52 tumor types using a large diverse cohort of 5,715 histopathology samples, of which 2,988 had paired DNA methylation profiling and 848 had paired RNA-sequencing. We evaluated Neuropath-AI on another large independent multi-institutional cohort of 5,516 CNS tumors, for which Neuropath-AI predicted tumor class with an associated confidence score. Neuropath-AI designated 46% of test samples as predictable with high-confidence, which it then accuracy classified in 97% of samples. It made moderate-confidence (and above) predictions for 87% of test samples, for which it achieved a diagnostic accuracy of 80% for the top-1 prediction and 86% accuracy for a top-2 predictions. A comparison with human neuropathologists showed that Neuropath-AI is comparable at classifying tumors. A second test showed that human neuropathologists were more accurate when the Neuropath-AI classifier results were provided to them, testifying to the potential translational benefit of integrating AI classification tools into the pathologist’s workflow. Our model provides the basis for a clinically applicable deep learning assistant to improve human efficiency and accuracy of CNS tumor diagnosis. The model will be made publicly available and can be readily implemented to assist human pathologists in clinical workflows, in further expanded prospective studies.

Abstract The prognosis for patients afflicted with GBM has remained dismal in spite of decades of investigations, which speaks to the need to identify targets that drive essential functions in GBM, using well-tolerated, brain permeant inhibitors. Here we report our studies of MT-125, a small molecule inhibitor of non-muscle myosin IIA and IIB. MT-125 has high brain penetrance and an excellent safety profile; blocks GBM invasion and cytokinesis; and prolongs survival in murine GBM models. By impairing mitochondrial fission, MT-125 increases redox stress and induces DNA damage and ferroptosis; and these effects explain why this drug synergizes with radiotherapy in prolonging survival in murine GBM models. MT-125 also induces oncogene addiction to receptor tyrosine kinase (RTK) signaling through a mechanism that is also driven by redox stress, and it also synergizes with FDA-approved RTK and MAP Kinase pathway inhibitors in vitro. Furthermore, MT-125 also synergizes with an FDA approved, RTK inhibitor in vivo, with the combination producing long-term, tumor free survival in an aggressive, preclinical murine model of GBM. MT-125’s long-term administration is well-tolerated at doses well above what is predicted to be therapeutic in multiple mammalian species. These data provide a powerful rationale for the clinical development of NMII targeting therapeutics to treat cancer and demonstrates that MT-125 has strong clinical potential for the treatment of GBM.

Abstract IDH-wildtype diffuse astrocytic gliomas with lower-grade histological features alongside specific genomic alterations (e.g., TERT promoter mutation, EGFR amplification, gain Chr7/loss Chr10) are presently diagnosed as glioblastoma, IDH-wildtype (GBM) under WHO 2021 criteria. Previous analyses categorized these into “early/evolving” or “surgically undersampled” GBMs. However, it remains unclear whether these tumors share identical clinical and prognostic features with histologic GBM. Data from IDH-wt molecular GBMs across six institutions were aggregated. Astrocytic IDH-wt tumors of any grade that lacked necrosis or microvascular proliferation on initial histopathology yet exhibited molecular alterations consistent with WHO 2021 GBM diagnosis, were included. Recursive partitioning analysis (RPA) was used to categorize patients into risk groups based on overall survival (OS). Among the 264 patients included, the median age was 60 years (IQR: 51-67), with 162 (61%) being male. Additionally, 210 (80%) were diagnosed since 2016, and 216 (82%) received chemoradiation plus adjuvant temozolomide (GBM-SOC). The median follow-up period was 3.9 years (95% CI: 3.4, 4.6). Identified univariate risk factors for worse survival included older age, biopsy-only status, EGFR amplification, absence of initial adjuvant treatment, low post-operative KPS, and tumor histologic grade of 3. RPA divided patients into four distinct survival groups (p<0.0001). The “best” risk group comprised lower grade (<=2) tumors (n=58, median OS (mOS): 40 months (95% CI: 33, NA)). The “second best” group included Grade 3 patients receiving GBM-SOC without steroids during initial RT (n=139, mOS: 25 months (95% CI: 22, 28)). The “second worst” group encompassed Grade 3 patients who were on steroids during initial RT while receiving GBM-SOC (n=38, mOS: 15 months (95% CI: 13, 20)). The “worst” group contained Grade 3 tumors that had not undergone SOC (n=29, mOS: 9 months (95% CI: 4, 26)). These data show that histologic features and treatment are strong indicators of patient outcomes.

Abstract Secondary central nervous system lymphoma (SCNSL) is defined as the diagnosis of CNS lymphoma diagnosed concurrently with systemic lymphoma or after prior treatment. Due to the poor prognosis associated with SCNSL, the lack of randomized trial data, and the need for international consensus guidelines, there is a high unmet need for effective therapy options for SCNSL. Here we present safety and efficacy data on 2 SCNSL patients treated with the combination of emavusertib and ibrutinib. Both patients had directly progressed on their prior BTKi treatment. One patient achieved an unconfirmed complete response (CRu) and remained on treatment for over 4 mos, while the other patient maintained stable disease (SD) with a 38% reduction in disease burden from baseline and was on treatment for more than 8 mos. The patient with a durable SD, who received 5 prior lines of therapy along with an ASCT, presented with 3 related AEs Grade ≥ 3 that were reversible and manageable. These included elevated ALT, AST, and bilirubin levels that resolved. The patient received emavusertib 300 mg BID and ibrutinib 560 mg QD. The CRu patient received 6 prior lines of therapy and experienced CK elevation, fatigue, hypoglycemia, sepsis, urinary retention, neutropenia, and constipation that resolved with either a dose reduction and/or supportive care. The initial dose for this patient was 150 mg emavusertib BID and ibrutinib 560 mg QD. Subsequently, the dose of emavusertib was decreased to 150 mg BID due to Grade 4 neutropenia, then increased to 200 mg AM and 150 mg PM once resolved. This patient achieved CRu within 60 days on treatment. The 2 patients presented here are supportive data for using the combination of emavusertib and ibrutinib in SCNSL.

Abstract BACKGROUND STELLAR was a phase III randomized, open-label trial of eflornithine (ornithine decarboxylase inhibitor) with lomustine versus lomustine alone in patients with recurrent anaplastic astrocytoma (AA). We previously reported an overall survival (OS) and progression free survival (PFS) of the combination in the patients with grade 3 IDH-mutant astrocytoma. Here we report updated OS and PFS outcomes based on additional molecular classification and blinded independent central review (BICR). METHOD Eligibility included: age ≥ 18 years, AA (2016 WHO criteria) with first recurrence ≥ 6 months after radiation, KPS ≥ 70, and no imaging findings consistent with grade 4 glioblastoma. Patients received eflornithine (2.8 g/m2 TID Q 2/3 weeks) with lomustine (90 mg/m2 Q 6 weeks) (Arm A) or lomustine alone (110 mg/m2 Q 6 weeks) (Arm B). Primary endpoint was OS. RESULTS Updated molecular data resulted in re-classification of the 343 AA patients enrolled into 3 WHO 2021 defined tumor subtypes, 196 tumors were IDHmut, CDKN2A/B intact, consistent with diagnosis of astrocytoma, IDHmut, WHO grade 3, 33 tumors had CDKN2A/B loss consistent with astrocytoma, IDHmut, WHO grade 4, 106 tumors were IDHwt consistent with diagnosis of glioblastoma, IDHwt, WHO grade 4. Updated results strengthen initial conclusion that eflornithine plus lomustine resulted in significant survival benefit in the astrocytoma, IDHmut, WHO grade 3 group (mOS 34.9 vs, 23.5 months, HR = 0.64, stratified log rank p =0.0136). PFS with eflornithine was also improved (15.8 vs, 7.2 months, HR = 0.57, stratified log rank p =0.0113). BICR demonstrated a high correlation between investigator and centrally determined PFS (p=0.0305), and high correlation between OS and PFS (p=.0001). CONCLUSION The clinically meaningful OS and PFS benefits observed with eflornithine in the molecularly defined 2021 WHO CNS grade 3 astrocytomas is further confirmed and expanded based on additional molecular classification and BICR of PFS.

Abstract Pediatric high-grade gliomas (pHGG) are aggressive primary brain neoplasms with a dismal prognosis, making them the leading cause of brain tumor-related deaths in children. pHGGs occur in specific anatomical locations at specific ages underscoring their origin in neurodevelopment and the critical importance of the brain tumor microenvironment. Many pHGGs originate from oligodendroglial precursor cells (OPCs) and, like OPCs, neuronal activity promotes the proliferation of pHGGs. Neuronal activity drives pHGG growth through electrochemical communication with pHGG cells. In turn, pHGGs increase neuronal excitability and remodel functional neural circuits. The interconnected network of glioma cells and neurons is fundamental to pHGG progression. Using single-nuclei RNA sequencing of mice harboring murine H3K27M-altered Diffused Midline Glioma (DMG), we observed gene expression changes indicating an increase in axonogenesis processes in glioma-associated neurons (GANs), primarily driven by EphA signaling. EphA4, EphA5, and EphA7 are overexpressed in GANs while the ligand, EphrinA1, is overexpressed in H3K27M gliomas. Performing in vitro neurite outgrowth and co-culture assays, we observed increased axonogenesis in neurons in the presence of DMG cells and DMG-conditioned media. We developed a two-color in vivo imaging method to study neuron-glioma interactions over time in freely behaving mice enabling us to record the frequency, pattern, and synchronicity of calcium transients in neurons, glioma cells, and their coactivity, giving us a comprehensive view of the changes in neuron-glioma circuit dynamics over time. We have observed increasing neuronal activity and synchronicity throughout the disease. We have also observed that gliomas also exhibit increased levels of activity and synchronicity as the tumor progresses. We verified our findings through longitudinal in vivo local field potential recordings, finding an increase in all power bands, especially in high-gamma activity over time. Ongoing experiments will test how glioma-induced axonogenesis contributes to the observed evolution of malignant circuit dynamics over time. Taken together, our data shows as gliomas progress, the neuron-glioma malignant circuitry evolves through axonogenesis driven by EphA signaling.

Abstract IDH-wildtype glioblastoma (GBM) is the most malignant primary adult brain tumor, with a five-year survival rate below 5%. Despite maximal treatment, including surgical resection, radiotherapy, and temozolomide (TMZ), recurrence is universal, driven by profound intratumoral heterogeneity, diffuse invasion, and therapy resistance. A hallmark of IDH-wildtype GBM is frequent alteration of epidermal growth factor receptor (EGFR), including amplification (50%), the EGFRvIII deletion variant (25%), and extracellular missense mutations such as G598V and A289V (10–15%). These missense mutations increase ligand affinity and receptor activity, yet their downstream signaling consequences and role in shaping the tumor phenotypes remain poorly defined. Recent pathway-based subclassifications identified four subtypes in IDH-wildtype GBM. Notably, neuronal (NEU) and glycolytic/plurimetabolic (GPM) subtypes predominate the invasive tumor margins. NEU programs are enriched in synaptic and neurodifferentiation signals, while GPM programs are associated with metabolic adaptation, angiogenesis, and immune evasion. Here, we show EGFR-G598V and EGFR-A289V mutations differentially regulate these invasive subtypes identities. Transcriptional analysis reveals EGFR G598V upregulates metabolic and inflammatory pathways consistent with the GPM phenotype, while EGFR A289V activates genes involved in neuronal differentiation and synaptic function, aligning with the NEU subtype. Phosphoproteomics and kinase-substrate analysis further uncovered distinct kinases to be functionally activated/inhibited in EGFR A289V-expressing cells and G598V cells. Mechanistic studies revealed EGFR A289V induces sustained EGFR phosphorylation at Y992, activating PLCγ2 via the SRC-family kinase LCK. This cascade drives calcium release, CAMK1 activation, and STAT5 phosphorylation, defining a novel EGFR A289V–LCK/PLCγ2/CAMK1/STAT5 axis. In addition, Y1068 phosphorylation is also constitutively active in EGFR A289V, resulting in increased BRAF activation. In contrast, EGFR G598V activates MAPK6 and CAMK2 inducing AKT2 activation, reinforcing GPM-associated signaling. These findings uncover mutation-specific signaling networks that drive subtype fate in invasive GBM and highlight unique pathway(s) as tractable targets for subtype-directed therapy in EGFR-mutant GBM.