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ImportancePhysical activity is associated with cognitive health, even in autosomal dominant forms of dementia. Higher physical activity is associated with slowed cognitive and functional declines over time in adults carrying autosomal dominant variants for frontotemporal lobar degeneration (FTLD), but whether axonal degeneration is a potential neuroprotective target of physical activity in individuals with FTLD is unknown.ObjectiveTo examine the association between physical activity and longitudinal neurofilament light chain (NfL) trajectories in individuals with autosomal dominant forms of FTLD.Design, Setting, and ParticipantsThis cohort study included individuals from the ALLFTD Consortium, which recruited patients from sites in the US and Canada. Symptomatic and asymptomatic adults with pathogenic variants in one of 3 common genes associated with FTLD (GRN, C9orf72, or MAPT) who reported baseline physical activity levels and completed annual blood draws were assessed annually for up to 4 years. Genotype, clinical measures, and blood draws were collected between December 2014 and June 2019; data were analyzed from August 2021 to January 2022. Associations between reported baseline physical activity and longitudinal plasma NfL changes were assessed using generalized linear mixed-effects models adjusting for baseline age, sex, education, functional severity, and motor symptoms.ExposuresBaseline physical activity levels reported via the Physical Activity Scale for the Elderly. To estimate effect sizes, marginal means were calculated at 3 levels of physical activity: 1 SD above the mean represented high physical activity, 0 SD represented average physical activity, and 1 SD below the mean represented low physical activity.Main Outcomes and MeasuresAnnual plasma NfL concentrations were measured with single-molecule array technology.ResultsOf 160 included FTLD variant carriers, 84 (52.5%) were female, and the mean (SD) age was 50.7 (14.7) years. A total of 51 (31.8%) were symptomatic, and 77 carried the C9orf72 variant; 39, GRN variant; and 44, MAPT variant. Higher baseline physical activity was associated with slower NfL trajectories over time. On average, NfL increased 45.8% (95% CI, 22.5 to 73.7) over 4 years in variant carriers. Variant carriers with high physical activity demonstrated 14.0% (95% CI, −22.7 to −4.3) slower NfL increases compared with those with average physical activity and 30% (95% CI, −52.2 to −8.8) slower NfL increases compared with those with low physical activity. Within genotype, C9orf72 and MAPT carriers with high physical activity evidenced 18% to 21% (95% CI, −43.4 to −7.2) attenuation in NfL, while the association between physical activity and NfL trajectory was not statistically significant in GRN carriers. Activities associated with higher cardiorespiratory and cognitive demands (sports, housework, and yardwork) were most strongly correlated with slower NfL trajectories (vs walking and strength training).Conclusions and RelevanceIn this study, higher reported physical activity was associated with slower progression of an axonal degeneration marker in individuals with autosomal dominant FTLD. Physical activity may serve as a primary prevention target in FTLD.

Abstract BACKGROUND Glioblastoma diagnostic criteria have been redefined with the 5th edition of WHO classification of tumors of the central nervous system. Glioblastomas are defined as IDH wildtype diffuse astrocytic glioma tumors with one of the following features: microvascular proliferation, or necrosis, or TERT promoter mutation, or EGFR gene amplification, or +7/-10 chromosome copy number changes. The aim of this study is to establish the impact of extent of resection in overall survival (OS) and progression free survival (PFS) in glioblastoma, IDH-wildtype (WT), WHO grade 4 (WHO 2021). METHODS Systematic literature search was performed using the following databases: PubMed, Web of Science, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews and ClinicalTrials.gov to identify studies comparing OS and PFS after gross total resection (GTR) vs subtotal resection (STR) or biopsy for glioblastoma IDH-WT. Prognostic hazard ratios (HR) for OS and PFS were analyzed using a random-effects model. RESULTS We identified 1439 publications. Nine studies met inclusion/exclusion criteria. 788 patients underwent GTR out of 1818. The meta-analysis showed a significant increase in OS and PFS duration when undergoing GTR for glioblastoma IDH-WT with a median OS of 20 months 95% CI (17-25) compared to 12 months 95% CI (9-15) for STR or biopsy and a median PFS of 11 months 95% CI (9-12) for GTR compared to 7 months 95% CI (5-7) for STR or biopsy respectively. GTR showed a 49% significant reduction of mortality risk HR=0.51 95%CI (0.42-0.59) and a 44% significant reduction of progression risk HR=0.56 95%CI (0.41-0.71) compared to STR or biopsy. CONCLUSIONS This systematic review indicates that GTR may be associated with improved OS and PFS compared to STR or biopsy for Glioblastoma, IDH-WT, WHO grade 4 (WHO 2021). However, this is limited by variable study design and significant clinical and methodological heterogeneity among studies.

Abstract BACKGROUND Standard of care (SOC) and patient survival in glioblastoma have changed little in the past 17 years. We evaluated in a phase 3 trial whether adding an autologous tumor lysate-loaded dendritic cell vaccine (murcidencel) to SOC extends survival. Patients and METHODS Newly diagnosed glioblastoma patients were randomized 2:1 to either murcidencel or placebo. Under a crossover design, all patients could receive murcidencel following tumor recurrence. All parties remained blinded regarding treatments before recurrence. Patients thus received murcidencel at new diagnosis (nGBM) or at recurrence (rGBM) following crossover from placebo. The primary and secondary endpoints compare overall survival (OS) with contemporaneous, matched external controls. Four sets of analyses were conducted to ensure rigorous matching of the controls, reduce biases, and confirm the robustness of the results. RESULTS 331 patients were enrolled. With the crossover, 89% received murcidencel. Median OS (mOS) for nGBM patients (n = 232) was 19.3 months from randomization (22.4 months from surgery) with murcidencel vs. 16.5 months from randomization in the controls (HR = 0.80, p = 0.002). Survival at 48 months from randomization was 15.7% vs. 9.9%, and at 60 months was 13% vs. 5.7%. For rGBM (n = 64), mOS was 13.2 months from relapse vs. 7.8 months in the controls (HR = 0.58, p < 0.001). Survival at 24 months post-recurrence was 20.7% vs. 9.6%, and at 30 months post-recurrence was 11.1% vs 5.1%. In nGBM patients with methylated MGMT (n = 90), mOS was 30.2 months from randomization (33 months from surgery) with murcidencel vs. 21.3 months from randomization in the controls (HR = 0.74, p = 0.027). The treatment was well tolerated, with only 5 serious adverse events deemed at least possibly related to the vaccine. CONCLUSION Clinically meaningful and statistically significant survival extension was seen in both nGBM and rGBM patients treated with murcidencel and SOC compared with contemporaneous, matched external controls who received SOC alone.

Abstract INTRODUCTION Glioblastomas (GBMs) are highly aggressive tumors. A common clinical challenge after standard of care treatment is differentiating tumor progression from treatment-related changes, also known as pseudoprogression (PsP). Usually, PsP resolves or stabilizes without further treatment or a course of steroids, whereas true progression (TP) requires more aggressive management. Differentiating PsP from TP will affect the patient's outcome. This study investigated using deep learning to distinguish PsP MRI features from progressive disease. METHOD We included newly diagnosed GBM patients who met the inclusion criteria, including a new or increasing enhancing lesion size within the original radiation field and who had clinical, medication, and any histopathology available. The interpretation of the MR images at the image inclusion time point had to be indeterminate. We labeled those who subsequently were stable or improved on imaging and clinically as PSP and those with clinical and imaging deterioration as TP. A subset of subjects underwent a second resection. We labeled these subjects as PSP or TP based on the histological diagnosis. We performed skull stripping, coregistered contrast-enhanced T1 MRIs with T2-weighted images for each patient and used them as input to a 3-D Densenet121 model. We used several augmentation techniques and five-fold cross-validation to achieve more robust predictions. RESULT We included 124 patients who met the criteria, and of those, 63 were PsP and 61 were TP. We trained a deep learning model that achieved 76.4% (ranged 70%-84%, SD 5.122) mean accuracy over the 5 folds, 0.7560(ranged 0.6553-0.8535, SD 0.069) mean AUROCC, 88.72% (SD 6.86) mean sensitivity, and 62.05%(SD 9.11) mean specificity. CONCLUSION We report the development of a deep learning model that distinguishes PsP from TP in GBM patients treated per the Stupp protocol. Further refinement and external validation are required prior to widespread adoption in clinical practice.

Abstract INTRODUCTION: Plasma extracellular vesicles (EVs) have been shown as a promising source for biomarker identification in glioblastoma (GBM) and could help differential diagnosis, treatment evaluation and tumor progression monitoring. These EVs are enriched in molecular signatures indicative of their cell origins, giving an indication of the key players in this pathology. In this project, we aimed to identify diagnostic biomarkers for GBM plasma EVs and their cells of origin. METHODS: Plasma EV samples were prepared following the MIFlowCyt-EV guideline of the International Society for Extracellular Vesicles, then stained for EV markers (CD9/CD63/CD81) and markers indicative of cell origins (CD31/CD45/CD41a/CD11b). Actin phalloidin was used as a negative marker. Stained plasma samples were analyzed using a Cytek Aurora flow cytometer. Percentages of different EV subpopulations were analyzed and compared between GBM and normal donor (ND) plasma EVs (reference group). Further clustering analysis was performed on EV events by t-distributed stochastic neighbor embedding (t-SNE) and self-organizing maps on flow cytometry data (FlowSOM) analysis. The predictive value of multiparametric qualities derived from the reference group was tested in blinded test group samples. RESULTS: Percentages of CD9, CD81, and CD11b positive EVs were higher in GBM patient plasma, while ND plasma had more CD41a positive EVs. GBM plasma EVs had unique multiparametric signatures compared to ND plasma EVs based on t-SNE and FlowSOM analysis. Our analysis also identified 15 distinct EV subpopulations which differed in size and various surface marker expression levels. Eight of these subpopulations were enriched for GBM EVs, while three were enriched for ND EVs. Our method of multiparametric analysis demonstrates high sensitivity and specificity in predicting disease status in human samples. CONCLUSIONS: GBM plasma EVs have a unique surface marker expression profile and distinct EV subpopulations compared to ND plasma EVs. Multiparametric signatures show promise as potential diagnostic markers of GBM.

Abstract IDH mutant gliomas depend on glutaminase for glutamate/glutathione generation from glutamine because R-2-hydroxyglutarate inhibits branched chain amino acid transaminase mediated glutamate biosynthesis. Telaglenastat (CB-839 HCl) is a potent glutaminase-1 specific inhibitor which depletes tumor glutamate in orthotopic IDH mutant glioma PDX models and extends survival in these orthotopic models when added to radiation/temozolomide. NCI-10218 (NCT03528642) is a phase I clinical trial investigating the safety and tolerability of telaglenastat administered orally concurrently with standard doses of radiation (50.4 Gy, grade 2; 59.4 Gy, grade 3) and temozolomide (75 mg/m2 orally daily) in patients (age 16+) with previously untreated IDH mutant grade 2/3 astrocytoma. Telaglenastat dose was escalated in cohorts (400-800 mg twice daily) based on a standard 3 + 3 design to determine the recommended phase 2 dose (RP2D). Toxicities were graded per CTCAE v5.0. An expansion cohort additionally incorporated a seven-day run-in of telaglenastat monotherapy at RP2D prior to radiation to evaluate the pharmacodynamic impact of telaglenastat on plasma and tumor metabolites. 23 patients with IDH mutant astrocytoma (WHO grade 2, n = 5; WHO grade 3, n = 18) were accrued between December 2018 and January 2022 (Dose Escalation: 16; Dose Expansion: 7). Median age was 32 years (range 23-69 years). 61% were male and 70% were ECOG 0. No dose-limiting toxicities were observed. Grade 3/4 adverse events (independent of attribution) included: lymphopenia (3), neutropenia (2), leukocytosis (2), alanine transaminase elevation (2), thrombocytopenia (1), leukopenia (1), maculopapular rash (1), hyperglycemia (1), hyponatremia (1). The RP2D of concurrent telaglenastat was defined as 800 mg twice daily. Following peak absorption on Day 15 at RP2D, the mean (%CV) terminal elimination half-life in the plasma was 4.2 (53.5%) hours (range 2.1-7.1 hours). The Cmax, Tmax, oral clearance, and AUC were 1496 ng/mL, 4.0 hr, 93.6 L/hr/m2, and 7430 ng/mL*hr, respectively.

AbstractObjectiveHigh BMI is associated with many comorbidities and mortality. This study aimed to elucidate the overall clinical risk of obesity using a genome‐ and phenome‐wide approach.MethodsThis study performed a phenome‐wide association study of BMI using a clinical cohort of 736,726 adults. This was followed by genetic association studies using two separate cohorts: one consisting of 65,174 adults in the Electronic Medical Records and Genomics (eMERGE) Network and another with 405,432 participants in the UK Biobank.ResultsClass 3 obesity was associated with 433 phenotypes, representing 59.3% of all billing codes in individuals with severe obesity. A genome‐wide polygenic risk score for BMI, accounting for 7.5% of variance in BMI, was associated with 296 clinical diseases, including strong associations with type 2 diabetes, sleep apnea, hypertension, and chronic liver disease. In all three cohorts, 199 phenotypes were associated with class 3 obesity and polygenic risk for obesity, including novel associations such as increased risk of renal failure, venous insufficiency, and gastroesophageal reflux.ConclusionsThis combined genomic and phenomic systematic approach demonstrated that obesity has a strong genetic predisposition and is associated with a considerable burden of disease across all disease classes.

PURPOSE To describe a newly established international registry recruiting diverse patients with advanced prostate cancer across academic and community practices to address unmet needs in this population. PATIENTS AND METHODS Initiated in 2017, IRONMAN (International Registry for Men with Advanced Prostate Cancer) is a prospective cohort of patients with advanced prostate cancer. The study will enroll 5,000 patients with metastatic hormone-sensitive prostate cancer (mHSPC) or castration-resistant prostate cancer (CRPC), recruited from Australia, the Bahamas, Barbados, Brazil, Canada, Ireland, Jamaica, Kenya, Nigeria, Norway, South Africa, Spain, Sweden, Switzerland, the United Kingdom, and the United States. The study is collecting datatypes to study variation in care and treatment of advanced prostate cancer across countries and across academic, community-based, and government practices with a focus on clinical outcomes, patient-reported outcomes, epidemiologic data, biologic subtypes, and clinician questionnaires. RESULTS Through July 2022, 2,682 eligible patients were enrolled in 11 of 12 active countries. Sixty-six percent of patients have mHSPC, and 34% have CRPC. On the basis of self-report, 11% of patients are Black and 9% are Hispanic. Five Veterans Affairs Medical Centers are enrolling patients. Globally, 23% of patients report being veterans of military service. CONCLUSION To our knowledge, this is the first international cohort of people newly diagnosed with advanced prostate cancer designed to describe variations in patient management, experiences, and outcomes. IRONMAN aims to identify optimal treatment sequences to improve survival, understand patient-reported outcomes, and explore novel biomarkers to understand treatment resistance mechanisms. Insights from IRONMAN will inform and guide future clinical management of people with mHSPC and CRPC. This cohort study will provide real-world evidence to facilitate a better understanding of the survivorship of people with advanced prostate cancer.