Decker, Paul A.

Background Clinical risk scores are used to identify those at high risk of atherosclerotic cardiovascular disease (ASCVD). Despite preventative efforts, residual risk remains for many individuals. Very low‐density lipoprotein cholesterol (VLDL‐C) and lipid discordance could be contributors to the residual risk of ASCVD. Methods and Results Cardiovascular disease–free residents, aged ≥40 years, living in Olmsted County, Minnesota, were identified through the Rochester Epidemiology Project. Low‐density lipoprotein cholesterol (LDL‐C) and VLDL‐C were estimated from clinically ordered lipid panels using the Sampson equation. Participants were categorized into concordant and discordant lipid pairings based on clinical cut points. Rates of incident ASCVD, including percutaneous coronary intervention, coronary artery bypass grafting, stroke, or myocardial infarction, were calculated during follow‐up. The association of LDL‐C and VLDL‐C with ASCVD was assessed using Cox proportional hazards regression. Interaction between LDL‐C and VLDL‐C was assessed. The study population (n=39 098) was primarily White race (94%) and female sex (57%), with a mean age of 54 years. VLDL‐C (per 10‐mg/dL increase) was significantly associated with an increased risk of incident ASCVD (hazard ratio, 1.07 [95% CI, 1.05–1.09]; P <0.001]) after adjustment for traditional risk factors. The interaction between LDL‐C and VLDL‐C was not statistically significant ( P =0.11). Discordant individuals with high VLDL‐C and low LDL‐C experienced the highest rate of incident ASCVD events, 16.9 per 1000 person‐years, during follow‐up. Conclusions VLDL‐C and lipid discordance are associated with a greater risk of ASCVD and can be estimated from clinically ordered lipid panels to improve ASCVD risk assessment.

Abstract Mayo Clinic has developed 111 GBM PDXs from newly diagnosed (72 PDX) and recurrent (39 PDX) patients. This large collection of PDXs provides a broad representation of genetic heterogeneity seen in patients. GBM PDXs that perform well in both in vitro and in vivo settings can be extensively utilized in the preclinical setting for downstream analysis. Based on 20 years of experience, we have defined the attributes that best enable preclinical use of our GBM PDX models. Among them are short-term in vitro culturing performance, large scale genomic evaluation data, benchmarked responses to standards of care, and median time to moribund for untreated orthotopic tumors. PDXs with prolonged survival timelines delay study readouts and, in some situations, confound efficacy results due to age-related animal decline. Setting median survival thresholds as part of the upfront experimental design allows for more timely study readouts that are unaffected by these confounding variables. Our preferred cutoff for the Mayo GBM PDX collection is 70 days median survival (n=64). Using this 64 PDX line panel, regimens expected to double survival would produce results within 4-5 months. This timeframe is well within the range of robust health for athymic nude mice. This 64-line collection features both newly diagnosed (nGBM; n=42) and recurrent (rGBM; n=22) tumors. MGMT promoter methylation status was determined by qMS-PCR (25 methylated, 37 unmethylated, 2 indeterminate). Available WES (n=62) and RNAseq (n=42) data, along with our tissue microarray (n=42), are critical resources for biomarker-based evaluations aimed at defining patient populations that are most likely to benefit from a given therapeutic. From these data, the molecular subtypes available include 26 classical, 14 proneural, and 3 mesenchymal. Twenty-seven of these 64 PDX models have also been successfully cultured from fresh as well as cryopreserved cell stocks to further expand their experimental value. Correlative clinical data including diagnosis and treatments are also available (n=61). Current standards of care for GBM include radiation, temozolomide, and bevacizumab. Defining sensitivity to these therapies is an important first step for evaluating the integration of novel therapeutics with these standards. Since the creation of our GBM PDX collection, efficacy of these therapies has been evaluated as follows: RT 26 PDXs, TMZ 20 PDXs, and Avastin 23 PDXs. The Mayo Clinic GBM PDX collection provides an important platform for preclinical evaluation of novel therapeutics. Through careful selection of PDX lines with favorable growth characteristics and known genetic features, researchers can select the most relevant models for their study. This approach will enable more meaningful preclinical work in the hopes of providing more tangible clinical benefits for GBM patients. Citation Format: Danielle M. Burgenske, Ann C. Mladek, Katrina K. Bakken, Zeng Hu, Brett L. Carlson, Paul A. Decker, Jeanette E. Eckel-Passow, Jann N. Sarkaria. Defining critical features for successful preclinical use of glioblastoma patient-derived xenografts (PDX) models for therapeutic assessment and clinical trial development [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6897.

ATM is a key mediator of radiation response, and pharmacological inhibition of ATM is a rational strategy to radiosensitize tumors. AZD1390 is a brain-penetrant ATM inhibitor and a potent radiosensitizer. This study evaluated the spectrum of radiosensitizing effects and the impact of TP53 mutation status in a panel of IDH1 wild-type (WT) glioblastoma (GBM) patient-derived xenografts (PDXs). AZD1390 suppressed radiation-induced ATM signaling, abrogated G 0 -G 1 arrest, and promoted a proapoptotic response specifically in p53-mutant GBM in vitro. In a preclinical trial using 10 orthotopic GBM models, AZD1390/RT afforded benefit in a cohort of TP53 -mutant tumors but not in TP53 -WT PDXs. In mechanistic studies, increased endogenous DNA damage and constitutive ATM signaling were observed in TP53 -mutant, but not in TP53 -WT, PDXs. In plasmid-based reporter assays, GBM43 ( TP53 -mutant) showed elevated DNA repair capacity compared with that in GBM14 (p53-WT), whereas treatment with AZD1390 specifically suppressed homologous recombination (HR) efficiency, in part, by stalling RAD51 unloading. Furthermore, overexpression of a dominant-negative TP53 (p53DD) construct resulted in enhanced basal ATM signaling, HR activity, and AZD1390-mediated radiosensitization in GBM14. Analyzing RNA-seq data from TCGA showed up-regulation of HR pathway genes in TP53 -mutant human GBM. Together, our results imply that increased basal ATM signaling and enhanced dependence on HR represent a unique susceptibility of TP53 -mutant cells to ATM inhibitor–mediated radiosensitization.

Abstract Radioresistance of melanoma brain metastases limits the clinical utility of conventionally fractionated brain radiation in this disease, and strategies to improve radiation response could have significant clinical impact. The catalytic subunit of DNA-dependent protein kinase (DNA-PKcs) is critical for repair of radiation-induced DNA damage, and inhibitors of this kinase can have potent effects on radiation sensitivity. In this study, the radiosensitizing effects of the DNA-PKcs inhibitor peposertib were evaluated in patient-derived xenografts of melanoma brain metastases (M12, M15, M27). In clonogenic survival assays, peposertib augmented radiation-induced killing of M12 cells at concentrations ≥100 nmol/L, and a minimum of 16 hours exposure allowed maximal sensitization. This information was integrated with pharmacokinetic modeling to define an optimal dosing regimen for peposertib of 125 mpk dosed just prior to and 7 hours after irradiation. Using this drug dosing regimen in combination with 2.5 Gy × 5 fractions of radiation, significant prolongation in median survival was observed in M12-eGFP (104%; P = 0.0015) and M15 (50%; P = 0.03), while more limited effects were seen in M27 (16%, P = 0.04). These data support the concept of developing peposertib as a radiosensitizer for brain metastases and provide a paradigm for integrating in vitro and pharmacokinetic data to define an optimal radiosensitizing regimen for potent DNA repair inhibitors.

Abstract Large PDX collections provide broad representation of tumor genetics and are commonly used to evaluate the clinical potential of novel therapeutic strategies. In many solid malignancies, profound benefit in PDX preclinical studies has foreshadowed eventual FDA approval of clinically impactful therapeutics. With a lack of corresponding progress in glioblastoma (GBM), the value of PDX testing has been questioned. Mayo Clinic has developed 111 GBM PDXs from newly diagnosed (72 PDX) and recurrent (39 PDX) patients, and over the past 23 years, we have used this collection for extensive in vivo preclinical testing of 145 drugs in both orthotopic and heterotopic settings. As part of this work, the impact of standard of care therapy with temozolomide (TMZ) and bevacizumab was evaluated in orthotopic models using clinically relevant dosing regimens. For each animal study, the ratio of median survival for treated vs. control animals were used to define a ‘survival ratio’ as a normalized metric of benefit. TMZ efficacy was evaluated in 26 newly diagnosed GBM PDXs, with equal representation of MGMT methylated and unmethylated tumors. As expected, MGMT methylated PDXs were much more sensitive to TMZ as compared to unmethylated PDXs (median survival ratio 4.47 vs 1.48, respectively), and similar to clinical experience, 2 MGMT unmethylated PDXs were markedly sensitive to TMZ, while 1 MGMT methylated PDX was relatively resistant. In a more limited study, dose-dense vs. standard TMZ dosing was compared in 7 PDXs (4 MGMT methylated, 3 MGMT unmethylated). In a pooled analysis of all lines, both standard (HR=0.09; 95% CI: 0.06–0.14) and dose-dense TMZ therapy (HR=0.09; 95% CI: 0.06–0.14) were superior to vehicle controls (p&lt;0.001). Similar to the clinical results in the Phase III randomized RTOG 0525 trial, survival with the dose-dense TMZ was no different than standard dosing (p=0.88, HR=0.98; 95% CI: 0.72-1.32). In an analysis of bevacizumab across 32 PDXs, mice were dosed once a week until moribund, and a minimum overall median survival benefit of 20% was used to define ‘responders’. Thirteen PDXs met this criterion, although the overall survival ratio among this subset was limited (range 1.21-1.65). Only 2 models had a 50% or greater survival benefit. Stratification by disease state (24 newly diagnosed vs 8 recurrent) showed equivalent performance (median survival benefit 1.13 for both). These results are consistent with the limited survival benefit observed with bevacizumab and the RTOG 0825 clinical trial. In summary, the results from these relatively inexpensive PDX studies demonstrate the potential of pre-clinical PDX trials to evaluate the extent of benefit and fraction of responsive PDXs to a novel therapeutic. If analyzed across an ‘adequate’ number of PDXs, these results potentially can be used to identify predictive biomarkers or to compare various treatment regimens prior to clinical testing. Citation Format: Danielle M Burgenske, Ann C Mladek, Katrina K Bakken, Zeng Hu, Brett L Carlson, Paul A Decker, Jeanette E Eckel-Passow, Jann N Sarkaria. The utility of pre-clinical trials in glioblastoma patient-derived xenografts (PDXs) models for informing clinical trial development of therapeutic strategies [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr A002.

Abstract Clinical management of IDH wildtype glioblastoma (GBM) and tumefactive multiple sclerosis (tMS) is drastically different. GBM requires maximal safe resection followed by chemoradiation, while tMS outcome is worsened by surgery and radiotherapy. Misdiagnosis of brain lesions may expose patients to unnecessary anxiety, surgery, or radiotherapy. Noninvasive methods to help with accurate diagnosis of tumor and non-tumor etiologies are needed. tMS subjects were identified by the Mayo Clinic Center for Multiple Sclerosis and Autoimmune Neurology (CMSAN). GBM subjects were matched to tMS by age at diagnosis, index MRI date, and sex. Inclusion criteria included one cm minimal lesion size and pre-operative post-contrast T1 and T2 images available for analysis. To identify potential experimental design bias, MRI technology and clinical characteristics were compared across groups. A 3D-DenseNet121 was used to develop a classification model using prespecified parameters: 600 epochs, batch size 16, learning rate 10-3, cross entropy loss, and AdamW optimizer. The stopping rule was defined as three sequential epoch cross entropy loss &lt; 0.02. Five-fold cross validation (CV) was utilized to obtain an unbiased estimate of predictive performance (overfitting) and sensitivity of the 3D-DenseNet121 algorithm was evaluated. 224 subjects (114 GBM, 110 tMS) were analyzed: 40% male, median age 46. After one round of CV, the average unbiased estimate of sensitivity and specificity for predicting GBM from the final classification model was 0.86 and 0.73, respectively. To assess the reproducibility of the deep learning algorithm (3D-DenseNet121), the exact same CV folds were rerun resulting in average sensitivity and specificity of 0.82 and 0.75, respectively. Obtaining unbiased estimates of model performance using internal validation is critical before evaluating a final model on an external dataset. Understanding sensitivity of a deep learning algorithm is important for model validity. Differentiation of GBM and tMS appears reasonable with MRI; external validation is in progress.

Abstract INTRODUCTION Prior to 2021, (classic) glioblastoma (GBM) required absence of IDH mutation and histologic features of hypercellularity, nuclear atypia, microvascular proliferation (MVP), and necrosis. Absence of histologic features can be a result of undersampling, with molecular, radiologic, and clinical features consistent with GBM. Accordingly, WHO 2021 defined molecular glioblastoma as diffuse glioma IDHwt, H3wt, with one or more of MVP, necrosis, TERT promoter mutation, EGFR gene amplification (EGFRamp), and/or +7/−10. We hypothesized that there is clinical and radiographic heterogeneity among tumors defined as molecular GBM. METHODS We identified 121 patients that met the criteria for molecular GBM. 121 Classic GBM, defined as IDHwt with hypercellularity, MVP or necrosis, were matched to molecular GBM cases by age, sex, and diagnosis date. All cases were reviewed for relevant histologic features and molecular features. Examined clinical variables included: first symptom, time from first symptom to date of pathological diagnosis, date of first MRI, tumor location, radiographic features of enhancement, diffusion or mass effect, time to progression and overall survival. Clinical, radiologic, and molecular features were compared between classic and molecular GBM. RESULTS Currently,160 cases have been reviewed. Preliminary results show that there is a longer time from first symptom to diagnosis for molecular GBM. Molecular GBM is significantly more likely to be discovered coincidentally, and without enhancement or radiographic necrosis. Classic GBM is significantly more likely to present with focal neurologic deficit as first symptom, regional mass effect on index imaging and have monosomy 10. CONCLUSION While pathologic undersampling accounts for a significant proportion of molecular GBM, our data suggest that there are significant clinical, radiographic, and outcome differences between classical and molecular GBM. Final analysis of the entire cohort will help better define this clinical spectrum.

Abstract There have been several attempts to predict the MGMT promoter methylation status of gliomas using deep learning (DL), with mixed results. These studies did not account for IDH mutation status and did not utilize a uniform methylation assay, introducing potential confounders in the experimental design. We assessed the performance of DL applied to brain MRI to predict the MGMT promoter methylation status of IDH-wildtype gliomas tested with a standardized assay. We included 539 IDH-wildtype gliomas tested with real-time methylation-specific PCR from 2017-2022; 205 (38%) were MGMT promoter methylated. The assay targets 8 downstream MGMT CpG sites using ACTB as control; methylation status is determined based on the difference of PCR crossing-point values: methylated if difference &lt; 5, unmethylated if difference &gt; 7, indeterminate otherwise. We used post-contrast T1 and T2 MRIs as inputs for our models trained using stratified 5-fold cross-validation, 400 epochs, batch size of 16, a learning rate scheduler starting at 10-3, weighted binary cross-entropy loss, and AdamW optimizer. We repeated the experiments using two 3D DL architectures (DenseNet121 and EfficientNetB0) and two image preprocessing pipelines: the BraTS protocol and one that uses padding instead of registration to an MRI atlas, keeping constant other experimental variables. For Densenet121, the best cross-validation AUROCC and F1-score (median, median absolute deviation) were 0.67 (0.06), 0.59 (0.02) using the BraTS protocol, and 0.67 (0.06), 0.58 (0.01) using padding. For EfficientNetB0, were 0.67 (0.02), 0.66 (0.01) using the BraTS protocol and 0.67 (0.01), 0.68 (0.01) using padding. Our findings suggest that it is unlikely that DL models trained on brain MRI can predict the MGMT promoter methylation of IDH-wildtype gliomas. Importantly, our study is the first to focus on an IDH-wildtype adult diffuse glioma cohort tested with a single, standardized MGMT methylation assay, eliminating the variability introduced by different assays and IDH status.

Abstract BACKGROUND D-2-hydroxyglutarate (D-2-HG) is a well-established oncometabolite of isocitrate dehydrogenase (IDH) mutant gliomas. While prior studies have demonstrated that D-2-HG is elevated in the cerebrospinal fluid (CSF) of patients with IDH-mutant gliomas, no study has evaluated the ability of CSF D-2-HG to quantitatively monitor tumor burden and therapeutic response. Toward this goal, we are routinely obtaining CSF samples from patients prior to, during, and after treatment via intra-operative collection and CSF-access devices. MATERIAL AND METHODS Patients were enrolled into our Ommaya reservoir study (NCT04692337), which enables longitudinal access to CSF. The catheter for the implanted reservoir was placed within the surgical resection cavity following a standard-of-care resection. Intra-operatively collected CSF samples were also biobanked through Mayo Clinic’s Neuro-Oncology biorepository. CSF samples were also acquired via clinically indicated ventriculoperitoneal shunts (VP shunts) or external ventricular drains via our ongoing CSF biomarkers study (NCT04692324). D-and-L-2-HG were assayed from each CSF sample via gas chromatography-mass spectrometry (GC-MS) at Mayo Clinic’s Biochemical Genetics Laboratory. RESULTS CSF was collected prior to and after resection in patients via Ommaya reservoirs or VP shunts, all of whom underwent near gross total resections (&gt;95% of tumor volume). D-2-HG and the D/L ratio fell on average by 57.9% (range: 15.1%-98.6%) and 68.8% (range: 49.3%-98.9%), respectively, following resection. In one patient with a largely intraventricular grade 4 IDH-mutant astrocytoma, D-and-L-2-HG fell by 99.1% and 99.3% by post-operative day 2, consistent with the impact of ventricular contact on baseline CSF D-2-HG levels. In patients for whom CSF was collected throughout chemoradiation, with or without immunotherapy, D-2-HG and the D/L ratio continued to decrease over time, despite concern for pseudoprogression versus progression on imaging. CONCLUSION Our early experience with this strategy demonstrates the potential for intracranial CSF D-2-HG as a monitoring biomarker for IDH-mutant gliomas. Work is ongoing to evaluate the reproducibility of these findings in a larger cohort of patients with low or high-grade gliomas, in addition to the impact of tumor recurrence on 2-HG. Future studies will evaluate the impact of IDH inhibitors and other experimental therapies on CSF 2-HG levels for pharmacodynamic monitoring of treatment response.

AbstractObjectiveTo describe demographic, clinical, and radiographic features of tumefactive demyelination (TD) and identify factors associated with severe attacks and poor outcomes.MethodsRetrospective review of TD cases seen at Mayo Clinic, 1990–2021.ResultsOf 257 patients with TD, 183/257 (71%) fulfilled the 2017 multiple sclerosis (MS) McDonald criteria at the last follow‐up, 12/257 (5%) had myelin oligodendrocyte glycoprotein antibody‐associated disease (MOGAD), 0 had aquaporin‐4‐IgG seropositive neuromyelitis optic spectrum disorders (AQP4+ NMOSD), and 62/257 (24%) were cryptogenic. Onset before age 18 was present in 18/257 (7%). Female to male ratio was 1.3:1. Cerebrospinal fluid oligoclonal (CSF) bands were present in 95/153 (62%). TD was the first demyelinating attack in 176/257 (69%). At presentation, 59/126 (47%) fulfilled Barkhof criteria for dissemination in space, 59/100 (59%) had apparent diffusion coefficient (ADC) restriction, and 57/126 (45%) had mass effect. Despite aggressive clinical presentation at onset, 181/257 (70%) of patients remained fully ambulatory (Expanded Disability Status Scale [EDSS] ≤4) after a 3.0‐year median follow‐up duration. Severe initial attack‐related disability (EDSS ≥4) was more common in patients with motor symptoms (81/143 vs. 35/106, p < 0.0001), encephalopathy (20/143 vs. 2/106, p < 0.0001) and ADC restriction on initial MRI (42/63 vs. 15/33, p = 0.04). Poor long‐term outcome (EDSS ≥4) was more common in patients with older onset age (41.9 ± 15 vs. 36.8 ± 15.6, p = 0.02) and motor symptoms at onset (49/76 vs. 66/171, p < 0.0001).InterpretationMost TD patients should be considered part of the MS spectrum after excluding MOGAD and NMOSD. Motor symptoms and older age at presentation portend a poor outcome.