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  • 1
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 80, No. 16_Supplement ( 2020-08-15), p. 2007-2007
    Abstract: Glioblastoma (GBM) is the most frequently reported primary malignant brain tumor (29.6%). The prognosis for patients who develop GBM is bleak, with average survival after diagnosis of 12-16 months. Although conventional treatment with surgery, irradiation, and temozolomide postpones tumor progression and extends patients survival, these tumors universally recur and unrelentingly result in patient death. Personalized therapies against molecular targets that drive the growth of the bulk of primary tumors have so far been unsuccessful in clinical trials, due to lack of biomarker driven approaches. Thus, there is significant unmet need to begin biomarker driven precision medicine trials for treatment of GBM. Arsenic trioxide (ATO) is an inorganic compound that induces apoptosis via multiple pathways. Arsenic trioxide (TRISENOX®) is approved by the FDA for patients with acute promyelocytic leukemia (APL). Pre-clinical studies in brain tumors suggest that ATO is synergistic with radiation therapy (RT) and may enhance effects of radiation. In an earlier Phase II clinical trial (NCT00275067) using intravenous ATO and temozolomide in combination with radiation therapy for patients with newly diagnosed malignant gliomas, a subset of patients demonstrated notable benefit (Progression free survival (avg. = 638 days) and overall survival (avg. = 967 days)). Comparing RNAseq data from preclinical models and specimen from the Phase II clinical trial, the responder group could be confidently distinguished from the non-responder cohort leading to gene signatures of differential ATO sensitivity. Applying a Relative Expression Ordering (REO) Analysis framework, we pinpointed a probability-based roster of 28 top scoring pairs (TSP) as the classifier by which to identify patients with a higher likelihood to benefit from including ATO in combination with TMZ and radiation. This method is completely independent of platform on which data is collected and can be used for analysis of individual, newly-enrolled, n = 1 patients. We are advancing a protocol using the above gene classifier as enrollment criteria for an Adaptive clinical trial testing an oral formulation of ATO for newly diagnosed IDH1 WT Primary GBM patients; the trial will test whether patients whose tumors with ATO Classifier show 6-month PFS benefit by addition of ATO to Standard-of-Care. The trial will validate and refine the comprehensive biomarker panel that could identify most likely GBM responders to ATO and TMZ treatment in combination with radiation. Supported by a grant from the Baylor Scott & White Foundation. Citation Format: Sen Peng, Jinghua Gu, Xuan Wang, Sanhita Rath, Jacob Cardenas, Nicholas Schork, George Snipes, Harshil Dhruv, Karen Fink, Michael Berens. Development of a clinical assay for predicting glioblastoma (GBM) patients most likely to respond to arsenic trioxide (ATO) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2007.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2020
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  • 2
    In: Neuro-Oncology, Oxford University Press (OUP), Vol. 23, No. Supplement_6 ( 2021-11-12), p. vi194-vi194
    Abstract: Glioblastoma is characterized by intra- and inter-tumoral heterogeneity. A glioblastoma umbrella signature trial (GUST) posits multiple investigational treatment arms based on corresponding biomarker signatures. A contingency of an efficient umbrella trial is a suite of orthogonal signatures to classify patients into the likely-most-beneficial arm. Assigning optimal thresholds of vulnerability signatures to classify patients as “most-likely responders” for each specific treatment arm is a crucial task. We utilized semi-supervised machine learning, Entropy-Regularized Logistic Regression, to predict vulnerability classification. By applying semi-supervised algorithms to the TCGA GBM cohort, we were able to transform the samples with the highest certainty of predicted response into a self-labeled dataset and thus augment the training data. In this case, we developed a predictive model with a larger sample size and potential better performance. Our GUST design currently includes four treatment arms for GBM patients: Arsenic Trioxide, Methoxyamine, Selinexor and Pevonedistat. Each treatment arm manifests its own signature developed by the customized machine learning pipelines based on selected gene mutation status and whole transcriptome data. In order to increase the robustness and scalability, we also developed a multi-class/label classification ensemble model that’s capable of predicting a probability of “fitness” of each novel therapeutic agent for each patient. Such a multi-class model would also enable us to rank each arm and provide sequential treatment planning. By expansion to four independent treatment arms within a single umbrella trial, a “mock” stratification of TCGA GBM patients labeled 56% of all cases into at least one “high likelihood of response” arm. Predicted vulnerability using genomic data from preclinical PDX models correctly placed 4 out of 6 models into the “responder” group. Our utilization of multiple vulnerability signatures in a GUST trial demonstrates how a precision medicine model can support an efficient clinical trial for heterogeneous diseases such as GBM. Surgical Therapies
    Type of Medium: Online Resource
    ISSN: 1522-8517 , 1523-5866
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2094060-9
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  • 3
    Online Resource
    Online Resource
    Wiley ; 2022
    In:  Pacing and Clinical Electrophysiology Vol. 45, No. 8 ( 2022-08), p. 950-957
    In: Pacing and Clinical Electrophysiology, Wiley, Vol. 45, No. 8 ( 2022-08), p. 950-957
    Abstract: Over the last 6 years, there has been a high percentage of unfilled cardiac electrophysiology (EP) training spots each year. The authors aimed to investigate potential explanations for the unfilled positions based on a survey from the current Fellows‐In‐Training (FITs). Methods An attempt was made to reach the current cardiology FITs across all programs of the U.S. via email. An anonymous questionnaire was created consisting of 14 questions. Questions posed were regarding factors affecting each participant's interest in or lack of pursuing an EP fellowship. Descriptive statistics of the responses were performed. Results A total of 26% (35/134) respondents expressed their interest in applying to an EP fellowship. The most common reasons to apply to EP were: Interest in EP, procedural specialty, and work‐life balance. Of the 99 respondents that were not applying to EP, the most common reasons not to apply were: Less interest in EP, two‐year training duration, and complexity of the specialty. The top reasons for the fellows to believe there is a dearth of EP FITs were: two‐year training duration, lack of interest in EP, and the complexity of the specialty. The changes that would encourage EP fellowship interest were: More exposure to EP training during general cardiology fellowship, shortening the EP training duration, and having more information available regarding employment opportunities. Conclusion The study was able to identify factors responsible for vacancies in EP fellowship positions from the view of current cardiology FITs. Stakeholders at the national level involved in framing policies related to fellowship education would be able to utilize this information to address the shortage of EP FITs and increase recruitment to EP fellowships.
    Type of Medium: Online Resource
    ISSN: 0147-8389 , 1540-8159
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2022
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  • 4
    Online Resource
    Online Resource
    AkiNik Publications ; 2020
    In:  International Journal of Orthopaedics Sciences Vol. 6, No. 1 ( 2020-01-01), p. 1168-1170
    In: International Journal of Orthopaedics Sciences, AkiNik Publications, Vol. 6, No. 1 ( 2020-01-01), p. 1168-1170
    Type of Medium: Online Resource
    ISSN: 2395-1958 , 2395-1958
    URL: Issue
    Language: Unknown
    Publisher: AkiNik Publications
    Publication Date: 2020
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  • 5
    In: Neuro-Oncology Advances, Oxford University Press (OUP), Vol. 2, No. 1 ( 2020-01-01)
    Abstract: Tumor heterogeneity underlies resistance and disease progression in glioblastoma (GBM), and tumors most commonly recur adjacent to the surgical resection margins in contrast non-enhancing (NE) regions. To date, no targeted therapies have meaningfully altered overall patient survival in the up-front setting. The aim of this study was to characterize intratumoral heterogeneity in recurrent GBM using bulk samples from primary resection and recurrent samples taken from contrast-enhancing (EN) and contrast NE regions. Methods Whole exome and RNA sequencing were performed on matched bulk primary and multiple recurrent EN and NE tumor samples from 16 GBM patients who received standard of care treatment alone or in combination with investigational clinical trial regimens. Results Private mutations emerge across multi-region sampling in recurrent tumors. Genomic clonal analysis revealed increased enrichment in gene alterations regulating the G2M checkpoint, Kras signaling, Wnt signaling, and DNA repair in recurrent disease. Subsequent functional studies identified augmented PI3K/AKT transcriptional and protein activity throughout progression, validated by phospho-protein levels. Moreover, a mesenchymal transcriptional signature was observed in recurrent EN regions, which differed from the proneural signature in recurrent NE regions. Conclusions Subclonal populations observed within bulk resected primary GBMs transcriptionally evolve across tumor recurrence (EN and NE regions) and exhibit aberrant gene expression of common signaling pathways that persist despite standard or targeted therapy. Our findings provide evidence that there are both adaptive and clonally mediated dependencies of GBM on key pathways, such as the PI3K/AKT axis, for survival across recurrences.
    Type of Medium: Online Resource
    ISSN: 2632-2498
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
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  • 6
    Online Resource
    Online Resource
    Institute of Electrical and Electronics Engineers (IEEE) ; 2022
    In:  IEEE Computer Graphics and Applications Vol. 42, No. 5 ( 2022-9-1), p. 37-50
    In: IEEE Computer Graphics and Applications, Institute of Electrical and Electronics Engineers (IEEE), Vol. 42, No. 5 ( 2022-9-1), p. 37-50
    Type of Medium: Online Resource
    ISSN: 0272-1716 , 1558-1756
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    Language: Unknown
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2022
    detail.hit.zdb_id: 2028246-1
    detail.hit.zdb_id: 245654-0
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  • 7
    Online Resource
    Online Resource
    Elsevier BV ; 2022
    In:  Journal of the Society for Cardiovascular Angiography & Interventions Vol. 1, No. 3 ( 2022-05), p. 100254-
    In: Journal of the Society for Cardiovascular Angiography & Interventions, Elsevier BV, Vol. 1, No. 3 ( 2022-05), p. 100254-
    Type of Medium: Online Resource
    ISSN: 2772-9303
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
    detail.hit.zdb_id: 3116631-3
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  • 8
    In: Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 26, No. 5 ( 2020-03-01), p. 1094-1104
    Abstract: Glioblastoma is the most frequent and lethal primary brain tumor. Development of novel therapies relies on the availability of relevant preclinical models. We have established a panel of 96 glioblastoma patient-derived xenografts (PDX) and undertaken its genomic and phenotypic characterization. Experimental Design: PDXs were established from glioblastoma, IDH-wildtype (n = 93), glioblastoma, IDH-mutant (n = 2), diffuse midline glioma, H3 K27M-mutant (n = 1), and both primary (n = 60) and recurrent (n = 34) tumors. Tumor growth rates, histopathology, and treatment response were characterized. Integrated molecular profiling was performed by whole-exome sequencing (WES, n = 83), RNA-sequencing (n = 68), and genome-wide methylation profiling (n = 76). WES data from 24 patient tumors was compared with derivative models. Results: PDXs recapitulate many key phenotypic and molecular features of patient tumors. Orthotopic PDXs show characteristic tumor morphology and invasion patterns, but largely lack microvascular proliferation and necrosis. PDXs capture common and rare molecular drivers, including alterations of TERT, EGFR, PTEN, TP53, BRAF, and IDH1, most at frequencies comparable with human glioblastoma. However, PDGFRA amplification was absent. RNA-sequencing and genome-wide methylation profiling demonstrated broad representation of glioblastoma molecular subtypes. MGMT promoter methylation correlated with increased survival in response to temozolomide. WES of 24 matched patient tumors showed preservation of most genetic driver alterations, including EGFR amplification. However, in four patient–PDX pairs, driver alterations were gained or lost on engraftment, consistent with clonal selection. Conclusions: Our PDX panel captures the molecular heterogeneity of glioblastoma and recapitulates many salient genetic and phenotypic features. All models and genomic data are openly available to investigators.
    Type of Medium: Online Resource
    ISSN: 1078-0432 , 1557-3265
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2020
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  • 9
    In: Neuro-Oncology, Oxford University Press (OUP), Vol. 23, No. Supplement_6 ( 2021-11-12), p. vi36-vi36
    Abstract: Neddylation is a specific pathway within the ubiquitin/proteasome system that is overactive in GBM, and whose upregulation has been associated with glioma progression and worse survival. Pevonedistat (MLN4924) is a first-in-class small-molecule neddylation inhibitor shown to inhibit growth of GBM cells by impacting protein degradation in culture and orthotopic xenografts. However, the determinants of vulnerability are not fully understood. Because the molecular heterogeneity within and across GBM patients obscures therapeutic targets and obfuscates signals of efficacy in clinical trials, we pursue the use of molecular “signatures of vulnerability” to targeted agents in subsets of preclinical models. Selective vulnerability to pevonedistat was shown in a subset of GBM; notably, models with mutations or copy number deletions of PTEN are associated with de novo resistance to pevonedistat. Time-course studies of sensitive and non-sensitive GBM cells using transcriptomics and proteomics/phosphoproteomics uncovered additional determinants of response to pevonedistat. Our results demonstrate that in GBM, resistance to pevonedistat is driven by reduced PTEN-chromatin binding (loss-of-function or lower expression) that is also independent of PTEN’s lipid phosphatase activity (i.e., PI3K/AKT signaling). Across 25 glioma cell lines, we found that PTEN signaling, DNA replication, and chromatin instability pathways are the most significant differentiators between pevonedistat sensitive vs. non-sensitive models. In GBM models with modest to low sensitivity to pevonedistat, TOP2A expression was elevated. Combination treatment with the TOP2A inhibitor, etoposide, proved synergistic with pevonedistat. We report that PTEN status both serves as a novel biomarker for GBM sensitivity to pevonedistat and reveals a synergistic vulnerability to TOP2A inhibitors in combination with pevonedistat. Paired use of GBM PDX models of varying sensitivity with drug development testing allows the advancement of a promising agent as well as a patient-enrollment “signature of vulnerability” likely to increase the likelihood of demonstrating therapeutic efficacy in early stage clinical trials.
    Type of Medium: Online Resource
    ISSN: 1522-8517 , 1523-5866
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
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  • 10
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 81, No. 13_Supplement ( 2021-07-01), p. 2534-2534
    Abstract: Glioblastoma (GBM) is the most common and aggressive primary malignant brain tumor in adults with a 5-year survival rate of ~3%. The ubiquitin/proteasome system maintains intracellular homeostasis via degradation of unwanted proteins. Bortezomib is a first-in-class, non-specific proteasome inhibitor exploiting this system, although it has poor penetration across the blood brain barrier, and its lack of specificity is accompanied by adverse events. Neddylation is a specific pathway within the ubiquitin/proteasome system that is overactive in glioblastoma (GBM), and whose upregulation has been associated with glioma progression and worse survival. Pevonedistat is a first-in-class small-molecule neddylation inhibitor shown to impact protein degradation, leading to elevated abundance of some tumor suppressor proteins (Wee1, others), which then inhibit growth of GBM cells in culture and orthotopic xenografts. Because the molecular heterogeneity within and across GBM patients obscures therapeutic targets and obfuscates signals of efficacy in clinical trials, we propose the use of molecular “signatures of vulnerability” to targeted agents in subsets of preclinical models. We and others have shown that pevonedistat interferes with the growth of multiple types of cancers, including GBM, but the determinants of vulnerability are not fully understood. Here, we report a selective vulnerability to pevonedistat in a subset of GBM, specifically, instances with mutations or copy number deletions of PTEN are associated with de novo resistance to pevonedistat. Time-course studies of sensitive and non-sensitive GBM cells using transcriptomics and proteomics/phosphoproteomics enable independent discovery and testing for determinants of response to pevonedistat. Our results demonstrate that in GBM, resistance to pevonedistat is driven by reduced PTEN-chromatin binding (loss-of-function or lower expression) that is also independent of PTEN's lipid phosphatase activity (i.e., PI3K/AKT signaling). Across 25 glioma cell lines, we found that PTEN signaling, DNA replication, and chromatin instability pathways are the most significant differentiators between pevonedistat sensitive vs. non-sensitive models. In GBM models with modest to low sensitivity to pevonedistat, TOP2A expression was elevated. Combination treatment with the TOP2A inhibitor, etoposide, proved synergistic with pevonedistat. We report, for the first time, that PTEN status both serves as a novel biomarker for GBM sensitivity to pevonedistat and reveals a synergistic vulnerability of TOP2A inhibitors in combination with pevonedistat. Paired use of GBM PDX models of varying sensitivity with drug development testing allows the advancement of a promising agent as well as a patient-enrollment “signature of vulnerability” likely to increase the likelihood of demonstrating therapeutic efficacy in early clinical trials. Citation Format: Shayesteh Ferdosi, Brett Taylor, Matthew Lee, Nanyun Tang, Sen Peng, Rita Bybee, George Reid, Lauren Hartman, Krystine Garcia-Mansfield, Ritin Sharma, Patrick Pirrotte, Frank Furnari, Harshil Dhruv, Michael Berens. Underlying mechanism of response to neddylation inhibition in a subset of glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2534.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2021
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    detail.hit.zdb_id: 410466-3
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