Diffuse Midline Glioma (DMG) are universally fatal, primarily pediatric malignancies affecting the midline structures (i.e., pons, thalamus, and spinal cord) of the central nervous system. Despite decades of clinical trials, no drugs have emerged as effective against this disease, and treatment remains limited to palliative radiation therapy. Primary treatment challenges include: A) Well-stablished, yet non-actionable, genetic alterations; B) significant intratumoral heterogeneity, and C) blood-brain barrier (BBB) drug permeability. Here, we address the former two challenges by leveraging network-based methodologies to dissect the heterogeneity of DMG tumors and to discover Master Regulators (MR) proteins representing pharmacologically accessible, mechanistic determinants of molecularly distinct DMG cell states. We reverse engineered the first DMG gene regulatory network from 122 publicly available DMG RNA-seq profiles with ARACNe and inferred sample-specific MR protein activity with VIPER based on the differential expression of their targets. Nine of the top 25 most active MRs (i.e., FOXM1, CENPF, TOP2A, ASF1B, E2F2, TIMELESS, MYBL2, CENPK, TRIP13) comprise a well-characterized MR block (MRB2), frequently activated across aggressive tumors, and found to be enriched in DMG patient MR signatures (Fisher’s Exact Test p = 3.96x10-16). A pooled CRISPR/Cas9-mediated knockout (KO) screen across three DMG patient cell lines targeting 1,433 genes identified a set of 73 essential genes that were enriched in the MR signature of 80% of patient samples (GSEA p = 0.000034). FOXM1 emerged as a highly essential MR, significantly activated across virtually all patients. We then generated drug-induced differential protein activity from RNA-seq profiles following perturbation with 372 oncology drugs in two DMG cell lines that together recapitulate DMG patient MR and used this to identify drugs that invert patient MR activity profiles using the NYS/CA Department of Health approved OncoTreat algorithm OncoTreat predicted sensitivity to HDAC, MEK, CDK, PI3K, and tyrosine kinase inhibitors in subsets of patients, overlapping with published DMG drug screens. Importantly, 80% of OncoTreat-predicted drugs (p < 10-5) from three DMG patient tumor biopsies showed in vitro sensitivity in cultured tumor cells from the respective patients, with overall 68% accuracy among 223 drugs evaluated by both OncoTreat and in vitro drug screen (Fisher’s Exact Test p = 0.0449). Given known resistance in DMG to single-agent therapy, we further interrogated single-cell DMG regulatory networks generated by ARACNe with gene expression signatures from 3,039 tumor cells previously published across six patients using VIPER to infer single-cell regulatory protein activity. Unsupervised clustering of cells by protein activity defined 7 patient-independent cell states with distinct MR profiles reflecting known glial lineage markers (OPC-like-S1, OPC-like-S2, OC-like-S1, OC-like-S2, Cycling, AC-like, and AC/OPC-like). We identified drugs that invert the MR activity profiles of the individual cell states by using OncoTarget (inhibitors of individual MRs) or OncoTreat using the drug-induced differential protein activity we previously generated. Predicted drugs were distinct across the previously defined cell states with bulk RNA-seq recapitulating predictions seen in the more prevalent OPC-like stated, but failing to recapitulate the MRs and drug predictions for the smaller AC-like stated. We selected five drugs targeting the OPC/cycling-like cells (Trametinib, Dinaciclib, Avapritinib, Mocetinostat, and Etoposide), and four drugs targeting the AC-like cells (Ruxolitinib, Venetoclax, Napabucasin, Larotrectinib) for further validation as these states comprised most tumor cells across patients. We then generated single-cell RNA-seq for 95,687 cells after 5 days of treatment with either vehicle control (n = 4) or candidate drug (n = 2-3/drug) in subcutaneous SU-DIPG-XVII patient cell line-derived mouse models. We show this model recapitulates DMG cell states seen in patients, and confirm reduction in tumor growth and significant depletion of either OPC/cycling-like cells or AC-like cells in line with our drug predictions for 8/9 candidate drugs (Chi-square p<0.01). We further treated a syngeneic (DIPG4423) orthotopic DMG model with each drug and demonstrate significant differences in survival with Avapritinib, Dinaciclib, and Trametinib. Notably, the combination of drugs targeting OPC/cycling-like and AC-like cells (i.e. Trametinib+Ruxolitinib, Dinaciclib+Ruxolitinib, Avapritinib+Venetoclax, etc.) showed significantly lower tumor volumes after 2 weeks of treatment as compared to vehicles or each drug alone, and significant survival differences for some of the combinations. This work provides a precision medicine platform to nominate much-needed novel drug combinations addressing DMG tumor heterogeneity for further study to improve outcomes in this devastating disease.

Introduction: Survivors of childhood brain tumors (SCBT) are an emerging group of cancer survivors that has an increased risk of cardiovascular disease, stroke, and type 2 diabetes. SCBT have equivalent obesity rates but excess fat mass (adiposity) when compared to the general population. As adiposity is an important and potentially modifiable risk factor for cardiometabolic outcomes in the general population, its measurement may allow for early stratification of adverse health outcomes in SCBT so that they can be targeted with prevention and treatment strategies designed to improve outcomes. However, measuring adiposity often requires specialized equipment that is not always readily available, and a clinical measure is needed to facilitate these measurements in a feasible fashion. Tri-ponderal Mass Index (TMI; kg/m3) is a superior measure of adiposity compared to Body Mass Index (BMI) z-score in healthy children. However, it has not been assessed in SCBT. The aim of this thesis was to validate TMI as an adiposity measure in SCBT compared to non-cancer controls. Methods: A cross-sectional analysis was completed from a cohort study sample including 44 SCBT (n=20 female) and 137 (n=64 female) healthy controls between 5-17 years of age. Total adiposity was determined by fat mass percentage (%FM) using bioelectrical impedance analysis and central adiposity was assessed by waist-to-hip (WHR) and waist-to-height (WHtR) ratios. Results: TMI demonstrated equally strong correlations with total adiposity and stronger association with WHtR compared to BMI z-score in SCBT and healthy control children. Conclusions: TMI may serve as a reliable and feasible clinical measure of adiposity in both SCBT and healthy children. The availability of TMI may allow for early stratification of survivors at risk of excess adiposity to allow early targeting with interventions to improve health outcomes. / Thesis / Master of Science in Medical Sciences (MSMS) / Over the last thirty years, childhood cancer survival rates have greatly improved. However, these rates decrease over the lifespan of survivors. Certain groups within the survivors of childhood cancer population, including survivors of childhood brain tumors (SCBT), are at a higher risk of obesity, heart disease and type 2 diabetes. Excess body fat is a major contributor to the development of these adverse health outcomes in the general population and may represent an entry point to prevent and treat these conditions in SCBT. However, measuring fat mass in the clinical setting requires specialized equipment that can be expensive, time-consuming and not readily available in all settings. Therefore, this thesis aims to explore measures of fat mass that are both feasible and reliable in a clinical setting in SCBT compared to the general pediatric population. We have identified the tri-ponderal mass index (TMI), defined as weight divided by height cubed (kg/m3) as a valid measure of the fat mass in both SCBT and healthy children. We conclude that TMI may serve as a reliable and feasible measure of adiposity in both SCBT and healthy children in clinical settings and assist in the early identification of survivors at risk of obesity and cardiometabolic outcomes to prioritize early interventions to improve outcomes.

Diffuse midline glioma (DMG) is the most aggressive primary brain tumor in children. All previous studies examining the role of systemic agents have failed to demonstrate a survival benefit; the only standard of care is radiation therapy (RT), which provides transient symptomatic relief and limited survival advantage. Successful implementation of radiosensitization strategies in DMG remains elusive. In this project, we identify Napabucasin, an NAD(P)H Quinone Dehydrogenase 1 (NQO1)-bioactivatable reactive oxygen species (ROS) inducer, as a potent radiosensitizer in DMG both in vitro and in vivo. We show Napabucasin-mediated ROS production and cytotoxicity are dependent on NQO1, and establish the novel safety, feasibility, and survival benefit of convection-enhanced drug delivery (CED) of Napabucasin to circumvent the blood-brain barrier (BBB) concurrent with RT in an orthotopic DMG mouse model. Using this multi-modality strategy, we identify a promising treatment paradigm in DMG that may also be utilized to develop novel therapeutic treatments for other brain tumors.

Call number: LD2668 .T4 1966 M22 / Master of Science

published_or_final_version / Pathology / Master / Master of Medical Sciences

The cellular origin of prostaglandins in human tumors was investigated using cell fractionation procedures and high resolution gas chromatography. Additionally, the role of macrophages and prostaglandins on human tumor cloning in vitro was investigated. Spontaneous human tumors were prepared as single cell suspensions which were subsequently manipulated to yield macrophage-enriched, and tumor cell enriched (macrophage-depleted) subpopulations of cells. A fused silica capillary gas chromatographic analysis with electron capture detection was developed to measure derivatized prostaglandins in the supernatant of the cell subpopulation incubations. The derivative used for the analysis was the pentafluorobenzyl ester-methoxime-trimethyl-silyl ether. The assay showed a detection limit of 25 picograms of prostaglandins E₁, E₂, F₂ₐ, and I₂ (which was detected as 6-Keto-PGF₁ₐ). Analysis of cell subpopulations of seventeeen tumor samples showed that the macrophage-enriched cells were responsible for the large majority of prostaglandin production in vitro (p ≤ 0.02). It was found that the major prostaglandins were PGE₂ and PGI₂. The range of values measured for macrophage produced prostaglandin E₂ was 1.1 to 704.8 ng/ml after a 24 hour incubation of 10⁶ cells. Prostaglandin I₂ was also produced by the macrophage-enriched cell subpopulation with values ranging from 1.2 to 334.3 ng/ml. This is the first report of prostaglandin I₂ production by host macrophages infiltrating human tumors. Studies of the effect of macrophage depletion and reconstitution on the ability of tumor cells to form colonies in vitro were performed. A two layer soft agar assay was used to evaluate tumor cells clonogenicity. The results demonstrated that macrophages infiltrating human carcinoma samples function in a supportive role for tumor cell colony formation in vitro. Using a prostaglandin synthesis inhibitor, flurbiprofen, it was shown that this support was not the result of a direct effect of prostaglandins on the tumor cells. Possible roles for macrophage produced prostaglandins in cancer are discussed.

No description available.

No description available.

Call number: LD2668 .T4 1959 S37

Understanding how tumors evolve and drive uncontrolled cellular growth may lead to better prognosis and therapy for individuals suffering from cancer. A key to understanding the paths of progression are to develop computational and experimental methods to dissect clonal heterogeneity and statistically model evolutionary routes. This thesis contains results from analysis of genomic data using computational methods that integrate diverse next generation sequencing data and evolutionary concepts to model tumor evolution and delineate likely routes of genomic alterations. First, I introduce some background and present studies into how tumor genomic sequencing tells us about tumor evolution. This will encompass some of the principles and practices related to tumor heterogeneity within the field of computional biology. Second, I will present a study of longitudinal sampling in Glioblastoma (GBM) in cohort of 114 individuals pre- and post-treatment. We will see how genomic alterations were dissected to uncover a diverse and largely unexpected landscape of recurrence. This details major observations that the recurrent tumor is not likely seeded by the primary lesion. Second, to dissect heterogeneity from clonal evolution, multiple biopsies will be added to extend our longitudinal GBM cohort. This new data will introduce analyses to explicate inter and intra-tumor heterogeneity of GBM. Specifically, we identify a metric of intratumor heterogeneity able to identify multisector biopsies and propose a model of tumor growth in multiple GBM. These results will relate to clinical outcome and are in agreement with previously established hypotheses in truncal mutation targeting. Fourth, I will introduce new models of clonal growth applicable to 2 patient biopsies and then fit these to our GBM cohort. Simulations are used to verify models and a brief proof is presented.