Search

PurposeDiffuse Intrinsic Pontine Glioma is a fatal tumor traditionally treated with radiotherapy (RT) and previously characterized as having a non-inflammatory tumor immune microenvironment (TIME). FLASH is a novel RT technique using an ultra-fast dose-rate which is associated with decreased toxicity, effective tumor control and potential immune-sparing properties. However, the effect of FLASH on the DIPG tumor immune microenvironment (TIME) has not yet been explored.MethodsHere, we perform single-cell RNA sequencing on immune cells isolated from an orthotopic syngeneic murine model of DIPG following the use of FLASH (90Gy/sec) or conventional (2Gy/min) dose-rate RT (CONV-RT), and compare to unirradiated tumor and normal brainstem.ResultsSequencing of immune cells reveals 17 unique populations, most abundant of which is microglia. In the most activated microglia subtypes, both CONV-RT and FLASH show upregulation of type 1 interferon (IFN1) genes and pathway scores compared to unirradiated tumor. In macrophages (MACs) and dendritic cells (DCs), CONV-RT is significantly enriched for IFN1 while this response is less seen with FLASH. Further, FLASH shows an increase in CNS border-associated MACs and upregulation of a myeloid-derived suppressor cell (MDSC) signature in MONOs, less seen with CONV-RT. In the lymphocytes, FLASH yields a higher mature B cell proportion and upregulation of T-cell activation and trafficking markers compared to CONV-RT. Finally, we correlate our data with myeloid cells from cerebrospinal fluid of human DIPG patients and find overlap with our murine tumor- and treatment-associated markers.ConclusionOur work is the first to map CONV-RT and FLASH immune alterations with single-cell resolution in the DIPG TIME. We find that CONV-RT and FLASH sculpt the microglial compartment similarly while recruiting distinct non-resident myeloid subsets and mature B-cell fractions, highlighting the potential to combine each modality with unique immunotherapy regimens in this fatal disease.

Diffuse Midline Glioma (DMG) are fatal pediatric brain tumors with no therapies. We leveraged network-based methodologies to dissect the heterogeneity of DMG tumors and to discover Master Regulator (MR) proteins representing pharmacologically accessible, mechanistic determinants of molecularly distinct cell states. We produced the first DMG regulatory network from 122 publicly available RNAseq profiles with ARACNe (Basso et al. Nat Genet 2005), and inferred sample-specific MR protein activity with VIPER (Alvarez et al. Nat Genet 2016) based on the differential expression of their targets. 7 of the top 25 most active MRs found comprise a well-characterized MR block (MRB2) (Paull et al.Cell 2021), frequently activated across aggressive tumors, and enriched in DMG patient MR signatures (Fisher’s Exact Test p=4.4 × 10−18). A CRISPR/Cas9 KO screen across 3 DMG patient cell lines identified a set of 73/77 essential genes that were enriched in the MR signature of 80% of patient samples (GSEA p=0.000034). FOXM1 emerged as an essential MR, significantly activated across virtually all patients. We then generated RNAseq profiles following perturbation with ~300 oncology drugs in 2 DMG cell lines most representative of patient MR signatures, and used this to identify drugs that invert patient MR activity profiles using the NYS/CA Dept. of Health approved OncoTreat algorithm (Alvarez et al. Nat Genet 2018). OncoTreat predicted sensitivity to HDAC, MEK, CDK, PI3K, and proteosome inhibitors in subsets of patients, overlapping with published DMG drug screens. Importantly, 80% of OncoTreat-predicted drugs (p Further analysis of DMG intra-tumor heterogeneity via protein activity inference across DMG single cells from 6 published scRNAseq profiles identified 6 tumor clusters with unique MR signatures co-existing in virtually all patients representing distinct cellular states (2 astrocyte-, 1 oligodendrocyte-, and 3 oligodendrocyte precursor cell-like states). Targetable MRs and OncoTreat-predicted drugs were distinct between these states. Bulk RNAseq analysis recapitulated predictions seen in the more prevalent OPC-like states, but failed to capture MR and drug predictions for the AC-like states (e.g. JAK1/Ruxolitinib and STAT3/Napabucasin). We are currently validating cell state-specific drug predictions in vivo at single-cell resolution in subcutaneous patient-derived xenograft and orthotopic syngeneic DMG models that we have shown recapitulate patient tumor heterogeneity, including with focused ultrasound-mediated drug delivery. This provides a platform to nominate much-needed novel drugs and drug combinations to treat DMG. Citation Format: Ester Calvo Fernandez, Junqiang Wang, Xu Zhang, Hong-Jian Wei, Hanna E. Minns, Aaron T. Griffin, Lukas Vlahos, Timothy J. Martins, Pamela S. Becker, John Crawford, Robyn D. Gartrell, Luca Szalontay, Stergios Zacharoulis, Zhiguo Zhang, Robert Wechsler-Reya, Cheng-Chia Wu, Andrea Califano, Jovana Pavisic. Network-based inference identifies cell state-specific drugs targeting master regulator vulnerabilities in diffuse midline glioma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4304.

Key Points Standard chemotherapy can still be used for new diagnosis of acute lymphoblastic leukemia in patients with SARS-CoV-2. Corticosteroid can be given safely to patients with SARS-CoV-2 presenting with acute respiratory distress syndrome and ALL.

Diffuse Midline Glioma (DMG), H3K27M altered, confers a dismal survival of 9-15 months and has a non-inflammatory tumor immune microenvironment (TIME). Radiation therapy (RT) is the mainstay treatment for DMG and has been shown in other cancers to recruit an immune component. However, the effect of RT on the DMG TIME has not been explored. In a syngeneic murine model of pontine DMG (PDGFB+, H3.3K27M, p53−/−), mice were treated with single fraction 15Gy RT or sham control, four mice per group. We performed single cell sequencing after CD45 isolation to evaluate the TIME 4 days post RT and compare to untreated tumor (sham control). Unsupervised clustering of 14,848 CD45+ cells revealed 16 immune cell subsets, most abundantly microglia at 75% of cells, with four subtypes representing a spectrum of homeostatic to activated. Microglia from RT are more concentrated in the activated subtypes with an upregulation of interferon response (i.e. Isg15, Ifit3) compared to untreated tumor with an increase in several interferon pathways using REACTOME. Consistent with RT response, RT treated tumors have increase in cell cycle regulatory genes such as Cdkn1a, across all clusters. In non-resident myeloid cells, compared to untreated tumor, RT is associated with a robust upregulation of interferon response genes in both macrophages (Isg15 Fold Change (FC) 2.30; Ifit1 FC 1.64; Ifit3 FC 2.02; Cxcl10 FC 2.29) and dendritic cells (Isg15 FC 2.67; Ifit1 FC 1.72; Ifit3 FC 2.06; Cxcl10 FC 1.50). We also find differential expression of immune checkpoints in RT-treated versus untreated tumor with decreased expression of Lag3, Tim3 (Havcr2), and Csf1R and increased expression of Cd47, Sirpa and Gitr (Tnfrsf18) post RT. In summary, RT stimulates a pro-inflammatory TIME response and alters immune checkpoints in DMG, highlighting the potential for combining RT and immunotherapy in these tumors.

Diffuse midline glioma (DMG) are fatal pediatric brain tumors with no effective systemic therapies. Molecular profiling demonstrates epigenetic dysregulation and heterogeneity, and novel approaches are needed to identify promising drugs and drug combinations. We used network-based computational analysis of RNA-seq to discover Master Regulator (MR) proteins that represent targetable, mechanistic determinants of distinct DMG cell states. We reverse-engineered the first DMG-specific regulatory network from 122 publicly available DMG RNA-seq profiles with ARACNe. Using this network, we measured sample-specific protein activity based on differential expression of their targets via VIPER. Activity-based clustering identified two clusters showing a trend in survival differences (>1 year, by χ2). The most activated MRs (i.e., TOP2A, CENPF, BUB1B, FOXM1, GTSE1, MKI67, E2F8), relative to normal caudate tissue, were enriched in cell cycle regulation members. The cluster with worse outcomes had significantly higher activity. Targetable MRs activated in subsets of patients () included TOP2A, CHEK1, CDK2, and EZH2. RNA-seq profiles were generated in two DMG cell lines following perturbation with ~400 oncology drugs, and used to identify drugs that invert MR activity profiles with the OncoTreat algorithm. We identified four pharmacotypes, and predicted sensitivity to HDAC, proteosome, EGFR, MEK, and PI3K inhibitors (), amongst others, consistent with published DMG high-throughput drug screens. To dissect intra-tumor heterogeneity, we measured protein activity from published single-cell RNA-seq profiles of 6 DMG patients, using single-cell based regulatory networks. Preliminary activity-based analysis identified 6 cell states representing distinct stages of differentiation/proliferation, including an oligodendrocyte precursor cell-like proliferative state whose MRs overlapped with bulk data (i.e. TOP2A, CENPF, FOXM1, E2F8, ZWINT, CCNA2), suggesting this as a key regulatory module. We are identifying cell state-specific MR-inverter drugs with OncoTreat to ultimately suggest drugs and drug combinations that collapse the transcriptional program and induce tumor kill for validation in MR-matched preclinical DMG models.

Diffuse Midline Glioma – H3K27M mutant (DMG), is a fatal and inoperable pediatric brain tumor with limited treatment options as radiation provides only temporary reprieve, leaving the median survival between 9-15 months. Conventional dose-rate radiation (2Gray/minute, CONV) has been shown in other cancers to recruit an immune component, however, this has not been studied in DMG. Ultra-high dose-rate radiation given at 90 Gray/second (FLASH), is a novel technique associated with decreased toxicity and effective tumor control. Using a syngeneic model of brainstem DMG, we performed single-cell RNA sequencing on CD45+ immune cells isolated from tumors irradiated with 15Gray using FLASH or CONV, and compared to unirradiated tumor and normal brainstem. Isolation of 33,308 immune cells revealed 17 unique clusters, most abundant of which was microglia (73.8%), present in four distinct subtypes representing a spectrum from homeostatic to activated. In the most activated microglia, both FLASH and CONV showed an enrichment in type 1 interferon (IFN1) pathway scores compared to untreated tumors (p< 0.001 and p< 0.001, respectively). The most differential response was found in macrophages (MAC) and dendritic cells (DC) with a robust enrichment of IFN1 pathway scores for CONV compared to FLASH (p< 0.001, MAC and p< 0.001 DC). FLASH showed an increase in anti-inflammatory MAC markers such as Mrc1, Cd163, and Maf and an enrichment of myeloid-derived suppressor cell (MDSC) signature in monocytes, not seen in CONV (p< 0.001). Finally, we correlated our data with publicly available single-cell data taken from the cerebrospinal fluid of DMG patients treated with anti-GD2 CAR T Cell therapy and found similar inflammatory markers characteristic of our unirradiated murine tumors. In summary, our work is the first to study immune alterations comparing different dose-rates of radiation with single-cell resolution in DMG, highlighting the potential for combining radiation and immunotherapy in these tumors.

Despite major advances in molecular profiling and numerous clinical trials, diffuse midline glioma (DMG) remains a fatal disease with median survival of only ~9 months and no identified effective drugs. To address this challenge, we leveraged network-based methodologies to dissect the heterogeneity of DMG tumors and to discover Master Regulator (MR) proteins representing pharmacologically accessible, mechanistic determinants of molecularly distinct DMG cell states. The study has produced the first DMG-specific regulatory network, reverse-engineered from 122 publicly available pediatric DMG RNA-seq profiles with ARACNe (Basso et al. Nat Genet 2005). Using this network, we measured protein activity for each sample via VIPER (Alvarez et al., Nat Genet 2016). Activity-based clustering identified 2 clusters, characterized by significant overall survival difference (>1 year, p-val=0.02 by χ2 analysis). Protein activity signatures were not significantly associated with tumor location and Histone3 mutation status. The most aberrantly activated MR proteins across all DMG patients (i.e., TOP2A, CENPF, BUB1B, FOXM1, GTSE1, MKI67, and E2F8), relative to normal caudate tissue from GTEx, were highly enriched in cell cycle regulation members, with samples in the worst outcome cluster showing significantly higher activity. Pharmacologically accessible MRs found to be significantly activated in subsets of patients (p-val To dissect DMG intra-tumor heterogeneity, we measured protein activity from published single-cell RNA-seq profiles of 6 DMG patients, using single-cell based regulatory networks. Activity-based analysis of tumor cells identified 8 clusters representing distinct differentiation and proliferation stages—i.e. astrocyte-like, oligodendrocyte-like, and multiple oligodendrocyte precursor cell (OPC)-like subpopulations. Consistent with bulk-based findings, these included an OPC-like-cycling population presenting highly aberrant activity of proliferative MRs (i.e. TOP2A, CENPF, FOXM1, E2F8, ZWINT, and CCNA2), suggesting this as a key DMG regulatory module (Tumor Checkpoint). We are working to define targetable MRs in these subpopulations, and generating RNA-seq profiles of SU-DIPG-VI and SF8628, two DMG cell lines showing protein activity similarity to >95% of patient samples by enrichment analysis (p-val < 10E-5), following perturbation with ~400 oncology drugs. This will allow us to identify drugs capable of inducing tumor demise by inverting the activity of the MRs of each tumor subpopulation, using the NY Dept. of Health approved OncoTreat algorithm (Alvarez et al., Nat Genet 2018). We are currently finalizing and validating both MR and drug predictions to nominate novel, much-needed therapeutic strategies. Citation Format: Ester Calvo Fernández, Junqiang Wang, Aaron T. Griffin, Luca Szalontay, Stergios Zacharoulis, Jovana Pavisic, Andrea Califano. A systems biology approach to defining tumor heterogeneity, prognostic and targetable master regulator protein signatures from bulk and single cell RNA-seq in diffuse midline glioma (DMG) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 486.

Despite many clinical trials, outcome for osteosarcoma (OS) patients remains poor, especially for those with metastatic or relapsed/refractory disease. We leveraged network-based systems biology approaches to discover Master Regulator (MR) proteins representing pharmacologically accessible, mechanistic determinants of OS cell state, and to dissect tumor transcriptional heterogeneity. MRs were identified by interrogating an OS regulatory network—generated from 87 RNAseq profiles in the TARGET OS cohort—with gene expression signatures from 149 diagnostic OS samples, using the VIPER algorithm. RNAseq profiles were generated in four sarcoma cell lines following perturbation with ~400 oncology drugs, and used to identify drugs capable of inverting MR activity profiles with the OncoTreat algorithm. Unsupervised, protein activity-based clustering of the samples identified two clusters, characterized by a significant overall survival difference (76% vs 38%, log-rank p-val 0.0041). Patients in the high-risk cluster presented aberrant activity of proteins involved in cell cycle (FOXM1, CENPF, TOP2A) and epigenetic remodeling (EZH2, KDM1A), while those in the low-risk cluster had aberrant activity of proteins involved in immune response (VAV1, CD86, CEBPE), interferon gama signaling (IRF5, MNDA), and senescence control (CREG1, TFEC). We further identified patients with metastatic disease and particularly poor outcome ( Citation Format: Somnath Tagore, Jovana Pavisic, Aaron T. Griffin, Katherine Janeway, Andrew L. Kung, Filemon Dela Cruz, Alejandro Sweet-Cordero, Inge Behroozfard, Stanley Leung, Alex Lee, Darrell Yamashiro, Julia Glade Bender, Andrea Califano. A systems biology approach to defining tumor heterogeneity and prognostic and targetable master regulator protein signatures from bulk and single-cell RNAseq in osteosarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 488.

Diffuse Midline Glioma with H3K27M mutation (DMG) is an aggressive unresectable central nervous system tumor of the brainstem, midline thalamus, or spine. Prognosis is poor and systemic agents have been ineffective partially due to limited permeability of the blood brain barrier (BBB). Non-invasive low intensity focused ultrasound (FUS) can be used for BBB opening (BBBO). Our preclinical studies showed safety and feasibility of targeting and BBBO in the brainstem; however, to our knowledge, FUS-guided BBBO for thalamic DMG has yet to be reported. RNA-seq was performed on mouse syngeneic DMG cells 4423 (PDGFB+, H3.3K27M, p53−/−) and results recapitulated molecular programs seen in human tumors. 4423 cells were injected into the thalamus of male B6 (Cg)-Tyrc-2J/J mice at 1.6mm lateral and 1.8mm posterior to the bregma at a depth of 3.2mm. MRI at 14-21 days post injection confirmed thalamic tumor growth. Histological analysis with Hematoxylin and Eosin stain was consistent with thalamic DMG. Tumor implantation rate was 85% and median survival was 38 days post injection. To test safety and feasibility of BBBO for thalamic tumors, a 1.5 MHz FUS transducer was used with concurrent microbubble injection. BBBO assessed by contrast-enhanced MRI. FUS achieved BBBO targeting the thalamic tumor without increased morbidity or mortality and BBB closure was observed on day 3 post-sonication. Next we tested the tolerance of drug delivery with panobinostat post-FUS at a dose of 20mg/kg weekly. The results are preliminary at this time; however, animals tolerated the combination therapy without morbidity or mortality. Preclinical models are crucial to improve the development of new therapeutic strategies. Establishing this syngeneic thalamic DMG murine model provides the opportunity to test FUS as a non-invasive drug delivery technology for thalamic DMG compared to brainstem DMG, and to re-visit therapeutic agents previously considered ineffective due to limited penetration of the BBB.

OBJECTIVE: To present an approach on using electronic health record (EHR) data that assesses how different eligibility criteria, either individually or in combination, can impact patient count and safety (exemplified by all-cause hospitalization risk) and further assist with criteria selection for prospective clinical trials. MATERIALS AND METHODS: Trials in three disease domains – relapsed/refractory (r/r) lymphoma/leukemia; hepatitis C virus (HCV); stages 3 and 4 chronic kidney disease (CKD) – were analyzed as case studies for this approach. For each disease domain, criteria were identified and all criteria combinations were used to create EHR cohorts. Per combination, two values were derived: (1) number of eligible patients meeting the selected criteria; (2) hospitalization risk, measured as the hazard ratio between those that qualified and those that did not. From these values, k-means clustering was applied to derive which criteria combinations maximized patient counts but minimized hospitalization risk. RESULTS: Criteria combinations that reduced hospitalization risk without substantial reductions on patient counts were as follows: for r/r lymphoma/leukemia (23 trials; 9 criteria; 623 patients), applying no infection and adequate absolute neutrophil count while forgoing no prior malignancy; for HCV (15; 7; 751), applying no human immunodeficiency virus and no hepatocellular carcinoma while forgoing no decompensated liver disease/cirrhosis; for CKD (10; 9; 23893), applying no congestive heart failure. CONCLUSIONS: Within each disease domain, the more drastic effects were generally driven by a few criteria. Similar criteria across different disease domains introduce different changes. Although results are contingent on the trial sample and the EHR data used, this approach demonstrates how EHR data can inform the impact on safety and available patients when exploring different criteria combinations for designing clinical trials.

BackgroundDiffuse intrinsic pontine gliomas (DIPG’s) are immunologically inert tumors with a median survival of 9–15 months. Radiation therapy (RT) is the mainstay treatment for DIPG but is associated with immunodepletion of the tumor microenvironment (TME) at high dose ranges. FLASH, or ultra-fast dose rate RT, represents a novel ablative technique that may spare TME immune responses while decreasing tumor burden. Here, we present single-cell immune profiling of DIPG tumors treated with FLASH, conventional dose rate RT (CONV) or no RT (SHAM).MethodsMurine H3.3K27M mutant DIPG cells were stereotactically injected and tumor induction confirmed by magnetic resonance imaging (MRI) 15 days later. DIPG-bearing mice were randomly assigned to one of three treatment groups (n=4/group), FLASH, CONV or SHAM. A fourth group with no tumor (NML) was included as a negative biological control. A modified linear accelerator was used to deliver 15 Gy of electron RT to the brainstem at dose rates of 90 Gy/second and 2 Gy/minute, for the FLASH and CONV groups, respectively. Four days post-RT, mice brainstems were harvested, homogenized, stained for CD45 and tagged with a hashtag antibody specific to each group. CD45+ immune cells were isolated and sequenced using the 10X Genomics chromium single-cell 3’ platform. After processing and alignment of the reads using CellRanger with default parameters, the data was quality checked and filtered before hashtag demultiplexing, unsupervised clustering and downstream analysis was implemented following the Seurat R package. Differential expression evaluated based on the non-parametric Wilcoxon rank sum test. Key genes determine by an adjusted p value of < 0.05 based on bonferroni correction and |avg log2FC| > 0.8.ResultsPreliminary analysis identifies 15 clusters with distinct CD45 immune phenotypes (figure 1). Differential gene expression analysis by hashtag antibody (treatment group) reveals 14 clusters differentially expressing key genes, including 3 clusters upregulated in DIPG compared to NML, and 2 clusters upregulated in irradiated tumors compared to SHAM and NML (figure 2). Notably, analysis demonstrates an individual cluster upregulated in FLASH versus all other groups (p = 3.07E-171). Further deconvolution of specific immune phenotypes represented by each cluster is ongoing.Abstract 91 Figure 1tSNE plot based on clustering of RNA signatures, grouped by RNAAbstract 91 Figure 2tSNE plot based on clustering of RNA signatures, grouped by hashtag antibodyConclusionsOur preliminary analysis shows differential immune responses among DIPG tumors compared to NML. We also find several immune cell subsets that are unique to DIPG treated with CONV or FLASH compared to unirradiated samples. Most notably, we identify a single immune cell subset that is exclusive to FLASH alone, indicating that FLASH elicits a unique immune response in murine DIPG.

Diffuse intrinsic pontine glioma (DIPG) remains a fatal disease with no effective drugs to date. Mutation-based precision oncology approaches are limited by lack of targetable mutations and genetic heterogeneity. We leveraged systems biology methodologies to discover common targetable disease drivers—master regulator proteins (MRs)—in DIPG to expand treatment options. Using the metaVIPER algorithm, we interrogated an integrated low grade glioma and GBM gene regulatory network with 31 DIPG-gene expression signatures to identify tumor-specific MRs by differential expression of their transcriptional targets. Unsupervised clustering identified MR signatures of upregulated activity in RRM2/TOP2A in 13 patients, CD3D in 5 patients, and MMP7, TACSTD2, RAC2 and SLC15A1/SLC34A2 in individual patients, all of which can be targeted. Notably, intratumoral administration of etoposide by convection enhanced delivery was effective in murine proneural gliomas in which TOP2 was identified as a MR while RRM2—targetable by drugs such as cladribine—has been shown to be a positive regulator of glioma progression whose knock-down inhibits tumor growth. We also prioritized drugs by their ability to reverse MR-activity signatures using a large drug-perturbation database. Patients clustered by predicted drug sensitivities with distinct groups of tumors predicted to respond to proteasome inhibitors, Thiotepa or Volasertib all of which have early evidence in treating gliomas. We will refine this analysis in a multi-institutional study of >100 patient gene expression profiles to define MR signatures driving known biological/molecular disease subtypes, use DIPG cell lines recapitulating common MR architectures to optimize therapy prioritization, and validate our findings in vivo.

Despite recent advances, overall survival for children with acute myeloid leukemia (AML) remains relatively low at 70 to 80%. Further refinement of risk stratification is paramount to guiding optimal therapy selection and improving outcomes. In this study, we leverage machine learning and network-based systems biology approaches that infer tumor protein activity and define key disease drivers - master regulator (MR) proteins - in pediatric AML to further refine existing patient risk stratification and identify potential therapeutic targets. Using the ARACNe and VIPER algorithms1, we reverse-engineered an AML gene regulatory network and inferred protein activity from enrichment of the proteins' transcriptional targets in gene expression signatures from a novel 1080-patient cohort treated on COG AAML1031. We integrated ensemble clustering with feed-forward feature selection on VIPER-inferred protein activity to identify groups of patients with unique protein activity signatures and correlated them to survival by Cox proportional-hazards regression analysis. We identified features predictive of each group by Monte Carlo cross-validation and binary classification. We found that the activity of 2-4 MR proteins was sufficient to predict patient stratification for each group with areas under the receiver-operator characteristic curve above 0.9. We validated our findings in three external test datasets: St-Jude Children's Research Hospital (n=249), TARGET (n=682) and Erasmus MC Sophia's Children's Hospital (n=237). We identified 10 groups with significant survival differences (P < 0.0001, overall survival range 42-85%). This includes a new high-risk group that is not associated with any known cytogenomic features, but shows high activity of NOTCH signaling pathway regulators HES1 and HEY2. Other groups show aberrant activity for known transcription regulators; for example RUNX1, KDM5B and POU4F1. In conclusion, we propose novel patient risk stratification based on VIPER-inferred MR protein activity in pediatric AML. We define 10 groups with differential survival, including refinement of a classically-characterized intermediate-risk cytogenomically normal group as high-risk. We classify patients into therapeutically-relevant risk groups that can guide treatment decision-making. We define the MR proteins driving these groups to offer mechanistic insights into AML tumorigenesis as well as suggest potential molecular targets for therapies. Reference: 1. Califano A, Alvarez M, The recurrent architecture of tumour initiation, progression and drug sensitivity, Nat Rev Cancer (2017), 17(2): 116-130 Citation Format: Alexandre P. Alloy, Jovana Pavisic, Rhonda E. Ries, Tanja Gruber, C Michel Zwaan, Monique L. den Boer, James R. Downing, Adolfo Ferrando, Soheil Meshinchi, Andrea Califano. Novel pediatric AML patient risk stratification by inferred protein activity through integrative network analysis and machine learning [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 1.

Diffuse intrinsic pontine glioma (DIPG) is the lethal high-grade brain tumor in children with no effective treatment options to date. Despite excessive clinical trials, the prognosis remains poor, with a median overall survival (mOS) of less than 1 year. Genomic studies of DIPG tissue have identified highly recurrent mutations in genes encoding histone H3 resulting in the substitution of lysine to methionine at position 27 (K27M), which is found in approximately 80% of DIPG. Recent drug screening studies identified the histone deacetylase (HDAC) inhibitors panobinostat as a highly effective drug against DIPG in vitro. However, due to the poor Blood-Brain Barrier (BBB) penetration of systemic administration, to enhance the delivery of panobinostat to improve treatment efficacy is needed. Focused ultrasound (FUS) has been shown to be able to safely and non-invasively open BBB to enhance drug delivery. Hence, in this study, we hypothesize that FUS-mediated BBBO (BBBO) can enhance the delivery of panobinostat for a therapeutic benefit in DIPG. Herein we established the syngeneic DIPG model by intracranially injecting mouse DIPG cells (PDGFB+, H3.3K27M, p53−/−) and used FUS and microbubbles to open BBB and enhance the panobinostat delivery. Magnetic resonance (MR) imaging was utilized to evaluate BBBO and tumor progression. We first demonstrated that FUS-mediated BBB-opening is safe and feasible to mice with DIPG tumors by MR imaging and passive cavitation detection. Moreover, this DIPG cell line is very sensitive to panobinostat in in vitro cytotoxicity assay. The combined treatment of FUS-mediated BBBO and panobinostat showed benefits in both local control and overall survival. The current results demonstrated FUS could increase the treatment efficacy of panobinostat to DIPG animals may be due to the increase of targeted delivery of systemic panobinostat to DIPG tumors in brainstem.

OBJECTIVE This study aims to evaluate the childhood cancer experience in commercially produced, readily available films that include a character with childhood cancer, with a particular focus on psychosocial care. METHODS We reviewed 29 films, using quantitative and qualitative content analysis, to identify the medical and psychosocial characteristics of the cinematic childhood cancer experience. We rated psychosocial support on a 5-point scale (0 to 4) based on the availability and efficacy of support characters in the categories of nonprofessional internal (eg, parent), nonprofessional external (eg, friend), professional medical (eg, oncologist), and professional psychosocial (eg, social worker) supports. RESULTS Film depicts an unrealistic, bleak picture of childhood cancer, with a 66% mortality rate among the 35 characters evaluated. Psychosocial supports portrayed in film are generally limited to resources already available to families before the cancer diagnosis: mean ratings across films were 2.4 for both nonprofessional, 1.6 for professional medical, and 0.3 for professional psychosocial supports (Kruskal-Wallis χ3=43.1051, P

Graft-versus-leukemia (GVL) against chronic-phase chronic myelogenous leukemia (CP-CML) is potent, but it is less efficacious against acute leukemias and blast-crisis chronic myelogenous leukemia (BC-CML). The mechanisms underlying GVL resistance are unknown. Previously, we found that alloreactive T cell targeting of GVL-sensitive bcr-abl–induced mouse CP-CML (mCP-CML) required TCR–MHC interactions and that multiple and redundant killing mechanisms were in play. To better understand why BC-CML is resistant to GVL, we performed a comprehensive analysis of GVL against mouse BC-CML (mBC-CML) induced by the retroviral transfer of the bcr-abl and NUP98/HOXA9 fusion cDNAs. Like human BC-CML, mBC-CML was GVL resistant, and this was not due to accelerated kinetics or a greater leukemia burden. To study T cell recognition and killing mechanisms, we generated a panel of gene-deficient leukemias by transducing bone marrow from gene-deficient mice. T cell target recognition absolutely required that mBC-CML cells express MHC molecules. GVL against both mCP-CML and mBC-CML required leukemia expression of ICAM-1. We hypothesized that mBC-CML would be resistant to some of the killing mechanisms sufficient to eliminate mCP-CML, but we found instead that the same mechanisms were effective against both types of leukemia, because GVL was similar against wild-type or mBC-CML genetically lacking Fas, TRAIL-R, Fas/TRAIL-R, or TNFR1/R2 or when donor T cells were perforin−/−. However, mCP-CML, but not mBC-CML, relied on expression of programmed death-1 ligands 1 and 2 (PD-L1/L2) to resist T cell killing, because only GVL against mCP-CML was augmented when leukemias lacked PD-L1/L2. Thus, mBC-CML cells have cell-intrinsic mechanisms, distinct from mCP-CML cells, which protect them from T cell killing.

Background Glutathione (GSH) plays an important role in anti-oxidant defense and detoxification reactions. It is primarily synthesized in the liver by the transsulfuration pathway and exported to provide precursors for in situ GSH synthesis by other tissues. Deficits in glutathione have been implicated in aging and a host of diseases including Alzheimer's disease, Parkinson's disease, cardiovascular disease, cancer, Down syndrome and autism. Approach We explore the properties of glutathione metabolism in the liver by experimenting with a mathematical model of one-carbon metabolism, the transsulfuration pathway, and glutathione synthesis, transport, and breakdown. The model is based on known properties of the enzymes and the regulation of those enzymes by oxidative stress. We explore the half-life of glutathione, the regulation of glutathione synthesis, and its sensitivity to fluctuations in amino acid input. We use the model to simulate the metabolic profiles previously observed in Down syndrome and autism and compare the model results to clinical data. Conclusion We show that the glutathione pools in hepatic cells and in the blood are quite insensitive to fluctuations in amino acid input and offer an explanation based on model predictions. In contrast, we show that hepatic glutathione pools are highly sensitive to the level of oxidative stress. The model shows that overexpression of genes on chromosome 21 and an increase in oxidative stress can explain the metabolic profile of Down syndrome. The model also correctly simulates the metabolic profile of autism when oxidative stress is substantially increased and the adenosine concentration is raised. Finally, we discuss how individual variation arises and its consequences for one-carbon and glutathione metabolism.