Novel Brain-Penetrant, Small-Molecule Tubulin Destabilizers for the Treatment of Glioblastoma.

Glioblastoma (GB) is the most lethal brain cancer in adults, with a 5-year survival rate of 5%. The standard of care for GB includes maximally safe surgical resection, radiation, and temozolomide (TMZ) therapy, but tumor recurrence is inevitable in most GB patients. Here, we describe the development of a blood-brain barrier (BBB)-penetrant tubulin destabilizer, RGN3067, for the treatment of GB. RGN3067 shows good oral bioavailability and achieves high concentrations in rodent brains after oral dosing (Cmax of 7807 ng/mL (20 µM), Tmax at 2 h). RGN3067 binds the colchicine binding site of tubulin and inhibits tubulin polymerization. The compound also suppresses the proliferation of the GB cell lines U87 and LN-18, with IC50s of 117 and 560 nM, respectively. In four patient-derived GB cell lines, the IC50 values for RGN3067 range from 148 to 616 nM. Finally, in a patient-derived xenograft (PDX) mouse model, RGN3067 reduces the rate of tumor growth compared to the control. Collectively, we show that RGN3067 is a BBB-penetrant small molecule that shows in vitro and in vivo efficacy and that its design addresses many of the physicochemical properties that prevent the use of microtubule destabilizers as treatments for GB and other brain cancers.

Therapeutic HDAC inhibition in hypermutant diffuse intrinsic pontine glioma.

Constitutional mismatch repair deficiency (CMMRD) is a cancer predisposition syndrome associated with the development of hypermutant pediatric high-grade glioma, and confers a poor prognosis. While therapeutic histone deacetylase (HDAC) inhibition of diffuse intrinsic pontine glioma (DIPG) has been reported; here, we use a clinically relevant biopsy-derived hypermutant DIPG model (PBT-24FH) and a CRISPR-Cas9 induced genetic model to evaluate the efficacy of HDAC inhibition against hypermutant DIPG. We screened PBT-24FH cells for sensitivity to a panel of HDAC inhibitors (HDACis) in vitro, identifying two HDACis associated with low nanomolar IC50s, quisinostat (27 nM) and romidepsin (2 nM). In vivo, quisinostat proved more efficacious, inducing near-complete tumor regression in a PBT-24FH flank model. RNA sequencing revealed significant quisinostat-driven changes in gene expression, including upregulation of neural and pro-inflammatory genes. To validate the observed potency of quisinostat in vivo against additional hypermutant DIPG models, we tested quisinostat in genetically-induced mismatch repair (MMR)-deficient DIPG flank tumors, demonstrating that loss of MMR function increases sensitivity to quisinostat in vivo. Here, we establish the preclinical efficacy of quisinostat against hypermutant DIPG, supporting further investigation of epigenetic targeting of hypermutant pediatric cancers with the potential for clinical translation. These findings support further investigation of HDAC inhibitors against pontine high-grade gliomas, beyond only those with histone mutations, as well as against other hypermutant central nervous system tumors.

Genome-wide analysis of aberrant position and sequence of plasma DNA fragment ends in patients with cancer.

Genome-wide fragmentation patterns in cell-free DNA (cfDNA) in plasma are strongly influenced by cellular origin due to variation in chromatin accessibility across cell types. Such differences between healthy and cancer cells provide the opportunity for development of novel cancer diagnostics. Here, we investigated whether analysis of cfDNA fragment end positions and their surrounding DNA sequences reveals the presence of tumor-derived DNA in blood. We performed genome-wide analysis of cfDNA from 521 samples and analyzed sequencing data from an additional 2147 samples, including healthy individuals and patients with 11 different cancer types. We developed a metric based on genome-wide differences in fragment positioning, weighted by fragment length and GC content [information-weighted fraction of aberrant fragments (iwFAF)]. We observed that iwFAF strongly correlated with tumor fraction, was higher for DNA fragments carrying somatic mutations, and was higher within genomic regions affected by copy number amplifications. We also calculated sample-level means of nucleotide frequencies observed at genomic positions spanning fragment ends. Using a combination of iwFAF and nine nucleotide frequencies from three positions surrounding fragment ends, we developed a machine learning model to differentiate healthy individuals from patients with cancer. We observed an area under the receiver operative characteristic curve (AUC) of 0.91 for detection of cancer at any stage and an AUC of 0.87 for detection of stage I cancer. Our findings remained robust with as few as 1 million fragments analyzed per sample, demonstrating that analysis of fragment ends can become a cost-effective and accessible approach for cancer detection and monitoring.

The Texas Immuno-Oncology Biorepository, a statewide biospecimen collection and clinical informatics system to enable longitudinal tumor and immune profiling.

A detailed understanding of the molecular and immunological changes that occur longitudinally across tumors exposed to immune checkpoint inhibitors is a significant knowledge gap in oncology. To address this unmet need, we created a statewide biospecimen collection and clinical informatics system to enable longitudinal tumor and immune profiling and to enhance translational research. The Texas Immuno-Oncology Biorepository (TIOB) consents patients to collect, process, store, and analyze serial biospecimens of tissue, blood, urine, and stool from a diverse population of over 100,000 cancer patients treated each year across the Baylor Scott & White Health system. Here we sought to demonstrate that these samples were fit for purpose with regard to downstream multi-omic assays. Plasma, urine, peripheral blood mononuclear cells, and stool samples from 11 enrolled patients were collected from various cancer types. RNA isolated from extracellular vesicles derived from plasma and urine was sufficient for transcriptomics. Peripheral blood mononuclear cells demonstrated excellent yield and viability. Ten of 11 stool samples produced RNA quality to enable microbiome characterization. Sample acquisition and processing methods are known to impact sample quality and performance. We demonstrate that consistent acquisition methodology, sample preparation, and sample storage employed by the TIOB can produce high-quality specimens, suited for employment in a wide array of multi-omic platforms, enabling comprehensive immune and molecular profiling.

Intraventricular B7-H3 CAR T Cells for Diffuse Intrinsic Pontine Glioma: Preliminary First-in-Human Bioactivity and Safety.

Diffuse intrinsic pontine glioma (DIPG) remains a fatal brainstem tumor demanding innovative therapies. As B7-H3 (CD276) is expressed on central nervous system (CNS) tumors, we designed B7-H3-specific chimeric antigen receptor (CAR) T cells, confirmed their preclinical efficacy, and opened BrainChild-03 (NCT04185038), a first-in-human phase I trial administering repeated locoregional B7-H3 CAR T cells to children with recurrent/refractory CNS tumors and DIPG. Here, we report the results of the first three evaluable patients with DIPG (including two who enrolled after progression), who received 40 infusions with no dose-limiting toxicities. One patient had sustained clinical and radiographic improvement through 12 months on study. Patients exhibited correlative evidence of local immune activation and persistent cerebrospinal fluid (CSF) B7-H3 CAR T cells. Targeted mass spectrometry of CSF biospecimens revealed modulation of B7-H3 and critical immune analytes (CD14, CD163, CSF-1, CXCL13, and VCAM-1). Our data suggest the feasibility of repeated intracranial B7-H3 CAR T-cell dosing and that intracranial delivery may induce local immune activation. SIGNIFICANCE: This is the first report of repeatedly dosed intracranial B7-H3 CAR T cells for patients with DIPG and includes preliminary tolerability, the detection of CAR T cells in the CSF, CSF cytokine elevations supporting locoregional immune activation, and the feasibility of serial mass spectrometry from both serum and CSF. This article is highlighted in the In This Issue feature, p. 1.

PTEN loss drives resistance to the neddylation inhibitor MLN4924 in glioblastoma and can be overcome with TOP2A inhibitors.

BACKGROUND: Neddylation inhibition, affecting posttranslational protein function and turnover, is a promising therapeutic approach to cancer. We report vulnerability to MLN4924 or pevonedistat (a neddylation inhibitor) in a subset of glioblastoma (GBM) preclinical models and identify biomarkers, mechanisms, and signatures of differential response. METHODS: GBM sequencing data were queried for genes associated with MLN4924 response status; candidates were validated by molecular techniques. Time-course transcriptomics and proteomics revealed processes implicated in MLN4924 response. RESULTS: Vulnerability to MLN4924 is associated with elevated S-phase populations, re-replication, and DNA damage. Transcriptomics and shotgun proteomics depict PTEN signaling, DNA replication, and chromatin instability pathways as significant differentiators between sensitive and resistant models. Loss of PTEN and its nuclear functions is associated with resistance to MLN4924. Time-course proteomics identified elevated TOP2A in resistant models through treatment. TOP2A inhibitors combined with MLN4924 prove synergistic. CONCLUSIONS: We show that PTEN status serves as both a novel biomarker for MLN4924 response in GBM and reveals a vulnerability to TOP2A inhibitors in combination with MLN4924.

Importance of the intersection of age and sex to understand variation in incidence and survival for primary malignant gliomas.

BACKGROUND: Gliomas are the most common type of malignant brain and other CNS tumors, accounting for 80.8% of malignant primary brain and CNS tumors. They cause significant morbidity and mortality. This study investigates the intersection between age and sex to better understand variation of incidence and survival for glioma in the United States. METHODS: Incidence data from 2000 to 2017 were obtained from CBTRUS, which obtains data from the NPCR and SEER, and survival data from the CDC's NPCR. Age-adjusted incidence rate ratios (IRR) per 100 000 were generated to compare male-to-female incidence by age group. Cox proportional hazard models were performed by age group, generating hazard ratios to assess male-to-female survival differences. RESULTS: Overall, glioma incidence was higher in males. Male-to-female incidence was lowest in ages 0-9 years (IRR: 1.04, 95% CI: 1.01-1.07, P = .003), increasing with age, peaking at 50-59 years (IRR: 1.56, 95% CI: 1.53-1.59, P < .001). Females had worse survival for ages 0-9 (HR: 0.93, 95% CI: 0.87-0.99), though male survival was worse for all other age groups, with the difference highest in those 20-29 years (HR: 1.36, 95% CI: 1.28-1.44). Incidence and survival differences by age and sex also varied by histological subtype of glioma. CONCLUSIONS: To better understand the variation in glioma incidence and survival, investigating the intersection of age and sex is key. The current work shows that the combined impact of these variables is dependent on glioma subtype. These results contribute to the growing understanding of sex and age differences that impact cancer incidence and survival.

Independently validated sex-specific nomograms for predicting survival in patients with newly diagnosed glioblastoma: NRG Oncology RTOG 0525 and 0825.

BACKGROUND/PURPOSE: Glioblastoma (GBM) is the most common primary malignant brain tumor. Sex has been shown to be an important prognostic factor for GBM. The purpose of this study was to develop and independently validate sex-specific nomograms for estimation of individualized GBM survival probabilities using data from 2 independent NRG Oncology clinical trials. METHODS: This analysis included information on 752 (NRG/RTOG 0525) and 599 (NRG/RTOG 0825) patients with newly diagnosed GBM. The Cox proportional hazard models by sex were developed using NRG/RTOG 0525 and significant variables were identified using a backward selection procedure. The final selected models by sex were then independently validated using NRG/RTOG 0825. RESULTS: Final nomograms were built by sex. Age at diagnosis, KPS, MGMT promoter methylation and location of tumor were common significant predictors of survival for both sexes. For both sexes, tumors in the frontal lobes had significantly better survival than tumors of multiple sites. Extent of resection, and use of corticosteroids were significant predictors of survival for males. CONCLUSIONS: A sex specific nomogram that assesses individualized survival probabilities (6-, 12- and 24-months) for patients with GBM could be more useful than estimation of overall survival as there are factors that differ between males and females. A user friendly online application can be found here- https://npatilshinyappcalculator.shinyapps.io/SexDifferencesInGBM/ .

Functional Precision Medicine Identifies New Therapeutic Candidates for Medulloblastoma.

Medulloblastoma is among the most common malignant brain tumors in children. Recent studies have identified at least four subgroups of the disease that differ in terms of molecular characteristics and patient outcomes. Despite this heterogeneity, most patients with medulloblastoma receive similar therapies, including surgery, radiation, and intensive chemotherapy. Although these treatments prolong survival, many patients still die from the disease and survivors suffer severe long-term side effects from therapy. We hypothesize that each patient with medulloblastoma is sensitive to different therapies and that tailoring therapy based on the molecular and cellular characteristics of patients' tumors will improve outcomes. To test this, we assembled a panel of orthotopic patient-derived xenografts (PDX) and subjected them to DNA sequencing, gene expression profiling, and high-throughput drug screening. Analysis of DNA sequencing revealed that most medulloblastomas do not have actionable mutations that point to effective therapies. In contrast, gene expression and drug response data provided valuable information about potential therapies for every tumor. For example, drug screening demonstrated that actinomycin D, which is used for treatment of sarcoma but rarely for medulloblastoma, was active against PDXs representing Group 3 medulloblastoma, the most aggressive form of the disease. Functional analysis of tumor cells was successfully used in a clinical setting to identify more treatment options than sequencing alone. These studies suggest that it should be possible to move away from a one-size-fits-all approach and begin to treat each patient with therapies that are effective against their specific tumor. SIGNIFICANCE: These findings show that high-throughput drug screening identifies therapies for medulloblastoma that cannot be predicted by genomic or transcriptomic analysis.

Temporospatial genomic profiling in glioblastoma identifies commonly altered core pathways underlying tumor progression.

BACKGROUND: 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.

Sexually dimorphic impact of the iron-regulating gene, HFE, on survival in glioblastoma.

BACKGROUND: The median survival for patients with glioblastoma (GBM), the most common primary malignant brain tumor in adults, has remained approximately 1 year for more than 2 decades. Recent advances in the field have identified GBM as a sexually dimorphic disease. It is less prevalent in females and they have better survival compared to males. The molecular mechanism of this difference has not yet been established. Iron is essential for many biological processes supporting tumor growth and its regulation is impacted by sex. Therefore, we interrogated the expression of a key component of cellular iron regulation, the HFE (homeostatic iron regulatory) gene, on sexually dimorphic survival in GBM. METHODS: We analyzed TCGA microarray gene expression and clinical data of all primary GBM patients (IDH-wild type) to compare tumor mRNA expression of HFE with overall survival, stratified by sex. RESULTS: In low HFE expressing tumors (below median expression, n = 220), survival is modulated by both sex and MGMT status, with the combination of female sex and MGMT methylation resulting in over a 10-month survival advantage (P < .0001) over the other groups. Alternatively, expression of HFE above the median (high HFE, n = 240) is associated with significantly worse overall survival in GBM, regardless of MGMT methylation status or patient sex. Gene expression analysis uncovered a correlation between high HFE expression and expression of genes associated with immune function. CONCLUSIONS: The level of HFE expression in GBM has a sexually dimorphic impact on survival. Whereas HFE expression below the median imparts a survival benefit to females, high HFE expression is associated with significantly worse overall survival regardless of established prognostic factors such as sex or MGMT methylation.

Gliomas display distinct sex-based differential methylation patterns based on molecular subtype.

BACKGROUND: Gliomas are the most common type of primary brain tumor and one of many cancers where males are diagnosed with greater frequency than females. However, little is known about the sex-based molecular differences in glioblastomas (GBMs) or lower grade glioma (non-GBM) subtypes. DNA methylation is an epigenetic mechanism involved in regulating gene transcription. In glioma and other cancers, hypermethylation of specific gene promoters downregulates transcription and may have a profound effect on patient outcome. The purpose of this study was to determine if sex-based methylation differences exist in different glioma subtypes. METHODS: Molecular and clinical data from glioma patients were obtained from The Cancer Genome Atlas and grouped according to tumor grade and molecular subtype (IDH1/2 mutation and 1p/19q chromosomal deletion). Sex-specific differentially methylated probes (DMPs) were identified in each subtype and further analyzed to determine if they were part of differentially methylated regions (DMRs) or associated with differentially methylated DNA transcription regulatory binding motifs. RESULTS: Analysis of methylation data in 4 glioma subtypes revealed unique sets of both sex-specific DMPs and DMRs in each subtype. Motif analysis based on DMP position also identified distinct sex-based sets of DNA-binding motifs that varied according to glioma subtype. Downstream targets of 2 of the GBM-specific transcription binding sites, NFAT5 and KLF6, showed differential gene expression consistent with increased methylation mediating downregulation. CONCLUSION: DNA methylation differences between males and females in 4 glioma molecular subtypes suggest an important, sex-specific role for DNA methylation in epigenetic regulation of gliomagenesis.

Proteins inform survival-based differences in patients with glioblastoma.

BACKGROUND: Improving the care of patients with glioblastoma (GB) requires accurate and reliable predictors of patient prognosis. Unfortunately, while protein markers are an effective readout of cellular function, proteomics has been underutilized in GB prognostic marker discovery. METHODS: For this study, GB patients were prospectively recruited and proteomics discovery using liquid chromatography-mass spectrometry analysis (LC-MS/MS) was performed for 27 patients including 13 short-term survivors (STS) (≤10 months) and 14 long-term survivors (LTS) (≥18 months). RESULTS: Proteomics discovery identified 11 941 peptides in 2495 unique proteins, with 469 proteins exhibiting significant dysregulation when comparing STS to LTS. We verified the differential abundance of 67 out of these 469 proteins in a small previously published independent dataset. Proteins involved in axon guidance were upregulated in STS compared to LTS, while those involved in p53 signaling were upregulated in LTS. We also assessed the correlation between LS MS/MS data with RNAseq data from the same discovery patients and found a low correlation between protein abundance and mRNA expression. Finally, using LC-MS/MS on a set of 18 samples from 6 patients, we quantified the intratumoral heterogeneity of more than 2256 proteins in the multisample dataset. CONCLUSIONS: These proteomic datasets and noted protein variations present a beneficial resource for better predicting patient outcome and investigating potential therapeutic targets.

Sex Differences in Cancer Incidence and Survival: A Pan-Cancer Analysis.

BACKGROUND: Sex plays an important role in the incidence, prognosis, and mortality of cancers, but often is not considered in disease treatment. METHODS: We quantified sex differences in cancer incidence using the United States Cancer Statistics (USCS) public use database and sex differences in cancer survival using Surveillance, Epidemiology, and End Results (SEER) public use data from 2001 to 2016. Age-adjusted male-to-female incidence rate ratios (IRR) with 95% confidence intervals (CI) were generated by primary cancer site, race, and age groups. In addition, age-adjusted hazard ratios with 95% CI by sex within site were generated. RESULTS: In general, cancer incidence and overall survival were lower in males than females, with Kaposi sarcoma (IRR: 9.751; 95% CI, 9.287-10.242; P < 0.001) having highest male-to-female incidence, and thyroid cancers (HR, 1.774; 95% CI, 1.707-1.845) having largest male-to-female survival difference. Asian or Pacific Islanders had particularly high male-to-female incidence in larynx cancers (IRR: 8.199; 95% CI, 7.203-9.363; P < 0.001), relative to other races. Among primary brain tumors, germ cell tumors had the largest male-to-female incidence (IRR: 3.03; 95% CI, 2.798-3.284, P < 0.001). CONCLUSIONS: Overall, incidence and survival of cancer vary significantly by sex, with males generally having lower incidence and survival compared with females. Male-to-female incidence differences were also noted across race and age groups. These results provide strong evidence that the fundamental biology of sex differences affects cancers of all types. IMPACT: This study represents the most recent and comprehensive reporting of sex differences in cancer incidence and survival in the United States. Identifying disadvantaged groups is critical as it can provide useful information to improve cancer survival, as well as to better understand the etiology and pathogenesis of specific cancers.

Genomic and Phenotypic Characterization of a Broad Panel of Patient-Derived Xenografts Reflects the Diversity of Glioblastoma.

PURPOSE: 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.

Sex is an important prognostic factor for glioblastoma but not for nonglioblastoma.

BACKGROUND: Glioblastoma (GBM) is the most common and most malignant glioma. Nonglioblastoma (non-GBM) gliomas (WHO Grades II and III) are invasive and also often fatal. The goal of this study is to determine whether sex differences exist in glioma survival. METHODS: Data were obtained from the National Cancer Database (NCDB) for years 2010 to 2014. GBM (WHO Grade IV; N = 2073) and non-GBM (WHO Grades II and III; N = 2963) were defined using the histology grouping of the Central Brain Tumor Registry of the United States. Non-GBM was divided into oligodendrogliomas/mixed gliomas and astrocytomas. Sex differences in survival were analyzed using Kaplan-Meier and multivariable Cox proportional hazards models adjusted for known prognostic variables. RESULTS: There was a female survival advantage in patients with GBM both in the unadjusted (P = .048) and adjusted (P = .003) models. Unadjusted, median survival was 20.1 months (95% CI: 18.7-21.3 months) for women and 17.8 months (95% CI: 16.9-18.7 months) for men. Adjusted, median survival was 20.4 months (95% CI: 18.9-21.6 months) for women and 17.5 months (95% CI: 16.7-18.3 months) for men. When stratifying by age group (18-55 vs 56+ years at diagnosis), this female survival advantage appeared only in the older group, adjusting for covariates (P = .017). Women (44.1%) had a higher proportion of methylated MGMT (O6-methylguanine-DNA methyltransferase) than men (38.4%). No sex differences were found for non-GBM. CONCLUSIONS: Using the NCDB data, there was a statistically significant female survival advantage in GBM, but not in non-GBM.

Multiscale, multimodal analysis of tumor heterogeneity in IDH1 mutant vs wild-type diffuse gliomas.

Glioma is recognized to be a highly heterogeneous CNS malignancy, whose diverse cellular composition and cellular interactions have not been well characterized. To gain new clinical- and biological-insights into the genetically-bifurcated IDH1 mutant (mt) vs wildtype (wt) forms of glioma, we integrated data from protein, genomic and MR imaging from 20 treatment-naïve glioma cases and 16 recurrent GBM cases. Multiplexed immunofluorescence (MxIF) was used to generate single cell data for 43 protein markers representing all cancer hallmarks, Genomic sequencing (exome and RNA (normal and tumor) and magnetic resonance imaging (MRI) quantitative features (protocols were T1-post, FLAIR and ADC) from whole tumor, peritumoral edema and enhancing core vs equivalent normal region were also collected from patients. Based on MxIF analysis, 85,767 cells (glioma cases) and 56,304 cells (GBM cases) were used to generate cell-level data for 24 biomarkers. K-means clustering was used to generate 7 distinct groups of cells with divergent biomarker profiles and deconvolution was used to assign RNA data into three classes. Spatial and molecular heterogeneity metrics were generated for the cell data. All features were compared between IDH mt and IDHwt patients and were finally combined to provide a holistic/integrated comparison. Protein expression by hallmark was generally lower in the IDHmt vs wt patients. Molecular and spatial heterogeneity scores for angiogenesis and cell invasion also differed between IDHmt and wt gliomas irrespective of prior treatment and tumor grade; these differences also persisted in the MR imaging features of peritumoral edema and contrast enhancement volumes. A coherent picture of enhanced angiogenesis in IDHwt tumors was derived from multiple platforms (genomic, proteomic and imaging) and scales from individual proteins to cell clusters and heterogeneity, as well as bulk tumor RNA and imaging features. Longer overall survival for IDH1mt glioma patients may reflect mutation-driven alterations in cellular, molecular, and spatial heterogeneity which manifest in discernable radiological manifestations.

Comparative Tumor RNA Sequencing Analysis for Difficult-to-Treat Pediatric and Young Adult Patients With Cancer.

Importance: Pediatric cancers are epigenetic diseases; therefore, considering tumor gene expression information is necessary for a complete understanding of the tumorigenic processes. Objective: To evaluate the feasibility and utility of incorporating comparative gene expression information into the precision medicine framework for difficult-to-treat pediatric and young adult patients with cancer. Design, Setting, and Participants: This cohort study was conducted as a consortium between the University of California, Santa Cruz (UCSC) Treehouse Childhood Cancer Initiative and clinical genomic trials. RNA sequencing (RNA-Seq) data were obtained from the following 4 clinical sites and analyzed at UCSC: British Columbia Children's Hospital (n = 31), Lucile Packard Children's Hospital at Stanford University (n = 80), CHOC Children's Hospital and Hyundai Cancer Institute (n = 46), and the Pacific Pediatric Neuro-Oncology Consortium (n = 24). The study dates were January 1, 2016, to March 22, 2017. Exposures: Participants underwent tumor RNA-Seq profiling as part of 4 separate clinical trials at partner hospitals. The UCSC either downloaded RNA-Seq data from a partner institution for analysis in the cloud or provided a Docker pipeline that performed the same analysis at a partner institution. The UCSC then compared each participant's tumor RNA-Seq profile with more than 11 000 uniformly analyzed tumor profiles from pediatric and young adult patients with cancer, downloaded from public data repositories. These comparisons were used to identify genes and pathways that are significantly overexpressed in each patient's tumor. Results of the UCSC analysis were presented to clinical partners. Main Outcomes and Measures: Feasibility of a third-party institution (UCSC Treehouse Childhood Cancer Initiative) to obtain tumor RNA-Seq data from patients, conduct comparative analysis, and present analysis results to clinicians; and proportion of patients for whom comparative tumor gene expression analysis provided useful clinical and biological information. Results: Among 144 samples from children and young adults (median age at diagnosis, 9 years; range, 0-26 years; 72 of 118 [61.0%] male [26 patients sex unknown]) with a relapsed, refractory, or rare cancer treated on precision medicine protocols, RNA-Seq-derived gene expression was potentially useful for 99 of 144 samples (68.8%) compared with DNA mutation information that was potentially useful for only 34 of 74 samples (45.9%). Conclusions and Relevance: This study's findings suggest that tumor RNA-Seq comparisons may be feasible and highlight the potential clinical utility of incorporating such comparisons into the clinical genomic interpretation framework for difficult-to-treat pediatric and young adult patients with cancer. The study also highlights for the first time to date the potential clinical utility of harmonized publicly available genomic data sets.

PPM1D mutations silence NAPRT gene expression and confer NAMPT inhibitor sensitivity in glioma.

Pediatric high-grade gliomas are among the deadliest of childhood cancers due to limited knowledge of early driving events in their gliomagenesis and the lack of effective therapies available. In this study, we investigate the oncogenic role of PPM1D, a protein phosphatase often found truncated in pediatric gliomas such as DIPG, and uncover a synthetic lethal interaction between PPM1D mutations and nicotinamide phosphoribosyltransferase (NAMPT) inhibition. Specifically, we show that mutant PPM1D drives hypermethylation of CpG islands throughout the genome and promotes epigenetic silencing of nicotinic acid phosphoribosyltransferase (NAPRT), a key gene involved in NAD biosynthesis. Notably, PPM1D mutant cells are shown to be sensitive to NAMPT inhibitors in vitro and in vivo, within both engineered isogenic astrocytes and primary patient-derived model systems, suggesting the possible application of NAMPT inhibitors for the treatment of pediatric gliomas. Overall, our results reveal a promising approach for the targeting of PPM1D mutant tumors, and define a critical link between oncogenic driver mutations and NAD metabolism, which can be exploited for tumor-specific cell killing.

Leveraging Spatial Variation in Tumor Purity for Improved Somatic Variant Calling of Archival Tumor Only Samples.

Archival tumor samples represent a rich resource of annotated specimens for translational genomics research. However, standard variant calling approaches require a matched normal sample from the same individual, which is often not available in the retrospective setting, making it difficult to distinguish between true somatic variants and individual-specific germline variants. Archival sections often contain adjacent normal tissue, but this tissue can include infiltrating tumor cells. As existing comparative somatic variant callers are designed to exclude variants present in the normal sample, a novel approach is required to leverage adjacent normal tissue with infiltrating tumor cells for somatic variant calling. Here we present lumosVar 2.0, a software package designed to jointly analyze multiple samples from the same patient, built upon our previous single sample tumor only variant caller lumosVar 1.0. The approach assumes that the allelic fraction of somatic variants and germline variants follow different patterns as tumor content and copy number state change. lumosVar 2.0 estimates allele specific copy number and tumor sample fractions from the data, and uses a to model to determine expected allelic fractions for somatic and germline variants and to classify variants accordingly. To evaluate the utility of lumosVar 2.0 to jointly call somatic variants with tumor and adjacent normal samples, we used a glioblastoma dataset with matched high and low tumor content and germline whole exome sequencing data (for true somatic variants) available for each patient. Both sensitivity and positive predictive value were improved when analyzing the high tumor and low tumor samples jointly compared to analyzing the samples individually or in-silico pooling of the two samples. Finally, we applied this approach to a set of breast and prostate archival tumor samples for which tumor blocks containing adjacent normal tissue were available for sequencing. Joint analysis using lumosVar 2.0 detected several variants, including known cancer hotspot mutations that were not detected by standard somatic variant calling tools using the adjacent tissue as presumed normal reference. Together, these results demonstrate the utility of leveraging paired tissue samples to improve somatic variant calling when a constitutional sample is not available.