Targeting of REST with rationally-designed small molecule compounds exhibits synergetic therapeutic potential in human glioblastoma cells

BACKGROUND

Glioblastoma (GBM) is an aggressive brain cancer associated with poor prognosis, intrinsic heterogeneity, plasticity, and therapy resistance. In some GBMs, cell proliferation is fueled by a transcriptional regulator, repressor element-1 silencing transcription factor (REST).

RESULTS

Using CRISPR/Cas9, we identified GBM cell lines dependent on REST activity. We developed new small molecule inhibitory compounds targeting small C-terminal domain phosphatase 1 (SCP1) to reduce REST protein level and transcriptional activity in glioblastoma cells. Top leads of the series like GR-28 exhibit potent cytotoxicity, reduce REST protein level, and suppress its transcriptional activity. Upon the loss of REST protein, GBM cells can potentially compensate by rewiring fatty acid metabolism, enabling continued proliferation. Combining REST inhibition with the blockade of this compensatory adaptation using long-chain acyl-CoA synthetase inhibitor Triacsin C demonstrated substantial synergetic potential without inducing hepatotoxicity.

CONCLUSIONS

Our results highlight the efficacy and selectivity of targeting REST alone or in combination as a therapeutic strategy to combat high-REST GBM.

Image-localized biopsy mapping of brain tumor heterogeneity: A single-center study protocol

Brain cancers pose a novel set of difficulties due to the limited accessibility of human brain tumor tissue. For this reason, clinical decision-making relies heavily on MR imaging interpretation, yet the mapping between MRI features and underlying biology remains ambiguous. Standard (clinical) tissue sampling fails to capture the full heterogeneity of the disease. Biopsies are required to obtain a pathological diagnosis and are predominantly taken from the tumor core, which often has different traits to the surrounding invasive tumor that typically leads to recurrent disease. One approach to solving this issue is to characterize the spatial heterogeneity of molecular, genetic, and cellular features of glioma through the intraoperative collection of multiple image-localized biopsy samples paired with multi-parametric MRIs. We have adopted this approach and are currently actively enrolling patients for our 'Image-Based Mapping of Brain Tumors' study. Patients are eligible for this research study (IRB #16-002424) if they are 18 years or older and undergoing surgical intervention for a brain lesion. Once identified, candidate patients receive dynamic susceptibility contrast (DSC) perfusion MRI and diffusion tensor imaging (DTI), in addition to standard sequences (T1, T1Gd, T2, T2-FLAIR) at their presurgical scan. During surgery, sample anatomical locations are tracked using neuronavigation. The collected specimens from this research study are used to capture the intra-tumoral heterogeneity across brain tumors including quantification of genetic aberrations through whole-exome and RNA sequencing as well as other tissue analysis techniques. To date, these data (made available through a public portal) have been used to generate, test, and validate predictive regional maps of the spatial distribution of tumor cell density and/or treatment-related key genetic marker status to identify biopsy and/or treatment targets based on insight from the entire tumor makeup. This type of methodology, when delivered within clinically feasible time frames, has the potential to further inform medical decision-making by improving surgical intervention, radiation, and targeted drug therapy for patients with glioma.

M2 isoform of pyruvate kinase rewires glucose metabolism during radiation therapy to promote an antioxidant response and glioblastoma radioresistance

BACKGROUND

Resistance to existing therapies is a significant challenge in improving outcomes for glioblastoma (GBM) patients. Metabolic plasticity has emerged as an important contributor to therapy resistance, including radiation therapy (RT). Here, we investigated how GBM cells reprogram their glucose metabolism in response to RT to promote radiation resistance.

METHODS

Effects of radiation on glucose metabolism of human GBM specimens were examined in vitro and in vivo with the use of metabolic and enzymatic assays, targeted metabolomics, and FDG-PET. Radiosensitization potential of interfering with M2 isoform of pyruvate kinase (PKM2) activity was tested via gliomasphere formation assays and in vivo human GBM models.

RESULTS

Here, we show that RT induces increased glucose utilization by GBM cells, and this is accompanied with translocation of GLUT3 transporters to the cell membrane. Irradiated GBM cells route glucose carbons through the pentose phosphate pathway (PPP) to harness the antioxidant power of the PPP and support survival after radiation. This response is regulated in part by the PKM2. Activators of PKM2 can antagonize the radiation-induced rewiring of glucose metabolism and radiosensitize GBM cells in vitro and in vivo.

CONCLUSIONS

These findings open the possibility that interventions designed to target cancer-specific regulators of metabolic plasticity, such as PKM2, rather than specific metabolic pathways, have the potential to improve the radiotherapeutic outcomes in GBM patients.

Subgroup-Enriched Pathways and Kinase Signatures in Medulloblastoma Patient-Derived Xenografts

Medulloblastoma (MB) is the most common malignant pediatric brain tumor. MB is classified into four primary molecular subgroups: wingless (WNT), sonic hedgehog (SHH), Group 3 (G3), and Group 4 (G4), and further genomic and proteomic subtypes have been reported. Subgroup heterogeneity and few actionable mutations have hindered the development of targeted therapies, especially for G3 MB, which has a particularly poor prognosis. To identify novel therapeutic targets for MB, we performed mass spectrometry-based deep expression proteomics and phosphoproteomics in 20 orthotopic patient-derived xenograft (PDX) models of MB comprising SHH, G3, and G4 subgroups. We found that the proteomic profiles of MB PDX tumors are closely aligned with those of primary human MB tumors illustrating the utility of PDX models. SHH PDXs were enriched for NFκB and p38 MAPK signaling, while G3 PDXs were characterized by MYC activity. Additionally, we found a significant association between actinomycin D sensitivity and increased abundance of MYC and MYC target genes. Our results highlight several candidate pathways that may serve as targets for new MB therapies. Mass spectrometry data are available via ProteomeXchange with identifier PXD035070.

Leveraging metabolic modeling to identify functional metabolic alterations associated with COVID-19 disease severity

OBJECTIVE

Since the COVID-19 pandemic began in early 2020, SARS-CoV2 has claimed more than six million lives world-wide, with over 510 million cases to date. To reduce healthcare burden, we must investigate how to prevent non-acute disease from progressing to severe infection requiring hospitalization.

METHODS

To achieve this goal, we investigated metabolic signatures of both non-acute (out-patient) and severe (requiring hospitalization) COVID-19 samples by profiling the associated plasma metabolomes of 84 COVID-19 positive University of Virginia hospital patients. We utilized supervised and unsupervised machine learning and metabolic modeling approaches to identify key metabolic drivers that are predictive of COVID-19 disease severity. Using metabolic pathway enrichment analysis, we explored potential metabolic mechanisms that link these markers to disease progression.

RESULTS

Enriched metabolites associated with tryptophan in non-acute COVID-19 samples suggest mitigated innate immune system inflammatory response and immunopathology related lung damage prevention. Increased prevalence of histidine- and ketone-related metabolism in severe COVID-19 samples offers potential mechanistic insight to musculoskeletal degeneration-induced muscular weakness and host metabolism that has been hijacked by SARS-CoV2 infection to increase viral replication and invasion.

CONCLUSIONS

Our findings highlight the metabolic transition from an innate immune response coupled with inflammatory pathway inhibition in non-acute infection to rampant inflammation and associated metabolic systemic dysfunction in severe COVID-19.

Immune landscape of a genetically engineered murine model of glioma compared with human glioma

Novel therapeutic strategies targeting glioblastoma (GBM) often fail in the clinic, partly because preclinical models in which hypotheses are being tested do not recapitulate human disease. To address this challenge, we took advantage of our previously developed spontaneous Qk/Trp53/Pten (QPP) triple-knockout model of human GBM, comparing the immune microenvironment of QPP mice with that of patient-derived tumors to determine whether this model provides opportunity for gaining insights into tumor physiopathology and preclinical evaluation of therapeutic agents. Immune profiling analyses and single-cell sequencing of implanted and spontaneous tumors from QPP mice and from patients with glioma revealed intratumoral immune components that were predominantly myeloid cells (e.g., monocytes, macrophages, and microglia), with minor populations of T, B, and NK cells. When comparing spontaneous and implanted mouse samples, we found more neutrophils and T and NK cells in the implanted model. Neutrophils and T and NK cells were increased in abundance in samples derived from human high-grade glioma compared with those derived from low-grade glioma. Overall, our data demonstrate that our implanted and spontaneous QPP models recapitulate the immunosuppressive myeloid-dominant nature of the tumor microenvironment of human gliomas. Our model provides a suitable tool for investigating the complex immune compartment of gliomas.

Shape matters: morphological metrics of glioblastoma imaging abnormalities as biomarkers of prognosis

Lacunarity, a quantitative morphological measure of how shapes fill space, and fractal dimension, a morphological measure of the complexity of pixel arrangement, have shown relationships with outcome across a variety of cancers. However, the application of these metrics to glioblastoma (GBM), a very aggressive primary brain tumor, has not been fully explored. In this project, we computed lacunarity and fractal dimension values for GBM-induced abnormalities on clinically standard magnetic resonance imaging (MRI). In our patient cohort (n = 402), we connect these morphological metrics calculated on pretreatment MRI with the survival of patients with GBM. We calculated lacunarity and fractal dimension on necrotic regions (n = 390), all abnormalities present on T1Gd MRI (n = 402), and abnormalities present on T2/FLAIR MRI (n = 257). We also explored the relationship between these metrics and age at diagnosis, as well as abnormality volume. We found statistically significant relationships to outcome for all three imaging regions that we tested, with the shape of T2/FLAIR abnormalities that are typically associated with edema showing the strongest relationship with overall survival. This link between morphological and survival metrics could be driven by underlying biological phenomena, tumor location or microenvironmental factors that should be further explored.

Improved methods for RNAseq-based alternative splicing analysis

The robust detection of disease-associated splice events from RNAseq data is challenging due to the potential confounding effect of gene expression levels and the often limited number of patients with relevant RNAseq data. Here we present a novel statistical approach to splicing outlier detection and differential splicing analysis. Our approach tests for differences in the percentages of sequence reads representing local splice events. We describe a software package called Bisbee which can predict the protein-level effect of splice alterations, a key feature lacking in many other splicing analysis resources. We leverage Bisbee's prediction of protein level effects as a benchmark of its capabilities using matched sets of RNAseq and mass spectrometry data from normal tissues. Bisbee exhibits improved sensitivity and specificity over existing approaches and can be used to identify tissue-specific splice variants whose protein-level expression can be confirmed by mass spectrometry. We also applied Bisbee to assess evidence for a pathogenic splicing variant contributing to a rare disease and to identify tumor-specific splice isoforms associated with an oncogenic mutation. Bisbee was able to rediscover previously validated results in both of these cases and also identify common tumor-associated splice isoforms replicated in two independent melanoma datasets.

Novel strategy for manufacturing autologous dendritic cell/allogeneic tumor lysate vaccines for glioblastoma

Background

Glioblastoma, the most common primary malignant brain tumor, is nearly universally fatal by 5 years. Dendritic cell vaccines are promising but often limited clinically by antigen choice, dendritic cell potency, and/or manufacturing yield. We optimized vaccine manufacture, generating potent mature autologous dendritic cells pulsed with allogeneic glioblastoma lysates.

Methods

Platelet lysate-based supplement was used to establish human glioblastoma cell lines. Phenotype and genotype were assessed. An improved culture technique to generate mature dendritic cells from glioblastoma patients’ monocytes was developed. The ability of T cells stimulated with autologous dendritic cells pulsed with allogeneic glioblastoma cell lysate to kill HLA-A2-matched glioblastoma cells was assessed.

Results

Glioblastoma cell lines established with platelet lysate supplement grew faster and expressed more stem-like markers than lines grown in neural stem cell media or in the presence of serum. They expressed a variety of glioma-associated antigens and had genomic abnormalities characteristic of glioblastoma stable up to 15 doublings. Unlike standard culture techniques, our optimized technique produced high levels of mature dendritic cells from glioblastoma patients’ monocytes. Autologous T cells stimulated with mature dendritic cells pulsed with allogeneic glioblastoma cell line lysate briskly killed HLA-A2-matched glioblastoma cells.

Conclusions

Our glioblastoma culture method provides a renewable source for a broad spectrum glioblastoma neoantigens while our dendritic cell culture technique results in more mature dendritic cells in glioblastoma patients than standard techniques. This broadly applicable strategy could be easily integrated into patient care.

Chimeric antigen receptor signaling: Functional consequences and design implications

Chimeric antigen receptor (CAR) T cell therapy has transformed the care of refractory B cell malignancies and holds tremendous promise for many aggressive tumors. Despite overwhelming scientific, clinical, and public interest in this rapidly expanding field, fundamental inquiries into CAR T cell mechanistic functioning are still in their infancy. Because CAR T cells are manufactured from donor T lymphocytes, and because CARs incorporate well-characterized T cell signaling components, it has largely been assumed that CARs signal analogously to canonical T cell receptors (TCRs). However, recent studies demonstrate that many aspects of CAR signaling are unique, distinct from endogenous TCR signaling, and potentially even distinct among various CAR constructs. Thus, rigorous and comprehensive proteomic investigations are required for rational engineering of improved CARs. Here, we review what is known about proximal CAR signaling in T cells, compare it to conventional TCR signaling, and outline unmet challenges to improving CAR T cell therapy.

Image-based metric of invasiveness predicts response to adjuvant temozolomide for primary glioblastoma

Background

Temozolomide (TMZ) has been the standard-of-care chemotherapy for glioblastoma (GBM) patients for more than a decade. Despite this long time in use, significant questions remain regarding how best to optimize TMZ therapy for individual patients. Understanding the relationship between TMZ response and factors such as number of adjuvant TMZ cycles, patient age, patient sex, and image–based tumor features, might help predict which GBM patients would benefit most from TMZ, particularly for those whose tumors lack O⁶–methylguanine–DNA methyltransferase (MGMT) promoter methylation.

Methods and findings

Using a cohort of 90 newly–diagnosed GBM patients treated according to the standard of care, we examined the relationships between several patient and tumor characteristics and volumetric and survival outcomes during adjuvant chemotherapy. Volumetric changes in MR imaging abnormalities during adjuvant therapy were used to assess TMZ response. T1Gd volumetric response is associated with younger patient age, increased number of TMZ cycles, longer time to nadir volume, and decreased tumor invasiveness. Moreover, increased adjuvant TMZ cycles corresponded with improved volumetric response only among more nodular tumors, and this volumetric response was associated with improved survival outcomes. Finally, in a subcohort of patients with known MGMT methylation status, methylated tumors were more diffusely invasive than unmethylated tumors, suggesting the improved response in nodular tumors is not driven by a preponderance of MGMT methylated tumors.

Conclusions

Our finding that less diffusely invasive tumors are associated with greater volumetric response to TMZ suggests patients with these tumors may benefit from additional adjuvant TMZ cycles, even for those without MGMT methylation.

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.

Engineering of a novel subnanomolar affinity fibronectin III domain binder targeting human programmed death-ligand 1

The programmed death-ligand 1 (PD-L1) is a major checkpoint protein that helps cancer cells evade the immune system. A non-invasive imaging agent with rapid clearance rate would be an ideal tool to predict and monitor the efficacy of anti-PD-L1 therapy. The aim of this research was to engineer a subnanomolar, high-affinity fibronectin type 3 domain (FN3)-based small binder targeted against human PD-L1 (hPD-L1) present on tumor cells. A naive yeast G4 library containing the FN3 gene with three binding loop sequences was used to isolate high-affinity binders targeted to purified full-length hPD-L1. The selected binder clones displayed several mutations in the loop regions of the FN3 domain. One unique clone (FN3hPD-L1-01) with a 6x His-tag at the C-terminus had a protein yield of >5 mg/L and a protein mass of 12 kDa. In vitro binding assays on six different human cancer cell lines (MDA-MB-231, DLD1, U87, 293 T, Raji and Jurkat) and murine CT26 colon carcinoma cells stably expressing hPD-L1 showed that CT26/hPD-L1 cells had the highest expression of hPD-L1 in both basal and IFN-γ-induced states, with a binding affinity of 2.38 ± 0.26 nM for FN3hPD-L1-01. The binding ability of FN3hPD-L1-01 was further confirmed by immunofluorescence staining on ex vivo CT26/hPD-L1 tumors sections. The FN3hPD-L1-01 binder represents a novel, small, high-affinity binder for imaging hPD-L1 expression on tumor cells and would aid in earlier imaging of tumors. Future clinical validation studies of the labeled FN3hPD-L1 binder(s) have the potential to monitor immune checkpoint inhibitors therapy and predict responders.

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.

PIK3CA activating mutations are associated with more disseminated disease at presentation and earlier recurrence in glioblastoma

Phosphatidylinositol 3-kinase signaling promotes cell growth and survival and is frequently activated in infiltrative gliomas. Activating mutations in PIK3CA gene are observed in 6-15% of glioblastomas, although their clinical significance is largely undescribed. The objective of this study was to examine whether PIK3CA mutations are associated with a specific clinical phenotype in glioblastoma. We retrospectively reviewed 157 consecutive newly diagnosed glioblastoma patients from December 2009 to June 2012 who underwent molecular profiling consisting of targeted hotspot genotyping, fluorescence in situ hybridization for gene amplification, and methylation-specific PCR for O6-methylguanine-DNA methyltransferase promoter methylation. Molecular alterations were correlated with clinical features, imaging and outcome. The Cancer Genome Atlas data was analyzed as a validation set. There were 91 males; median age was 58 years (range, 23-85). With a median follow-up of 20.9 months, median progression-free survival (PFS) and estimated overall survival (OS) were 11.9 and 24.0 months, respectively. Thirteen patients (8.3%) harbored PIK3CA mutation, which was associated with younger age (mean 49.4 vs. 58.1 years, p = 0.02). PIK3CA mutation correlated with shorter PFS (median 6.9 vs. 12.4 months, p = 0.01) and OS (median 21.2 vs. 24.2 months, p = 0.049) in multivariate analysis. A significant association between PIK3CA mutation and more disseminated disease at diagnosis, as defined by gliomatosis, multicentric lesions, or distant leptomeningeal lesions, was observed (46.2% vs. 11.1%, p = 0.004). In conclusion, despite the association with younger age, PIK3CA activating mutations are associated with earlier recurrence and shorter survival in adult glioblastoma. The aggressive course of these tumors may be related to their propensity for disseminated presentation.