Faculty Bibliography

BACKGROUND:Glioblastoma (GBM) is a complex disease with extensive molecular and transcriptional heterogeneity. GBM can be subcategorized into four distinct subtypes; tumors that shift towards the mesenchymal phenotype upon recurrence are generally associated with treatment resistance, unfavorable prognosis, and the infiltration of pro-tumorigenic macrophages. RESULTS:TAMs also significantly accelerate tumor engraftment and growth in vivo. Moreover, both MA-TAM master regulators and their target genes are significantly correlated with poor clinical outcomes and are often associated with genomic aberrations in neurofibromin 1 (NF1) and phosphoinositide 3-kinases/mammalian target of rapamycin/Akt pathway (PI3K-mTOR-AKT)-related genes. We further demonstrate the origination of MA-TAMs from peripheral blood, as well as their potential association with tumor-induced polarization states and immunosuppressive environments. CONCLUSIONS:Collectively, our study characterizes the global transcriptional profile of TAMs driving mesenchymal GBM pathogenesis, providing potential therapeutic targets for improving the effectiveness of GBM immunotherapy.

The tumor microenvironment (TME) plays critical roles in tumor growth and progression, however key regulators of gene expression in the TME of cutaneous malignant peripheral nerve sheath tumor (C-MPNST) and spindle cell melanoma (SCM) have not been well elucidated. Herein, we investigate the epigenetic regulation of promoters and gene bodies and their effect on the TME composition of C-MPNSTs and SCMs. A cohort of 30 patients was analyzed using differential gene expression (DGE) and gene set enrichment analysis (GSEA) using the Nanostring platform. Methylation analysis was carried out utilizing an Infinium Methylation EPIC array targeting 866,562 methylation site (CpG) islands. DGE revealed overexpression of genes related to mast cells in the TME of SCMs, and a predominance of exhausted CD8⁺ T cells and macrophages in the TME of C-MPNSTs. Interestingly, we further observed promoter hypermethylation in key overexpressed genes and corresponding gene body hypomethylation. Analysis using ENCODE ChIP-sequencing data identified CTCF as the common transcription factor at the site of the hypomethylated probe. These findings support that the TME composition of C-MPNSTs and SCMs is at least partially independent on promoter methylation status, suggesting a possible relationship between gene body enhancers and expression of key TME genes in both entities.

INTRODUCTION/BACKGROUND:The prognostic role of racial and socioeconomic factors in patients with glioblastoma is controversially debated. We aimed to evaluate how these factors may affect survival outcomes in an overall and cause-specific manner using large, national cancer registry cohort data in the temozolomide chemoradiation era. METHODS:The National Cancer Institute's Surveillance, Epidemiology, and End Results database was queried for patients diagnosed with glioblastoma between 2005 and 2016. Overall survival was assessed using Cox proportional hazard models using disease intrinsic and extrinsic factors. Cause-specific mortality was assessed using cumulative incidence curves and modeled using multivariate cumulative risk regression. RESULTS:A total of 28,952 patients met the prespecified inclusion criteria and were included in this analysis. The following factors were associated with all-cause mortality: age, calendar year of diagnosis, sex, treatment receipt, tumor size, tumor location, extent of resection, median household income, and race. Asian/Pacific Islanders and Hispanic Whites had lower mortality compared to Non-Hispanic Whites. Cause-specific mortality was associated with both racial and socioeconomic groups. After adjusting for treatment and tumor-related factors, Asian/Pacific and black patients had lower glioblastoma-specific mortality. However, lower median household income and black race were associated with significantly higher non-glioblastoma mortality. CONCLUSIONS:Despite the aggressive nature of glioblastoma, racial and socioeconomic factors influence glioblastoma-specific and non-glioblastoma associated mortality. Our study shows that patient race has an impact on glioblastoma-associated mortality independently of tumor and treatment related factors. Importantly, socioeconomic and racial differences largely contribute to non-glioblastoma mortality, including death from other cancers, cardio- and cerebrovascular events.

Personalized cancer treatments using combinations of drugs with a synergistic effect is attractive but proves to be highly challenging. Here we present an approach to uncover the efficacy of drug combinations based on the analysis of mono-drug effects. For this we used dose-response data from pharmacogenomic encyclopedias and represent these as a drug atlas. The drug atlas represents the relations between drug effects and allows to identify independent processes for which the tumor might be particularly vulnerable when attacked by two drugs. Our approach enables the prediction of combination-therapy which can be linked to tumor-driving mutations. By using this strategy, we can uncover potential effective drug combinations on a pan-cancer scale. Predicted synergies are provided and have been validated in glioblastoma, breast cancer, melanoma and leukemia mouse-models, resulting in therapeutic synergy in 75% of the tested models. This indicates that we can accurately predict effective drug combinations with translational value.

PURPOSE OF REVIEW/OBJECTIVE:Glioblastoma (GBM) is the most common malignant primary brain tumor, and the available treatment options are limited. This article reviews the recent preclinical and clinical investigations that seek to expand the repertoire of effective medical and radiotherapy options for GBM. RECENT FINDINGS/RESULTS:Recent phase III trials evaluating checkpoint inhibition did not result in significant survival benefit. Select vaccine strategies have yielded promising results in early phase clinical studies and warrant further validation. Various targeted therapies are being explored but have yet to see breakthrough results. In addition, novel radiotherapy approaches are in development to maximize safe dose delivery. A multitude of preclinical and clinical studies in GBM explore promising immunotherapies, targeted agents, and novel radiation modalities. Recent phase III trial failures have once more highlighted the profound tumor heterogeneity and diverse resistance mechanisms of glioblastoma. This calls for the development of biomarker-driven and personalized treatment approaches.

PURPOSE/OBJECTIVE:Exploration of novel strategies to extend the benefit of PARP inhibitors beyond BRCA-mutant cancers is of great interest in personalized medicine. Here we identified EGFR-amplification as a potential biomarker to predict sensitivity to PARP inhibition, providing selection for GBM patient population who will benefit from PARP inhibition therapy. EXPERIMENTAL DESIGN/METHODS:Selective sensitivity to PARP inhibitor talazoparib was screened and validated in two sets [test set (n=14) and validation set (n=13)] of well-characterized patient-derived glioma-sphere-forming cells (GSC). FISH was used to detect EGFR copy number. DNA damage response following talazoparib treatment was evaluated by γH2AX and 53BP1 staining and neutral comet assay. PARP-DNA trapping was analyzed by subcellular fractionation. The selective monotherapy of talazoparib was confirmed using in-vivo glioma models. RESULTS:EGFR-amplified GSCs showed remarkable sensitivity to talazoparib treatment. EGFR- amplification was associated with increased ROS and subsequent increased basal expression of DNA repair pathways to counter elevated oxidative stress, and thus rendered vulnerability to PARP inhibition. Following talazoparib treatment, EGFR-amplified GSCs showed enhanced DNA damage and increased PARP-DNA trapping which augmented the cytotoxicity. EGFR-amplification associated selective sensitivity was further supported by the in vivo experimental results showing that talazoparib significantly suppressed tumor growth in EGFR-amplified subcutaneous models but not in non-amplified models. CONCLUSION/CONCLUSIONS:EGFR-amplified cells are highly sensitive to talazoparib. Our data provide insight into the potential of using EGFR amplification as a selection biomarker for the development of personalized therapy.

PURPOSE/OBJECTIVE: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/METHODS:PDX 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: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.