Faculty Bibliography

Glioblastoma stem cells (GSCs) are implicated in tumor neovascularization, invasiveness, and therapeutic resistance. To illuminate mechanisms governing these hallmark features, we developed a de novo glioblastoma multiforme (GBM) model derived from immortalized human neural stem/progenitor cells (hNSCs) to enable precise system-level comparisons of pre-malignant and oncogene-induced malignant states of NSCs. Integrated transcriptomic and epigenomic analyses uncovered a PAX6/DLX5 transcriptional program driving WNT5A-mediated GSC differentiation into endothelial-like cells (GdECs). GdECs recruit existing endothelial cells to promote peritumoral satellite lesions, which serve as a niche supporting the growth of invasive glioma cells away from the primary tumor. Clinical data reveal higher WNT5A and GdECs expression in peritumoral and recurrent GBMs relative to matched intratumoral and primary GBMs, respectively, supporting WNT5A-mediated GSC differentiation and invasive growth in disease recurrence. Thus, the PAX6/DLX5-WNT5A axis governs the diffuse spread of glioma cells throughout the brain parenchyma, contributing to the lethality of GBM.

Molecularly defined subclassification is associated with phenotypic malignancy of glioblastoma (GBM). However, current understanding of the molecular basis of subclass conversion that is often involved in GBM recurrence remain rudimentary at best. Here we report that canonical Wnt signalling that is active in proneural (PN) but inactive in mesenchymal (MES) GBM, along with miR-125b and miR-20b that are expressed at high levels in PN compared with MES GBM, comprise a regulatory circuit involving TCF4-miR-125b/miR-20b-FZD6. FZD6 acts as a negative regulator of this circuit by activating CaMKII-TAK1-NLK signalling, which, in turn, attenuates Wnt pathway activity while promoting STAT3 and NF-κB signalling that are important regulators of the MES-associated phenotype. These findings are confirmed by targeting differentially enriched pathways in PN versus MES GBM that results in inhibition of distinct GBM subtypes. Correlative expressions of the components of this circuit are prognostic relevant for clinical GBM. Our findings provide insights for understanding GBM pathogenesis and for improving treatment of GBM.

INTRODUCTION/BACKGROUND:Imaging is the modality of choice for noninvasive characterization of biological tissue and organ systems; imaging serves as early diagnostic tool for most disease processes and is rapidly evolving, thus transforming the way we diagnose and follow patients over time. A vast number of cancer imaging characteristics have been correlated to underlying genomics; however, none have established causality. Therefore, our objectives were to test if there is a causal relationship between imaging and genomic information; and to develop a clinically relevant radiomic pipeline for glioblastoma molecular characterization. METHODS:Functional validation was performed using a prototypic in vivo RNA-interference-based orthotopic xenograft mouse model. The automated pipeline collects 4800 MRI-derived texture features per tumor. Using univariate feature selection and boosted tree predictive modeling, a patient-specific genomic probability map was derived and patient survival predicted (The Cancer Genome Atlas/MD Anderson data sets). RESULTS:Data demonstrated a significant xenograft to human association (area under the curve [AUC] 84%, P < .001). Further, epidermal growth factor receptor amplification (AUC 86%, P < .0001), O-methylguanine-DNA-methyltransferase methylation/expression (AUC 92%, P = .001), glioblastoma molecular subgroups (AUC 88%, P = .001), and survival in 2 independent data sets (AUC 90%, P < .001) was predicted. CONCLUSION/CONCLUSIONS:Our results for the first time illustrate a causal relationship between imaging features and genomic tumor composition. We present a directly clinically applicable analytical imaging method termed Radiome Sequencing to allow for automated image analysis, prediction of key genomic events, and survival. This method is scalable and applicable to any type of medical imaging. Further, it allows for human-mouse matched coclinical trials, in-depth end point analysis, and upfront noninvasive high-resolution radiomics-based diagnostic, prognostic, and predictive biomarker development.

The World Health Organization (WHO) classification and grading system attempts to predict the clinical course of meningiomas based on morphological parameters. However, because of high interobserver variation of some criteria, more reliable prognostic markers are required. Here, we assessed the TERT promoter for mutations in the hotspot regions C228T and C250T in meningioma samples from 252 patients. Mutations were detected in 16 samples (6.4% across the cohort, 1.7%, 5.7%, and 20.0% of WHO grade I, II, and III cases, respectively). Data were analyzed by t test, Fisher's exact test, log-rank test, and Cox proportional hazard model. All statistical tests were two-sided. Within a mean follow-up time in surviving patients of 68.1 months, TERT promoter mutations were statistically significantly associated with shorter time to progression (P < .001). Median time to progression among mutant cases was 10.1 months compared with 179.0 months among wild-type cases. Our results indicate that the inclusion of molecular data (ie, analysis of TERT promoter status) into a histologically and genetically integrated classification and grading system for meningiomas increases prognostic power. Consequently, we propose to incorporate the assessment of TERT promoter status in upcoming grading schemes for meningioma.

BACKGROUND:Sensitizing effects of poly-ADP-ribose polymerase inhibitors have been studied in several preclinical models, but a clear understanding of predictive biomarkers is lacking. In this study, in vivo efficacy of veliparib combined with temozolomide (TMZ) was evaluated in a large panel of glioblastoma multiforme (GBM) patient-derived xenografts (PDX) and potential biomarkers were analyzed. METHODS:The efficacy of TMZ alone vs TMZ/veliparib was compared in a panel of 28 GBM PDX lines grown as orthotopic xenografts (8-10 mice per group); all tests of statistical significance were two-sided. DNA damage was analyzed by γH2AX immunostaining and promoter methylation of DNA repair gene O6-methylguanine-DNA-methyltransferase (MGMT) by Clinical Laboratory Improvement Amendments-approved methylation-specific polymerase chain reaction. RESULTS:The combination of TMZ/veliparib statistically significantly extended survival of GBM models (P < .05 by log-rank) compared with TMZ alone in five of 20 MGMT-hypermethylated lines (average extension in median survival = 87 days, range = 20-150 days), while the combination was ineffective in six MGMT-unmethylated lines. In the MGMT promoter-hypermethylated GBM12 line (median survival with TMZ+veliparib = 189 days, 95% confidence interval [CI] = 59 to 289 days, vs TMZ alone = 98 days, 95% CI = 49 to 210 days, P = .04), the profound TMZ-sensitizing effect of veliparib was lost when MGMT was overexpressed (median survival with TMZ+veliparib = 36 days, 95% CI = 28 to 38 days, vs TMZ alone = 35 days, 95% CI = 32 to 37 days, P = .87), and a similar association was observed in two nearly isogenic GBM28 sublines with an intact vs deleted MGMT locus. In comparing DNA damage signaling after dosing with veliparib/TMZ or TMZ alone, increased phosphorylation of damage-responsive proteins (KAP1, Chk1, Chk2, and H2AX) was observed only in MGMT promoter-hypermethylated lines. CONCLUSION/CONCLUSIONS:Veliparib statistically significantly enhances (P < .001) the efficacy of TMZ in tumors with MGMT promoter hypermethylation. Based on these data, MGMT promoter hypermethylation is being used as an eligibility criterion for A071102 (NCT02152982), the phase II/III clinical trial evaluating TMZ/veliparib combination in patients with GBM.