Tran, Nhan L

Abstract Glioblastoma is the most frequent primary brain tumor in adults and a highly lethal malignancy with a median survival of about 15 months. The aggressive invasion of the surrounding normal brain makes complete surgical resection impossible, increases the resistance to radiation and chemotherapy, and assures tumor recurrence. Thus, there is an urgent need to develop innovative therapeutics to target the invasive tumor cells for improved treatment outcomes of this disease. Expression of TROY (TNFRSF19), a member of the tumor necrosis factor (TNF) receptor family, increases with increasing glial tumor grade and inversely correlates with patient survival. Increased expression of TROY stimulates glioblastoma cell invasion in vitro and in vivo and increases resistance to temozolomide and radiation therapy. Conversely, silencing TROY expression inhibits glioblastoma cell invasion, increases temozolomide sensitivity, and prolongs survival in an intracranial xenograft model. Here, a novel complex is identified between TROY and EGFR, which is mediated predominantly by the cysteine-rich CRD3 domain of TROY. Glioblastoma tumors with elevated TROY expression have a statistically positive correlation with increased EGFR expression. TROY expression significantly increases the capacity of EGF to stimulate glioblastoma cell invasion, whereas depletion of TROY expression blocks EGF stimulation of glioblastoma cell invasion. Mechanistically, TROY expression modulates EGFR signaling by facilitating EGFR activation and delaying EGFR receptor internalization. Moreover, the association of EGFR with TROY increases TROY-induced NF-κB activation. These findings substantiate a critical role for the TROY–EGFR complex in regulation of glioblastoma cell invasion. Implications: The TROY–EGFR signaling complex emerges as a potential therapeutic target to inhibit glioblastoma cell invasion. Mol Cancer Res; 16(2); 322–32. ©2017 AACR.

Abstract Purpose: Glioblastoma is an aggressive and molecularly heterogeneous cancer with few effective treatment options. We hypothesized that next-generation sequencing can be used to guide treatment recommendations within a clinically acceptable time frame following surgery for patients with recurrent glioblastoma. Experimental Design: We conducted a prospective genomics-informed feasibility trial in adults with recurrent and progressive glioblastoma. Following surgical resection, genome-wide tumor/normal exome sequencing and tumor RNA sequencing were performed to identify molecular targets for potential matched therapy. A multidisciplinary molecular tumor board issued treatment recommendations based on the genomic results, blood–brain barrier penetration of the indicated therapies, drug–drug interactions, and drug safety profiles. Feasibility of generating genomics-informed treatment recommendations within 35 days of surgery was assessed. Results: Of the 20 patients enrolled in the study, 16 patients had sufficient tumor tissue for analysis. Exome sequencing was completed for all patients, and RNA sequencing was completed for 14 patients. Treatment recommendations were provided within the study's feasibility time frame for 15 of 16 (94%) patients. Seven patients received treatment based on the tumor board recommendations. Two patients reached 12-month progression-free survival, both adhering to treatments based on the molecular profiling results. One patient remained on treatment and progression free 21 months after surgery, 3 times longer than the patient's previous time to progression. Analysis of matched nonenhancing tissue from 12 patients revealed overlapping as well as novel putatively actionable genomic alterations. Conclusions: Use of genome-wide molecular profiling is feasible and can be informative for guiding real-time, central nervous system–penetrant, genomics-informed treatment recommendations for patients with recurrent glioblastoma. Clin Cancer Res; 24(2); 295–305. ©2017 AACR. See related commentary by Wick and Kessler, p. 256

Abstract Archival tumor samples present a rich resource of annotated specimens for genomics research. However, standard variant calling approaches require a matched normal sample from the same individual, which is often not available with archival tissue. Without a matched normal sample, it is very difficult to distinguish between true somatic variants and germline variants that are private to the individual. Archival FFPE sections often contain adjacent normal tissue, but this normal tissue is often contaminated with infiltrating tumor cells. Comparative somatic variant callers are designed to exclude variants present in the normal sample, so a novel approach is required to leverage sequencing of adjacent normal tissue. Here we present LumosVar 2.0, a software package designed to jointly analyze multiple samples from the same patient. The approach is based on the concept that the allelic fraction of somatic variants, but not germline variants, would be diluted by the presence of normal tissue. Given the allele specific copy number state and expected tumor fraction of each sample, one can model the expected allelic fractions of somatic and germline variants. LumosVar estimates allele specific copy number and tumor sample fractions from the data, and uses the model to call somatic and germline variants. LumosVar is also able to detect sub clonal events and spatial heterogeneity between samples. To evaluate this approach, we used a glioblastoma dataset, where enhancing (high tumor content) and non-enhancing (low tumor content) samples were available for each patient, as well as the matched normal sample to define the true somatic variants. We show that both sensitivity and positive predictive value are improved by analyzing the high tumor and low tumor jointly compared to analyzing the samples individually or in silico pooling of the two samples. Finally, we apply this approach to a set of breast and prostate archival FFPE tumor samples where normal samples were not available for germline sequencing. Citation Format: Rebecca F. Halperin, Winnie S. Liang, Erica Tassone, Jonathan Adkins, Megan Russell, Nhan Tran, Nicole Hank, James Newell, Sandeep Gupta, Michael Berens, Ronald Korn, David W. Craig, Sara A. Byron. Leveraging spatial heterogeneity in tumor purity for improved somatic variant calling of archival tumor-only samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-007. doi:10.1158/1538-7445.AM2017-LB-007

Abstract Glioblastoma Multiforme (GBM) is the most common tumor of the CNS with a median survival of approximately 15 months. The highly aggressive invasion of malignant cells into the surrounding normal brain tissue renders complete surgical resection impossible, increases therapeutic resistance, and virtually assures tumor recurrence. We have previously demonstrated that TROY (TNFRSF19) has an important role in GBM invasion and resistance. TROY expression is correlated with glial tumor grade and inversely correlated with patient survival. Increased TROY expression stimulated cell migration/invasion in vitro and in vivo and confers resistance to both ionizing radiation- and temozolomide-induced apoptosis via activation of Akt and NF-κB. These data indicate that TROY stimulated migration/invasion is associated with signaling pathways that also increase survival and therapeutic resistance, however, the mechanistic basis of this signaling remains unclear. To investigate the mechanism by which TROY induces GBM cell invasion, we performed immunoprecipitation of the TROY receptor coupled with MALDI-TOF and MS/MS analysis and identified PDZ-RhoGEF as a binding partner for TROY. We validated the interaction of TROY with PDZ-RhoGEF by immunoprecipitation and western blotting, and demonstrated that PDZ-RhoGEF can exchange for both RhoA and RhoC in glioma cells and is implicated in GBM cell invasion, proliferation, and survival. In order to assess the specific role of PDZ-RhoGEF in TROY signaling, we examined the effects of PDZ-RhoGEF on TROY-mediated activation of NF-κB. While overexpression of TROY alone strongly stimulated NF-κB transcriptional activity in serum-free conditions, increased expression of PDZ-RhoGEF alone had no effect on NF-κB activity. Co-transfection of PDZ-RhoGEF with TROY synergistically promoted NF-κB activation. Mutation of the TRAF binding domain (TBD) in the cytoplasmic domain of TROY abolished its capacity to activate NF-κB, even in the presence of PDZ-RhoGEF, suggesting that the TBD is important for TROY induced NF-κB activation. Furthermore, knockdown of PDZ-RhoGEF by shRNA attenuated NF-κB activation in TROY expressing cells, blocked TROY mediated invasion of primary GBM xenograft cells and increased sensitivity to temozolomide. Collectively, these data indicate that PDZ-RhoGEF plays an important role in TROY signaling and provides insights into a potential node of vulnerability to limit GBM cell invasion and decrease therapeutic resistance. Citation Format: Zonghui Ding, Alison Roos, Jean Kloss, Harshil Dhruv, Marc Symons, Nhan L. Tran, Joseph C. Loftus. PDZ-RhoGEF functions as a critical signaling effector for TROY [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1878. doi:10.1158/1538-7445.AM2017-1878

Glioblastoma (GBM) is a highly aggressive and lethal form of primary brain cancer. Numerous barriers exist to the effective treatment ofGBMincluding the tightly controlled interface between the bloodstream and central nervous system termed the ‘neurovascular unit,’ a narrow and tortuous tumor extracellular space containing a dense meshwork of proteins and glycosaminoglycans, and genomic heterogeneity and instability. A major goal ofGBMtherapy is achieving sustained drug delivery to glioma cells while minimizing toxicity to adjacent neurons and glia. Targeted nanotherapeutics have emerged as promising drug delivery systems with the potential to improve pharmacokinetic profiles and therapeutic efficacy. Some of the key cell surface molecules that have been identified asGBMtargets include the transferrin receptor, low‐density lipoprotein receptor‐related protein, αvβ3integrin, glucose transporter(s), glial fibrillary acidic protein, connexin 43, epidermal growth factor receptor (EGFR),EGFRvariantIII, interleukin‐13 receptor α chain variant 2, and fibroblast growth factor‐inducible factor 14. However, most targeted therapeutic formulations have yet to demonstrate improved efficacy related to disease progression or survival. Potential limitations to current targeted nanotherapeutics include: (1) adhesive interactions with nontarget structures, (2) low density or prevalence of the target, (3) lack of target specificity, and (4) genetic instability resulting in alterations of either the target itself or its expression level in response to treatment. In this review, we address these potential limitations in the context of the keyGBMtargets with the goal of advancing the understanding and development of targeted nanotherapeutics forGBM.WIREs Nanomed Nanobiotechnol2017, 9:e1439. doi: 10.1002/wnan.1439This article is categorized under:Therapeutic Approaches and Drug Discovery > Emerging TechnologiesTherapeutic Approaches and Drug Discovery > Nanomedicine for Neurological DiseaseTherapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease

AbstractBackgroundGlioblastoma (GBM) exhibits profound intratumoral genetic heterogeneity. Each tumor comprises multiple genetically distinct clonal populations with different therapeutic sensitivities. This has implications for targeted therapy and genetically informed paradigms. Contrast-enhanced (CE)-MRI and conventional sampling techniques have failed to resolve this heterogeneity, particularly for nonenhancing tumor populations. This study explores the feasibility of using multiparametric MRI and texture analysis to characterize regional genetic heterogeneity throughout MRI-enhancing and nonenhancing tumor segments.MethodsWe collected multiple image-guided biopsies from primary GBM patients throughout regions of enhancement (ENH) and nonenhancing parenchyma (so called brain-around-tumor, [BAT]). For each biopsy, we analyzed DNA copy number variants for core GBM driver genes reported by The Cancer Genome Atlas. We co-registered biopsy locations with MRI and texture maps to correlate regional genetic status with spatially matched imaging measurements. We also built multivariate predictive decision-tree models for each GBM driver gene and validated accuracies using leave-one-out-cross-validation (LOOCV).ResultsWe collected 48 biopsies (13 tumors) and identified significant imaging correlations (univariate analysis) for 6 driver genes: EGFR, PDGFRA, PTEN, CDKN2A, RB1, and TP53. Predictive model accuracies (on LOOCV) varied by driver gene of interest. Highest accuracies were observed for PDGFRA (77.1%), EGFR (75%), CDKN2A (87.5%), and RB1 (87.5%), while lowest accuracy was observed in TP53 (37.5%). Models for 4 driver genes (EGFR, RB1, CDKN2A, and PTEN) showed higher accuracy in BAT samples (n = 16) compared with those from ENH segments (n = 32).ConclusionMRI and texture analysis can help characterize regional genetic heterogeneity, which offers potential diagnostic value under the paradigm of individualized oncology.

Abstract Glioblastoma (GB) is the highest grade and most common form of primary adult brain tumors. Despite surgical removal followed by concomitant radiation and chemotherapy with the alkylating agent temozolomide, GB tumors develop treatment resistance and ultimately recur. Impaired response to treatment occurs rapidly, conferring a median survival of just fifteen months. Thus, it is necessary to identify the genetic and signaling mechanisms that promote tumor resistance to develop targeted therapies to combat this refractory disease. Previous observations indicated that SGEF (ARHGEF26), a RhoG-specific guanine nucleotide exchange factor (GEF), is overexpressed in GB tumors and plays a role in promoting TWEAK-Fn14–mediated glioma invasion. Here, further investigation revealed an important role for SGEF in glioma cell survival. SGEF expression is upregulated by TWEAK-Fn14 signaling via NF-κB activity while shRNA-mediated reduction of SGEF expression sensitizes glioma cells to temozolomide-induced apoptosis and suppresses colony formation following temozolomide treatment. Nuclear SGEF is activated following temozolomide exposure and complexes with the DNA damage repair (DDR) protein BRCA1. Moreover, BRCA1 phosphorylation in response to temozolomide treatment is hindered by SGEF knockdown. The role of SGEF in promoting chemotherapeutic resistance highlights a heretofore unappreciated driver, and suggests its candidacy for development of novel targeted therapeutics for temozolomide-refractory, invasive GB cells. Implication: SGEF, as a dual process modulator of cell survival and invasion, represents a novel target for treatment refractory glioblastoma. Mol Cancer Res; 14(3); 302–12. ©2016 AACR.

Abstract BACKGROUND/PURPOSE The Mayo Clinic has developed a large panel of patient-derived xenografts (PDX) from patients with glioblastoma multiforme (GBM). Here we report initial molecular profiling of the Mayo PDX panel and a comparison of patient and PDX molecular profile and response to therapy. METHODS & MATERIALS Clinical data was retrieved by retrospective chart review. Animal data from all PDX investigations conducted between 2004-2014 were retrieved from experimental logs and subsequently consolidated into a database for analysis. RESULTS From 1999 to 2014, 182 patient tumor samples of varying histological grades were attempted for xenograft with 73 resulting viable PDX lines. Viable xenografts were only produced from WHO grade IV tumor specimens, yielding an overall success rate of 49% for these tumors. GBM patients that produced viable xenografts compared to those that did not exhibited a trend for decreased overall survival (P = 0.18). There was no significant association between successful xenografting and whether tissue was from newly diagnosed (45/93%) or recurrent (20/40; 50%) tumors. Patient age > 45 at diagnosis was correlated with increased PDX viability in GBMs (p = 0.05). Of the viable PDX models analyzed, EGFR mutation was identified in 17 lines, TERT mutation was found in 13 lines, IDH mutation in 1 line, and MGMT hypermethylation in 25 lines. RNAseq was performed on orthotopic tumor samples from 53 PDX models. After excluding contaminating murine sequence reads, expression analysis demonstrated 32 models with a mesenchymal phenotype. Array comparative genomic hybridization was performed on 9 patient samples and derivative early, mid and late passage PDX tumors. Using unbiased hierarchical clustering, there was a high concordance between patient and xenograft models. Within the PDX panel, fractionated radiation (RT) alone and RT combined with temozolomide (TMZ) was tested in orthotopic tumors in 38 lines. The overall median survival benefit (ratio of median survival for treated vs. placebo) in PDX lines treated with RT only was 1.6 (range: 0.9-2.5) and with RT/TMZ was 2.5 (range: 1.1 - 8.9). There was a positive association between observed patient survival and the corresponding survival benefit in the PDX for subjects treated with RT/TMZ (r = 0.2; n = 17). Response to adjuvant TMZ was evaluated in 42 tumor lines, and response to bevacizumab was tested in 33 tumor lines, and correlations with clinical treatment response are being evaluated. CONCLUSIONS: The Mayo GBM PDX panel is widely used in the neuro-oncology community. The initial molecular analysis suggests a good correlation between patient and PDX at the level of genotypic characteristics and therapeutic sensitivity. Citation Format: Dioval A. Remonde, Brett L. Carlson, Mark A. Schroeder, Brock Armstrong, Sen Peng, Lisa Evers, Paul A. Decker, Jeanette Eckel Passow, Michael E. Berens, Nhan L. Tran, Robert B. Jenkins, Jann N. Sarkaria. Characterization of patient-derived xenograft (PDX) models to evaluate clinical and therapeutic responses of glioblastoma multiforme. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1468. doi:10.1158/1538-7445.AM2015-1468