Mladek, Ann C

Abstract Background Antibody drug conjugates (ADCs) targeting the epidermal growth factor receptor (EGFR), such as depatuxizumab mafodotin (Depatux-M), is a promising therapeutic strategy for glioblastoma (GBM) but recent clinical trials did not demonstrate a survival benefit. Understanding the mechanisms of failure for this promising strategy is critically important. Methods PDX models were employed to study efficacy of systemic vs intracranial delivery of Depatux-M. Immunofluorescence and MALDI-MSI were performed to detect drug levels in the brain. EGFR levels and compensatory pathways were studied using quantitative flow cytometry, Western blots, RNAseq, FISH, and phosphoproteomics. Results Systemic delivery of Depatux-M was highly effective in nine of 10 EGFR-amplified heterotopic PDXs with survival extending beyond one year in eight PDXs. Acquired resistance in two PDXs (GBM12 and GBM46) was driven by suppression of EGFR expression or emergence of a novel short-variant of EGFR lacking the epitope for the Depatux-M antibody. In contrast to the profound benefit observed in heterotopic tumors, only two of seven intrinsically sensitive PDXs were responsive to Depatux-M as intracranial tumors. Poor efficacy in orthotopic PDXs was associated with limited and heterogeneous distribution of Depatux-M into tumor tissues, and artificial disruption of the BBB or bypass of the BBB by direct intracranial injection of Depatux-M into orthotopic tumors markedly enhanced the efficacy of drug treatment. Conclusions Despite profound intrinsic sensitivity to Depatux-M, limited drug delivery into brain tumor may have been a key contributor to lack of efficacy in recently failed clinical trials.

Abstract Human tissue samples commonly preserved as formalin-fixed paraffin-embedded (FFPE) tissues after diagnostic or surgical procedures in the clinic represent an invaluable source of clinical specimens for in-depth characterization of signaling networks to assess therapeutic options. Tyrosine phosphorylation (pTyr) plays a fundamental role in cellular processes and is commonly dysregulated in cancer but has not been studied to date in FFPE samples. In addition, pTyr analysis that may otherwise inform therapeutic interventions for patients has been limited by the requirement for large amounts of frozen tissue. Here we describe a method for highly sensitive, quantitative analysis of pTyr signaling networks, with hundreds of sites quantified from one to two 10-μm sections of FFPE tissue specimens. A combination of optimized magnetic bead–based sample processing, optimized pTyr enrichment strategies, and tandem mass tag multiplexing enabled in-depth coverage of pTyr signaling networks from small amounts of input material. Phosphotyrosine profiles of flash-frozen and FFPE tissues derived from the same tumors suggested that FFPE tissues preserve pTyr signaling characteristics in patient-derived xenografts and archived clinical specimens. pTyr analysis of FFPE tissue sections from breast cancer tumors as well as lung cancer tumors highlighted patient-specific oncogenic driving kinases, indicating potential targeted therapies for each patient. These data suggest the capability for direct translational insight from pTyr analysis of small amounts of FFPE tumor tissue specimens. Significance: This study reports a highly sensitive method utilizing FFPE tissues to identify dysregulated signaling networks in patient tumors, opening the door for direct translational insights from FFPE tumor tissue banks in hospitals.

Abstract Tesevatinib is a potent oral brain penetrant EGFR inhibitor currently being evaluated for glioblastoma therapy. Tesevatinib distribution was assessed in wild-type (WT) and Mdr1a/b(-/-)Bcrp(-/-) triple knockout (TKO) FVB mice after dosing orally or via osmotic minipump; drug–tissue binding was assessed by rapid equilibrium dialysis. Two hours after tesevatinib dosing, brain concentrations in WT and TKO mice were 0.72 and 10.03 μg/g, respectively. Brain-to-plasma ratios (Kp) were 0.53 and 5.73, respectively. With intraperitoneal infusion, brain concentrations were 1.46 and 30.6 μg/g (Kp 1.16 and 25.10), respectively. The brain-to-plasma unbound drug concentration ratios were substantially lower (WT mice, 0.03–0.08; TKO mice, 0.40–1.75). Unbound drug concentrations in brains of WT mice were 0.78 to 1.59 ng/g. In vitro cytotoxicity and EGFR pathway signaling were evaluated using EGFR-amplified patient-derived glioblastoma xenograft models (GBM12, GBM6). In vivo pharmacodynamics and efficacy were assessed using athymic nude mice bearing either intracranial or flank tumors treated by oral gavage. Tesevatinib potently reduced cell viability [IC50 GBM12 = 11 nmol/L (5.5 ng/mL), GBM6 = 102 nmol/L] and suppressed EGFR signaling in vitro. However, tesevatinib efficacy compared with vehicle in intracranial (GBM12, median survival: 23 vs. 18 days, P = 0.003) and flank models (GBM12, median time to outcome: 41 vs. 33 days, P = 0.007; GBM6, 44 vs. 33 days, P = 0.007) was modest and associated with partial inhibition of EGFR signaling. Overall, tesevatinib efficacy in EGFR-amplified PDX GBM models is robust in vitro but relatively modest in vivo, despite a high brain-to-plasma ratio. This discrepancy may be explained by drug-tissue binding and compensatory signaling.

Abstract Non-genotoxic reactivation of p53 by MDM2 inhibitors represents a promising therapeutic strategy for tumors with wild-type TP53, particularly tumors harboring MDM2 amplification. MDM2 controls p53 levels by targeting it for degradation, while disruption of the MDM2-p53 interaction causes rapid accumulation of p53 and activation of the p53 pathway. We examined the efficacy of the small molecule MDM2 inhibitor KRT-232, alone and in combination with radiation therapy (RT), in MDM2-amplified and/or p53 wildtype patient-derived xenograft (PDX) models of glioblastoma in vitro and in vivo. In vitro, glioblastoma PDX explant cultures showed sensitivity to KRT-232, both tumors with MDM2 amplification (GBM108 and G148) and non-amplified but TP53-wildtype lines (GBM10, GBM14, and GBM39), with IC50s ranging from 300-800 nM in FBS culture conditions. A TP53 p.F270C mutant PDX (GBM43) was inherently resistant, with IC50 >3000 nM. In the MDM2-amplified GBM108 line, KRT-232 led to a robust (5-6 fold) induction of p53-target genes p21, PUMA, and NOXA, with initiation of both apoptosis and senescence. Expression of p21 and PUMA was greater with KRT-232 in combination with RT (25-35 fold induction), while stable knock-down of p53 in GBM108 led to complete resistance to KRT-232. In contrast, GBM10 showed lower induction of p21 and PUMA (2-3 fold) and was more resistant to KRT-232. In an orthotopic GBM108 xenograft model, treatment with KRT-232 +/- RT for one week extended survival from 22 days (placebo) to 46 days (KRT-232 alone); combination KRT-232 + RT further extended survival (77 days) over RT alone (31 days). KRT-232 is an effective treatment in a subset of glioblastoma pre-clinical models alone and in combination with RT. Further studies are underway to understand the mechanisms conferring innate sensitivity or resistance to KRT-232.

Abstract Chromosome region maintenance protein 1 (CRM1) mediates protein export from the nucleus and is a new target for anticancer therapeutics. Broader application of KPT-330 (selinexor), a first-in-class CRM1 inhibitor recently approved for relapsed multiple myeloma and diffuse large B-cell lymphoma, have been limited by substantial toxicity. We discovered that salicylates markedly enhance the antitumor activity of CRM1 inhibitors by extending the mechanisms of action beyond CRM1 inhibition. Using salicylates in combination enables targeting of a range of blood cancers with a much lower dose of selinexor, thereby potentially mitigating prohibitive clinical adverse effects. Choline salicylate (CS) with low-dose KPT-330 (K+CS) had potent, broad activity across high-risk hematological malignancies and solid-organ cancers ex vivo and in vivo. The K+CS combination was not toxic to nonmalignant cells as compared with malignant cells and was safe without inducing toxicity to normal organs in mice. Mechanistically, compared with KPT-330 alone, K+CS suppresses the expression of CRM1, Rad51, and thymidylate synthase proteins, leading to more efficient inhibition of CRM1-mediated nuclear export, impairment of DNA-damage repair, reduced pyrimidine synthesis, cell-cycle arrest in S-phase, and cell apoptosis. Moreover, the addition of poly (ADP-ribose) polymerase inhibitors further potentiates the K+CS antitumor effect. K+CS represents a new class of therapy for multiple types of blood cancers and will stimulate future investigations to exploit DNA-damage repair and nucleocytoplasmic transport for cancer therapy in general.

Abstract 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.

Abstract In glioblastoma (GBM), invasion and proliferation are reciprocally related—e.g., targeting one stimulates the other. Thus, effective therapy for GBM requires finding targets that drive both invasion and proliferation and which are druggable, ideally with FDA approved therapeutics. We find that the atypical protein kinase C isoform, PKCi meets these criteria. Using a human GBM tissue microarray, we find that PKCi protein expression fits a bimodal distribution, with >35% of GBMs showing high levels of PKCi expression. Genetic deletion of Prkci, the gene encoding mouse PKCi, impairs tumor invasion and proliferation both in vitro and in vivo, and significantly prolongs survival in an immunocompetent PDGF-driven orthotopic mouse model of GBM. PKCi can be selectively targeted with Auranofin, a small molecule PKCi inhibitor that has been FDA approved for treatment of inflammatory diseases. Like genetic deletion of Prkci Auranofin treatment significantly prolongs survival in our murine GBM model, and does so to a similar degree. Interestingly, analysis of a panel of human and murine GBM cells reveals that sensitivity to Auranofin inhibition of transformed growth directly correlates with expression of PKCi, indicating that PKCi expression profiling could serve as a predictive biomarker for responsiveness to Auranofin. However, genetically deleting or pharmacologically inactivating PKCi does not permanently arrest tumor growth, implying that GBM cells acquire mechanisms that allow them to compensate for the loss of this important signaling molecule. We are currently examining potential “escape” mechanisms through ‘omics-based approaches, which may enable us to enhance the therapeutic potential of Auranofin. Taken together, our results demonstrate that PKCi is a compelling therapeutic target for treatment of GBM that deserves further investigation.

AbstractBackgroundGlioblastoma (GBM) represents an aggressive cancer type with a median survival of only 14 months. With fewer than 5% of patients surviving 5 years, comprehensive profiling of these rare patients could elucidate prognostic biomarkers that may confer better patient outcomes. We utilized multiple molecular approaches to characterize the largest patient cohort of isocitrate dehydrogenase (IDH)–wildtype GBM long-term survivors (LTS) to date.MethodsRetrospective analysis was performed on 49 archived formalin-fixed paraffin embedded tumor specimens from patients diagnosed with GBM at the Mayo Clinic between December 1995 and September 2013. These patient samples were subdivided into 2 groups based on survival (12 LTS, 37 short-term survivors [STS]) and subsequently examined by mutation sequencing, copy number analysis, methylation profiling, and gene expression.ResultsOf the 49 patients analyzed in this study, LTS were younger at diagnosis (P = 0.016), more likely to be female (P = 0.048), and MGMT promoter methylated (UniD, P = 0.01). IDH-wildtype STS and LTS demonstrated classic GBM mutations and copy number changes. Pathway analysis of differentially expressed genes showed LTS enrichment for sphingomyelin metabolism, which has been linked to decreased GBM growth, invasion, and angiogenesis. STS were enriched for DNA repair and cell cycle control networks.ConclusionsWhile our findings largely report remarkable similarity between these LTS and more typical STS, unique attributes were observed in regard to altered gene expression and pathway enrichment. These attributes may be valuable prognostic markers and are worth further examination. Importantly, this study also underscores the limitations of existing biomarkers and classification methods in predicting patient prognosis.

Abstract Background Predictive molecular biomarkers to select optimal treatment for patients with glioblastoma and other cancers are lacking. New strategies are needed when large randomized trials with correlative molecular data are not feasible. Methods Gene signatures (GS) were developed from 31 orthotopic glioblastoma patient-derived xenografts (PDXs), treated with standard therapies, to predict benefit from radiotherapy (RT-GS), temozolomide (Chemo-GS), or the combination (ChemoRT-GS). Independent validation was performed in a heterogeneously treated clinical cohort of 502 glioblastoma patients with overall survival as the primary endpoint. Multivariate Cox analysis was used to adjust for confounding variables and evaluate interactions between signatures and treatment. Results PDX models recapitulated the clinical heterogeneity of glioblastoma patients. RT-GS, Chemo-GS, and ChemoRT-GS were correlated with benefit from treatment in the PDX models. In independent clinical validation, higher RT-GS scores were associated with increased survival only in patients receiving RT (P = 0.0031, hazard ratio [HR] = 0.78 [0.66–0.92]), higher Chemo-GS scores were associated with increased survival only in patients receiving chemotherapy (P < 0.0001, HR = 0.66 [0.55–0.8]), and higher ChemoRT-GS scores were associated with increased survival only in patients receiving ChemoRT (P = 0.0001, HR = 0.54 [0.4–0.74]). RT-GS and ChemoRT-GS had significant interactions with treatment on multivariate analysis (P = 0.0009 and 0.02, respectively), indicating that they are bona fide predictive biomarkers. Conclusions Using a novel PDX-driven methodology, we developed and validated 3 platform-independent molecular signatures that predict benefit from standard of care therapies for glioblastoma. These signatures may be useful to personalize glioblastoma treatment in the clinic and this approach may be a generalizable method to identify predictive biomarkers without resource-intensive randomized trials.