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Purpose: Recurrent malignant glioma carries a dismal prognosis, and novel therapies are needed. We examined the feasibility and safety of vaccination with irradiated autologous glioma cells mixed with irradiated GM-K562 cells in patients undergoing craniotomy for recurrent malignant glioma.Experimental Design: We initiated a phase I study examining the safety of 2 doses of GM-K562 cells mixed with autologous cells. Primary endpoints were feasibility and safety. Feasibility was defined as the ability for 60% of enrolled subjects to initiate vaccination. Dose-limiting toxicity was assessed via a 3+3 dose-escalation format, examining irradiated tumor cells mixed with 5 × 106 GM-K562 cells or 1 × 107 GM-K562 cells. Eligibility required a priori indication for resection of a recurrent high-grade glioma. We measured biological activity by measuring delayed type hypersensitivity (DTH) responses, humoral immunity against tumor-associated antigens, and T-lymphocyte activation.Results: Eleven patients were enrolled. Sufficient numbers of autologous tumor cells were harvested in 10 patients, all of whom went on to receive vaccine. There were no dose-limiting toxicities. Vaccination strengthened DTH responses to irradiated autologous tumor cells in most patients, and vigorous humoral responses to tumor-associated angiogenic cytokines were seen as well. T-lymphocyte activation was seen with significantly increased expression of CTLA-4, PD-1, 4-1BB, and OX40 by CD4+ cells and PD-1 and 4-1BB by CD8+ cells. Activation was coupled with vaccine-associated increase in the frequency of regulatory CD4+ T lymphocytes.Conclusions: Vaccination with irradiated autologous tumor cells mixed with GM-K562 cells is feasible, well tolerated, and active in patients with recurrent malignant glioma. Clin Cancer Res; 22(12); 2885–96. ©2016 AACR.

Extended methods for flow cytometry for lymphocyte phenotyping.

Extended methods for ELISA assay for angiogenic cytokines.

Purpose: Measurements of objective response rates are critical to evaluate new glioma therapies. The hallmark metabolic alteration in gliomas with mutant isocitrate dehydrogenase (IDH) is the overproduction of oncometabolite 2-hydroxyglutarate (2HG), which plays a key role in malignant transformation. 2HG represents an ideal biomarker to probe treatment response in IDH-mutant glioma patients, and we hypothesized a decrease in 2HG levels would be measureable by in vivo magnetic resonance spectroscopy (MRS) as a result of antitumor therapy.Experimental Design: We report a prospective longitudinal imaging study performed in 25 IDH-mutant glioma patients receiving adjuvant radiation and chemotherapy. A newly developed 3D MRS imaging was used to noninvasively image 2HG. Paired Student t test was used to compare pre- and posttreatment tumor 2HG values. Test–retest measurements were performed to determine the threshold for 2HG functional spectroscopic maps (fSM). Univariate and multivariate regression were performed to correlate 2HG changes with Karnofsky performance score (KPS).Results: We found that mean 2HG (2HG/Cre) levels decreased significantly (median = 48.1%; 95% confidence interval = 27.3%–56.5%; P = 0.007) in the posttreatment scan. The volume of decreased 2HG correlates (R2 = 0.88, P = 0.002) with clinical status evaluated by KPS.Conclusions: We demonstrate that dynamic measurements of 2HG are feasible by 3D fSM, and the decrease of 2HG levels can monitor treatment response in patients with IDH-mutant gliomas. Our results indicate that quantitative in vivo 2HG imaging may be used for precision medicine and early response assessment in clinical trials of therapies targeting IDH-mutant gliomas. Clin Cancer Res; 22(7); 1632–41. ©2015 AACR.

Purpose: Structural and functional alterations in tumor vasculature are thought to contribute to tumor hypoxia which is a primary driver of malignancy through its negative impact on the efficacy of radiation, immune surveillance, apoptosis, genomic stability, and accelerated angiogenesis. We performed a prospective, multicenter study to test the hypothesis that abnormal tumor vasculature and hypoxia, as measured with MRI and PET, will negatively impact survival in patients with newly diagnosed glioblastoma.Experimental Design: Prior to the start of chemoradiation, patients with glioblastoma underwent MRI scans that included dynamic contrast enhanced and dynamic susceptibility contrast perfusion sequences to quantitate tumor cerebral blood volume/flow (CBV/CBF) and vascular permeability (ktrans) as well as 18F-Fluoromisonidazole (18F-FMISO) PET to quantitate tumor hypoxia. ROC analysis and Cox regression models were used to determine the association of imaging variables with progression-free and overall survival.Results: Fifty patients were enrolled of which 42 had evaluable imaging data. Higher pretreatment 18F-FMISO SUVpeak (P = 0.048), mean ktrans (P = 0.024), and median ktrans (P = 0.045) were significantly associated with shorter overall survival. Higher pretreatment median ktrans (P = 0.021), normalized RCBV (P = 0.0096), and nCBF (P = 0.038) were significantly associated with shorter progression-free survival. SUVpeak [AUC = 0.75; 95% confidence interval (CI), 0.59–0.91], nRCBV (AUC = 0.72; 95% CI, 0.56–0.89), and nCBF (AUC = 0.72; 95% CI, 0.56–0.89) were predictive of survival at 1 year.Conclusions: Increased tumor perfusion, vascular volume, vascular permeability, and hypoxia are negative prognostic markers in newly diagnosed patients with gioblastoma, and these important physiologic markers can be measured safely and reliably using MRI and 18F-FMISO PET. Clin Cancer Res; 22(20); 5079–86. ©2016 AACR.

Purpose: Isocitrate dehydrogenase (IDH) mutations in glioma patients confer longer survival and may guide treatment decision making. We aimed to predict the IDH status of gliomas from MR imaging by applying a residual convolutional neural network to preoperative radiographic data.Experimental Design: Preoperative imaging was acquired for 201 patients from the Hospital of University of Pennsylvania (HUP), 157 patients from Brigham and Women's Hospital (BWH), and 138 patients from The Cancer Imaging Archive (TCIA) and divided into training, validation, and testing sets. We trained a residual convolutional neural network for each MR sequence (FLAIR, T2, T1 precontrast, and T1 postcontrast) and built a predictive model from the outputs. To increase the size of the training set and prevent overfitting, we augmented the training set images by introducing random rotations, translations, flips, shearing, and zooming.Results: With our neural network model, we achieved IDH prediction accuracies of 82.8% (AUC = 0.90), 83.0% (AUC = 0.93), and 85.7% (AUC = 0.94) within training, validation, and testing sets, respectively. When age at diagnosis was incorporated into the model, the training, validation, and testing accuracies increased to 87.3% (AUC = 0.93), 87.6% (AUC = 0.95), and 89.1% (AUC = 0.95), respectively.Conclusions: We developed a deep learning technique to noninvasively predict IDH genotype in grade II–IV glioma using conventional MR imaging using a multi-institutional data set. Clin Cancer Res; 24(5); 1073–81. ©2017 AACR.

Supplementary Data

This file contains 3 Tables and 9 Figures with additional results and details of analysis related to the main results presented in the manuscript. The complete list of figures and tables is provided below. Table 1S. Baseline metabolite levels relative to creatine. Table 2S. Demographic, genomic, molecular, histological, radiological and clinical data. Table 3S. Fractional changes for all imaging biomarkers. Table 4S. General Linear Model with change of KPS as dependent variable and grade, age and fractional volume of decreased 2HG/Cre as covariates. Figure 1S. 3D MRSI pulse sequence for 2HG imaging, detailed diagram. Figure 2S. Quantum mechanics simulations of 2HG spectral editing for MEGA-LASER, MEGA-PRESS and PRESS-97 sequences. Figure 3S. Simulations of 2HG editing for MEGA-LASER and PRESS-97 sequences in the presence of B1 field inhomogeneity. Figure 4S. Mitigation of subtraction artifacts caused by motion and scanner instability in J-difference MR spectroscopy using real-time prospective motion correction, shim update and reacquisition. Figure 5S. Metabolic maps before image interpolation. Figure 6S. Examples of OFF and difference (DIFF) MEGA-LASER spectra from 3D MRSI voxels located in the tumor and contralateral normal appearing white matter, pre- and post-treatment respectively. Figure 7S. Distributions of Δ2HG/Cre in the test-retest and post-pre longitudinal data sets. Figure 8S. Comparison of functional spectroscopic maps (fSM) and functional diffusion maps (fDM). Figure 9S. Relation between residual tumor measured by FLAIR hyperintensity volume and the SNR and CRLB of 2HG. Notes. Details related to data analysis in Figures 7S and 9S.

Full flow cytometry panel for white blood cell immunophenotyping.

Complete inclusion and exclusion criteria are listed.

supplemental legend

Detailed description of histopathological scoring of vaccination site and delayed-type hypersensitivity biopsies.

Figure, Table, and MRI acquisition protocol

Supplemental Table 1: Participating centers that enrolled patients; Supplemental Table 2: Serial FMISO PET Imaging.

Purpose:Targeting tumor blood vessels is an attractive therapy in glioblastoma (GBM), but the mechanism of action of these agents and how they modulate delivery of concomitant chemotherapy are not clear in humans. We sought to elucidate how bevacizumab modulates tumor vasculature and the impact those vascular changes have on drug delivery in patients with recurrent GBM.Experimental Design:Temozolomide was labeled with [11C], and serial PET-MRI scans were performed in patients with recurrent GBM treated with bevacizumab and daily temozolomide. PET-MRI scans were performed prior to the first bevacizumab dose, 1 day after the first dose, and prior to the third dose of bevacizumab. We calculated tumor volume, vascular permeability (Ktrans), perfusion (cerebral blood flow), and the standardized uptake values (SUV) of [11C] temozolomide within the tumor.Results:Twelve patients were enrolled, resulting in 23 evaluable scans. Within the entire contrast-enhancing tumor volume, both temozolomide uptake and vascular permeability decreased after initiation of bevacizumab in most patients, whereas change in perfusion was more variable. In subregions of the tumor where permeability was low and the blood–brain barrier not compromised, increased perfusion correlated with increased temozolomide uptake.Conclusions:Bevacizumab led to a decrease in permeability and concomitant delivery of temozolomide. However, in subregions of the tumor where permeability was low, increased perfusion improved delivery of temozolomide, suggesting that perfusion may modulate the delivery of chemotherapy in certain settings. These results support exploring whether lower doses of bevacizumab improve perfusion and concomitant drug delivery.

Purpose: GDC-0084 is an oral, brain-penetrant small-molecule inhibitor of PI3K and mTOR. A first-in-human, phase I study was conducted in patients with recurrent high-grade glioma. Patients and Methods: GDC-0084 was administered orally, once daily, to evaluate safety, pharmacokinetics (PK), and activity. Fluorodeoxyglucose-PET (FDG-PET) was performed to measure metabolic responses. Results: Forty-seven heavily pretreated patients enrolled in eight cohorts (2–65 mg). Dose-limiting toxicities included 1 case of grade 2 bradycardia and grade 3 myocardial ischemia (15 mg), grade 3 stomatitis (45 mg), and 2 cases of grade 3 mucosal inflammation (65 mg); the MTD was 45 mg/day. GDC-0084 demonstrated linear and dose-proportional PK, with a half-life (∼19 hours) supportive of once-daily dosing. At 45 mg/day, steady-state concentrations exceeded preclinical target concentrations producing antitumor activity in xenograft models. FDG-PET in 7 of 27 patients (26%) showed metabolic partial response. At doses ≥45 mg/day, a trend toward decreased median standardized uptake value in normal brain was observed, suggesting central nervous system penetration of drug. In two resection specimens, GDC-0084 was detected at similar levels in tumor and brain tissue, with a brain tissue/tumor-to-plasma ratio of >1 and >0.5 for total and free drug, respectively. Best overall response was stable disease in 19 patients (40%) and progressive disease in 26 patients (55%); 2 patients (4%) were nonevaluable. Conclusions: GDC-0084 demonstrated classic PI3K/mTOR–inhibitor related toxicities. FDG-PET and concentration data from brain tumor tissue suggest that GDC-0084 crossed the blood–brain barrier.

Purpose: Although antiangiogenic therapy for high-grade glioma (HGG) is promising, responses are not durable. Correlative clinical studies suggest that the SDF-1α/CXCR4 axis may mediate resistance to VEGFR inhibition. Preclinical data have demonstrated that plerixafor (a reversible CXCR4 inhibitor) could inhibit glioma progression after anti-VEGF pathway inhibition. We conducted a phase I study to determine the safety of plerixafor and bevacizumab in recurrent HGG. Patients and Methods: Part 1 enrolled 23 patients with a 3 × 3 dose escalation design to a maximum planned dose of plerixafor 320 μg/kg subcutaneously on days 1 to 21 and bevacizumab 10 mg/kg intravenously on days 1 and 15 of each 28-day cycle. Cerebrospinal fluid (CSF) and plasma samples were obtained for pharmacokinetic analyses. Plasma and cellular biomarkers were evaluated before and after treatment. Part 2 enrolled 3 patients and was a surgical study to determine plerixafor's penetration in tumor tissue. Results: In Part 1, no dose-limiting toxicities were seen at the maximum planned dose of plerixafor + bevacizumab. Treatment was well tolerated. After plerixafor 320 μg/kg treatment, the average CSF drug concentration was 26.8 ± 19.6 ng/mL. Plerixafor concentration in resected tumor tissue from patients pretreated with plerixafor was 10 to 12 μg/g. Circulating biomarker data indicated that plerixafor + bevacizumab induces rapid and persistent increases in plasma SDF-1α and placental growth factor. Progression-free survival correlated with pretreatment plasma soluble mesenchymal–epithelial transition receptor and sVEGFR1, and overall survival with the change during treatment in CD34+ progenitor/stem cells and CD8 T cells. Conclusions: Plerixafor + bevacizumab was well tolerated in HGG patients. Plerixafor distributed to both the CSF and brain tumor tissue, and treatment was associated with biomarker changes consistent with VEGF and CXCR4 inhibition. Clin Cancer Res; 24(19); 4643–9. ©2018 AACR.

Purpose: Isocitrate dehydrogenase (IDH) mutations in glioma patients confer longer survival and may guide treatment decision making. We aimed to predict the IDH status of gliomas from MR imaging by applying a residual convolutional neural network to preoperative radiographic data. Experimental Design: Preoperative imaging was acquired for 201 patients from the Hospital of University of Pennsylvania (HUP), 157 patients from Brigham and Women's Hospital (BWH), and 138 patients from The Cancer Imaging Archive (TCIA) and divided into training, validation, and testing sets. We trained a residual convolutional neural network for each MR sequence (FLAIR, T2, T1 precontrast, and T1 postcontrast) and built a predictive model from the outputs. To increase the size of the training set and prevent overfitting, we augmented the training set images by introducing random rotations, translations, flips, shearing, and zooming. Results: With our neural network model, we achieved IDH prediction accuracies of 82.8% (AUC = 0.90), 83.0% (AUC = 0.93), and 85.7% (AUC = 0.94) within training, validation, and testing sets, respectively. When age at diagnosis was incorporated into the model, the training, validation, and testing accuracies increased to 87.3% (AUC = 0.93), 87.6% (AUC = 0.95), and 89.1% (AUC = 0.95), respectively. Conclusions: We developed a deep learning technique to noninvasively predict IDH genotype in grade II–IV glioma using conventional MR imaging using a multi-institutional data set. Clin Cancer Res; 24(5); 1073–81. ©2017 AACR.

Purpose: Anti-VEGF therapies remain controversial in the treatment of recurrent glioblastoma (GBM). In the current study, we demonstrate that recurrent GBM patients with a specific diffusion MR imaging signature have an overall survival (OS) advantage when treated with cediranib, bevacizumab, cabozantinib, or aflibercept monotherapy at first or second recurrence. These findings were validated using a separate trial comparing bevacizumab with lomustine. Experimental Design: Patients with recurrent GBM and diffusion MRI from the monotherapy arms of 5 separate phase II clinical trials were included: (i) cediranib (NCT00035656); (ii) bevacizumab (BRAIN Trial, AVF3708g; NCT00345163); (iii) cabozantinib (XL184-201; NCT00704288); (iv) aflibercept (VEGF Trap; NCT00369590); and (v) bevacizumab or lomustine (BELOB; NTR1929). Apparent diffusion coefficient (ADC) histogram analysis was performed prior to therapy to estimate “ADCL,” the mean of the lower ADC distribution. Pretreatment ADCL, enhancing volume, and clinical variables were tested as independent prognostic factors for OS. Results: The coefficient of variance (COV) in double baseline ADCL measurements was 2.5% and did not significantly differ (P = 0.4537). An ADCL threshold of 1.24 μm2/ms produced the largest OS differences between patients (HR ∼ 0.5), and patients with an ADCL > 1.24 μm2/ms had close to double the OS in all anti-VEGF therapeutic scenarios tested. Training and validation data confirmed that baseline ADCL was an independent predictive biomarker for OS in anti-VEGF therapies, but not in lomustine, after accounting for age and baseline enhancing tumor volume. Conclusions: Pretreatment diffusion MRI is a predictive imaging biomarker for OS in patients with recurrent GBM treated with anti-VEGF monotherapy at first or second relapse. Clin Cancer Res; 23(19); 5745–56. ©2017 AACR.

A feared complication within oncology is the development of brain metastases (BM), as this is associated with grim prognosis and substantial morbidity. Despite the remarkable response of immune checkpoint inhibitors (ICI) for unresectable, chemotherapy-refractory tumors of varied histologies, many patients do not respond to ICI. Furthermore, median overall survival for BM patients remains poor as many responses to ICI are not durable. Reasons for this wide variability in outcomes, as well as predictive biomarkers for ICI response, remain unknown. Recently, a growing body of work has demonstrated the importance of the tumor immune microenvironment (iTME) in dictating ICI response. For example, the degree of tumor-infiltrating lymphocytes (TILs) and expression of inflammatory markers, such as interferon-gamma (IFNγ) and perforin, have been correlated with patient outcomes and durability of ICI response. However, in order to integrate these biomarkers into clinical precision medicine, non-invasive assays are needed. Brain biopsies to characterize the BM phenotype are rarely feasible due to the clear morbidity associated with surgery. Answering the need for a non-invasive method of stratifying patients by likelihood of response to ICI, we leveraged a cohort of 44 patients with brain metastases of diverse primary histologies treated with pembrolizumab. To determine if risk factors are discernable on MRI, we trained a deep learning model to predict overall survival (OS) after ICI. The model achieved 0.755 AUC-ROC in predicting OS greater than one year (HR=1.46, 95% CI: 1.11-1.92, p=0.01). In comparison with commonly used measures of progression, change in risk score from the pretreatment MRI to the first follow-up MRI was significantly associated with increasing severity of Response Assessment in Neuro-Oncology criterion for Brain Metastases (RANO-BM) (p=0.05). By developing non-invasive immunotyping for brain metastases, we anticipate our findings have the potential to result in more precise tailoring of existing therapies. To parse the degree to which model predictions were driven by tumor phenotype vs tumor immune microenvironment (iTME) we further applied the model to a unique dataset of surgically-excised melanoma metastases. The model generalized to this cohort with HR=1.37, 95% CI: 0.79-2.37, p=0.26. Feature representations learned by the convolutional neural network (CNN) were subsequently correlated with immune-relevant biomarkers, such as PD1, PDL1, and MHCII, obtained through cyclic immunofluorescence (CyCIF). Finally, features of the pretrained survival network were applied to the secondary task of ICI response prediction in the melanoma metastases cohort (accuracy=0.875). Transfer learning of the ICI survival model reveals the degree to which learned imaging patterns are mutually salient to both survival and response assessment, paving the way to identify molecular processes synonymous to both tasks. Citation Format: Mishka Gidwani, Albert Kim, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer. Convolutional neural network assessment of immune activation state of brain metastases [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PO-026.

Purpose: Measurements of objective response rates are critical to evaluate new glioma therapies. The hallmark metabolic alteration in gliomas with mutant isocitrate dehydrogenase (IDH) is the overproduction of oncometabolite 2-hydroxyglutarate (2HG), which plays a key role in malignant transformation. 2HG represents an ideal biomarker to probe treatment response in IDH-mutant glioma patients, and we hypothesized a decrease in 2HG levels would be measureable by in vivo magnetic resonance spectroscopy (MRS) as a result of antitumor therapy. Experimental Design: We report a prospective longitudinal imaging study performed in 25 IDH-mutant glioma patients receiving adjuvant radiation and chemotherapy. A newly developed 3D MRS imaging was used to noninvasively image 2HG. Paired Student t test was used to compare pre- and posttreatment tumor 2HG values. Test–retest measurements were performed to determine the threshold for 2HG functional spectroscopic maps (fSM). Univariate and multivariate regression were performed to correlate 2HG changes with Karnofsky performance score (KPS). Results: We found that mean 2HG (2HG/Cre) levels decreased significantly (median = 48.1%; 95% confidence interval = 27.3%–56.5%; P = 0.007) in the posttreatment scan. The volume of decreased 2HG correlates (R2 = 0.88, P = 0.002) with clinical status evaluated by KPS. Conclusions: We demonstrate that dynamic measurements of 2HG are feasible by 3D fSM, and the decrease of 2HG levels can monitor treatment response in patients with IDH-mutant gliomas. Our results indicate that quantitative in vivo 2HG imaging may be used for precision medicine and early response assessment in clinical trials of therapies targeting IDH-mutant gliomas. Clin Cancer Res; 22(7); 1632–41. ©2015 AACR.

Although lung adenocarcinomas frequently metastasize to the brain, treatment options for lung adenocarcinoma brain metastases (BM-LUAD) are limited. We discovered novel candidate drivers of progression by using case-control analyses to compare whole-exome sequencing data from a cohort of 73 BM-LUAD to a control cohort of 503 primary lung adenocarcinomas. We identified MYC, YAP1 and MMP13 as genomic regions with significantly more frequent amplifications in BM-LUAD compared to control cohort. We validated that MYC, YAP1 and MMP13 can drive brain metastases in a patient-derived xenograft mouse model, where incidence of brain metastases was higher in mice injected with tumor cells expressing the candidate drivers compared to tumor cells expressing LacZ. These results indicate that somatic alterations can drive lung adenocarcinomas to metastasize to the brain. These candidate drivers may serve as therapeutic targets in patients with brain metastatic lung adenocarcinomas. Citation Format: Naema Nayyar, David J. Shih, Ivanna Bihun, Ibiayi Dagogo-Jack, Corey M. Gill, Elisa Aquilanti, Mia Bertalan, Alexander Kaplan, Megan R. D'Andrea, Ugonma Chukwueke, Christopher Alvarez-Breckenridge, Matthew Lastrapes, Ben Kuter, Matthew R. Strickland, Juan Carlos Martinez-Gutierrez, Deepika Nagabhushan, Magali De Sauvage, Michael D. White, Brandyn A. Castro, Kaitlin Hoang, Sun Ha Paek, Sun Hye Park, Maria Martinez-Lage, Anna S. Berghoff, Parker Merrill, Elizabeth R. Gerstner, Tracy T. Batchelor, Matthew P. Frosch, Ryan P. Frazier, Darrell R. Borger, A John Iafrate, Sandro Santagata, Matthias Preusser, Daniel P. Cahill, Scott L. Carter, Priscilla K. Brastianos. Identifying genomic drivers of lung adenocarcinoma brain metastases [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4729.

The most common malignant primary brain tumor, glioblastoma multiforme (GBM) is a devastating disease with a grim prognosis. Patient survival is typically less than two years and fewer than 10% of patients survive more than five years. Magnetic resonance imaging (MRI) can have great utility in the diagnosis, grading, and management of patients with GBM as many of the physical manifestations of the pathologic processes in GBM can be visualized and quantified using MRI. Newer MRI techniques such as dynamic contrast enhanced and dynamic susceptibility contrast MRI provide functional information about the tumor hemodynamic status. Diffusion MRI can shed light on tumor cellularity and the disruption of white matter tracts in the proximity of tumors. MR spectroscopy can be used to study new tumor tissue markers such as IDH mutations. MRI is helping to noninvasively explore the link between the molecular basis of gliomas and the imaging characteristics of their physical processes. We, here, review several approaches to MR-based imaging and discuss the potential for these techniques to quantify the physical processes in glioblastoma, including tumor cellularity and vascularity, metabolite expression, and patterns of tumor growth and recurrence. We conclude with challenges and opportunities for further research in applying physical principles to better understand the biologic process in this deadly disease. See all articles in this Cancer Research section, “Physics in Cancer Research.” Cancer Res; 74(17); 4622–37. ©2014 AACR.

Introduction: Recent theoretical [1], pre-clinical [2] and human tumor data [3] suggest anti-hypertensives with an extracellular matrix-depleting effect improve vascular function by reducing the solid stress that can squeeze tumor vessels shut [4]. This work is contrasted by studies showing that certain matrix-depleting anti-hypertensives (angiotensin-II receptor blockers) are also associated with reduced peri-tumoral edema [5]. We here show that combined matrix-depleting and anti-angiogenic therapy does reduce vasogenic edema in newly diagnosed glioblastomas but not in recurrent disease and that the mechanisms of action are therefore not fully understood. Methods: We retrospectively assessed data from 40 patients with newly diagnosed glioblastomas (nGBM) and 30 patients with recurrent glioblastomas (rGBM) receiving cediranib, an oral pan-VEGFR inhibitor, with- (NCT00662506) and without (NCT00305656) chemoradiation, respectively. Conventional, perfusion and vessel caliber MRI were performed at baseline and repeated weekly (nGBM) or monthly (rGBM) [6, 7]. Vasogenic edema was measured as the relative volume of peri-tumoral hyper T2-Fluid Attenuated Inversion Recovery (FLAIR) signal on the conventional MRIs. For nGBM, after cediranib onset, 12/40 patients received angiotensin II receptor blockers (Valsartan), β1 receptor antagonists (Atenolol) or angiotensin-converting enzyme inhibitors (Lisinopril), while 8/40 patients received calcium antagonists (Norvasc, Amlodipine) [3]. Similarly, for rGBM, 15/30 patients received Atenolol and 7/30 patients Norvasc. Results: While angiotensin-system inhibitors (ASIs) significantly improved the perfused vessel fraction (% of tumor values >½ the value of healthy tissue; Wilcoxon P Conclusion: The potential anti-edema effect associated with ASI anti-hypertensives is an attractive feature for reduced administration of steroids in patients with glioblastoma. However, our data indicate that the matrix-depleting activity of some anti-hypertensives improves vascular function in both nGBMs and rGBMs [3], but only reduces vasogenic edema in the newly diagnosed setting [5]. Further studies to understand the mechanisms of benefit of ASIs in cancer are warranted. References: 1: PNAS 2013;110:18632-37 2: Nat Commun 2013; 4, 2516 3: Proc AACR Annual Meeting 2016; p3975 4: PNAS 2012; 109, 15101-8 5: J Neurol. 2016; 263, 524-30 6: PNAS 2013; 110, 19059-64 7: Nat Med 2013; 19, 1178-83 Citation Format: Kyrre E. Emblem, Elizabeth R. Gerstner, A Gregory Sorensen, Bruce R. Rosen, Patrick Y. Wen, Tracy T. Batchelor, Rakesh K. Jain. Adding angiotensin-system inhibitors to anti-angiogenic therapy reduces vasogenic edema in newly diagnosed glioblastomas but not in recurrent disease. [abstract]. In: Proceedings of the AACR Special Conference on Engineering and Physical Sciences in Oncology; 2016 Jun 25-28; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2017;77(2 Suppl):Abstract nr B12.

Introduction: Impaired tumor perfusion is associated with poor drug delivery, hypoxia and metastatic behavior that effectively make cancers difficult to treat [1]. A main driver of impaired perfusion in permeable and impermeable tumor vessels is solid stress caused by proliferating tumor cells and the extracellular matrix that squeeze vessels shut [2]. Here, we demonstrate improved vascular function in glioblastoma patients who receive hypertension treatments with an anti-cancer cell, matrix-depleting effect as part of anti-angiogenic therapy. Methods: We retrospectively assessed data from 40 patients with newly diagnosed glioblastomas (nGBM) and 30 with recurrent glioblastomas (rGBM) receiving cediranib, an oral pan-VEGFR inhibitor, with- (NCT00662506) and without (NCT00305656) chemoradiation, respectively. After cediranib onset, for nGBM, 12/40 patients received matrix-depleting angiotensin II receptor blockers (Valsartan), β1 receptor antagonists (Atenolol) or angiotensin-converting enzyme inhibitors (Lisinopril), while 8/40 patients received non-depleting calcium antagonists (Norvasc, Amlodipine) [3, 4]. For rGBM, 15/30 patients received Atenolol and 7/30 patients Norvasc. Perfusion and vessel caliber MRI were performed at baseline and repeated weekly (nGBM) or monthly (rGBM) [5, 6]. Tumor values were normalized to healthy tissue to account for patient-level systemic effects and variations in hypertension. Results: In the total tumor bed (enhancing + edematous regions), the matrix-depleting alternatives significantly improved the perfused vessel fraction (% of tumor values >½ the value of healthy tissue) from 81% to 93% in nGBM (Wilcoxon: P Conclusion: In line with theoretical [7] and pre-clinical [3] findings, we here present human data demonstrating that adding matrix-depleting anti-hypertensives, safe and inexpensive drugs with decades of use, improve vascular function in glioblastoma patients receiving anti-cancer therapy. Vascular MRI can help refine matrix-depleting drugs by directly assessing mechanisms of action in vivo. References: 1: Science 2005; 307, 58-62 2: PNAS 2012; 109, 15101-8 3: Nat Commun 2013; 4, 2516 4: Blood Press 2006; 15, 198-206 5: PNAS 2013; 110, 19059-64 6: Nat Med 2013; 19, 1178-83 7: PNAS 2013;110:18632-37 Citation Format: Kyrre E. Emblem, Elizabeth R. Gerstner, Gregory Sorensen, Bruce R. Rosen, Patrick Y. Wen, Tracy T. Batchelor, Rakesh K. Jain. Matrix-depleting anti-hypertensives decompress tumor blood vessels and improve perfusion in patients with glioblastomas receiving anti-angiogenic therapy. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3975.

Antiangiogenic therapy is associated with increased radiographic responses in glioblastomas (GBMs), but tumors invariably recur. Because tumor-associated macrophages (TAMs) have been shown to mediate escape from antiangiogenic therapy in preclinical models, we examined the role of TAMs in recurrent glioblastoma (rGBM) patients. We compared autopsy brain specimens from 20 rGBM patients who received antiangiogenic treatment and chemoradiation (AAT+) to 8 patients who received chemotherapy and/or radiotherapy without antiangiogenic therapy, or no treatment (AAT-). TAMs were morphologically and phenotypically analyzed using flow cytometry and immunohistochemistry (IHC) for CD68, CD14, CD163, and CD11b expression. Flow cytometry showed an increase in TAMs in the AAT+ patients. IHC analysis demonstrated an increase in CD68+ TAMs in the tumor bulk (p Citation Format: Christine Lu-Emerson, Matija Snuderl, Nathaniel D. Kirkpatrick, Jermaine Goveia, Jennie Taylor, Christian Davidson, Yuhui Huang, Lars Riedemann, S. Percy Ivy, G. Dan Duda, Marek Ancukiewicz3, Scott R. Plotkin, Andrew Chi, Elizabeth R. Gerstner, April F. Eichler, Jorg Dietrich, Anat O. Stemmer-Rachamimov, Tracy T. Batchelor, Rakesh K. Jain. Increase in tumor-associated macrophages (TAMs) after antiangiogenic therapy is associated with poor survival in recurrent glioblastoma (GBM) patients. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr LB-339. doi:10.1158/1538-7445.AM2013-LB-339