Multiparametric magnetic resonance imaging in the assessment of anti-egfrviii chimeric antigen receptor t cell therapy in patients with recurrent glioblastoma

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Multiparametric magnetic resonance imaging in the assessment of anti-egfrviii chimeric antigen receptor t cell therapy in patients with recurrent glioblastoma"


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ABSTRACT EGFRvIII targeted chimeric antigen receptor T (CAR-T) cell therapy has recently been reported for treating glioblastomas (GBMs); however, physiology-based MRI parameters have not


been evaluated in this setting. Ten patients underwent multiparametric MRI at baseline, 1, 2 and 3 months after CAR-T therapy. Logistic regression model derived progression probabilities


(PP) using imaging parameters were used to assess treatment response. Four lesions from “early surgery” group demonstrated high PP at baseline suggestive of progression, which was confirmed


histologically. Out of eight lesions from remaining six patients, three lesions with low PP at baseline remained stable. Two lesions with high PP at baseline were associated with large


decreases in PP reflecting treatment response, whereas other two lesions with high PP at baseline continued to demonstrate progression. One patient didn’t have baseline data but demonstrated


progression on follow-up. Our findings indicate that multiparametric MRI may be helpful in monitoring CAR-T related early therapeutic changes in GBM patients. INTRODUCTION Glioblastoma


(GBM) is the most common primary malignant brain tumor in adults with poor prognosis. Recurrence is almost inevitable and the median survival for these recurrent patients is only 6.6–9.6


months.1 Epidermal growth factor receptor variant III (EGFRvIII) is expressed in about one third of GBM patients, promotes oncogenesis and is associated with poor prognosis.2,3 A recent


study demonstrated successful synthesis, delivery, and acceptable safety profile of chimeric antigen receptor T (CAR-T) cell therapy targeting against EGFRvIII epitope in patients with


recurrent GBM.4 Since immunotherapy including CAR-T therapy, triggers patient’s immune system to fight cancer cells, a pronounced inflammatory response occurs within the tumour bed,5


complicating the appearance on conventional MRI for evaluation of therapeutic response. Multiparametric analysis using diffusion tensor imaging (DTI),6 dynamic susceptibility contrast (DSC)


perfusion imaging7 and proton MR spectroscopy8 have been reported to distinguish true progression (TP) from pseudo-progression (PsP) with high accuracy.6,9 This rationale formed the basis of


this study in which treatment response of CART-EGFRvIII immunotherapy in recurrent GBMs was evaluated using DTI, DSC and spectroscopic imaging. METHODS The study was approved by the


Institutional Review Board. Informed consent was obtained from all patients. Ten recurrent GBM patients (5M/5F, mean age, 60.56 ± 10.31 years) were included based on inclusion criteria


(Supplementary Material). Clinical/demographic information, EGFRvIII expression levels and overall survival (OS) were described in Table S1. Baseline images were acquired within one week


before CAR-T cell infusion. Tumour progression was determined based on a combination of clinical status and RANO criteria. Seven of 10 patients underwent resection after demonstrating


progression following CAR-T cell infusion. Patients were divided into three groups according to the time of repeat surgery after CAR-T cell infusion: (1) no surgery (_no surgery group_, _n_ 


= 3); (2) surgery within a month (_early surgery group_, _n_ = 4); (3) surgery over a month (_late surgery group_, _n_ = 3) (Table S1). Data acquisition/analysis of DTI, DSC and 3-D echo


planar spectroscopic imaging (3D-EPSI) sequences were performed as previously described.6,8,10 All contrast enhancing lesions (_n_ = 12) ≥ 1 cm3 were selected for quantitative analysis. A


semi-automatic segmentation approach was used to generate a mask from the enhancing region of the neoplasm (Supplementary Material). The enhancing and central non-enhancing regions were used


to compute tumour volume. Mean diffusivity (MD), fractional anisotropy (FA), linear anisotropy (CL), planar anisotropy (CP), spherical anisotropy (CS), relative cerebral blood volume (rCBV)


and choline/creatine (Cho/Cr) ratio from enhancing lesions were estimated at each time point. Percent changes for each parameter between baseline and subsequent scans (N) were calculated as


(N – baseline)/baseline × 100 for the non-surgery and late surgery groups. Baseline 3D-EPSI data were available from two lesions in one patient. Hence, percentage changes in Cho/Cr from


these two lesions were also evaluated. In our previous study,6 for patients who underwent surgery and chemoradiation therapy (CRT) and exhibited new enhancing lesions on follow-up imaging


within six months, a combination of FA, CL and rCBVmax was reported to be the best model in differentiating PsP from TP with high accuracy (AUC 0.91). This model was determined based on the


histological analysis of surgical samples. Therefore, these three parameters were used in this study to compute the progression probabilities (PP) of tumour progression of each lesion at


each time point using the following regression equation6: $$f({\mathrm{FA}},{\mathrm{CL}},{\mathrm{rCBV}}_{\mathrm{max}}) = \frac{1}{{1 + \exp ( - (\beta_0 + \beta_ 1{\mathrm{FA}} +


\beta_2{\mathrm{CL}} + \beta_3{\mathrm{rCBV}_{\mathrm{max}}}))}}$$ where _β_0 = −16.17, _β_1 = 194.01, _β_2 = −285.65, and _β_3 = 1.21. Lesions were considered TP (predominant viable tumour)


if the predictive PP was ≥ 50% and PsP (predominant treatment effects) if predictive PP was ≤ 50%. In order to evaluate CAR-T treatment efficacy, we included 10 recurrent GBM patients


without CAR-T therapy (Table S2) and calculated PP values. OS was measured from the date of diagnosis and CAR-T cell infusion to the date of death for deceased patients, or the date of last


clinical follow-up for surviving patients. RESULTS Three out of 10 patients died within 6 months after CAR-T cell infusion. Six patients survived > 6 months before succumbing to the


disease. One patient (209) was still alive at the time of the writing of this manuscript with a survival of 34.0 months (1033 days). Median OS from all 10 patients was 247 days (Table S1).


Serial anatomical images, parametric maps and histologic findings from patient 209 at baseline and follow-up periods are shown in Figure S1. Baseline imaging parameters and PP obtained using


the classification model for the three groups are presented in Table 1. Percentage changes in tumour volume and imaging parameters at follow-up periods in comparison to baseline are shown


in Fig. 1a. Six out of eight lesions demonstrated increased tumour volume at follow-up periods relative to baseline. The enhancing lesions from four patients in “early surgery” group


demonstrated high PP (72–99%) and were classified as progressive disease. These four patients underwent repeat surgery within a month following CAR-T cell infusion and were excluded from


longitudinal analysis. Histopathological findings confirmed the diagnosis of TP in these patients. For remaining six patients (total of eight lesions), three lesions (204, 205 and 209 L2)


with low PP at baseline remained stable at follow-up. Two lesions (202, 209 L1) initially with high PP at baseline were associated with large decreases in PP and were classified as PsP at


follow-up. The remaining two lesions (207 L1 and L2) with high PP at baseline continued to demonstrate aggressive imaging features at follow-up. No baseline data was available for patient


201. However, this patient showed features of TP at follow-up. Predicted PP values at baseline and follow-up periods are shown in Table S3. The plots of these predictive PPs are shown in


Fig. 1b. Predicted PPs obtained from our classification model were confirmed on histopathology for all patients in the early and late surgery groups. Predicted PPs for recurrent GBMs without


CAR-T therapy are shown in Table S4 and Fig. 1c. Eight patients showed increased PP at follow-up time points. DISCUSSION We used a predictive model from multiparametric MRI to assess the


behaviour of neoplastic lesions following anti-EGFR CAR-T cell immunotherapy. All patients with available histopathology were correctly predicted as TP or PsP, indicating utility of


multiparametric MRI in evaluating therapeutic response to CAR-T cell immunotherapy. Harnessing of immune response involves inflammatory sequelae that complicates conventional MRI appearance


and limits the use of RANO criteria. As immunotherapies enter clinical trials for treating GBM, there is an urgent need to reliably assess the efficacy of these treatment modalities in


detecting elusive disease and redefining response.5 Multiparametric MRI has been widely used to predict treatment response in GBM patients.6,7,8 When percent changes in individual imaging


parameters were assessed from enhancing lesions at different follow-up periods relative to baseline, no definite trends were observed, indicating that imaging parameters, in isolation, may


have a limited role in assessing heterogeneity of treatment response to EGFRvIII CAR-T cell therapy. However, when we used the PP derived from multiparametric MRI, we were able to


objectively characterise each lesion as either progression or response at each individual time point, suggesting that a multiparametric approach may allow more accurate characterisation of


treatment response in GBM patients treated with immune/targeted therapies. These results need to be validated in a larger patient cohort and correlated with clinical endpoints of progression


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Research Center, Providence Health & Services, Portland, Oregon for statistical analysis. This work was partly funded by a grant from Novartis (NCI K08 16639). AUTHOR INFORMATION AUTHORS


AND AFFILIATIONS * Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA Sumei Wang, Sanjeev Chawla, 


Gaurav Verma, Ronald L. Wolf, Harish Poptani & Suyash Mohan * Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA Donald M.


O’Rourke, Steven Brem & Eileen Maloney * Department of Pathology and Laboratory Medicine, Division of Neuropathology, Perelman School of Medicine at the University of Pennsylvania,


Philadelphia, PA, USA MacLean P. Nasrallah * Department of Pathology and Laboratory Medicine, Division of Precision and Computational Diagnostics, Perelman School of Medicine at the


University of Pennsylvania, Philadelphia, PA, USA Jennifer J. D. Morrissette * Center for Cellular Immunotherapies, University of Pennsylvania, Philadelphia, PA, USA Gabriela Plesa & 


Carl H. June * Department of Medicine, Division of Hematology-Oncology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA Arati Desai * Department of


Cellular and Molecular Physiology, University of Liverpool, Liverpool, UK Harish Poptani Authors * Sumei Wang View author publications You can also search for this author inPubMed Google


Scholar * Donald M. O’Rourke View author publications You can also search for this author inPubMed Google Scholar * Sanjeev Chawla View author publications You can also search for this


author inPubMed Google Scholar * Gaurav Verma View author publications You can also search for this author inPubMed Google Scholar * MacLean P. Nasrallah View author publications You can


also search for this author inPubMed Google Scholar * Jennifer J. D. Morrissette View author publications You can also search for this author inPubMed Google Scholar * Gabriela Plesa View


author publications You can also search for this author inPubMed Google Scholar * Carl H. June View author publications You can also search for this author inPubMed Google Scholar * Steven


Brem View author publications You can also search for this author inPubMed Google Scholar * Eileen Maloney View author publications You can also search for this author inPubMed Google


Scholar * Arati Desai View author publications You can also search for this author inPubMed Google Scholar * Ronald L. Wolf View author publications You can also search for this author


inPubMed Google Scholar * Harish Poptani View author publications You can also search for this author inPubMed Google Scholar * Suyash Mohan View author publications You can also search for


this author inPubMed Google Scholar CORRESPONDING AUTHOR Correspondence to Suyash Mohan. ETHICS DECLARATIONS COMPETING INTERESTS This work was partly funded by a grant from Novartis (NCI K08


16639). The authors certify that there are no known conflicts of interest associated with this publication. NOTE This work is published under the standard license to publish agreement.


After 12 months the work will become freely available and the license terms will switch to a Creative Commons Attribution 4.0 International (CC BY 4.0). ADDITIONAL INFORMATION A portion of


this work was presented at the 24th annual meeting of ISMRM, Singapore, 2016. ELECTRONIC SUPPLEMENTARY MATERIAL SUPPLEMENTAL MATERIAL SUPPLEMENTARY TABLE S1 SUPPLEMENTARY TABLE S2


SUPPLEMENTARY TABLE S3 SUPPLEMENTARY TABLE S4 SUPPLEMENTARY FIGURE S1 RIGHTS AND PERMISSIONS This article is distributed under the terms of the Creative Commons Attribution 4.0 International


License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original


author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Wang, S., O’Rourke,


D.M., Chawla, S. _et al._ Multiparametric magnetic resonance imaging in the assessment of anti-EGFRvIII chimeric antigen receptor T cell therapy in patients with recurrent glioblastoma. _Br


J Cancer_ 120, 54–56 (2019). https://doi.org/10.1038/s41416-018-0342-0 Download citation * Received: 30 April 2018 * Revised: 29 October 2018 * Accepted: 30 October 2018 * Published: 27


November 2018 * Issue Date: 08 January 2019 * DOI: https://doi.org/10.1038/s41416-018-0342-0 SHARE THIS ARTICLE Anyone you share the following link with will be able to read this content:


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