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Berro A, Assi A, Farhat M, Hatoum L, Saad JP, Mohanna R, Bechara AMA, Prince G, Hachem MCR, Zalaquett Z, Kourie HR. Unlocking Hope: Anti-VEGFR inhibitors and their potential in glioblastoma treatment. Crit Rev Oncol Hematol 2024; 198:104365. [PMID: 38677355 DOI: 10.1016/j.critrevonc.2024.104365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 04/19/2024] [Indexed: 04/29/2024] Open
Abstract
PURPOSE This systematic review summarizes evidence of VEGFR gene mutations and VEGF/VEGFR protein expression in glioblastoma multiforme (GBM) patients, alongside the efficacy and safety of anti-VEGFR tyrosine kinase inhibitors (TKIs) for GBM treatment. METHODS A comprehensive literature review was conducted using PubMed up to August 2023. Boolean operators and MeSH term "glioma," along with specific VEGFR-related keywords, were utilized following thorough examination of existing literature. RESULTS VEGFR correlates with glioma grade and GBM progression, presenting a viable therapeutic target. Regorafenib and axitinib show promise among studied TKIs. Other multi-targeted TKIs (MTKI) and combination therapies exhibit potential, albeit limited by blood-brain barrier penetration and toxicity. Combining treatments like radiotherapy and enhancing BBB penetration may benefit patients. Further research is warranted in patient quality of life and biomarker-guided selection. CONCLUSION While certain therapies hold promise for GBM, future research should prioritize personalized medicine and innovative strategies for improved treatment outcomes.
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Affiliation(s)
- Ali Berro
- Hematology-Oncology Department, Hôtel-Dieu de France University Hospital, Saint Joseph University of Beirut, Beirut, Lebanon
| | - Ahmad Assi
- Hematology-Oncology Department, Hôtel-Dieu de France University Hospital, Saint Joseph University of Beirut, Beirut, Lebanon
| | - Mohamad Farhat
- Hematology-Oncology Department, Hôtel-Dieu de France University Hospital, Saint Joseph University of Beirut, Beirut, Lebanon
| | - Lea Hatoum
- Hematology-Oncology Department, Hôtel-Dieu de France University Hospital, Saint Joseph University of Beirut, Beirut, Lebanon
| | - Jean-Pierre Saad
- Hematology-Oncology Department, Hôtel-Dieu de France University Hospital, Saint Joseph University of Beirut, Beirut, Lebanon
| | - Rami Mohanna
- Hematology-Oncology Department, Hôtel-Dieu de France University Hospital, Saint Joseph University of Beirut, Beirut, Lebanon
| | - Anna Maria Antoun Bechara
- Hematology-Oncology Department, Hôtel-Dieu de France University Hospital, Saint Joseph University of Beirut, Beirut, Lebanon
| | - Gilles Prince
- Hematology-Oncology Department, Hôtel-Dieu de France University Hospital, Saint Joseph University of Beirut, Beirut, Lebanon
| | - Maria Catherine Rita Hachem
- Hematology-Oncology Department, Hôtel-Dieu de France University Hospital, Saint Joseph University of Beirut, Beirut, Lebanon
| | - Ziad Zalaquett
- Hematology-Oncology Department, Hôtel-Dieu de France University Hospital, Saint Joseph University of Beirut, Beirut, Lebanon.
| | - Hampig-Raphael Kourie
- Hematology-Oncology Department, Hôtel-Dieu de France University Hospital, Saint Joseph University of Beirut, Beirut, Lebanon
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2
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Everson RG, Hugo W, Sun L, Antonios J, Lee A, Ding L, Bu M, Khattab S, Chavez C, Billingslea-Yoon E, Salazar A, Ellingson BM, Cloughesy TF, Liau LM, Prins RM. TLR agonists polarize interferon responses in conjunction with dendritic cell vaccination in malignant glioma: a randomized phase II Trial. Nat Commun 2024; 15:3882. [PMID: 38719809 PMCID: PMC11078958 DOI: 10.1038/s41467-024-48073-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 04/19/2024] [Indexed: 05/12/2024] Open
Abstract
In this randomized phase II clinical trial, we evaluated the effectiveness of adding the TLR agonists, poly-ICLC or resiquimod, to autologous tumor lysate-pulsed dendritic cell (ATL-DC) vaccination in patients with newly-diagnosed or recurrent WHO Grade III-IV malignant gliomas. The primary endpoints were to assess the most effective combination of vaccine and adjuvant in order to enhance the immune potency, along with safety. The combination of ATL-DC vaccination and TLR agonist was safe and found to enhance systemic immune responses, as indicated by increased interferon gene expression and changes in immune cell activation. Specifically, PD-1 expression increases on CD4+ T-cells, while CD38 and CD39 expression are reduced on CD8+ T cells, alongside an increase in monocytes. Poly-ICLC treatment amplifies the induction of interferon-induced genes in monocytes and T lymphocytes. Patients that exhibit higher interferon response gene expression demonstrate prolonged survival and delayed disease progression. These findings suggest that combining ATL-DC with poly-ICLC can induce a polarized interferon response in circulating monocytes and CD8+ T cells, which may represent an important blood biomarker for immunotherapy in this patient population.Trial Registration: ClinicalTrials.gov Identifier: NCT01204684.
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Affiliation(s)
- Richard G Everson
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Willy Hugo
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA
- Department of Medicine, Division of Dermatology, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA
- Parker Institute for Cancer Immunotherapy, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Lu Sun
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Joseph Antonios
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Alexander Lee
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Lizhong Ding
- Department of Medicine, Division of Dermatology, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Melissa Bu
- Department of Medicine, Division of Dermatology, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Sara Khattab
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Carolina Chavez
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Emma Billingslea-Yoon
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | | | - Benjamin M Ellingson
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Timothy F Cloughesy
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA
- Department of Neurology/Neuro-Oncology, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Linda M Liau
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA.
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA.
| | - Robert M Prins
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA.
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA.
- Parker Institute for Cancer Immunotherapy, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA.
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, CA, 90095, USA.
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3
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Bobholz SA, Lowman AK, Connelly JM, Duenweg SR, Winiarz A, Nath B, Kyereme F, Brehler M, Bukowy J, Coss D, Lupo JM, Phillips JJ, Ellingson BM, Krucoff MO, Mueller WM, Banerjee A, LaViolette PS. Noninvasive Autopsy-Validated Tumor Probability Maps Identify Glioma Invasion Beyond Contrast Enhancement. Neurosurgery 2024:00006123-990000000-01091. [PMID: 38501824 DOI: 10.1227/neu.0000000000002898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 01/09/2024] [Indexed: 03/20/2024] Open
Abstract
BACKGROUND AND OBJECTIVES This study identified a clinically significant subset of patients with glioma with tumor outside of contrast enhancement present at autopsy and subsequently developed a method for detecting nonenhancing tumor using radio-pathomic mapping. We tested the hypothesis that autopsy-based radio-pathomic tumor probability maps would be able to noninvasively identify areas of infiltrative tumor beyond traditional imaging signatures. METHODS A total of 159 tissue samples from 65 subjects were aligned to MRI acquired nearest to death for this retrospective study. Demographic and survival characteristics for patients with and without tumor beyond the contrast-enhancing margin were computed. An ensemble algorithm was used to predict pixelwise tumor presence from pathological annotations using segmented cellularity (Cell), extracellular fluid, and cytoplasm density as input (6 train/3 test subjects). A second level of ensemble algorithms was used to predict voxelwise Cell, extracellular fluid, and cytoplasm on the full data set (43 train/22 test subjects) using 5-by-5 voxel tiles from T1, T1 + C, fluid-attenuated inversion recovery, and apparent diffusion coefficient as input. The models were then combined to generate noninvasive whole brain maps of tumor probability. RESULTS Tumor outside of contrast was identified in 41.5% of patients, who showed worse survival outcomes (hazard ratio = 3.90, P < .001). Tumor probability maps reliably tracked nonenhancing tumor on a range of local and external unseen data, identifying tumor outside of contrast in 69% of presurgical cases that also showed reduced survival outcomes (hazard ratio = 1.67, P = .027). CONCLUSION This study developed a multistage model for mapping gliomas using autopsy tissue samples as ground truth, which was able to identify regions of tumor beyond traditional imaging signatures.
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Affiliation(s)
- Samuel A Bobholz
- Department of Radiology, Medical College of Wisconsin, Milwaukee , Wisconsin , USA
| | - Allison K Lowman
- Department of Radiology, Medical College of Wisconsin, Milwaukee , Wisconsin , USA
| | - Jennifer M Connelly
- Department of Neurology, Medical College of Wisconsin, Milwaukee , Wisconsin , USA
| | - Savannah R Duenweg
- Department of Biophysics, Medical College of Wisconsin, Milwaukee , Wisconsin , USA
| | - Aleksandra Winiarz
- Department of Biophysics, Medical College of Wisconsin, Milwaukee , Wisconsin , USA
| | - Biprojit Nath
- Department of Biophysics, Medical College of Wisconsin, Milwaukee , Wisconsin , USA
| | - Fitzgerald Kyereme
- Department of Radiology, Medical College of Wisconsin, Milwaukee , Wisconsin , USA
| | - Michael Brehler
- Department of Radiology, Medical College of Wisconsin, Milwaukee , Wisconsin , USA
| | - John Bukowy
- Department of Electrical Engineering and Computer Science, Milwaukee School of Engineering, Milwaukee , Wisconsin , USA
| | - Dylan Coss
- Department of Pathology, Medical College of Wisconsin, Milwaukee , Wisconsin , USA
| | - Janine M Lupo
- Department of Radiology and Biomedical Imaging, University of California, San Francisco , California , USA
- UCSF/UC Berkeley Graduate Program in Bioengineering, University of California, San Francisco and Berkeley , California , USA
| | - Joanna J Phillips
- Department of Neurological Surgery, University of California, San Francisco , California , USA
- Department of Pathology, University of California, San Francisco , California , USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles , California , USA
| | - Max O Krucoff
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee , Wisconsin , USA
| | - Wade M Mueller
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee , Wisconsin , USA
| | - Anjishnu Banerjee
- Department of Biostatistics, Medical College of Wisconsin, Milwaukee , Wisconsin , USA
| | - Peter S LaViolette
- Department of Radiology, Medical College of Wisconsin, Milwaukee , Wisconsin , USA
- Department of Biophysics, Medical College of Wisconsin, Milwaukee , Wisconsin , USA
- Department of Biomedical Engineering, Medical College of Wisconsin, Milwaukee , Wisconsin , USA
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4
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Patel KS, Tessema KK, Kawaguchi R, Dudley L, Alvarado AG, Muthukrishnan SD, Perryman T, Hagiwara A, Swarup V, Liau LM, Wang AC, Yong W, Geschwind DH, Nakano I, Goldman SA, Everson RG, Ellingson BM, Kornblum HI. Single-nucleus expression characterization of non-enhancing region of recurrent high-grade glioma. Neurooncol Adv 2024; 6:vdae005. [PMID: 38616896 PMCID: PMC11012612 DOI: 10.1093/noajnl/vdae005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/16/2024] Open
Abstract
Background Non-enhancing (NE) infiltrating tumor cells beyond the contrast-enhancing (CE) bulk of tumor are potential propagators of recurrence after gross total resection of high-grade glioma. Methods We leveraged single-nucleus RNA sequencing on 15 specimens from recurrent high-grade gliomas (n = 5) to compare prospectively identified biopsy specimens acquired from CE and NE regions. Additionally, 24 CE and 22 NE biopsies had immunohistochemical staining to validate RNA findings. Results Tumor cells in NE regions are enriched in neural progenitor cell-like cellular states, while CE regions are enriched in mesenchymal-like states. NE glioma cells have similar proportions of proliferative and putative glioma stem cells relative to CE regions, without significant differences in % Ki-67 staining. Tumor cells in NE regions exhibit upregulation of genes previously associated with lower grade gliomas. Our findings in recurrent GBM paralleled some of the findings in a re-analysis of a dataset from primary GBM. Cell-, gene-, and pathway-level analyses of the tumor microenvironment in the NE region reveal relative downregulation of tumor-mediated neovascularization and cell-mediated immune response, but increased glioma-to-nonpathological cell interactions. Conclusions This comprehensive analysis illustrates differing tumor and nontumor landscapes of CE and NE regions in high-grade gliomas, highlighting the NE region as an area harboring likely initiators of recurrence in a pro-tumor microenvironment and identifying possible targets for future design of NE-specific adjuvant therapy. These findings also support the aggressive approach to resection of tumor-bearing NE regions.
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Affiliation(s)
- Kunal S Patel
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Kaleab K Tessema
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Riki Kawaguchi
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Lindsey Dudley
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Alvaro G Alvarado
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Sree Deepthi Muthukrishnan
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Travis Perryman
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Akifumi Hagiwara
- UCLA Brain Tumor Imaging Laboratory (BTIL), Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Vivek Swarup
- Department of Neurobiology and Behavior, UCI School of Biological Sciences, Irvine, California, USA
| | - Linda M Liau
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Anthony C Wang
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - William Yong
- Department of Pathology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Daniel H Geschwind
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Ichiro Nakano
- Department of Neurosurgery, Hokuto Social Medical Corporation, Hokuto Hospital, Hokuto, Japan
| | - Steven A Goldman
- Center for Translational Neuromedicine, University of Rochester Medical Center, Rochester, New York, USA
- Faculty of Health and Medical Sciences, Center for Translational Neuromedicine, University of Copenhagen, Copenhagen, Denmark
| | - Richard G Everson
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
- Department of Radiation Oncology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Benjamin M Ellingson
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Harley I Kornblum
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
- Departments of Pediatrics, Psychiatry, and Molecular and Medical Pharmacology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
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5
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Ellingson BM, Hagiwara A, Morris CJ, Cho NS, Oshima S, Sanvito F, Oughourlian TC, Telesca D, Raymond C, Abrey LE, Garcia J, Aftab DT, Hessel C, Minei TR, Harats D, Nathanson DA, Wen PY, Cloughesy TF. Depth of Radiographic Response and Time to Tumor Regrowth Predicts Overall Survival Following Anti-VEGF Therapy in Recurrent Glioblastoma. Clin Cancer Res 2023; 29:4186-4195. [PMID: 37540556 PMCID: PMC10592195 DOI: 10.1158/1078-0432.ccr-23-1235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 06/04/2023] [Accepted: 08/01/2023] [Indexed: 08/05/2023]
Abstract
PURPOSE Antiangiogenic therapies are known to cause high radiographic response rates due to reduction in vascular permeability resulting in a lower degree of contrast extravasation. In this study, we investigate the prognostic ability for model-derived parameters describing enhancing tumor volumetric dynamics to predict survival in recurrent glioblastoma treated with antiangiogenic therapy. EXPERIMENTAL DESIGN N = 276 patients in two phase II trials were used as training data, including bevacizumab ± irinotecan (NCT00345163) and cabozantinib (NCT00704288), and N = 74 patients in the bevacizumab arm of a phase III trial (NCT02511405) were used for validation. Enhancing volumes were estimated using T1 subtraction maps, and a biexponential model was used to estimate regrowth (g) and regression (d) rates, time to tumor regrowth (TTG), and the depth of response (DpR). Response characteristics were compared to diffusion MR phenotypes previously shown to predict survival. RESULTS Optimized thresholds occurred at g = 0.07 months-1 (phase II: HR = 0.2579, P = 5 × 10-20; phase III: HR = 0.2197, P = 5 × 10-5); d = 0.11 months-1 (HR = 0.3365, P < 0.0001; HR = 0.3675, P = 0.0113); TTG = 3.8 months (HR = 0.2702, P = 6 × 10-17; HR = 0.2061, P = 2 × 10-5); and DpR = 11.3% (HR = 0.6326, P = 0.0028; HR = 0.4785, P = 0.0206). Multivariable Cox regression controlling for age and baseline tumor volume confirmed these factors as significant predictors of survival. Patients with a favorable pretreatment diffusion MRI phenotype had a significantly longer TTG and slower regrowth. CONCLUSIONS Recurrent glioblastoma patients with a large, durable radiographic response to antiangiogenic agents have significantly longer survival. This information is useful for interpreting activity of antiangiogenic agents in recurrent glioblastoma.
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Affiliation(s)
- Benjamin M. Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Neuroscience Interdepartmental PhD Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA, USA
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Akifumi Hagiwara
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Connor J. Morris
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA
- Medical Scientist Training Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Nicholas S. Cho
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA, USA
- Medical Scientist Training Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Sonoko Oshima
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Francesco Sanvito
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Talia C. Oughourlian
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Neuroscience Interdepartmental PhD Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Donatello Telesca
- Department of Biostatistics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | | | | | | | | | | | | | - David A. Nathanson
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Patrick Y. Wen
- Center for Neuro-Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
| | - Timothy F. Cloughesy
- UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
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6
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Everson RG, Hugo W, Sun L, Antonios J, Lee A, Ding L, Bu M, Khattab S, Chavez C, Billingslea-Yoon E, Salazar A, Ellingson BM, Cloughesy TF, Liau LM, Prins RM. Dendritic Cell Vaccination in Conjunction with a TLR Agonist Polarizes Interferon Immune Responses in Malignant Glioma Patients. RESEARCH SQUARE 2023:rs.3.rs-3287211. [PMID: 37790490 PMCID: PMC10543402 DOI: 10.21203/rs.3.rs-3287211/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Autologous tumor lysate-pulsed dendritic cell (ATL-DC) vaccination is a promising immunotherapy for patients with high grade gliomas, but responses have not been demonstrated in all patients. To determine the most effective combination of autologous tumor lysate-pulsed DC vaccination, with or without the adjuvant toll-like receptor (TLR) agonists poly-ICLC or resiquimod, we conducted a Phase 2 clinical trial in 23 patients with newly diagnosed or recurrent WHO Grade III-IV malignant gliomas. We then performed deep, high-dimensional immune profiling of these patients to better understand how TLR agonists may influence the systemic immune responses induced by ATL-DC vaccination. Bulk RNAseq data demonstrated highly significant upregulation of type 1 and type 2 interferon gene expression selectively in patients who received adjuvant a TLR agonist together with ATL-DC. CyTOF analysis of patient peripheral blood mononuclear cells (PBMCs) showed increased expression of PD-1 on CD4+ T-cells, decreases in CD38 and CD39 on CD8+ T cells and elevated proportion of monocytes after ATL-DC + TLR agonist administration. In addition, scRNA-seq demonstrated a higher expression fold change of IFN-induced genes with poly-ICLC treatment in both peripheral blood monocytes and T lymphocytes. Patients who had higher expression of interferon response genes lived significantly longer and had longer time to progression compared to those with lower expression. The results suggest that ATL-DC in conjunction with adjuvant poly-ICLC induces a polarized interferon response in circulating monocytes and specific activation of a CD8+ T cell population, which may represent an important blood biomarker for immunotherapy in this patient population. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT01204684.
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Affiliation(s)
- Richard G. Everson
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
- Richard Everson and Willy Hugo contributed equally to this work as first authors
| | - Willy Hugo
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
- Department of Medicine, Division of Dermatology, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
- Parker Institute for Cancer Immunotherapy, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
- Richard Everson and Willy Hugo contributed equally to this work as first authors
| | - Lu Sun
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
| | - Joseph Antonios
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
| | - Alexander Lee
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
- Department of Molecular and Medical Pharmacology , David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
| | - Lizhong Ding
- Department of Medicine, Division of Dermatology, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
| | - Melissa Bu
- Department of Medicine, Division of Dermatology, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
| | - Sarah Khattab
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
| | - Carolina Chavez
- Department of Molecular and Medical Pharmacology , David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
| | - Emma Billingslea-Yoon
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
| | | | - Benjamin M. Ellingson
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
| | - Timothy F. Cloughesy
- Department of Molecular and Medical Pharmacology , David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
- Department of Neurology/Neuro-Oncology, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
| | - Linda M. Liau
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
| | - Robert M. Prins
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
- Parker Institute for Cancer Immunotherapy, David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
- Department of Molecular and Medical Pharmacology , David Geffen School of Medicine at UCLA, University of California Los Angeles, Los Angeles, California, 90095, U.S.A
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7
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Quan G, Wang T, Ren JL, Xue X, Wang W, Wu Y, Li X, Yuan T. Prognostic and predictive impact of abnormal signal volume evolution early after chemoradiotherapy in glioblastoma. J Neurooncol 2023; 162:385-396. [PMID: 36991305 DOI: 10.1007/s11060-023-04299-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 03/14/2023] [Indexed: 03/31/2023]
Abstract
INTRODUCTION This study was designed to explore the feasibility of semiautomatic measurement of abnormal signal volume (ASV) in glioblastoma (GBM) patients, and the predictive value of ASV evolution for the survival prognosis after chemoradiotherapy (CRT). METHODS This retrospective trial included 110 consecutive patients with GBM. MRI metrics, including the orthogonal diameter (OD) of the abnormal signal lesions, the pre-radiation enhancement volume (PRRCE), the volume change rate of enhancement (rCE), and fluid attenuated inversion recovery (rFLAIR) before and after CRT were analyzed. Semi-automatic measurements of ASV were done through the Slicer software. RESULTS In logistic regression analysis, age (HR = 2.185, p = 0.012), PRRCE (HR = 0.373, p < 0.001), post CE volume (HR = 4.261, p = 0.001), rCE1m (HR = 0.519, p = 0.046) were the significant independent predictors of short overall survival (OS) (< 15.43 months). The areas under the receiver operating characteristic curve (AUCs) for predicting short OS with rFLAIR3m and rCE1m were 0.646 and 0.771, respectively. The AUCs of Model 1 (clinical), Model 2 (clinical + conventional MRI), Model 3 (volume parameters), Model 4 (volume parameters + conventional MRI), and Model 5 (clinical + conventional MRI + volume parameters) for predicting short OS were 0.690, 0.723, 0.877, 0.879, 0.898, respectively. CONCLUSION Semi-automatic measurement of ASV in GBM patients is feasible. The early evolution of ASV after CRT was beneficial in improving the survival evaluation after CRT. The efficacy of rCE1m was better than that of rFLAIR3m in this evaluation.
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Affiliation(s)
- Guanmin Quan
- Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, People's Republic of China
| | - Tianda Wang
- Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, People's Republic of China
| | - Jia-Liang Ren
- GE Healthcare China, Beijing, People's Republic of China
| | - Xiaoying Xue
- Department of Radiotherapy, The Second Hospital of Hebei Medical University, Shijiazhuang, People's Republic of China
| | - Wenyan Wang
- Department of Radiotherapy, The Second Hospital of Hebei Medical University, Shijiazhuang, People's Republic of China
| | - Yankai Wu
- Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, People's Republic of China
| | - Xiaotong Li
- Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, People's Republic of China
| | - Tao Yuan
- Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, People's Republic of China.
- Department of Medical Imaging, The Second Hospital of Hebei Medical University, 215 Hepingxi Road, Shijiazhuang, 050000, Hebei, People's Republic of China.
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8
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Bai JW, Qiu SQ, Zhang GJ. Molecular and functional imaging in cancer-targeted therapy: current applications and future directions. Signal Transduct Target Ther 2023; 8:89. [PMID: 36849435 PMCID: PMC9971190 DOI: 10.1038/s41392-023-01366-y] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Revised: 01/19/2023] [Accepted: 02/14/2023] [Indexed: 03/01/2023] Open
Abstract
Targeted anticancer drugs block cancer cell growth by interfering with specific signaling pathways vital to carcinogenesis and tumor growth rather than harming all rapidly dividing cells as in cytotoxic chemotherapy. The Response Evaluation Criteria in Solid Tumor (RECIST) system has been used to assess tumor response to therapy via changes in the size of target lesions as measured by calipers, conventional anatomically based imaging modalities such as computed tomography (CT), and magnetic resonance imaging (MRI), and other imaging methods. However, RECIST is sometimes inaccurate in assessing the efficacy of targeted therapy drugs because of the poor correlation between tumor size and treatment-induced tumor necrosis or shrinkage. This approach might also result in delayed identification of response when the therapy does confer a reduction in tumor size. Innovative molecular imaging techniques have rapidly gained importance in the dawning era of targeted therapy as they can visualize, characterize, and quantify biological processes at the cellular, subcellular, or even molecular level rather than at the anatomical level. This review summarizes different targeted cell signaling pathways, various molecular imaging techniques, and developed probes. Moreover, the application of molecular imaging for evaluating treatment response and related clinical outcome is also systematically outlined. In the future, more attention should be paid to promoting the clinical translation of molecular imaging in evaluating the sensitivity to targeted therapy with biocompatible probes. In particular, multimodal imaging technologies incorporating advanced artificial intelligence should be developed to comprehensively and accurately assess cancer-targeted therapy, in addition to RECIST-based methods.
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Affiliation(s)
- Jing-Wen Bai
- Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast Cancer, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China
- Xiamen Key Laboratory of Endocrine-Related Cancer Precision Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China
- Xiamen Research Center of Clinical Medicine in Breast and Thyroid Cancers, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China
- Department of Breast-Thyroid-Surgery and Cancer Center, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China
- Department of Medical Oncology, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China
- Cancer Research Center of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China
| | - Si-Qi Qiu
- Diagnosis and Treatment Center of Breast Diseases, Clinical Research Center, Shantou Central Hospital, 515041, Shantou, China
- Guangdong Provincial Key Laboratory for Breast Cancer Diagnosis and Treatment, Shantou University Medical College, 515041, Shantou, China
| | - Guo-Jun Zhang
- Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast Cancer, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China.
- Xiamen Key Laboratory of Endocrine-Related Cancer Precision Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China.
- Xiamen Research Center of Clinical Medicine in Breast and Thyroid Cancers, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China.
- Department of Breast-Thyroid-Surgery and Cancer Center, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China.
- Cancer Research Center of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China.
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9
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Maroto P, Porta C, Capdevila J, Apolo AB, Viteri S, Rodriguez-Antona C, Martin L, Castellano D. Cabozantinib for the treatment of solid tumors: a systematic review. Ther Adv Med Oncol 2022; 14:17588359221107112. [PMID: 35847482 PMCID: PMC9284205 DOI: 10.1177/17588359221107112] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 05/25/2022] [Indexed: 11/29/2022] Open
Abstract
Background: Cabozantinib is approved, in various settings, for the treatment of renal
cell carcinoma, medullary thyroid cancer, and hepatocellular carcinoma, and
it has been investigated for the treatment of other cancers. With the
available evidence and the real-world performance of cabozantinib compared
with clinical trial data, we performed a systematic review of cabozantinib
monotherapy as treatment for solid tumors in adults. Methods: This study was designed in accordance with Preferred Reporting Items for
Systematic Reviews and Meta-Analyses and registered with PROSPERO
(CRD42020144680). We searched for clinical and observational studies of
cabozantinib monotherapy for solid tumors using Embase, MEDLINE, and
Cochrane databases (October 2020), and screened relevant congress abstracts.
Eligible studies reported clinical or safety outcomes, or biomarker data.
Small studies (n < 25) and studies of cabozantinib
combination therapies were excluded. Quality was assessed using National
Institute for Health and Care Excellence methodology, and study
characteristics were described qualitatively. Results: Of 2888 citations, 114 were included (52 randomized studies, 29 observational
studies, 32 nonrandomized phase I or II studies or pilot trials, and 1
analysis of data from a randomized study and a nonrandomized study). Beyond
approved indications, other tumors studied were castration-resistant
prostate cancer, urothelial carcinoma, Ewing sarcoma, osteosarcoma, uveal
melanoma, non-small-cell lung cancer, Merkel cell carcinoma, glioblastoma,
pheochromocytomas and paragangliomas, cholangiocarcinoma, gastrointestinal
stromal tumor, colorectal cancer, salivary gland cancer, carcinoid and
pancreatic neuroendocrine tumors, and breast, endometrial and ovarian
cancers. The most common adverse events were hypertension, diarrhea, and
fatigue. Conclusion: The identified evidence demonstrates the positive efficacy/effectiveness of
cabozantinib monotherapy in various solid tumor types, with safety findings
being consistent with those observed with other VEGFR-targeting tyrosine
kinase inhibitors. When available, real-world findings were consistent with
the data reported from clinical trials. A limitation of this review is the
high proportion of abstracts; however, this allowed us to capture the most
up-to-date findings.
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Affiliation(s)
- Pablo Maroto
- Medical Oncology Services, Hospital de la Santa Creu i Sant Pau, Mas Casanovas, Barcelona, 08025, Spain
| | - Camillo Porta
- Interdisciplinary Department of Medicine, University of Bari "Aldo Moro," Bari, Italy
| | - Jaume Capdevila
- Department of Medical Oncology, Vall d'Hebron University Hospital, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain
| | - Andrea B Apolo
- Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Santiago Viteri
- UOMI Cancer Center, Clínica Mi Tres Torres, Barcelona, Spain
| | | | | | - Daniel Castellano
- Medical Oncology Department, University Hospital 12 de Octubre, Madrid, Spain
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10
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Li AY, Iv M. Conventional and Advanced Imaging Techniques in Post-treatment Glioma Imaging. FRONTIERS IN RADIOLOGY 2022; 2:883293. [PMID: 37492665 PMCID: PMC10365131 DOI: 10.3389/fradi.2022.883293] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 06/06/2022] [Indexed: 07/27/2023]
Abstract
Despite decades of advancement in the diagnosis and therapy of gliomas, the most malignant primary brain tumors, the overall survival rate is still dismal, and their post-treatment imaging appearance remains very challenging to interpret. Since the limitations of conventional magnetic resonance imaging (MRI) in the distinction between recurrence and treatment effect have been recognized, a variety of advanced MR and functional imaging techniques including diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), perfusion-weighted imaging (PWI), MR spectroscopy (MRS), as well as a variety of radiotracers for single photon emission computed tomography (SPECT) and positron emission tomography (PET) have been investigated for this indication along with voxel-based and more quantitative analytical methods in recent years. Machine learning and radiomics approaches in recent years have shown promise in distinguishing between recurrence and treatment effect as well as improving prognostication in a malignancy with a very short life expectancy. This review provides a comprehensive overview of the conventional and advanced imaging techniques with the potential to differentiate recurrence from treatment effect and includes updates in the state-of-the-art in advanced imaging with a brief overview of emerging experimental techniques. A series of representative cases are provided to illustrate the synthesis of conventional and advanced imaging with the clinical context which informs the radiologic evaluation of gliomas in the post-treatment setting.
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Affiliation(s)
- Anna Y. Li
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, United States
| | - Michael Iv
- Division of Neuroimaging and Neurointervention, Department of Radiology, Stanford University School of Medicine, Stanford, CA, United States
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11
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Johnson DR, Glenn CA, Javan R, Olson JJ. Congress of Neurological Surgeons systematic review and evidence-based guidelines update on the role of imaging in the management of progressive glioblastoma in adults. J Neurooncol 2022; 158:139-165. [PMID: 34694565 DOI: 10.1007/s11060-021-03853-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 09/21/2021] [Indexed: 12/27/2022]
Abstract
TARGET POPULATION These recommendations apply to adults with glioblastoma who have been previously treated with first-line radiation or chemoradiotherapy and who are suspected of experiencing tumor progression. QUESTION In patients with previously treated glioblastoma, is standard contrast-enhanced magnetic resonance imaging including diffusion weighted imaging useful for diagnosing tumor progression and differentiating progression from treatment-related changes? LEVEL II Magnetic resonance imaging with and without gadolinium enhancement including diffusion weighted imaging is recommended as the imaging surveillance method to detect the progression of previously diagnosed glioblastoma. QUESTION In patients with previously treated glioblastoma, does magnetic resonance spectroscopy add useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement? LEVEL II Magnetic resonance spectroscopy is recommended as a diagnostic method to differentiate true tumor progression from treatment-related imaging changes or pseudo-progression in patients with suspected progressive glioblastoma. QUESTION In patients with previously treated glioblastoma, does magnetic resonance perfusion add useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement? LEVEL III Magnetic resonance perfusion is suggested as a diagnostic method to differentiate true tumor progression from treatment-related imaging changes or pseudo-progression in patients with suspected progressive glioblastoma. QUESTION In patients with previously treated glioblastoma, does the addition of single-photon emission computed tomography (SPECT) provide additional useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement? LEVEL III Single-photon emission computed tomography imaging is suggested as a diagnostic method to differentiate true tumor progression from treatment-related imaging changes or pseudo-progression in patients with suspected progressive glioblastoma. QUESTION In patients with previously treated glioblastoma, does 18F-fluorodeoxyglucose positron emission tomography add useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement? LEVEL III The routine use of 18F-fluorodeoxyglucose positron emission tomography to identify progression of glioblastoma is not recommended. QUESTION In patients with previously treated glioblastoma, does positron emission tomography with amino acid agents add useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement? LEVEL III It is suggested that amino acid positron emission tomography be considered to assist in the differentiation of progressive glioblastoma from treatment related changes.
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Affiliation(s)
- Derek Richard Johnson
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
| | - Chad Allan Glenn
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Ramin Javan
- Department of Neuroradiology, George Washington University Hospital, Washington, DC, USA
| | - Jeffrey James Olson
- Department of Neurosurgery, Emory University School of Medicine, Atlanta, GA, USA
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12
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Bobholz SA, Lowman AK, Brehler M, Kyereme F, Duenweg SR, Sherman J, McGarry SD, Cochran EJ, Connelly J, Mueller WM, Agarwal M, Banerjee A, LaViolette PS. Radio-Pathomic Maps of Cell Density Identify Brain Tumor Invasion beyond Traditional MRI-Defined Margins. AJNR Am J Neuroradiol 2022; 43:682-688. [PMID: 35422419 PMCID: PMC9089258 DOI: 10.3174/ajnr.a7477] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 02/07/2022] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Currently, contrast-enhancing margins on T1WI are used to guide treatment of gliomas, yet tumor invasion beyond the contrast-enhancing region is a known confounding factor. Therefore, this study used postmortem tissue samples aligned with clinically acquired MRIs to quantify the relationship between intensity values and cellularity as well as to develop a radio-pathomic model to predict cellularity using MR imaging data. MATERIALS AND METHODS This single-institution study used 93 samples collected at postmortem examination from 44 patients with brain cancer. Tissue samples were processed, stained with H&E, and digitized for nuclei segmentation and cell density calculation. Pre- and postgadolinium contrast T1WI, T2 FLAIR, and ADC images were collected from each patient's final acquisition before death. In-house software was used to align tissue samples to the FLAIR image via manually defined control points. Mixed-effects models were used to assess the relationship between single-image intensity and cellularity for each image. An ensemble learner was trained to predict cellularity using 5 × 5 voxel tiles from each image, with a two-thirds to one-third train-test split for validation. RESULTS Single-image analyses found subtle associations between image intensity and cellularity, with a less pronounced relationship in patients with glioblastoma. The radio-pathomic model accurately predicted cellularity in the test set (root mean squared error = 1015 cells/mm2) and identified regions of hypercellularity beyond the contrast-enhancing region. CONCLUSIONS A radio-pathomic model for cellularity trained with tissue samples acquired at postmortem examination is able to identify regions of hypercellular tumor beyond traditional imaging signatures.
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Affiliation(s)
- S A Bobholz
- From the Departments of Biophysics (S.A.B., S.R.D., J.S., S.D.M.)
| | | | - M Brehler
- Radiology (A.L., M.B., M.A., P.S.L.)
| | | | - S R Duenweg
- From the Departments of Biophysics (S.A.B., S.R.D., J.S., S.D.M.)
| | - J Sherman
- From the Departments of Biophysics (S.A.B., S.R.D., J.S., S.D.M.)
| | - S D McGarry
- From the Departments of Biophysics (S.A.B., S.R.D., J.S., S.D.M.)
| | | | | | | | - M Agarwal
- Radiology (A.L., M.B., M.A., P.S.L.)
| | | | - P S LaViolette
- Radiology (A.L., M.B., M.A., P.S.L.)
- Biomedical Engineering (P.S.L.), Medical College of Wisconsin, Milwaukee, Wisconsin
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13
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Roberts JW, Powlovich L, Sheybani N, LeBlang S. Focused ultrasound for the treatment of glioblastoma. J Neurooncol 2022; 157:237-247. [PMID: 35267132 PMCID: PMC9021052 DOI: 10.1007/s11060-022-03974-0] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 02/21/2022] [Indexed: 12/05/2022]
Abstract
Purpose Six years ago, in 2015, the Focused Ultrasound Foundation sponsored a workshop to discuss, and subsequently transition the landscape, of focused ultrasound as a new therapy for treating glioblastoma. Methods This year, in 2021, a second workshop was held to review progress made in the field. Discussion topics included blood–brain barrier opening, thermal and nonthermal tumor ablation, immunotherapy, sonodynamic therapy, and desired focused ultrasound device improvements. Results The outcome of the 2021 workshop was the creation of a new roadmap to address knowledge gaps and reduce the time it takes for focused ultrasound to become part of the treatment armamentarium and reach clinical adoption for the treatment of patients with glioblastoma. Priority projects identified in the roadmap include determining a well-defined algorithm to confirm and quantify drug delivery following blood–brain barrier opening, identifying a focused ultrasound-specific microbubble, exploring the role of focused ultrasound for liquid biopsy in glioblastoma, and making device modifications that better support clinical needs. Conclusion This article reviews the key preclinical and clinical updates from the workshop, outlines next steps to research, and provides relevant references for focused ultrasound in the treatment of glioblastoma.
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Affiliation(s)
- Jill W Roberts
- Focused Ultrasound Foundation, 1230 Cedars Court, Suite 206, Charlottesville, VA, 22903, USA.
| | - Lauren Powlovich
- Focused Ultrasound Foundation, 1230 Cedars Court, Suite 206, Charlottesville, VA, 22903, USA
| | - Natasha Sheybani
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, 22908, USA
| | - Suzanne LeBlang
- Focused Ultrasound Foundation, 1230 Cedars Court, Suite 206, Charlottesville, VA, 22903, USA
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14
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Ellingson BM, Patel K, Wang C, Raymond C, Brenner A, de Groot JF, Butowski NA, Zach L, Campian JL, Schlossman J, Rizvi S, Cohen YC, Lowenton-Spier N, Minei TR, Shmueli SF, Wen PY, Cloughesy TF. Validation of diffusion MRI as a biomarker for efficacy using randomized phase III trial of bevacizumab with or without VB-111 in recurrent glioblastoma. Neurooncol Adv 2021; 3:vdab082. [PMID: 34377989 PMCID: PMC8350152 DOI: 10.1093/noajnl/vdab082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Background Evidence from single and multicenter phase II trials have suggested diffusion MRI is a predictive imaging biomarker for survival benefit in recurrent glioblastoma (rGBM) treated with anti-VEGF therapy. The current study confirms these findings in a large, randomized phase III clinical trial. Methods Patients with rGBM were enrolled in a phase III randomized (1:1), controlled trial (NCT02511405) to compare the efficacy and safety of bevacizumab (BV) versus BV in combination with ofranergene obadenovec (BV+VB-111), an anti-cancer viral therapy. In 170 patients with diffusion MRI available, pretreatment enhancing tumor volume and ADC histogram analysis were used to phenotype patients as having high (>1.24 µm2/ms) or low (<1.24 µm2/ms) ADCL, the mean value of the lower peak of the ADC histogram, within the contrast enhancing tumor. Results Baseline tumor volume (P = .3460) and ADCL (P = .2143) did not differ between treatment arms. Univariate analysis showed patients with high ADCL had a significant survival advantage in all patients (P = .0006), as well as BV (P = .0159) and BV+VB-111 individually (P = .0262). Multivariable Cox regression accounting for treatment arm, age, baseline tumor volume, and ADCL identified continuous measures of tumor volume (P < .0001; HR = 1.0212) and ADCL phenotypes (P = .0012; HR = 0.5574) as independent predictors of OS. Conclusion Baseline diffusion MRI and tumor volume are independent imaging biomarkers of OS in rGBM treated with BV or BV+VB-111.
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Affiliation(s)
- Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,UCLA Neuro Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Kunal Patel
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Chencai Wang
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Andrew Brenner
- University of Texas Health San Antonio Cancer Center, San Antonio, Texas, USA
| | - John F de Groot
- Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Nicholas A Butowski
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Leor Zach
- Oncology Institute, Chaim Sheba Medical Center, Tel HaShomer, Israel
| | - Jian L Campian
- Division of Medical Oncology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Jacob Schlossman
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Shan Rizvi
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | | | | | | | | | - Patrick Y Wen
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Timothy F Cloughesy
- UCLA Neuro Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
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15
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Cloughesy TF, Brenner A, de Groot JF, Butowski NA, Zach L, Campian JL, Ellingson BM, Freedman LS, Cohen YC, Lowenton-Spier N, Rachmilewitz Minei T, Fain Shmueli S, Wen PY. A randomized controlled phase III study of VB-111 combined with bevacizumab vs bevacizumab monotherapy in patients with recurrent glioblastoma (GLOBE). Neuro Oncol 2021; 22:705-717. [PMID: 31844890 PMCID: PMC7229248 DOI: 10.1093/neuonc/noz232] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Background Ofranergene obadenovec (VB-111) is an anticancer viral therapy that demonstrated in a phase II study a survival benefit for patients with recurrent glioblastoma (rGBM) who were primed with VB-111 monotherapy that was continued after progression with concomitant bevacizumab. Methods This pivotal phase III randomized, controlled trial compared the efficacy and safety of upfront combination of VB-111 and bevacizumab versus bevacizumab monotherapy. Patients were randomized 1:1 to receive VB-111 1013 viral particles every 8 weeks in combination with bevacizumab 10 mg/kg every 2 weeks (combination arm) or bevacizumab monotherapy (control arm). The primary endpoint was overall survival (OS), and secondary endpoints were objective response rate (ORR) by Response Assessment in Neuro-Oncology (RANO) criteria and progression-free survival (PFS). Results Enrolled were 256 patients at 57 sites. Median exposure to VB-111 was 4 months. The study did not meet its primary or secondary goals. Median OS was 6.8 versus 7.9 months in the combination versus control arm (hazard ratio, 1.20; 95% CI: 0.91–1.59; P = 0.19) and ORR was 27.3% versus 21.9% (P = 0.26). A higher rate of grades 3–5 adverse events was reported in the combination arm (67% vs 40%), mainly attributed to a higher rate of CNS and flu-like/fever events. Trends for improved survival with combination treatment were seen in the subgroup of patients with smaller tumors and in patients who had a posttreatment febrile reaction. Conclusions In this study, upfront concomitant administration of VB-111 and bevacizumab failed to improve outcomes in rGBM. Change of treatment regimen, with the lack of VB-111 monotherapy priming, may explain the differences from the favorable phase II results. Clinical trials registration NCT02511405
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Affiliation(s)
- Timothy F Cloughesy
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Andrew Brenner
- University of Texas Health San Antonio Cancer Center, San Antonio, Texas, USA
| | - John F de Groot
- Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Nicholas A Butowski
- Department of Neurological Surgery, University of California San Francisco, San Francisco, California, USA
| | - Leor Zach
- Oncology Institute, Chaim Sheba Medical Center, Tel HaShomer, Israel
| | - Jian L Campian
- Division of Medical Oncology, Washington University School of Medicine, St Louis, Missouri, USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Laurence S Freedman
- Biostatistics and Biomathematics Unit, Gertner Institute for Epidemiology and Health Policy Research, Chaim Sheba Medical Center, Tel HaShomer, Israel
| | | | | | | | | | | | - Patrick Y Wen
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
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16
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Discriminating pseudoprogression and true progression in diffuse infiltrating glioma using multi-parametric MRI data through deep learning. Sci Rep 2020; 10:20331. [PMID: 33230285 PMCID: PMC7683728 DOI: 10.1038/s41598-020-77389-0] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Accepted: 10/30/2020] [Indexed: 12/23/2022] Open
Abstract
Differentiating pseudoprogression from true tumor progression has become a significant challenge in follow-up of diffuse infiltrating gliomas, particularly high grade, which leads to a potential treatment delay for patients with early glioma recurrence. In this study, we proposed to use a multiparametric MRI data as a sequence input for the convolutional neural network with the recurrent neural network based deep learning structure to discriminate between pseudoprogression and true tumor progression. In this study, 43 biopsy-proven patient data identified as diffuse infiltrating glioma patients whose disease progressed/recurred were used. The dataset consists of five original MRI sequences; pre-contrast T1-weighted, post-contrast T1-weighted, T2-weighted, FLAIR, and ADC images as well as two engineered sequences; T1post-T1pre and T2-FLAIR. Next, we used three CNN-LSTM models with a different set of sequences as input sequences to pass through CNN-LSTM layers. We performed threefold cross-validation in the training dataset and generated the boxplot, accuracy, and ROC curve, AUC from each trained model with the test dataset to evaluate models. The mean accuracy for VGG16 models ranged from 0.44 to 0.60 and the mean AUC ranged from 0.47 to 0.59. For CNN-LSTM model, the mean accuracy ranged from 0.62 to 0.75 and the mean AUC ranged from 0.64 to 0.81. The performance of the proposed CNN-LSTM with multiparametric sequence data was found to outperform the popular convolutional CNN with a single MRI sequence. In conclusion, incorporating all available MRI sequences into a sequence input for a CNN-LSTM model improved diagnostic performance for discriminating between pseudoprogression and true tumor progression.
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17
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Shankar A, Bomanji J, Hyare H. Hybrid PET-MRI Imaging in Paediatric and TYA Brain Tumours: Clinical Applications and Challenges. J Pers Med 2020; 10:jpm10040218. [PMID: 33182433 PMCID: PMC7711629 DOI: 10.3390/jpm10040218] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2020] [Revised: 10/29/2020] [Accepted: 11/03/2020] [Indexed: 12/12/2022] Open
Abstract
(1) Background: Standard magnetic resonance imaging (MRI) remains the gold standard for brain tumour imaging in paediatric and teenage and young adult (TYA) patients. Combining positron emission tomography (PET) with MRI offers an opportunity to improve diagnostic accuracy. (2) Method: Our single-centre experience of 18F-fluorocholine (FCho) and 18fluoro-L-phenylalanine (FDOPA) PET–MRI in paediatric/TYA neuro-oncology patients is presented. (3) Results: Hybrid PET–MRI shows promise in the evaluation of gliomas and germ cell tumours in (i) assessing early treatment response and (ii) discriminating tumour from treatment-related changes. (4) Conclusions: Combined PET–MRI shows promise for improved diagnostic and therapeutic assessment in paediatric and TYA brain tumours.
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Affiliation(s)
- Ananth Shankar
- Children and Young People’s Cancer Services, University College London hospitals NHS Foundation Trust, London NW1 2PG, UK
- Correspondence: ; Tel.: +44-20-3447-9950
| | - Jamshed Bomanji
- Department of Nuclear Medicine, University College London hospitals NHS Foundation Trust, London NW1 2PG, UK;
| | - Harpreet Hyare
- Department of Radiology, University College London Hospitals NHS Foundation Trust, London NW1 2PG, UK;
- Department of Brain Repair and Rehabilitation, Institute of Neurology, University College London, London WC1N 3BG, UK
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18
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Decorin expression is associated with predictive diffusion MR phenotypes of anti-VEGF efficacy in glioblastoma. Sci Rep 2020; 10:14819. [PMID: 32908231 PMCID: PMC7481206 DOI: 10.1038/s41598-020-71799-w] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 08/04/2020] [Indexed: 12/13/2022] Open
Abstract
Previous data suggest that apparent diffusion coefficient (ADC) imaging phenotypes predict survival response to anti-VEGF monotherapy in glioblastoma. However, the mechanism by which imaging may predict clinical response is unknown. We hypothesize that decorin (DCN), a proteoglycan implicated in the modulation of the extracellular microenvironment and sequestration of pro-angiogenic signaling, may connect ADC phenotypes to survival benefit to anti-VEGF therapy. Patients undergoing resection for glioblastoma as well as patients included in The Cancer Genome Atlas (TCGA) and IVY Glioblastoma Atlas Project (IVY GAP) databases had pre-operative imaging analyzed to calculate pre-operative ADCL values, the average ADC in the lower distribution using a double Gaussian mixed model. ADCL values were correlated to available RNA expression from these databases as well as from RNA sequencing from patient derived mouse orthotopic xenograft samples. Targeted biopsies were selected based on ADC values and prospectively collected during resection. Surgical specimens were used to evaluate for DCN RNA and protein expression by ADC value. The IVY Glioblastoma Atlas Project Database was used to evaluate DCN localization and relationship with VEGF pathway via in situ hybridization maps and RNA sequencing data. In a cohort of 35 patients with pre-operative ADC imaging and surgical specimens, DCN RNA expression levels were significantly larger in high ADCL tumors (41.6 vs. 1.5; P = 0.0081). In a cohort of 17 patients with prospectively targeted biopsies there was a positive linear correlation between ADCL levels and DCN protein expression between tumors (Pearson R2 = 0.3977; P = 0.0066) and when evaluating different targets within the same tumor (Pearson R2 = 0.3068; P = 0.0139). In situ hybridization data localized DCN expression to areas of microvascular proliferation and immunohistochemical studies localized DCN protein expression to the tunica adventitia of blood vessels within the tumor. DCN expression positively correlated with VEGFR1 & 2 expression and localized to similar areas of tumor. Increased ADCL on diffusion MR imaging is associated with high DCN expression as well as increased survival with anti-VEGF therapy in glioblastoma. DCN may play an important role linking the imaging features on diffusion MR and anti-VEGF treatment efficacy. DCN may serve as a target for further investigation and modulation of anti-angiogenic therapy in GBM.
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19
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Ellingson BM, Yao J, Raymond C, Nathanson DA, Chakhoyan A, Simpson J, Garner JS, Olivero AG, Mueller LU, Rodon J, Gerstner E, Cloughesy TF, Wen PY. Multiparametric MR-PET Imaging Predicts Pharmacokinetics and Clinical Response to GDC-0084 in Patients with Recurrent High-Grade Glioma. Clin Cancer Res 2020; 26:3135-3144. [PMID: 32269051 DOI: 10.1158/1078-0432.ccr-19-3817] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2019] [Revised: 02/14/2020] [Accepted: 04/03/2020] [Indexed: 11/16/2022]
Abstract
PURPOSE GDC-0084 is an oral, brain-penetrant small-molecule inhibitor of PI3K and mTOR. Because these two targets alter tumor vascularity and metabolism, respectively, we hypothesized multiparametric MR-PET could be used to quantify the response, estimate pharmacokinetic (PK) parameters, and predict progression-free survival (PFS) in patients with recurrent malignant gliomas. PATIENTS AND METHODS Multiparametric advanced MR-PET imaging was performed to evaluate physiologic response in a first-in-man, multicenter, phase I, dose-escalation study of GDC-0084 (NCT01547546) in 47 patients with recurrent malignant glioma. RESULTS Measured maximum concentration (C max) was associated with a decrease in enhancing tumor volume (P = 0.0287) and an increase in fractional anisotropy (FA; P = 0.0418). Posttreatment tumor volume, 18F-FDG uptake, Ktrans, and relative cerebral blood volume (rCBV) were all correlated with C max. A linear combination of change in 18F-FDG PET uptake, apparent diffusion coefficient (ADC), FA, Ktrans, vp, and rCBV was able to estimate both C max (R2 = 0.4113; P < 0.0001) and drug exposure (AUC; R2 = 0.3481; P < 0.0001). Using this composite multiparametric MR-PET imaging response biomarker to predict PK, patients with an estimated C max > 0.1 μmol/L and AUC > 1.25 μmol/L*hour demonstrated significantly longer PFS compared with patients with a lower estimated concentration and exposure (P = 0.0039 and P = 0.0296, respectively). CONCLUSIONS Results from this study suggest composite biomarkers created from multiparametric MR-PET imaging targeting metabolic and/or physiologic processes specific to the drug mechanism of action may be useful for subsequent evaluation of treatment efficacy for larger phase II-III studies.
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Affiliation(s)
- Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California. .,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California.,Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, California.,Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California.,Brain Research Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California.,UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, California
| | - Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California.,Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, California
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - David A Nathanson
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Ararat Chakhoyan
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Jeremy Simpson
- Kazia Therapeutics Limited, Sydney, New South Wales, Australia
| | - James S Garner
- Kazia Therapeutics Limited, Sydney, New South Wales, Australia
| | | | | | - Jordi Rodon
- Vall d'Hebron Institute of Oncology, Barcelona, Spain
| | - Elizabeth Gerstner
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, California.,Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Patrick Y Wen
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
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20
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Brenner AJ, Peters KB, Vredenburgh J, Bokstein F, Blumenthal DT, Yust-Katz S, Peretz I, Oberman B, Freedman LS, Ellingson BM, Cloughesy TF, Sher N, Cohen YC, Lowenton-Spier N, Rachmilewitz Minei T, Yakov N, Mendel I, Breitbart E, Wen PY. Safety and efficacy of VB-111, an anticancer gene therapy, in patients with recurrent glioblastoma: results of a phase I/II study. Neuro Oncol 2020; 22:694-704. [PMID: 31844886 PMCID: PMC7229257 DOI: 10.1093/neuonc/noz231] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND VB-111 is a non-replicating adenovirus carrying a Fas-chimera transgene, leading to targeted apoptosis of tumor vascular endothelium and induction of a tumor-specific immune response. This phase I/II study evaluated the safety, tolerability, and efficacy of VB-111 with and without bevacizumab in recurrent glioblastoma (rGBM). METHODS Patients with rGBM (n = 72) received VB-111 in 4 treatment groups: subtherapeutic (VB-111 dose escalation), limited exposure (LE; VB-111 monotherapy until progression), primed combination (VB-111 monotherapy continued upon progression with combination of bevacizumab), and unprimed combination (upfront combination of VB-111 and bevacizumab). The primary endpoint was median overall survival (OS). Secondary endpoints were safety, overall response rate, and progression-free survival (PFS). RESULTS VB-111 was well tolerated. The most common adverse event was transient mild-moderate fever. Median OS time was significantly longer in the primed combination group compared with both LE (414 vs 223 days; hazard ratio [HR], 0.48; P = 0.043) and unprimed combination (414 vs 141.5 days; HR, 0.24; P = 0.0056). Patients in the combination phase of the primed combination group had a median PFS time of 90 days compared with 60 in the LE group (HR, 0.36; P = 0.032), and 63 in the unprimed combination group (P = 0.72). Radiographic responders to VB-111 exhibited characteristic, expansive areas of necrosis in the areas of initial enhancing disease. CONCLUSIONS Patients with rGBM who were primed with VB-111 monotherapy that continued after progression with the addition of bevacizumab showed significant survival and PFS advantage, as well as specific imaging characteristics related to VB-111 mechanism of action. These results warrant further assessment in a randomized controlled study.
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Affiliation(s)
- Andrew J Brenner
- University of Texas Health San Antonio Mays Cancer Center, San Antonio, Texas, USA
| | - Katherine B Peters
- Preston Robert Tisch Brain Tumor Center, Duke University Medical Center, Durham, North Carolina, USA
| | - James Vredenburgh
- Saint Francis Hospital and Medical Center, Hartford, Connecticut, USA
| | - Felix Bokstein
- Tel Aviv Sourasky Medical Center and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Deborah T Blumenthal
- Tel Aviv Sourasky Medical Center and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Shlomit Yust-Katz
- Neuro-Oncology Unit, Davidoff Cancer Center at Rabin Medical Center, Petach Tikvah, Israel and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Idit Peretz
- Neuro-Oncology Unit, Davidoff Cancer Center at Rabin Medical Center, Petach Tikvah, Israel and Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Bernice Oberman
- Biostatistics and Biomathematics Unit, Gertner Institute for Epidemiology and Health Policy Research, Chaim Sheba Medical Center, Tel Hashomer, Israel
| | - Laurence S Freedman
- Biostatistics and Biomathematics Unit, Gertner Institute for Epidemiology and Health Policy Research, Chaim Sheba Medical Center, Tel Hashomer, Israel
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Timothy F Cloughesy
- Department of Neurology, Ronald Reagan UCLA Medical Center, University of California Los Angeles, Los Angeles, California, USA
| | | | | | | | | | | | | | | | - Patrick Y Wen
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
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21
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Radiomics and MGMT promoter methylation for prognostication of newly diagnosed glioblastoma. Sci Rep 2019; 9:14435. [PMID: 31594994 PMCID: PMC6783410 DOI: 10.1038/s41598-019-50849-y] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2019] [Accepted: 09/20/2019] [Indexed: 11/16/2022] Open
Abstract
We attempted to establish a magnetic resonance imaging (MRI)-based radiomic model for stratifying prognostic subgroups of newly diagnosed glioblastoma (GBM) patients and predicting O (6)-methylguanine-DNA methyltransferase promotor methylation (pMGMT-met) status of the tumor. Preoperative MRI scans from 201 newly diagnosed GBM patients were included in this study. A total of 489 texture features including the first-order feature, second-order features from 162 datasets, and location data from 182 datasets were collected. Supervised principal component analysis was used for prognostication and predictive modeling for pMGMT-met status was performed based on least absolute shrinkage and selection operator regression. 22 radiomic features that were correlated with prognosis were used to successfully stratify patients into high-risk and low-risk groups (p = 0.004, Log-rank test). The radiomic high- and low-risk stratification and pMGMT status were independent prognostic factors. As a matter of fact, predictive accuracy of the pMGMT methylation status was 67% when modeled by two significant radiomic features. A significant survival difference was observed among the combined high-risk group, combined intermediate-risk group (this group consists of radiomic low risk and pMGMT-unmet or radiomic high risk and pMGMT-met), and combined low-risk group (p = 0.0003, Log-rank test). Radiomics can be used to build a prognostic score for stratifying high- and low-risk GBM, which was an independent prognostic factor from pMGMT methylation status. On the other hand, predictive accuracy of the pMGMT methylation status by radiomic analysis was insufficient for practical use.
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22
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Cloughesy TF, Mochizuki AY, Orpilla JR, Hugo W, Lee AH, Davidson TB, Wang AC, Ellingson BM, Rytlewski JA, Sanders CM, Kawaguchi ES, Du L, Li G, Yong WH, Gaffey SC, Cohen AL, Mellinghoff IK, Lee EQ, Reardon DA, O'Brien BJ, Butowski NA, Nghiemphu PL, Clarke JL, Arrillaga-Romany IC, Colman H, Kaley TJ, de Groot JF, Liau LM, Wen PY, Prins RM. Neoadjuvant anti-PD-1 immunotherapy promotes a survival benefit with intratumoral and systemic immune responses in recurrent glioblastoma. Nat Med 2019; 25:477-486. [PMID: 30742122 PMCID: PMC6408961 DOI: 10.1038/s41591-018-0337-7] [Citation(s) in RCA: 840] [Impact Index Per Article: 168.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Accepted: 12/17/2018] [Indexed: 12/18/2022]
Abstract
Glioblastoma is the most common primary malignant brain tumor in adults and is associated with poor survival. The Ivy Foundation Early Phase Clinical Trials Consortium conducted a randomized, multi-institution clinical trial to evaluate immune responses and survival following neoadjuvant and/or adjuvant therapy with pembrolizumab in 35 patients with recurrent, surgically resectable glioblastoma. Patients who were randomized to receive neoadjuvant pembrolizumab, with continued adjuvant therapy following surgery, had significantly extended overall survival compared to patients that were randomized to receive adjuvant, post-surgical programmed cell death protein 1 (PD-1) blockade alone. Neoadjuvant PD-1 blockade was associated with upregulation of T cell- and interferon-γ-related gene expression, but downregulation of cell-cycle-related gene expression within the tumor, which was not seen in patients that received adjuvant therapy alone. Focal induction of programmed death-ligand 1 in the tumor microenvironment, enhanced clonal expansion of T cells, decreased PD-1 expression on peripheral blood T cells and a decreasing monocytic population was observed more frequently in the neoadjuvant group than in patients treated only in the adjuvant setting. These findings suggest that the neoadjuvant administration of PD-1 blockade enhances both the local and systemic antitumor immune response and may represent a more efficacious approach to the treatment of this uniformly lethal brain tumor.
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Affiliation(s)
- Timothy F Cloughesy
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Medical and Molecular Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, USA.
| | - Aaron Y Mochizuki
- Division of Hematology/Oncology, Department of Pediatrics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Joey R Orpilla
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Willy Hugo
- Division of Dermatology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Alexander H Lee
- Department of Medical and Molecular Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Tom B Davidson
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, USA
- Division of Hematology/Oncology, Department of Pediatrics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Anthony C Wang
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Benjamin M Ellingson
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | | | | | - Eric S Kawaguchi
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - Lin Du
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - Gang Li
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - William H Yong
- Department of Pathology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Sarah C Gaffey
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Adam L Cohen
- Department of Neurosurgery, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA
| | - Ingo K Mellinghoff
- Department of Neurology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Eudocia Q Lee
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - David A Reardon
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Barbara J O'Brien
- Department of Neuro-Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Nicholas A Butowski
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Phioanh L Nghiemphu
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jennifer L Clarke
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | | | - Howard Colman
- Department of Neurosurgery, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA
| | - Thomas J Kaley
- Department of Neurology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - John F de Groot
- Department of Neuro-Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Linda M Liau
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Patrick Y Wen
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Robert M Prins
- Department of Medical and Molecular Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA.
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