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Salphati L, Pang J, Alicke B, Plise EG, Cheong J, Jaochico A, Olivero AG, Sampath D, Wong S, Zhang X. Preclinical characterization of the absorption and disposition of the brain penetrant PI3K/mTOR inhibitor paxalisib and prediction of its pharmacokinetics and efficacy in human. Xenobiotica 2024; 54:64-74. [PMID: 38197324 DOI: 10.1080/00498254.2024.2303586] [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: 11/20/2023] [Accepted: 01/06/2024] [Indexed: 01/11/2024]
Abstract
Glioblastoma multiforme (GBM) is the most common primary brain tumour in adults. Available treatments have not markedly improved patient survival in the last twenty years. However, genomic investigations have showed that the PI3K pathway is frequently altered in this glioma, making it a potential therapeutic target.Paxalisib is a brain penetrant PI3K/mTOR inhibitor (mouse Kp,uu 0.31) specifically developed for the treatment of GBM. We characterised the preclinical pharmacokinetics and efficacy of paxalisib and predicted its pharmacokinetics and efficacious dose in humans.Plasma protein binding of paxalisib was low, with the fraction unbound ranging from 0.25 to 0.43 across species. The hepatic clearance of paxalisib was predicted to be low in mice, rats, dogs and humans, and high in monkeys, from hepatocytes incubations. The plasma clearance was low in mice, moderate in rats and high in dogs and monkeys. Oral bioavailability ranged from 6% in monkeys to 76% in rats.The parameters estimated from the pharmacokinetic/pharmacodynamic modelling of the efficacy in the subcutaneous U87 xenograft model combined with the human pharmacokinetics profile predicted by PBPK modelling suggested that a dose of 56 mg may be efficacious in humans. Paxalisib is currently tested in Phase III clinical trials.
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Affiliation(s)
- Laurent Salphati
- Department of Drug Metabolism and Pharmacokinetics, Genentech, Inc, South San Francisco, CA, USA
| | - Jodie Pang
- Department of Drug Metabolism and Pharmacokinetics, Genentech, Inc, South San Francisco, CA, USA
| | - Bruno Alicke
- Translational Oncology, Genentech, Inc, South San Francisco, CA, USA
| | - Emile G Plise
- Department of Drug Metabolism and Pharmacokinetics, Genentech, Inc, South San Francisco, CA, USA
| | - Jonathan Cheong
- Department of Drug Metabolism and Pharmacokinetics, Genentech, Inc, South San Francisco, CA, USA
| | - Allan Jaochico
- Department of Drug Metabolism and Pharmacokinetics, Genentech, Inc, South San Francisco, CA, USA
| | | | - Deepak Sampath
- Translational Oncology, Genentech, Inc, South San Francisco, CA, USA
| | - Susan Wong
- Department of Drug Metabolism and Pharmacokinetics, Genentech, Inc, South San Francisco, CA, USA
| | - Xiaolin Zhang
- Department of Drug Metabolism and Pharmacokinetics, Genentech, Inc, South San Francisco, CA, USA
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Panwar V, Singh A, Bhatt M, Tonk RK, Azizov S, Raza AS, Sengupta S, Kumar D, Garg M. Multifaceted role of mTOR (mammalian target of rapamycin) signaling pathway in human health and disease. Signal Transduct Target Ther 2023; 8:375. [PMID: 37779156 PMCID: PMC10543444 DOI: 10.1038/s41392-023-01608-z] [Citation(s) in RCA: 33] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 07/25/2023] [Accepted: 08/14/2023] [Indexed: 10/03/2023] Open
Abstract
The mammalian target of rapamycin (mTOR) is a protein kinase that controls cellular metabolism, catabolism, immune responses, autophagy, survival, proliferation, and migration, to maintain cellular homeostasis. The mTOR signaling cascade consists of two distinct multi-subunit complexes named mTOR complex 1/2 (mTORC1/2). mTOR catalyzes the phosphorylation of several critical proteins like AKT, protein kinase C, insulin growth factor receptor (IGF-1R), 4E binding protein 1 (4E-BP1), ribosomal protein S6 kinase (S6K), transcription factor EB (TFEB), sterol-responsive element-binding proteins (SREBPs), Lipin-1, and Unc-51-like autophagy-activating kinases. mTOR signaling plays a central role in regulating translation, lipid synthesis, nucleotide synthesis, biogenesis of lysosomes, nutrient sensing, and growth factor signaling. The emerging pieces of evidence have revealed that the constitutive activation of the mTOR pathway due to mutations/amplification/deletion in either mTOR and its complexes (mTORC1 and mTORC2) or upstream targets is responsible for aging, neurological diseases, and human malignancies. Here, we provide the detailed structure of mTOR, its complexes, and the comprehensive role of upstream regulators, as well as downstream effectors of mTOR signaling cascades in the metabolism, biogenesis of biomolecules, immune responses, and autophagy. Additionally, we summarize the potential of long noncoding RNAs (lncRNAs) as an important modulator of mTOR signaling. Importantly, we have highlighted the potential of mTOR signaling in aging, neurological disorders, human cancers, cancer stem cells, and drug resistance. Here, we discuss the developments for the therapeutic targeting of mTOR signaling with improved anticancer efficacy for the benefit of cancer patients in clinics.
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Affiliation(s)
- Vivek Panwar
- Department of Pharmaceutical Chemistry, School of Pharmaceutical Sciences, Shoolini University, Solan, Himachal Pradesh, 173229, India
| | - Aishwarya Singh
- Amity Institute of Molecular Medicine and Stem Cell Research (AIMMSCR), Amity University Uttar Pradesh, Sector-125, Noida, Uttar Pradesh, 201313, India
| | - Manini Bhatt
- Department of Biomedical Engineering, Indian Institute of Technology, Ropar, Punjab, 140001, India
| | - Rajiv K Tonk
- Department of Pharmaceutical Chemistry, School of Pharmaceutical Sciences, Delhi Pharmaceutical Sciences and Research University (DPSRU), New Delhi, 110017, India
| | - Shavkatjon Azizov
- Laboratory of Biological Active Macromolecular Systems, Institute of Bioorganic Chemistry, Academy of Sciences Uzbekistan, Tashkent, 100125, Uzbekistan
- Faculty of Life Sciences, Pharmaceutical Technical University, 100084, Tashkent, Uzbekistan
| | - Agha Saquib Raza
- Rajive Gandhi Super Speciality Hospital, Tahirpur, New Delhi, 110093, India
| | - Shinjinee Sengupta
- Amity Institute of Molecular Medicine and Stem Cell Research (AIMMSCR), Amity University Uttar Pradesh, Sector-125, Noida, Uttar Pradesh, 201313, India.
| | - Deepak Kumar
- Department of Pharmaceutical Chemistry, School of Pharmaceutical Sciences, Shoolini University, Solan, Himachal Pradesh, 173229, India.
| | - Manoj Garg
- Amity Institute of Molecular Medicine and Stem Cell Research (AIMMSCR), Amity University Uttar Pradesh, Sector-125, Noida, Uttar Pradesh, 201313, India.
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Mellinghoff IK, Cloughesy TF. Balancing Risk and Efficiency in Drug Development for Rare and Challenging Tumors: A New Paradigm for Glioma. J Clin Oncol 2022; 40:3510-3519. [PMID: 35201903 PMCID: PMC10166355 DOI: 10.1200/jco.21.02166] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 12/15/2021] [Accepted: 01/26/2022] [Indexed: 12/14/2022] Open
Abstract
The process of developing cancer therapies is well established and has enabled the incorporation of many new drugs and classes of agents into the standard of care for common cancers. Clinical drug development is fundamentally different for rare and difficult-to-treat solid tumors, such as glioma or pancreatic cancer. The failure to develop effective new agents for the latter diseases has discouraged the development of therapeutics for these cancers. Using glioma as an example, we describe a process toward obtaining more reliable early-stage signals of drug activity and a process toward translating those signals into clinical benefits with more efficient late-stage development. If linked together, these processes should increase the likelihood of benefit in late-stage settings at a lower cost and encourage more drug development for patients with rare and difficult-to-treat cancers.
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Affiliation(s)
- Ingo K. Mellinghoff
- Department of Neurology and Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Timothy F. Cloughesy
- Department of Neurology, Ronald Reagan UCLA Medical Center, University of California, Los Angeles, CA
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Stumpo V, Guida L, Bellomo J, Van Niftrik CHB, Sebök M, Berhouma M, Bink A, Weller M, Kulcsar Z, Regli L, Fierstra J. Hemodynamic Imaging in Cerebral Diffuse Glioma—Part B: Molecular Correlates, Treatment Effect Monitoring, Prognosis, and Future Directions. Cancers (Basel) 2022; 14:cancers14051342. [PMID: 35267650 PMCID: PMC8909110 DOI: 10.3390/cancers14051342] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 03/01/2022] [Accepted: 03/02/2022] [Indexed: 02/05/2023] Open
Abstract
Gliomas, and glioblastoma in particular, exhibit an extensive intra- and inter-tumoral molecular heterogeneity which represents complex biological features correlating to the efficacy of treatment response and survival. From a neuroimaging point of view, these specific molecular and histopathological features may be used to yield imaging biomarkers as surrogates for distinct tumor genotypes and phenotypes. The development of comprehensive glioma imaging markers has potential for improved glioma characterization that would assist in the clinical work-up of preoperative treatment planning and treatment effect monitoring. In particular, the differentiation of tumor recurrence or true progression from pseudoprogression, pseudoresponse, and radiation-induced necrosis can still not reliably be made through standard neuroimaging only. Given the abundant vascular and hemodynamic alterations present in diffuse glioma, advanced hemodynamic imaging approaches constitute an attractive area of clinical imaging development. In this context, the inclusion of objective measurable glioma imaging features may have the potential to enhance the individualized care of diffuse glioma patients, better informing of standard-of-care treatment efficacy and of novel therapies, such as the immunotherapies that are currently increasingly investigated. In Part B of this two-review series, we assess the available evidence pertaining to hemodynamic imaging for molecular feature prediction, in particular focusing on isocitrate dehydrogenase (IDH) mutation status, MGMT promoter methylation, 1p19q codeletion, and EGFR alterations. The results for the differentiation of tumor progression/recurrence from treatment effects have also been the focus of active research and are presented together with the prognostic correlations identified by advanced hemodynamic imaging studies. Finally, the state-of-the-art concepts and advancements of hemodynamic imaging modalities are reviewed together with the advantages derived from the implementation of radiomics and machine learning analyses pipelines.
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Affiliation(s)
- Vittorio Stumpo
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
- Correspondence:
| | - Lelio Guida
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Jacopo Bellomo
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Christiaan Hendrik Bas Van Niftrik
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Martina Sebök
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Moncef Berhouma
- Department of Neurosurgical Oncology and Vascular Neurosurgery, Pierre Wertheimer Neurological and Neurosurgical Hospital, Hospices Civils de Lyon, 69500 Lyon, France;
| | - Andrea Bink
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
- Department of Neuroradiology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Michael Weller
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
- Department of Neurology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Zsolt Kulcsar
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
- Department of Neuroradiology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Luca Regli
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Jorn Fierstra
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
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Hagiwara A, Yao J, Raymond C, Cho NS, Everson R, Patel K, Morrow DH, Desousa BR, Mareninov S, Chun S, Nathanson DA, Yong WH, Andrei G, Divakaruni AS, Salamon N, Pope WB, Nghiemphu PL, Liau LM, Cloughesy TF, Ellingson BM. "Aerobic glycolytic imaging" of human gliomas using combined pH-, oxygen-, and perfusion-weighted magnetic resonance imaging. Neuroimage Clin 2022; 32:102882. [PMID: 34911188 PMCID: PMC8609049 DOI: 10.1016/j.nicl.2021.102882] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 11/10/2021] [Accepted: 11/11/2021] [Indexed: 01/24/2023]
Abstract
Aerobic glycolytic imaging combines pH-, oxygen-, and perfusion-weighted MRI. Aerobic glycolytic imaging depicts abnormal glucose metabolism of gliomas. IDH wild-type gliomas show higher aerobic glycolytic index compared with mutants. Aerobic glycolytic index in IDH wild-type glioma is correlated with glucose uptake. Aerobic glycolytic index in IDH mutant glioma is correlated to lactate transporters.
Purpose To quantify abnormal metabolism of diffuse gliomas using “aerobic glycolytic imaging” and investigate its biological correlation. Methods All subjects underwent a pH-weighted amine chemical exchange saturation transfer spin-and-gradient-echo echoplanar imaging (CEST-SAGE-EPI) and dynamic susceptibility contrast perfusion MRI. Relative oxygen extraction fraction (rOEF) was estimated as the ratio of reversible transverse relaxation rate R2′ to normalized relative cerebral blood volume. An aerobic glycolytic index (AGI) was derived by the ratio of pH-weighted image contrast (MTRasym at 3.0 ppm) to rOEF. AGI was compared between different tumor types (N = 51, 30 IDH mutant and 21 IDH wild type). Metabolic MR parameters were correlated with 18F-FDG uptake (N = 8, IDH wild-type glioblastoma), expression of key glycolytic proteins using immunohistochemistry (N = 38 samples, 21 from IDH mutant and 17 from IDH wild type), and bioenergetics analysis on purified tumor cells (N = 7, IDH wild-type high grade). Results AGI was significantly lower in IDH mutant than wild-type gliomas (0.48 ± 0.48 vs. 0.70 ± 0.48; P = 0.03). AGI was strongly correlated with 18F-FDG uptake both in non-enhancing tumor (Spearman, ρ = 0.81; P = 0.01) and enhancing tumor (ρ = 0.81; P = 0.01). AGI was significantly correlated with glucose transporter 3 (ρ = 0.71; P = 0.004) and hexokinase 2 (ρ = 0.73; P = 0.003) in IDH wild-type glioma, and monocarboxylate transporter 1 (ρ = 0.59; P = 0.009) in IDH mutant glioma. Additionally, a significant correlation was found between AGI derived from bioenergetics analysis and that estimated from MRI (ρ = 0.79; P = 0.04). Conclusion AGI derived from molecular MRI was correlated with glucose uptake (18F-FDG and glucose transporter 3/hexokinase 2) and cellular AGI in IDH wild-type gliomas, whereas AGI in IDH mutant gliomas appeared associated with monocarboxylate transporter density.
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Affiliation(s)
- 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
| | - Jingwen Yao
- 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
| | - 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
| | - 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
| | - Richard Everson
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Kunal Patel
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Danielle H Morrow
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Brandon R Desousa
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Sergey Mareninov
- Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Saewon Chun
- UCLA Neuro-Oncology Program, 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
| | - William H Yong
- Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Gafita Andrei
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Ajit S Divakaruni
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Noriko Salamon
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Whitney B Pope
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Phioanh L Nghiemphu
- 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
| | - Linda M Liau
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 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
| | - 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; Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, 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.
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Ellingson BM, Wen PY, Cloughesy TF. Therapeutic Response Assessment of High-Grade Gliomas During Early-Phase Drug Development in the Era of Molecular and Immunotherapies. Cancer J 2021; 27:395-403. [PMID: 34570454 PMCID: PMC8480435 DOI: 10.1097/ppo.0000000000000543] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
ABSTRACT Several new therapeutic strategies have emerged over the past decades to address unmet clinical needs in high-grade gliomas, including targeted molecular agents and various forms of immunotherapy. Each of these strategies requires addressing fundamental questions, depending on the stage of drug development, including ensuring drug penetration into the brain, engagement of the drug with the desired target, biologic effects downstream from the target including metabolic and/or physiologic changes, and identifying evidence of clinical activity that could be expanded upon to increase the likelihood of a meaningful survival benefit. The current review article highlights these strategies and outlines how imaging technology can be used for therapeutic response evaluation in both targeted and immunotherapies in early phases of drug development in high-grade gliomas.
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Affiliation(s)
- Benjamin M. Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Patrick Y. Wen
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Harvard University, Boston, MA
| | - Timothy F. Cloughesy
- UCLA Neuro Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
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Li D, Patel CB, Xu G, Iagaru A, Zhu Z, Zhang L, Cheng Z. Visualization of Diagnostic and Therapeutic Targets in Glioma With Molecular Imaging. Front Immunol 2020; 11:592389. [PMID: 33193439 PMCID: PMC7662122 DOI: 10.3389/fimmu.2020.592389] [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] [Received: 08/07/2020] [Accepted: 10/08/2020] [Indexed: 02/04/2023] Open
Abstract
Gliomas, particularly high-grade gliomas including glioblastoma (GBM), represent the most common and malignant types of primary brain cancer in adults, and carry a poor prognosis. GBM has been classified into distinct subgroups over the years based on cellular morphology, clinical characteristics, biomarkers, and neuroimaging findings. Based on these classifications, differences in therapeutic response and patient outcomes have been established. Recently, the identification of complex molecular signatures of GBM has led to the development of diverse targeted therapeutic regimens and translation into multiple clinical trials. Chemical-, peptide-, antibody-, and nanoparticle-based probes have been designed to target specific molecules in gliomas and then be visualized with multimodality molecular imaging (MI) techniques including positron emission tomography (PET), single-photon emission computed tomography (SPECT), near-infrared fluorescence (NIRF), bioluminescence imaging (BLI), and magnetic resonance imaging (MRI). Thus, multiple molecules of interest can now be noninvasively imaged to guide targeted therapies with a potential survival benefit. Here, we review developments in molecular-targeted diagnosis and therapy in glioma, MI of these targets, and MI monitoring of treatment response, with a focus on the biological mechanisms of these advanced molecular probes. MI probes have the potential to noninvasively demonstrate the pathophysiologic features of glioma for diagnostic, treatment, and response assessment considerations for various targeted therapies, including immunotherapy. However, most MI tracers are in preclinical development, with only integrin αVβ3 and isocitrate dehydrogenase (IDH)-mutant MI tracers having been translated to patients. Expanded international collaborations would accelerate translational research in the field of glioma MI.
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Affiliation(s)
- Deling Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, China National Clinical Research Center for Neurological Diseases (NCRC-ND), Beijing, China
| | - Chirag B Patel
- Molecular Imaging Program at Stanford (MIPS), Department of Radiology, School of Medicine, Stanford University, Stanford, CA, United States.,Division of Neuro-Oncology, Department of Neurology and Neurological Sciences, School of Medicine, Stanford University, Stanford, CA, United States
| | - Guofan Xu
- Molecular Imaging Program at Stanford (MIPS), Department of Radiology, School of Medicine, Stanford University, Stanford, CA, United States
| | - Andrei Iagaru
- Molecular Imaging Program at Stanford (MIPS), Department of Radiology, School of Medicine, Stanford University, Stanford, CA, United States
| | - Zhaohui Zhu
- Department of Nuclear Medicine, Peking Union Medical College Hospital, Beijing, China
| | - Liwei Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, China National Clinical Research Center for Neurological Diseases (NCRC-ND), Beijing, China.,Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Zhen Cheng
- Molecular Imaging Program at Stanford (MIPS), Department of Radiology, School of Medicine, Stanford University, Stanford, CA, United States
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