Massachusetts Institute of Technology (MIT) PS-OC
MIT/Mayo Physical Sciences Center for Drug Distribution and Drug Efficacy in Brain Tumors
The selection of relevant therapeutic agents with optimal pharmacokinetic and pharmacodynamic properties to adequately suppress the intended target across the entire target cell population will be central to the success of genomics-guided precision medicine strategies.
Optimal drug therapy for brain tumors is especially challenging due to multiple physical barriers within the vasculature and tumor microenvironment that can result in highly heterogeneous drug delivery. This results in a significant fraction of tumor cells being exposed to sub-therapeutic drug levels that limit the efficacy of therapy and may lead to compensatory cell signaling and emergence of drug resistance.
Thus, a central tenet of this PS-OC is that failure to understand limitations in the physical delivery and distribution of novel therapeutics into brain tumors is a major reason for the collective failure to extend the exciting treatment advances and survival gains realized in peripheral malignancies to the treatment of brain tumors.
This PS-OC is investigating physical factors that influence heterogeneous drug distribution and the resulting biology in a highly integrated analysis of patient and animal brain tumor models using 3-dimensional magnetic resonance imaging (MRI), stimulated Raman scattering (SRS) microscopy, matrix assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), immunohistochemistry (IHC), phosphoproteomics, proximity ligation assays (PLA), and RNAseq.
Integration of these data sets across a series of drugs evaluated in multiple tumor models will elaborate critical factors that modulate distribution of these drugs and provide the platform for construction of a multi-scale model that could be used to select a targeted therapeutic with an optimal predicted drug distribution based on MRI features of an individual tumor.
Project 1: Modeling the Interface between Non-invasive Imaging and Drug Distribution
The goal of this project is to develop and validate a “minimal” model that will capture intra- and inter-tumor heterogeneity to predict clinically relevant levels of drug distribution using routine imaging.
PS-OC investigators are using a combination of patient data, glioblastoma (GBM) patient-derived xenografts (PDXs), matrix-assisted laser desorption/ionization mass spectroscopy imaging (MALDI-MSI), and stimulated Raman spectroscopy (SRS) to quantify the differences in drug distribution within and across tumors. Additionally, they are using experimental data to develop a computational framework for predicting the efficacy of blood brain barrier (BBB)-penetrant and BBB-impenetrant drugs for the treatment of GBMs.
Project 2: Defining the Relationship Between Tumor Composition, Spatial Heterogeneity, Drug Delivery, and Drug Efficacy
Ultimately, this project aims to determine the physical factors regulating therapeutic distribution and therapeutic efficacy in brain tumors. To this end, PS-OC researchers have developed a highly innovative integrated strategy to quantitatively map therapeutic distribution with spatially registered characterization of the tumor architecture and therapeutic efficacy, all within a given tumor specimen.
Specifically, in this approach, the PS-OC will combine MALDI-MSI to quantify drug distribution, SRS imaging for label free analysis of tumor architecture with optical imaging resolution, immunohistochemistry to determine the tumor cell state and target distribution, proximity ligation assays for cellular spatial resolution of signaling response to therapy, and laser-capture microdissection RNA-seq to quantify spatially resolved transcriptional response to therapy. All of these approaches are being performed in serial sections from individual tumors, thereby enabling the integration of spatially registered data.
Together with mass spectrometry-based phosphoproteomics and RNA-seq analysis to quantify the dynamic signaling and transcriptional network response to a spectrum of defined drug concentrations in additional tumor specimens. The data generated in this project will
- Map spatially heterogeneous drug distribution and drug efficacy
- Enable the computational modeling of the physical factors governing distribution and the cellular and molecular response to different local drug concentrations
Core 1: Animal and Pharmacology
The studies in this PS-OC are evaluating a spectrum of EGFR- and RAF-targeted therapies in animal tumor models of glioblastoma (GBM) and melanoma brain metastases. The Animal and Pharmacology Core will provide critical infrastructure for these studies.
The main function of the core is the management of all aspects of the experiments that involve live animals and the distribution of biospecimens and imaging data to the appropriate investigators. This core also manages some experiments that are performed for the PS-OC. The core also has access to the extensive Mayo PDX collection in collaboration with the Mayo SPORE.
Core 2: Data Handling and Integration
The Data Handling and Integration Core provides key infrastructure to the PS-OC through data management and storage, integration of diverse data types, and model construction. PS-OC investigators with multidisciplinary expertise provide the requisite experience to fulfill each of the core’s functions.
Education and Outreach Unit
The education and outreach activities of this PSOC focus on training at a variety of levels. It supports the development of collaborative researchers who can integrate physical sciences and oncology to advance the understanding of the role of the blood-brain barrier (BBB) in limiting drug distribution in brain tumors and brain cancer heterogeneity.
Learn more about the MIT/Mayo PS-OC Education and Outreach Activities.
Dr. Forest White is the Principal Investigator of the PS-OC. He is a Professor in the Department of Biological Engineering at MIT, where he serves as co-Chair of the Biological Engineering Graduate Program. He is a member of the Koch Institute for Integrative Cancer Research and the Center for Environmental Health Sciences at MIT.
Dr. White received his Ph.D. from Florida State University in 1997 and was a post-doctoral associate at the University of Virginia from 1997-1999. After completion of his post-doc, he joined MDS Proteomics as a Senior Research Scientist and developed phosphoproteomics capabilities for the company. In July 2003, he joined the Department of Biological Engineering at MIT as an Assistant Professor. He was promoted to Associate Professor in 2007 and Full Professor in 2014. His laboratory investigates cellular signaling mechanisms in cancer, metabolic diseases, and immunology.
Jann Sarkaria, M.D.
Dr. Jann Sarkaria is a physician-scientist and Professor of Radiation Oncology at the Mayo Clinic. His clinical focus is treating lung and brain malignancies with external beam photon or proton radiation. His laboratory work focuses on developing novel therapeutic strategies for treating both primary and metastatic brain tumors.
Central to this work is the development and characterization of a large panel of patient-derived xenografts (PDXs) developed from brain tumor resection specimens. His laboratory has used these PDX models extensively to evaluate the efficacy of conventional and molecularly targeted therapies for glioblastoma (GBM). Central research themes include the evaluation of genetic and epigenetic mechanisms of therapy resistance to radiation and temozolomide, development of novel radio- or chemo-sensitizing agents for brain tumors, and understanding the influence of heterogeneous drug delivery into brain tumors on treatment response and the evolution of therapy resistance.
Protein engineers can engineer antibodies and scaffold proteins with widely varying size and affinity; however, the field has lacked any design principles for how best to exploit this capability.
Dr. K. Dane Wittrup’s lab developed simple scaling analyses that illustrated the tradeoffs between fundamental rate processes (clearance, extravasation, endocytosis) and has successfully predicted all subsequent experimental exploration of the effects of varying size and affinity on tumor uptake. He uses these models to design new drug candidates and examine their pharmacokinetics.
Douglas A. Lauffenburger, Ph.D.
Dr. Douglas A. Lauffenburger is a Ford Professor of Bioengineering and (founding) Head of the Department of Biological Engineering at MIT. He also holds appointments in the Department of Biology and the Department of Chemical Engineering, is a member of the Center for Biomedical Engineering, Center for Environmental Health Sciences, Center for Gynepathology Research, and Koch Institute for Integrative Cancer Research.
A central focus of his research program is in receptor-mediated cell communication and intracellular signal transduction important in pathophysiology with application to drug discovery and development. His lab focuses on the development of predictive computational models derived from quantitative experimental studies. More than 100 doctoral students and postdoctoral associates have undertaken research education under his supervision, and he has served as a consultant or scientific advisory board member for a number of bio/pharma companies (including Applied BioMath, Array BioPharm, Astra-Zeneca, Complete Genomics, Entelos, Genentech, Immuneering, Merrimack Pharmaceuticals, Nodality, Pfizer, and Torque Therapeutics).
Nathalie Y.R. Agar, Ph.D.
Brigham and Women’s Hospital
Dr. Nathalie Y.R. Agar is the founding Director of the Surgical Molecular Imaging Laboratory (SMIL) in the Department of Neurosurgery at Brigham and Women’s Hospital, and Associate Professor of Neurosurgery and of Radiology at Harvard Medical School. Her multidisciplinary training includes a B.Sc. in Biochemistry, Ph.D. in Chemistry, and postdoctoral fellowships in Neurosurgery at McGill University, and BWH/HMS.
Dr. Agar’s research aims to implement comprehensive molecular diagnoses through improved biochemical classification, enabling surgeons and oncologists to tailor treatment from the time of surgery. Her laboratory focuses on the study of targeted therapeutics for brain cancer from pre-clinical animal models to patient samples from clinical trials. Her group uses a range of imaging and analytical technologies such as 3D MALDI FTICR mass spectrometry imaging, LESA mass spectrometry, stimulated Raman scattering, bright field and fluorescence microscopy, and specialized data and image analyses.
William F. Elmquist, PharmD, Ph.D.
University of Minnesota
Dr. William F. Elmquist is currently a Professor and Director of the Brain Barriers Research Center at the University of Minnesota, Department of Pharmaceutics. He received his pharmacy degree at the University of Florida, and his Pharm.D. and Ph.D. (pharmacokinetics) from the University of Minnesota.
Dr. Elmquist has studied the influence of active efflux transporters in the BBB on drug distribution. An important project currently underway is examining the determinants of anticancer drug permeability in the BBB to improve the treatment of brain tumors. Long-term objectives his research include examining expression and regulation of transport systems in key tissues that influence drug disposition, and determining how variability in expression may contribute to variability in drug responses in the patients. Dr. Elmquist has long been a consultant to the pharmaceutical industry and the NIH, served on many journal editorial boards, and is a Fellow of the American Association of Pharmaceutical Scientists (AAPS).
Nhan L. Tran, Ph.D.
Dr. Nhan L. Tran is a Professor in the Department of Research and Cancer Biology at Mayo Clinic - Arizona. His research has been focused on determining the cellular and biochemical mechanisms of action of candidate genes expressed in highly invasive GBM cells and their matrix of aberrant signaling to discover points of convergence that can serve as targets of vulnerability for therapeutic intervention. His laboratory focuses on the identification and characterization of certain members of the super family of cytokine receptors, the tumor necrosis factor receptors (TNFR), which play important roles in modulating GBM cell adhesion, invasion and cell survival.
In addition, Dr. Tran’s expertise also lies in high-throughput assay development and applying molecular chemical library screens to exploit novel GBM targets. His research also focuses on characterizing GBM intratumor heterogeneity and genomic aberration of invasive GBM cells by implementing range of genomic technologies (whole genome, exome, RNA sequencing and methylation) to study therapeutic resistance and drug delivery.
Leland S. Hu, M.D.
Dr. Hu is an Assistant Professor in Radiology at the Mayo Clinic College of Medicine and serves as an attending Neuroradiologist at Mayo Clinic in Phoenix, Arizona. He received his medical degree at the University of Texas – Southwestern Medical School, where he also completed his medical internship and residency training in Diagnostic Radiology. After completing his two-year clinical fellowship in Diagnostic Neuroradiology at Barrow Neurological Institute, he joined the medical faculty at Mayo Clinic in 2008.
Dr. Hu’s research focuses on the development and implementation of advanced imaging methods to improve diagnosis, treatment planning, and treatment monitoring in brain tumors. His initial work sought to improve the accuracy of surveillance imaging in glioma, and his group published one of the first studies that validated the accuracy of Dynamic Susceptibility-weighted Contrast-enhanced (DSC) perfusion MRI (pMRI) to distinguish high-grade glioma recurrence from post-treatment radiation effects (e.g., pseudoprogression, radiation necrosis). He and his group have utilized image-guide tissue analysis and stereotactic coregistration to help overcome the challenges of intratumoral heterogeneity. Dr. Hu has recently published studies that have developed MRI and texture-based biomarkers of regional tumor cell invasion and intratumoral genetic heterogeneity in GBM. He currently serves on the Imaging Committee for the Alliance for Clinical Trials in Oncology and is an Associate Member of the NIH Quantitative Imaging Network (QIN).
Daniel J. Ma, M.D.
Dr. Daniel J. Ma is currently an Assistant Professor of Radiation Oncology at the Mayo Clinic in Rochester, MN. He received his M.D. from the Washington University School of Medicine in St. Louis, MO and did residency training at the Mallinckrodt Institute of Radiology.
His research is centered on using next-generation sequencing techniques to predict treatment response in GBM and using circulating tumor DNA to detect early treatment failure. Dr. Ma serves on the Radiation Oncology Research Executive Committee at Mayo Clinic.
Ian F. Parney M.D., Ph.D.
Dr. Parney is Associate Professor and Vice-Chair (Research) of the Department of Neurosurgery at Mayo Clinic Rochester where he is also a member of the Department of Immunology and the Neuro-Oncology Program of the Mayo Clinic Cancer Center. He received his M.D. and Ph.D. degrees and completed his neurosurgical training at the University of Alberta and completed further subspecialty and post-doctoral training in the Dept. of Neurosurgery at the University of California San Francisco.
Dr. Parney’s clinical efforts are focused on malignant brain tumor surgery. His laboratory focuses on malignant glioma immunology and immunotherapy. He is a principal investigator on multiple local and national glioma immunotherapy clinical trials.
Kristin Swanson M.D., Ph.D.
Dr. Swanson received her B.S. in Mathematics in 1996 from Tulane University followed by her M.S. (1998) and Ph.D. (1999) in Mathematical Biology from the University of Washington. Following a postdoctoral fellowship in Mathematical Medicine at UCSF, she joined the faculty at the University of Washington in 2000, with appointments in both Neuropathology and Applied Mathematics. In 2015, she joined Mayo Clinic in Arizona as Professor and Vice Chair of the department of Neurological Surgery. She also holds appointments at Arizona State University and the Translational Genomics Institute.
Dr. Swanson’s research lab has served to pioneer the burgeoning field of mathematical neuro-oncology generating compelling data to support the practical application of patient-specific bio-mathematical models of glioma to assess, predict and optimize treatment. Her research efforts have been supported through funding by the NIH, numerous foundations, the James D. Murray Endowed Chair at the University of Washington, TGen and the Mayo Clinic.