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MNO Lecture Series: DAVID R. GRIMES, PH.D.

The Mathematical Neuro-Oncology Research Lab Presents

David R. Grimes, PH.D.
Post-Doctoral Research Associate
CR UK/MRC Oxford Institute for Radiation Oncology
Gray Labs, Radiation Research Institute
University of Oxford


Modeling the role of oxygen in the tumor micro-environment

MONDAY, MARCH 2ND, 2015
2:00 PM–3:00 PM
ARKES PAVILION,
676 N. SAINT CLAIR ST. SUITE 1300
MATHEMATICAL NEURO-ONCOLOGY LAB

In tumours, hypoxia is associated with poor prognosis, increased likelihood of metastasis and a marked resistance to radiotherapy. While imaging techniques, such as PET with hypoxia tracers can indicate hypoxic sub-volumes inside a tumour, these modalities are limited by the physics of the system to a resolution in the millimetre regime, whereas tumour oxygen levels can vary over a micron scale. Mathematical models of cellular oxygen distribution are of paramount importance to bridge this scale gap and aid interpretation of clinical image data, and ultimately treatment prescription. This talk discusses some approaches to -and challenges of -the oxygen micro-environment and its significance to treatment.

Written on February 26th, 2015. 0 Comments

MNO Lecture Series: December 11th 2014, Kit Curtius

The Mathematical Neuro-Oncology Research Lab Presents

Kathleen (Kit) Curtius
NSF Research Fellow
Department of Applied Mathematics
University of Washington
Fred Hutchinson Cancer Research Center


How long has that been there?
Multi-scale modeling of Barrett’s Esophagus

Thursday, December 11th, 2014
12:00 pm – 1:00 pm
Arkes Pavilion,
676 n. Saint Clair St. Suite 1300
Mathematical Neuro-Oncology Lab

Although the development of Barrett’s esophagus (BE) is considered an important first step in the progression to esophageal adenocarcinoma (EAC), BE is asymptomatic – so the duration of time a patient has harbored BE is generally not known when she/he is first diagnosed. This is particularly unfortunate because the duration that BE has been present in a patient correlates strongly with the risk of BE transforming into EAC. Recently identified clock-CpGs allow a novel characterization of a tissue in terms of its biological age, and these markers are used to show accelerated tissue aging in a variety of tumors. We seek markers of differential epigenetic drift from genome-wide DNA-methylation array data from BE patients in order to predict BE tissue age. We then estimate individual-level BE onset times and the subsequent risk of progressing to dysplasia and EAC using a mathematical model. This work translates DNA-methylation “footprints” of tissue-aging into “time” information to estimate important time scales in the step-wise progression to dysplasia and cancer in BE patients.

Written on December 10th, 2014. 0 Comments

MNO Lecture Series: November 7, 2014 Natalia Komarova PhD

The Mathematical Neuro-Oncology Research Lab Presents

Natalia Komarova
Professor of Mathematics
University of California – Irvine
 

Stochastic Modeling of Chronic Lymphocytic Leukemia Treatment
 
 
 
Friday, November 7th, 2014
2:30 pm – 3:30 pm
Arkes Pavilion,
676 n. Saint Clair St. Suite 1300
Mathematical Neuro-Oncology Lab

Chronic lymphocytic leukemia (CLL) is the most common leukemia, mostly arising in patients over the age of 50. The disease has been treated with chemo-immunotherapies with varying outcomes, depending on the genetic make-up of the tumor cells. Recently, a promising new tyrosine kinase inhibitor, ibrutinib, has been developed, which resulted in successful responses in clinical trials, even for the most aggressive chronic lymphocytic leukemia types. The crucial current questions include how long disease control can be maintained in individual patients, when drug resistance is expected to arise, and what can be done to counter it. Computational evolutionary models, based on measured kinetic parameters of patients, allow us to address these questions and to pave the way toward a personalized prognosis.

Written on November 7th, 2014. 0 Comments

MNO Lecture Series: September 19, 2014 Alexander Fletcher, DPhil

The Mathematical Neuro-Oncology Research Lab Presents

Alexander Fletcher, DPhil.
Research Fellow
Wolfson Centre for Mathematical Biology
Oxford University, Oxford, UK

A Computational Modelling Approach for Deriving Biomarkers for Cancer Risk in Premalignant Disease


Friday, September 19th, 2014
1:00 pm – 2:00 pm
Arkes Pavilion,
676 n. Saint Clair St. Suite 1300
Mathematical Neuro-Oncology Lab

Carcinogenesis is an evolutionary process, so biomarkers for cancer prognosis are fundamentally measures that attempt to predict the future course of cancer evolution. How best should we measure the evolutionary process to derive prognostic value? Here we derive evolutionary-motivated biomarkers from an analysis of a computational model of carcinogenesis in premalignant disease. We propose a novel measure of heterogeneity, termed the positive proliferation index, that is the strongest predictor of outcome of all indices studied in our model. These findings suggest biomarkers that may be clinically validated in future studies to ultimately improve risk stratification among patients with premalignant disease.

Alex has held a Research Fellowship in Computational Science associated with the 2020 Science project, a collaborative research programmebased at the University of Oxford, University College London and Microsoft Research, Cambridge since 2011. Dr. Fletcher is a member of the WolfsonCentre for Mathematical Biology (WCMB) at the Mathematical Institute, University of Oxford and a stipendiary lecturer at St Hugh’s College, Oxford. The main focus of his research is to advance the application of, and mathematics underlying, models of epithelial tissues in development, health and disease.

Written on September 10th, 2014. 0 Comments

MNO Lecture Series: August 20th 2014 Phillip Altrock, PhD

The Mathematical Neuro-Oncology Research Lab Presents

Phillip Altrock, PhD
Postdoctoral Fellow
Department of Biostatistics and Computational Biology
Dana-Farber Cancer Institute

Non-cell-autonomous driving of tumor growth support sub-clonal heterogeneity

 
  
 

Wednesday, August 20th, 2014
12:00 pm – 12:30 pm
Arkes Pavilion,
676 n. Saint Clair St. Suite 1300
Mathematical Neuro-Oncology Lab

Philipp studied physics at the University of Leipzig, Germany, where he minored in chemistry and mathematics and focused on theoretical physics. Philipp received his PhD from University of Kiel, Germany in 2011. He gained his first research experience in statistical mechanics working with Prof. Ulrich Behn in Leipzig, and then went on to study evolutionary game theory, evolutionary dynamics, and population genetics with Arne Traulsen and Floyd A. Reed at the Max Planck Institute for Evolutionary Biology.
At the Dana-Farber Cancer Institute, Philipp investigates cancer initiation, progression, diversity, and response to treatment. With a micro-evolutionary framework, Philipp uses computational and mathematical analyses of cancer genomics and expression data to aim at improving cancer mortality and morbidity.

Written on August 15th, 2014. 0 Comments

Our new Journal of Clinical Investigation paper using patient-specific mathematical modeling to prove efficacy of a novel gene therapy of glioblastoma

https://www.jci.org/articles/view/76739

 

Gene therapy enhances chemotherapy tolerance and efficacy in glioblastoma patients

Jennifer E. Adair1,2, Sandra K. Johnston3, Maciej M. Mrugala4,5, Brian C. Beard1,2, Laura A. Guyman6,7, Anne L. Baldock6,7, Carly A. Bridge6,7, Andrea Hawkins-Daarud6,7, Jennifer L. Gori1, Donald E. Born8, Luis F. Gonzalez-Cuyar9, Daniel L. Silbergeld3,9, Russell C. Rockne6,7, Barry E. Storer1,10, Jason K. Rockhill3,11, Kristin R. Swanson6,7,12 and Hans-Peter Kiem1,2,9

1Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA. 2Department of Medicine, 3Department of Radiology, 4Department of Neurosurgery, and 5Department of Neurology, University of Washington (UW), Seattle, Washington, USA. 6Department of Neurological Surgery and 7Northwestern Brain Tumor Institute, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA. 8Department of Pathology, Stanford University, Stanford, California, USA. 9Department of Pathology, 10Department of Biostatistics, and 11Department of Radiation Oncology, UW, Seattle, Washington, USA. 12Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.

Address correspondence to: Hans-Peter Kiem, Fred Hutchinson Cancer Research Center, Mail Stop D1-100, P.O. Box 19024, Seattle, Washington 98109-1024, USA. Phone: 206.667.4425; E-mail: hkiem@fhcrc.org.

Published August 8, 2014 Received for publication April 29, 2014, and accepted in revised form July 1, 2014.

BACKGROUND. Temozolomide (TMZ) is one of the most potent chemotherapy agents for the treatment of glioblastoma. Unfortunately, almost half of glioblastoma tumors are TMZ resistant due to overexpression of methylguanine methyltransferase (MGMThi). Coadministration of O6-benzylguanine (O6BG) can restore TMZ sensitivity, but causes off-target myelosuppression. Here, we conducted a prospective clinical trial to test whether gene therapy to confer O6BG resistance in hematopoietic stem cells (HSCs) improves chemotherapy tolerance and outcome.

METHODS. We enrolled 7 newly diagnosed glioblastoma patients with MGMThi tumors. Patients received autologous gene-modified HSCs following single-agent carmustine administration. After hematopoietic recovery, patients underwent O6BG/TMZ chemotherapy in 28-day cycles. Serial blood samples and tumor images were collected throughout the study. Chemotherapy tolerance was determined by the observed myelosuppression and recovery following each cycle. Patient-specific biomathematical modeling of tumor growth was performed. Progression-free survival (PFS) and overall survival (OS) were also evaluated.

RESULTS. Gene therapy permitted a significant increase in the mean number of tolerated O6BG/TMZ cycles (4.4 cycles per patient, P < 0.05) compared with historical controls without gene therapy (n = 7 patients, 1.7 cycles per patient). One patient tolerated an unprecedented 9 cycles and demonstrated long-term PFS without additional therapy. Overall, we observed a median PFS of 9 (range 3.5–57+) months and OS of 20 (range 13–57+) months. Furthermore, biomathematical modeling revealed markedly delayed tumor growth at lower cumulative TMZ doses in study patients compared with patients that received standard TMZ regimens without O6BG.

CONCLUSION. These data support further development of chemoprotective gene therapy in combination with O6BG and TMZ for the treatment of glioblastoma and potentially other tumors with overexpression of MGMT.

TRIAL REGISTRATION. Clinicaltrials.gov NCT00669669.

FUNDING. R01CA114218, R01AI080326, R01HL098489, P30DK056465, K01DK076973, R01HL074162, R01CA164371, R01NS060752, U54CA143970.

Written on August 8th, 2014. 0 Comments

Our new Journal of Clinical Investigation paper using patient-specific mathematical modeling to prove efficacy of a novel gene therapy of glioblastoma

https://www.jci.org/articles/view/76739

 

Gene therapy enhances chemotherapy tolerance and efficacy in glioblastoma patients

Jennifer E. Adair1,2, Sandra K. Johnston3, Maciej M. Mrugala4,5, Brian C. Beard1,2, Laura A. Guyman6,7, Anne L. Baldock6,7, Carly A. Bridge6,7, Andrea Hawkins-Daarud6,7, Jennifer L. Gori1, Donald E. Born8, Luis F. Gonzalez-Cuyar9, Daniel L. Silbergeld3,9, Russell C. Rockne6,7, Barry E. Storer1,10, Jason K. Rockhill3,11, Kristin R. Swanson6,7,12 and Hans-Peter Kiem1,2,9

1Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA. 2Department of Medicine, 3Department of Radiology, 4Department of Neurosurgery, and 5Department of Neurology, University of Washington (UW), Seattle, Washington, USA. 6Department of Neurological Surgery and 7Northwestern Brain Tumor Institute, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA. 8Department of Pathology, Stanford University, Stanford, California, USA. 9Department of Pathology, 10Department of Biostatistics, and 11Department of Radiation Oncology, UW, Seattle, Washington, USA. 12Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.

Address correspondence to: Hans-Peter Kiem, Fred Hutchinson Cancer Research Center, Mail Stop D1-100, P.O. Box 19024, Seattle, Washington 98109-1024, USA. Phone: 206.667.4425; E-mail: hkiem@fhcrc.org.

Published August 8, 2014 Received for publication April 29, 2014, and accepted in revised form July 1, 2014.

BACKGROUND. Temozolomide (TMZ) is one of the most potent chemotherapy agents for the treatment of glioblastoma. Unfortunately, almost half of glioblastoma tumors are TMZ resistant due to overexpression of methylguanine methyltransferase (MGMThi). Coadministration of O6-benzylguanine (O6BG) can restore TMZ sensitivity, but causes off-target myelosuppression. Here, we conducted a prospective clinical trial to test whether gene therapy to confer O6BG resistance in hematopoietic stem cells (HSCs) improves chemotherapy tolerance and outcome.

METHODS. We enrolled 7 newly diagnosed glioblastoma patients with MGMThi tumors. Patients received autologous gene-modified HSCs following single-agent carmustine administration. After hematopoietic recovery, patients underwent O6BG/TMZ chemotherapy in 28-day cycles. Serial blood samples and tumor images were collected throughout the study. Chemotherapy tolerance was determined by the observed myelosuppression and recovery following each cycle. Patient-specific biomathematical modeling of tumor growth was performed. Progression-free survival (PFS) and overall survival (OS) were also evaluated.

RESULTS. Gene therapy permitted a significant increase in the mean number of tolerated O6BG/TMZ cycles (4.4 cycles per patient, P < 0.05) compared with historical controls without gene therapy (n = 7 patients, 1.7 cycles per patient). One patient tolerated an unprecedented 9 cycles and demonstrated long-term PFS without additional therapy. Overall, we observed a median PFS of 9 (range 3.5–57+) months and OS of 20 (range 13–57+) months. Furthermore, biomathematical modeling revealed markedly delayed tumor growth at lower cumulative TMZ doses in study patients compared with patients that received standard TMZ regimens without O6BG.

CONCLUSION. These data support further development of chemoprotective gene therapy in combination with O6BG and TMZ for the treatment of glioblastoma and potentially other tumors with overexpression of MGMT.

TRIAL REGISTRATION. Clinicaltrials.gov NCT00669669.

FUNDING. R01CA114218, R01AI080326, R01HL098489, P30DK056465, K01DK076973, R01HL074162, R01CA164371, R01NS060752, U54CA143970.

Written on August 8th, 2014. 0 Comments

See Kristin Swanson’s TEDxUChicago Talk

Written on August 8th, 2014. 0 Comments

Lab receives James S. McDonnell Foundation grant for The “ENDURES” Study: ENvironmental Dynamics Underlying Responsive Extreme Survivors of Glioblastoma

Written on July 23rd, 2014. 0 Comments

MNO Lecture Series: July 28th 2014 – Jasmine Foo, Ph.D. and Kevin Leder, Ph.D.

The Mathematical Neuro-Oncology Research Lab Presents:

 

Monday, July 28th, 2014
1:30 – 2pm
Arkes Pavilion
676 N. Saint Clair St. Suite 1300
 
JASMINE FOO, Ph.D.
Assistant Professor of Mathematics
The University of Minnesota
Title: Hitchhiking Index: Identifying driver and passenger mutations in cancer
Bio: Jasmine Foo is an McKnight Land Grant assistant professor at the University of Minnesota math department. She completed her PhD in Applied Math at Brown University in 2008, and carried out postdoctoral work at Harvard University/Dana Farber Cancer Center and the Memorial Sloan Kettering Cancer Center. Her research involves using stochastic processes to formulate and analyze mathematical theories of cancer evolution.
Abstract: The traditional view of cancer as a genetic disease that can successfully be treated with drugs targeting mutantoncoproteins has motivated whole-genome sequencing efforts in many human cancer types. However, only a subset of mutations found within the genomic landscape of cancer is likely to provide a fitness advantage to the cell. Distinguishing such “driver’ mutations from innocuous “passenger” events is critical for prioritizing the validation of candidate mutations in disease-relevant models. Here we propose a novel statistical index, called the Hitchhiking Index, which reflects the probability that any observed candidate gene is a passenger alteration, given the frequency of alterations in a cross-sectional cancer sample set. Our methodology is based upon a evolutionary population-dynamics model of mutation accumulation and selection in the tissue prior to cancer initiation as well as during tumorigenesis.

Monday, July 28th, 2014
2:30 – 3pm
Arkes Pavilion
676 N. Saint Clair St. Suite 1300

KEVIN LEDER, Ph.D.
Assistant Professor of Industrial and Systems Engineering The University of Minnesota
Title: Mathematical Modeling and OptimalFractionationated Irradiation for Proneural Glioblastomas
Bio: Dr. Leder is an assistant professor in Industrial and Systems Engineering at University of Minnesota.
He is interested in stochastic process models of cancer evolution, and the use of these models to investigate important biological questions regarding the initiation, progression and treatment of cancer. In addition he is interested in the study of rare events in stochastic systems. Previously, he was a postdoc at Dana Farber Cancer Institute and the Department of Industrial Engineering and Operations Research at Columbia, and received his PhD in 2008 from the Department of Applied Mathematics at Brown University. As an undergraduate, he attended the University of Colorado at Boulder and majored in Applied Math.
Abstract: Glioblastomas (GBM) are the most common and malignant primary tumors of the brain and are commonly treated with radiation therapy. Despite modest advances in chemotherapy and radiation, survival has changed very little over the last 50 years. Radiation therapy is one of the pillars of adjuvant therapy for GBM but despite treatment, recurrence inevitably occurs. Here we develop a mathematical model for the tumor response to radiation that takes into account the plasticity of the hierarchical structure of the tumor population. Based on this mathematical model we develop an optimized radiation delivery schedule. This strategy was validated to be superior in mice and nearly doubled the efficacy of each Gray of radiation administered. Time permitting I will also discuss recent extensions of this work that consider the impact of including normal tissue toxicity constraints. This is based on joint work with Hamidreza Badri, Ken Pitter, Eric Holland, and Franziska Michor.

Written on July 23rd, 2014. 0 Comments


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