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.

https://www.omagdigital.com/publication/?i=189294&p=3
pgs 517-523

The Article made the cover of June 2014 Issue!

https://neuro-oncology.oxfordjournals.org/content/current

https://www.nucats.northwestern.edu/about/newsroom-content/2013-news/december-2013/2014-dixon-translational-research-grant-awards-announced.html

The Mathematical Neuro-Oncology Research Lab Presents:

JACOB G. SCOTT, MD
Departments of Radiation Oncology and Integrated Mathematical Oncology
H. Lee Moffitt Cancer Center

Mathematical modeling of glioma cancer stem cell evolutionary dynamics and the non-genetic determinants of the metastatic process

Monday, April 14th, 2014
11am – 12 noon
Arkes Pavilion,
676 n. Saint Clair St. Suite 1300
Mathematical Neuro-Oncology Lab

Jacob Scott is a research associate in the department of radiation oncology at H. Lee Moffitt Cancer Center in Tampa Florida and is currently working on a Doctoral degree in mathematics at Oxford University at the Centre for Mathematical Biology. Dr. Scott began his academic career in the fields of physics and engineering before entering medical school. As a trained clinician and scientist, Dr. Scott pursues a combination of basic and clinical research with the hope that each motivates and strengthens the other.

The focus of Dr. Scott’s research is building theoretical models of cancer with Integrative Mathematical Oncology – a group headed by Alexander (Sandy) Anderson, Ph.D. that focuses on applying mathematical and evolutionary models to the study of cancer. Dr. Scott finds that spending time doing a combination of theoretical cancer research and patient care keeps him thinking outside the box in the clinic, but keeps theoretical questions grounded to ideas that can be translated to patient care.

Dr. Scott is active in social media. Follow him on twitter at
@CancerConnector

Modeling tumor-associated edema in gliomas during anti-angiogenic therapy and its impact on imageable tumor

• ¹Department of Neurological Surgery, Northwestern University, Chicago, IL, USA
• ²Integrated Mathematical Oncology, Moffitt Cancer Center, Tampa, FL, USA

Glioblastoma, the most aggressive form of primary brain tumor, is predominantly assessed with gadolinium-enhanced T1-weighted (T1Gd) and T2-weighted magnetic resonance imaging (MRI). Pixel intensity enhancement on the T1Gd image is understood to correspond to the gadolinium contrast agent leaking from the tumor-induced neovasculature, while hyperintensity on the T2/FLAIR images corresponds with edema and infiltrated tumor cells. None of these modalities directly show tumor cells; rather, they capture abnormalities in the microenvironment caused by the presence of tumor cells. Thus, assessing disease response after treatments impacting the microenvironment remains challenging through the obscuring lens of MR imaging. Anti-angiogenic therapies have been used in the treatment of gliomas with spurious results ranging from no apparent response to significant imaging improvement with the potential for extremely diffuse patterns of tumor recurrence on imaging and autopsy. Anti-angiogenic treatment normalizes the vasculature, effectively decreasing vessel permeability and thus reducing tumor-induced edema, drastically altering T2-weighted MRI. We extend a previously developed mathematical model of glioma growth to explicitly incorporate edema formation allowing us to directly characterize and potentially predict the effects of anti-angiogenics on imageable tumor growth. A comparison of simulated glioma growth and imaging enhancement with and without bevacizumab supports the current understanding that anti-angiogenic treatment can serve as a surrogate for steroids and the clinically driven hypothesis that anti-angiogenic treatment may not have any significant effect on the growth dynamics of the overall tumor cell populations. However, the simulations do illustrate a potentially large impact on the level of edematous extracellular fluid, and thus on what would be imageable on T2/FLAIR MR. Additionally, by evaluating virtual tumors with varying growth kinetics, we see tumors with lower proliferation rates will have the most reduction in swelling from such treatments.

https://www.frontiersin.org/Molecular_and_Cellular_Oncology/10.3389/fonc.2013.00066/abstract

Dr. Pamela Jackson just received the “Research Supplement to Promote Diversity in Health-Related Research” .

Congratulations to Russ Rockne who successfully defended his dissertation “Toward Patient-Specific Mathematical Radiation Oncology”!!