City of Hope PS-OP
Information Flow and State Transitions at the System and Multi-Dimensional Scales in Leukemia Progression
Cancer begins as a disease of the genome, with DNA mutations initiating a cascade of events that lead to cancer progression. As single or small collection of cells undergo state transitions to become cancer cells (and ultimately evolve into a malignant neoplasm), the immune system is activated and new vasculature is formed.
This process involves the flow and transfer of information across multiple scales in time and space. Information is encoded within and transferred between cells and across multiple genomic scales that may be detected at the system’s level. Our hypothesis is that information contained in one or multiple genomic landscapes can be used to detect oncogenic perturbations and predict response to therapy.
It has been shown that mutations associated with acute myeloid leukemia (AML) can be detected years before the onset of disease; However, they do not predict when the disease will manifest or response to treatment. Nevertheless, these sets of mutations can be characterized by distinct gene expression signatures collectively representing perturbations underlying the observed clinical phenotypes.
PS-OP researchers are validating a mathematical model that considers genome-wide gene activity as state transition from a healthy state to a cancer state from the perspectives of mRNAs, non-coding microRNAs, and DNA methylation. The theory and mathematics of state transitions is well known in the systems biology community and is a powerful tool for interpreting and predicting the behavior of complex systems, such as genomics and cancer biology.
The central hypothesis of this project is that information produced during a biological process can be detected from different viewpoints (i.e., transcriptome, miRome, epigenome) such that information contained in one viewpoint of the genomic landscape can be mapped into another. Further, it considers that disease development and progression can be interpreted and predicted with mathematical models of information flow in a multidimensional genomic space.
The PS-OP is investigating three specific aims:
- Parameterize a mathematical model of multi-dimensional state transition.
- Quantify the impact of treatment on state transition dynamics and develop a model of therapy response and relapse in a controlled AML mouse model.
- Characterize the information contained in the transcriptome, miRome, and epigenome state-spaces in both mouse and human samples.
Through an iterative dialog between biological experiments and mathematical modeling, this work will provide insight into perturbations contributing to leukemia initiation and progression. Ultimately, it will guide the design of new therapies targeting pathways at critical state-transition points.
Russell Rockne, Ph.D.
City of Hope
Dr. Russell Rockne is an Assistant Professor and Director of the Division of Mathematical Oncology in the Department of Computational and Quantitative Medicine at City of Hope. His research lies at the interface of precision medicine, data science, and mathematical modeling. Dr. Rockne’s research approach uses mathematical models to connect data from multiple modalities and scales to predict cancer growth and response to therapy.
He has made contributions to mathematical model parameterization and applications, with patented algorithms as well as first and senior author level peer reviewed publications in the field of Mathematical Oncology. The aim of Dr. Rockne’s research is to bring mathematics into the clinic to help improve outcomes for patients with cancer.
Ya-Huei Kuo, Ph.D.
Emory Vaccine Center
Dr. Ya Huei Kuo is an Associate Professor in the Department of Hematologic Malignancies Translational Science. Her long-term research goals are to unravel the mechanisms driving malignant cell transformation and maintenance, and to develop mechanism-based targeted therapies. She has established a conditional Cbfb-MYH11 knock-in mouse model that mimics somatic acquisition of a common AML-associated chromosomal aberration, inv(16)(p13.1q22) or t(16;16)(p13.1;q22). Dr. Kuo demonstrated that this model represents a pertinent experimental system to dissect pre-malignant perturbations, genetic modifiers, disease dynamics and evaluation of therapeutic response relevant to human disease.
Leukemia stem cell (LSC) are recognized as the critical leukemia-initiating cells, which are resistant to chemotherapy and contribute to refractory disease and subsequent relapse. Dr. Kuo has made contributions to uncover novel mechanisms underlying LSC transformation and persistence and identify therapeutic targets aimed at eliminating LSC and improving patient outcome.
Guido Marcucci, M.D.
City of Hope
Dr. Guido Marcucci is Chair and Professor, Department of Hematologic Malignancies Translational Science; Director, Gehr Family Center for Leukemia Research, and Professor in the Department of Hematology & Hematopoietic Cell Transplantation. In addition to being a practicing clinician in medical oncology and stem cell transplantation, he has extensive research experience in basic, translational and clinical research in leukemia, specifically AML and myelodysplastic syndrome (MDS).
Over the years, Dr. Marcucci has focused on drug development and discovery of basic mechanisms of leukemogenesis, novel therapeutic targets and epigenetic and genetic prognostic biomarkers in AML. He has chaired several Phase I, II and III single and multi-institutional clinical trials within the Oncology Cooperative Group Alliance, and currently serves as the vice-chair of the Leukemia Committee and a member of the Leukemia Correlative Science Committee. Dr. Marcucci is also the director of the City of Hope Hematopoietic Tissue Bank