Cancer Biology & Evolution (CBE) is a first-in-kind CCSG Program that emerged from systematic in-house collaborations of mathematicians, evolutionary biologists, and basic and clinical cancer researchers. Although these research teams investigate cancer via traditional means, they include mathematicians and theorists who integrate multi-scalar data through quantitative models founded on evolutionary first principles. Specifically, the CBE integrates the genocentric focus of conventional cancer research into broader Darwinian dynamics where: (i) evolution selects for cellular adaptive phenotypes that emerge in complex ways from both mutations and changes in the expression of normal genes; and (ii) the fitness of each cancer cell is dependent on environmental context and will vary with temporal and spatial changes in the tumor milieu. Mathematicians play critical roles in the CBE Program by deconvoluting the nonlinear dynamics that are manifest in complex open systems such as cancer and by developing and applying mathematical models and computer simulations. The unique scientific ?ecosystem? of the CBE has driven the formation of innovative multidisciplinary teams that are investigating virtually every aspect of cancer biology and therapy through a quantitative evolutionary lens. The overall goals of CBE are to investigate and define the complex dynamics that govern the biology and therapeutic responses of cancer, and to deliver new agents and strategies to prevent and treat refractory or relapsed malignancies. Specifically, CBE Members: (i) generate and apply sophisticated experimental models and methods to define and quantify spatial and temporal dynamics of molecular, cellular, and tissue properties during cancer development, progression, metastasis, and treatment (Aim 1); (ii) develop and test theoretical models, which are based on evolution by natural selection and are parameterized by experimental data, to define cancer dynamics and inform new strategies for control and treatment (Aim 2); and (iii) design new studies and clinical trials that test model predictions, to deliver effective, adaptive therapies into the clinic, and to refine the understanding of cancer biology and therapy (Aim 3). CBE teams have implemented these goals through: (i) combining in vivo and in silico models to understand, prevent and treat metastasis; (ii) targeting never genes, i.e., genes where mutations are never or rarely observed, to produce a durable treatment response; (iii) exploiting tumor dynamics to ?steer? cancers toward a less invasive evolutionary trajectory; (iv) modeling tumor evolutionary strategies that result in therapy resistance; and (v) mathematical models that have been translated into adaptive, personalized clinical trials. The CBE Program has 24 members from nine different academic departments. During the past funding cycle, CBE Members have published 399 cancer- related articles, with 22% representing intra-programmatic publications and 32% being inter-programmatic publications. Total annual grant funding for the CBE Program is robust and is currently at $9.1 million; $8.2 million is peer-reviewed, including $6.3 million from NCI.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Center Core Grants (P30)
Project #
5P30CA076292-20
Application #
9419807
Study Section
Subcommittee I - Transistion to Independence (NCI)
Project Start
Project End
Budget Start
2018-02-01
Budget End
2019-01-31
Support Year
20
Fiscal Year
2018
Total Cost
Indirect Cost
Name
H. Lee Moffitt Cancer Center & Research Institute
Department
Type
DUNS #
139301956
City
Tampa
State
FL
Country
United States
Zip Code
33612
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Gjyshi, Anxhela; Dash, Sweta; Cen, Ling et al. (2018) Early transcriptional response of human ovarian and fallopian tube surface epithelial cells to norepinephrine. Sci Rep 8:8291
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Hampras, Shalaka S; Locke, Frederick L; Chavez, Julio C et al. (2018) Prevalence of cutaneous viral infections in incident cutaneous squamous cell carcinoma detected among chronic lymphocytic leukemia and hematopoietic stem cell transplant patients. Leuk Lymphoma 59:911-917
Kim, Youngchul; Pierce, Christine M; Robinson, Lary A (2018) Impact of viral presence in tumor on gene expression in non-small cell lung cancer. BMC Cancer 18:843
Persi, Erez; Duran-Frigola, Miquel; Damaghi, Mehdi et al. (2018) Systems analysis of intracellular pH vulnerabilities for cancer therapy. Nat Commun 9:2997

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