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 #
5P30CA076292-21
Application #
9637361
Study Section
Subcommittee I - Transistion to Independence (NCI)
Project Start
Project End
Budget Start
2019-02-01
Budget End
2020-01-31
Support Year
21
Fiscal Year
2019
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
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
Rosenberger, Albert; Hung, Rayjean J; Christiani, David C et al. (2018) Genetic modifiers of radon-induced lung cancer risk: a genome-wide interaction study in former uranium miners. Int Arch Occup Environ Health 91:937-950
Chen, Yan; Zhu, Jin-Yi; Hong, Kwon Ho et al. (2018) Structural Basis of ALDH1A2 Inhibition by Irreversible and Reversible Small Molecule Inhibitors. ACS Chem Biol 13:582-590
Kahen, Elliot John; Brohl, Andrew; Yu, Diana et al. (2018) Neurofibromin level directs RAS pathway signaling and mediates sensitivity to targeted agents in malignant peripheral nerve sheath tumors. Oncotarget 9:22571-22585
Hoffman, Melissa A; Fang, Bin; Haura, Eric B et al. (2018) Comparison of Quantitative Mass Spectrometry Platforms for Monitoring Kinase ATP Probe Uptake in Lung Cancer. J Proteome Res 17:63-75
Puri, Sonam; Hyland, Kelly A; Weiss, Kristine Crowe et al. (2018) Prediction of chemotherapy-induced nausea and vomiting from patient-reported and genetic risk factors. Support Care Cancer 26:2911-2918
Gonzalez, Brian D; Small, Brent J; Cases, Mallory G et al. (2018) Sleep disturbance in men receiving androgen deprivation therapy for prostate cancer: The role of hot flashes and nocturia. Cancer 124:499-506
Eroglu, Zeynep; Zaretsky, Jesse M; Hu-Lieskovan, Siwen et al. (2018) High response rate to PD-1 blockade in desmoplastic melanomas. Nature 553:347-350
Lu, Yingchang; Beeghly-Fadiel, Alicia; Wu, Lang et al. (2018) A Transcriptome-Wide Association Study Among 97,898 Women to Identify Candidate Susceptibility Genes for Epithelial Ovarian Cancer Risk. Cancer Res 78:5419-5430

Showing the most recent 10 out of 1254 publications