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.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Center Core Grants (P30)
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Subcommittee I - Transistion to Independence (NCI)
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H. Lee Moffitt Cancer Center & Research Institute
United States
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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
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
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
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
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
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
Kasting, Monica L; Christy, Shannon M; Sutton, Steven K et al. (2018) Florida physicians' reported use of AFIX-based strategies for human papillomavirus vaccination. Prev Med 116:143-149
Phadke, Manali; Remsing Rix, Lily L; Smalley, Inna et al. (2018) Dabrafenib inhibits the growth of BRAF-WT cancers through CDK16 and NEK9 inhibition. Mol Oncol 12:74-88
Park, Jae H; Rivière, Isabelle; Gonen, Mithat et al. (2018) Long-Term Follow-up of CD19 CAR Therapy in Acute Lymphoblastic Leukemia. N Engl J Med 378:449-459
Jiang, Kun; Neill, Kevin; Cowden, Daniel et al. (2018) Expression of CAS/CSE1L, the Cellular Apoptosis Susceptibility Protein, Correlates With Neoplastic Progression in Barrett's Esophagus. Appl Immunohistochem Mol Morphol 26:552-556

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