Acute myeloid leukemia (AML) is rapidly fatal, poorly controlled disease that can be rapidly brought into complete remission but where relapse kills the vast majority of patients. The genetic evolution of the disease has been defined retrospectively, but the basis for resistance to therapy and effective strategies to overcome it are lacking. This project seeks to take advantage of well-defined mouse models where a human leukemogenic allele induces highly penetrant, lethal AML that can be temporarily brought into remission by chemotherapy agents used in patients. Combining these basic biologic features with novel strategies for quantitatively assessing clonal behavior, clonal molecular features, physical localization and the in vivo parameters of growth pathway, cell cycle and apoptosis over time will provide multidimensional datasets for mathematical modeling of the parameters correlating with: 1. Clonal dominance in vivo (Specific Aim 1) and, 2. Sensitivity/resistance to chemotherapy in vivo (Specific Aim 2). The models will guide experimental testing of the role of the parameters in the in vivo behavior of the disease that will then be used to develop and test methods for enhancing durable control of AML (Specific Aim 3).

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54CA193461-02
Application #
9152270
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Hanlon, Sean E
Project Start
Project End
Budget Start
2016-05-01
Budget End
2017-04-30
Support Year
2
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Dana-Farber Cancer Institute
Department
Type
DUNS #
076580745
City
Boston
State
MA
Country
United States
Zip Code
Ozawa, Tatsuya; Arora, Sonali; Szulzewsky, Frank et al. (2018) A De Novo Mouse Model of C11orf95-RELA Fusion-Driven Ependymoma Identifies Driver Functions in Addition to NF-?B. Cell Rep 23:3787-3797
Cimino, Patrick J; Kim, Youngmi; Wu, Hua-Jun et al. (2018) Increased HOXA5 expression provides a selective advantage for gain of whole chromosome 7 in IDH wild-type glioblastoma. Genes Dev 32:512-523
Stein, Shayna; Zhao, Rui; Haeno, Hiroshi et al. (2018) Mathematical modeling identifies optimum lapatinib dosing schedules for the treatment of glioblastoma patients. PLoS Comput Biol 14:e1005924
Hinohara, Kunihiko; Wu, Hua-Jun; Vigneau, Sébastien et al. (2018) KDM5 Histone Demethylase Activity Links Cellular Transcriptomic Heterogeneity to Therapeutic Resistance. Cancer Cell 34:939-953.e9
Maley, Carlo C; Aktipis, Athena; Graham, Trevor A et al. (2017) Classifying the evolutionary and ecological features of neoplasms. Nat Rev Cancer 17:605-619
Dasgupta, Arko; Lim, Andrea R; Ghajar, Cyrus M (2017) Circulating and disseminated tumor cells: harbingers or initiators of metastasis? Mol Oncol 11:40-61
Gil Del Alcazar, Carlos R; Huh, Sung Jin; Ekram, Muhammad B et al. (2017) Immune Escape in Breast Cancer During In Situ to Invasive Carcinoma Transition. Cancer Discov 7:1098-1115
Kievit, Forrest M; Wang, Kui; Ozawa, Tatsuya et al. (2017) Nanoparticle-mediated knockdown of DNA repair sensitizes cells to radiotherapy and extends survival in a genetic mouse model of glioblastoma. Nanomedicine 13:2131-2139
Pattwell, Siobhan S; Holland, Eric C (2017) Putting Glioblastoma in Its Place: IRF3 Inhibits Invasion. Trends Mol Med 23:773-776
Peinado, Héctor; Zhang, Haiying; Matei, Irina R et al. (2017) Pre-metastatic niches: organ-specific homes for metastases. Nat Rev Cancer 17:302-317

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