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 #
5U54CA193461-03
Application #
9265434
Study Section
Special Emphasis Panel (ZCA1-TCRB-5)
Project Start
Project End
Budget Start
2017-05-01
Budget End
2018-04-30
Support Year
3
Fiscal Year
2017
Total Cost
$475,338
Indirect Cost
$120,904
Name
Dana-Farber Cancer Institute
Department
Type
Independent Hospitals
DUNS #
076580745
City
Boston
State
MA
Country
United States
Zip Code
02215
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
Han, Lin; Wu, Hua-Jun; Zhu, Haiying et al. (2017) Bisulfite-independent analysis of CpG island methylation enables genome-scale stratification of single cells. Nucleic Acids Res 45:e77
McDonald, Thomas O; Michor, Franziska (2017) SIApopr: a computational method to simulate evolutionary branching trees for analysis of tumor clonal evolution. Bioinformatics 33:2221-2223
Smith, Kyle S; Liu, Lin L; Ganesan, Shridar et al. (2017) Nuclear topology modulates the mutational landscapes of cancer genomes. Nat Struct Mol Biol 24:1000-1006
Amankulor, Nduka M; Kim, Youngmi; Arora, Sonali et al. (2017) Mutant IDH1 regulates the tumor-associated immune system in gliomas. Genes Dev 31:774-786
Mishima, Yuji; Paiva, Bruno; Shi, Jiantao et al. (2017) The Mutational Landscape of Circulating Tumor Cells in Multiple Myeloma. Cell Rep 19:218-224
Yu, H A; Sima, C; Feldman, D et al. (2017) Phase 1 study of twice weekly pulse dose and daily low-dose erlotinib as initial treatment for patients with EGFR-mutant lung cancers. Ann Oncol 28:278-284

Showing the most recent 10 out of 36 publications