The major problem in therapy of acute myeloid leukemia (AML), like most cancers, is therapeutic resistance. Although >85% of patients respond to chemotherapy, over half will relapse. Chemotherapeutic resistance implies heterogeneity among cancer cells. Two hypotheses exist to explain this heterogeneity. The stem cell hypothesis proposes a functional heterogeneity within an ordered structure in which the bulk of leukemic cells differentiate from leukemic stem cells (LSC). In this model, LSCs are intrinsically resistant to chemotherapy. Consequently, relapsed tumors arise from LSCs and their genetic diversity will reflect that of the original tumor. As such, chemotherapeutics are targeted toward the genetic lesion found within the LSC. The clonal evolution model proposes that there is heritable variation between cells, some or all of which have the potential to form a new tumor. External stressors, such as chemotherapeutics, apply evolutionary stress on the entire population, driving clonal evolution and selecting for resistant clones. In this model, (epi)genetic diversity in the original tumor will increase the probability of chemoresistance, due to the wider repertoire of mutations that could provide a selective advantage. Moreover, as tumor cells evolve and develop new mechanisms of resistance, the profile of genetic and epigenetic lesions in the relapsed tumor continues to change. Accordingly, optimal therapy will require a mix of therapeutics with diverse mechanistic bases. Here, we will test our hypothesis that chemotherapy resistance in AML is best modeled by clonal evolution and utilize our results to better understand the mechanism(s) of chemotherapy resistance in AML.
In Specific Aim 1, we will use a novel xenotransplantation model of AML to determine empiricially if LSCs are enriched after chemotherapy.
In Specific Aim 2, we will use innovative single cell approaches to characterize a cohort of 30 AML paired samples (de novo diagnosis vs. relapse) for clonal diversity to determine if therapy selects for clones.
In Specific Aim 3, we will perform an exploratory study to determine if clonal diversity (as measured by a novel emulsion bisulfite sequencing (BBS) assay) predicts the probability of relapse in AML patients.
Specific Aim 4 will identify and confirm gene mutations that are selected by chemotherapy, by performing RNA sequencing and SNP arrays to compare the level of expression, sequence of expressed genes and copy number alterations between the de novo and relapsed AML from 30 matched pairs of patient samples. Through these diverse approaches, we will test the several features of the LSC vs. clonal evolution models of chemotherapy resistance. These results will have important implications for the development of novel therapeutics for AML, the treatment of chemoresistant disease and the prevention of relapse.
Acute myeloid leukemia (AML) is a malignant disease of the blood which affects almost thirteen thousand Americans each year and leads to death of approximately 10,000 people per year. The disease is refractory to chemotherapy but the mechanism of chemotherapy resistance is not understood. In this application, we will study the mechanism of chemotherapy resistance in AML in order to develop better therapy for AML.
|Li, Sheng; Garrett-Bakelman, Francine; Perl, Alexander E et al. (2014) Dynamic evolution of clonal epialleles revealed by methclone. Genome Biol 15:472|
|Sanchez, P V; Glantz, S T; Scotland, S et al. (2014) Induced differentiation of acute myeloid leukemia cells by activation of retinoid X and liver X receptors. Leukemia 28:749-60|
|Alcock, Joe; Maley, Carlo C; Aktipis, C Athena (2014) Is eating behavior manipulated by the gastrointestinal microbiota? Evolutionary pressures and potential mechanisms. Bioessays 36:940-9|
|Wertheim, Gerald B W; Smith, Catherine; Figueroa, Maria E et al. (2014) Microsphere-based multiplex analysis of DNA methylation in acute myeloid leukemia. J Mol Diagn 16:207-15|
|Im, A P; Sehgal, A R; Carroll, M P et al. (2014) DNMT3A and IDH mutations in acute myeloid leukemia and other myeloid malignancies: associations with prognosis and potential treatment strategies. Leukemia 28:1774-83|
|Li, Sheng; ?abaj, Pawe? P; Zumbo, Paul et al. (2014) Detecting and correcting systematic variation in large-scale RNA sequencing data. Nat Biotechnol 32:888-95|
|Scotland, S; Saland, E; Skuli, N et al. (2013) Mitochondrial energetic and AKT status mediate metabolic effects and apoptosis of metformin in human leukemic cells. Leukemia 27:2129-38|
|Sprouffske, Kathleen; Athena Aktipis, C; Radich, Jerald P et al. (2013) An evolutionary explanation for the presence of cancer nonstem cells in neoplasms. Evol Appl 6:92-101|
|Carroll, Martin; Borden, Katherine L B (2013) The oncogene eIF4E: using biochemical insights to target cancer. J Interferon Cytokine Res 33:227-38|
|Kostadinov, Rumen L; Kuhner, Mary K; Li, Xiaohong et al. (2013) NSAIDs modulate clonal evolution in Barrett's esophagus. PLoS Genet 9:e1003553|
Showing the most recent 10 out of 12 publications