Although knowledge ofthe target of transformation Is important for an understanding ofthe natural history of cancers and has therapeutic implications, the cell of origin of most cancers is still unknown. As preliminary data, we have designed a stochastic mathematical model of stem and progenitor cells to study the evolutionary dynamics of initiation of JAK2V617F-positive myeloproliferative neoplasms (MPNs). We considered different evolutionary pathways in order to investigate which cell is the most likely cell of origin of JAK2V617F-mutant MPN. (i) The JAK2V617F mutation is acquired in a hematopoietic stem cell;(ii) a progenitor cell may first acquire a mutation conferring self-renewal, followed by acquisition of JAK2V617F;(iii) the JAK2V617F mutation first emerges in a progenitor cell, followed by a mutation conferring self-renewal;and (iv) a mutation conferring self-renewal to progenitors arises in the stem cell population without causing a change in the cell's phenotype, followed by the JAK2V617F mutation emerging in a progenitor cell. We found mathematical evidence that a progenitor is the most likely cell of origin of JAK2V617F-mutant MPN. In this project, we aim to 1) test the predictions of the mathematical framework in mouse models of JAK2-positive MPN and use this data to further refine the model;2) design a mathematical framework to investigate the cell of origin of glioma stem cells;we will consider three different mutations leading to glioma formation: a mutation causing overexpression of PDGF and genetic alterations inactivating both alleles of the tumor suppressors PTEN and ARF. We will design stochastic mathematical models to investigate which cell is the most likely cell of origin of glioma. These investigations will also involve detailed three-dimensional computer simulations of glioma formation to investigate spatial as well as temporal aspects of tumorigenesis;and 3) validate the predictions and further refine the mathematical model with data derived from murine models of glioma which allow for expression of the known pathogenic mutations in the appropriate stem/progenitor cell compartments.
Knowledge of the cell of origin of human cancers will allow us to develop more accurate genetic models and to improve our understanding of the biology of these neoplasms. We will then use these in vivo models to better elucidate the pathogenesis of the diseases and to better understand whether the cell of origin might explain the limited benefits of therapies for these disorders.
|Han, Lin; Zi, Xiaoyuan; Garmire, Lana X et al. (2014) Co-detection and sequencing of genes and transcripts from the same single cells facilitated by a microfluidics platform. Sci Rep 4:6485|
|Dunn, Gavin P; Cheung, Hiu Wing; Agarwalla, Pankaj K et al. (2014) In vivo multiplexed interrogation of amplified genes identifies GAB2 as an ovarian cancer oncogene. Proc Natl Acad Sci U S A 111:1102-7|
|Singh, Tanya; Kothapalli, Chandrasekhar; Varma, Devika et al. (2014) Carboxymethylcellulose hydrogels support central nervous system-derived tumor-cell chemotactic migration: comparison with conventional extracellular matrix macromolecules. J Biomater Appl 29:433-41|
|Meador, Catherine B; Micheel, Christine M; Levy, Mia A et al. (2014) Beyond histology: translating tumor genotypes into clinically effective targeted therapies. Clin Cancer Res 20:2264-75|
|Marusyk, Andriy; Tabassum, Doris P; Altrock, Philipp M et al. (2014) Non-cell-autonomous driving of tumour growth supports sub-clonal heterogeneity. Nature 514:54-8|
|Foo, Jasmine; Michor, Franziska (2014) Evolution of acquired resistance to anti-cancer therapy. J Theor Biol 355:10-20|
|Tkach, Karen E; Oyler, Jennifer E; Altan-Bonnet, Grégoire (2014) Cracking the NF-?B code. Sci Signal 7:pe5|
|Guo, Shangqin; Zi, Xiaoyuan; Schulz, Vincent P et al. (2014) Nonstochastic reprogramming from a privileged somatic cell state. Cell 156:649-62|
|Leder, Kevin; Pitter, Ken; Laplant, Quincey et al. (2014) Mathematical modeling of PDGF-driven glioblastoma reveals optimized radiation dosing schedules. Cell 156:603-16|
|Elitas, Meltem; Brower, Kara; Lu, Yao et al. (2014) A microchip platform for interrogating tumor-macrophage paracrine signaling at the single-cell level. Lab Chip 14:3582-8|
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