GSE133642
State-Transition Analysis of Time-Sequential Gene Expression Identifies Critical Points That Predict Leukemia Development
Temporal dynamics of gene expression are informative of changes associated with disease development and evolution. Given the complexity of high-dimensionaltemporal datasets, an analytical framework guided by a robust theory is needed to interpret time-sequential changes and to predict system dynamics. Herein, we use acute myeloid leukemia as a proof-of-principle to model gene expression dynamics in a transcriptome state-space constructed based on time-sequential RNA-sequencing data. We describe the construction of a state-transition model to identify state-transition critical points which accurately predicts leukemia development. We show an analytical approach based on state-transition critical points identifies step-wise transcriptomic perturbations driving leukemia progression. Furthermore, the gene(s) trajectory and geometry of the transcriptome state-space provides biologically-relevant gene expression signals that are not synchronized in time, and allows quantification of gene(s) contribution to leukemia development. Therefore, our state-transition model can synthesize information, identify critical points to guide interpretation of transcriptome trajectories and predict disease development. Overall design: We conducted a longitudinal study in a mouse AML model induced by the Cbfb-MYH11 (CM) oncogene to observe the temporal evolution of the transcriptome from healthy state to leukemia state. In the conditional CM knock-in mouse model (Cbfb+/56MMx1Cre), expression of CM in the adult bone marrow alters normal hematopoietic differentiation creating aberrant pre-leukemic progenitor cells which acquire additional genetic, epigenetic alterations needed for malignant transformation and AML development. In a cohort of CM mice (Cbfb+/56MMx1Cre; N=7) and littermate controls (Ctrl; N=7) lacking one or both transgenes (Cbfb+/56M or  Mx1Cre), peripheral blood was sampled prior to and following CM induction (by poly (I:C) treatment) monthly for up to 10 months (or when mice were moribund with leukemia). Blood samples were subjected to bulk RNA-sequencing and flow cytometry analysis.