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Chronic myeloid leukemia (CML) is initiated and maintained by BCR::ABL which is clinically targeted using tyrosine kinase inhibitors (TKIs). TKIs can induce long-term remission but are also not curative. Thus, CML is an ideal system to test our hypothesis that transcriptome-based state-transition models accurately predict cancer evolution and treatment response. We collected time-sequential blood samples from tetracycline-off (Tet-Off) BCR::ABL-inducible transgenic mice and wild-type controls. From the transcriptome, we constructed a CML state-space and a three-well leukemogenic potential landscape. The potential's stable critical points defined observable disease states. Early states were characterized by anti-CML genes opposing leukemia; late states were characterized by pro-CML genes. Genes with expression patterns shaped similarly to the potential landscape were identified as drivers of disease transition. Re-introduction of tetracycline to silence the BCR::ABL gene returned diseased mice transcriptomes to a near healthy state, without reaching it, suggesting parts of the transition are irreversible. TKI only reverted the transcriptome to an intermediate disease state, without approaching a state of health; disease relapse occurred soon after treatment. Using only the earliest time-point as initial conditions, our state-transition models accurately predicted both disease progression and treatment response, supporting this as a potentially valuable approach to time clinical intervention, before phenotypic changes become detectable.

MicroRNAs (miRNAs) have been shown to hold prognostic value in acute myeloid leukemia (AML); however, the temporal dynamics of miRNA expression in AML are poorly understood. Using serial samples from a mouse model of AML to generate time-series miRNA sequencing data, we are the first to show that the miRNA transcriptome undergoes state-transition during AML initiation and progression. We modeled AML state-transition as a particle undergoing Brownian motion in a quasi-potential and validated the AML state-space and state-transition model to accurately predict time to AML in an independent cohort of mice. The critical points of the model provided a framework to align samples from mice that developed AML at different rates. Our mathematical approach allowed discovery of dynamic processes involved during AML development and, if translated to humans, has the potential to predict an individual's disease trajectory.

BackgroundDuring acute myeloid leukemia (AML) growth, the bone marrow (BM) niche acquires significant vascular changes that can be offset by therapeutic blast cytoreduction. The molecular mechanisms of this vascular plasticity remain to be fully elucidated. Herein, we report on the changes that occur in the vascular compartment of the FLT3-ITD+ AML BM niche pre and post treatment and their impact on leukemic stem cells (LSCs).MethodsBM vasculature was evaluated in FLT3-ITD+ AML models (MllPTD/WT/Flt3ITD/ITD mouse and patient-derived xenograft) by 3D confocal imaging of long bones, calvarium vascular permeability assays, and flow cytometry analysis. Cytokine levels were measured by Luminex assay and miR-126 levels evaluated by Q-RT-PCR and miRNA staining. Wild-type (wt) and MllPTD/WT/Flt3ITD/ITD mice with endothelial cell (EC) miR-126 knockout or overexpression served as controls. The impact of treatment-induced BM vascular changes on LSC activity was evaluated by secondary transplantation of BM cells after administration of tyrosine kinase inhibitors (TKIs) to MllPTD/WT/Flt3ITD/ITD mice with/without either EC miR-126 KO or co-treatment with tumor necrosis factor alpha (TNFα) or anti-miR-126 miRisten.ResultsIn the normal BM niche, CD31+Sca-1high ECs lining arterioles have miR-126 levels higher than CD31+Sca-1low ECs lining sinusoids. We noted that during FLT3-ITD+ AML growth, the BM niche lost arterioles and gained sinusoids. These changes were mediated by TNFα, a cytokine produced by AML blasts, which induced EC miR-126 downregulation and caused depletion of CD31+Sca-1high ECs and gain in CD31+Sca-1low ECs. Loss of miR-126high ECs led to a decreased EC miR-126 supply to LSCs, which then entered the cell cycle and promoted leukemia growth. Accordingly, antileukemic treatment with TKI decreased the BM blast-produced TNFα and increased miR-126high ECs and the EC miR-126 supply to LSCs. High miR-126 levels safeguarded LSCs, as shown by more severe disease in secondary transplanted mice. Conversely, EC miR-126 deprivation via genetic or pharmacological EC miR-126 knock-down prevented treatment-induced BM miR-126high EC expansion and in turn LSC protection.ConclusionsTreatment-induced CD31+Sca-1high EC re-vascularization of the leukemic BM niche may represent a LSC extrinsic mechanism of treatment resistance that can be overcome with therapeutic EC miR-126 deprivation.

Temporal dynamics of gene expression inform cellular and molecular perturbations associated with disease development and evolution. Given the complexity of high-dimensional temporal genomic data, an analytic framework guided by a robust theory is needed to interpret time-sequential changes and to predict system dynamics. Here we model temporal dynamics of the transcriptome of peripheral blood mononuclear cells in a two-dimensional state-space representing states of health and leukemia using time-sequential bulk RNA-seq data from a murine model of acute myeloid leukemia (AML). The state-transition model identified critical points that accurately predict AML development and identifies stepwise transcriptomic perturbations that drive leukemia progression. The geometry of the transcriptome state-space provided a biological interpretation of gene dynamics, aligned gene signals that are not synchronized in time across mice, and allowed quantification of gene and pathway contributions to leukemia development. Our state-transition model synthesizes information from multiple cell types in the peripheral blood and identifies critical points in the transition from health to leukemia to guide interpretation of changes in the transcriptome as a whole to predict disease progression. SIGNIFICANCE: These findings apply the theory of state transitions to model the initiation and development of acute myeloid leukemia, identifying transcriptomic perturbations that accurately predict time to disease development.See related commentary by Kuijjer, p. 3072 GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/15/3157/F1.large.jpg.

DNA methylation is a well-established epigenetic mark, whose pattern throughout the genome, especially in the promoter or CpG islands, may be modified in a cell at a disease stage. Recently developed probabilistic approaches allow distributing methylation signals at nucleotide resolution from MethylCap-seq data. Standard statistical methods for detecting differential methylation suffer from 'curse of dimensionality' and sparsity in signals, resulting in high false-positive rates. Strong correlation of signals between CG sites also yields spurious results. In this article, we review applicability of highdimensional mean vector tests for detection of differentially methylated regions (DMRs) and compare and contrast such tests with other methods for detecting DMRs. Comprehensive simulation studies are conducted to highlight the performance of these tests under different settings. Based on our observation, we make recommendations on the optimal test to use. We illustrate the superiority of mean vector tests in detecting cancer-related canonical gene pathways, which are significantly enriched for acute myeloid leukemia and ovarian cancer. [ABSTRACT FROM AUTHOR]

Background: Cancer cachexia is a debilitating condition that impacts patient morbidity, mortality, and quality of life and for which effective therapies are lacking. The anticachectic activity of the novel HDAC inhibitor AR-42 was investigated in murine models of cancer cachexia.Methods: The effects of AR-42 on classic features of cachexia were evaluated in the C-26 colon adenocarcinoma and Lewis lung carcinoma (LLC) models. Effects on survival in comparison with approved HDAC inhibitors (vorinostat, romidepsin) were determined. The muscle metabolome and transcriptome (by RNA-seq), as well as serum cytokine profile, were evaluated. Data were analyzed using mixed effects models, analysis of variance, or log-rank tests. All statistical tests were two-sided.Results: In the C-26 model, orally administered AR-42 preserved body weight (23.9±2.6 grams, AR-42-treated; 20.8±1.3 grams, vehicle-treated; P = .005), prolonged survival (P < .001), prevented reductions in muscle and adipose tissue mass, muscle fiber size, and muscle strength and restored intramuscular mRNA expression of the E3 ligases MuRF1 and Atrogin-1 to basal levels (n = 8). This anticachectic effect, confirmed in the LLC model, was not observed after treatment with vorinostat and romidepsin. AR-42 suppressed tumor-induced changes in inflammatory cytokine production and multiple procachexia drivers (IL-6, IL-6Rα, leukemia inhibitory factor, Foxo1, Atrogin-1, MuRF1, adipose triglyceride lipase, uncoupling protein 3, and myocyte enhancer factor 2c). Metabolomic analysis revealed cachexia-associated changes in glycolysis, glycogen synthesis, and protein degradation in muscle, which were restored by AR-42 to a state characteristic of tumor-free mice.Conclusions: These findings support further investigation of AR-42 as part of a comprehensive therapeutic strategy for cancer cachexia. [ABSTRACT FROM AUTHOR]

Background: Increasing evidence suggests the unique susceptibility of estrogen receptor and progesterone receptor negative (ERPR-) breast cancer to dietary fat amount and type. Dietary n-3 polyunsaturated fatty acids (PUFAs), such as docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), may modulate breast adipose fatty acid profiles and downstream bioactive metabolites to counteract pro-inflammatory, pro-carcinogenic signaling in the mammary microenvironment., Objective: To determine effects of ~1 to 5 g/d EPA+DHA over 12 months on breast adipose fatty acid and oxylipin profiles in women with ERPR(-) breast cancer, a high-risk molecular subtype., Methods: We conducted a 12-month randomized controlled, double-blind clinical trial of ~5g/d vs ~1g/d DHA+EPA supplementation in women within 5 years of completing standard therapy for ERPR(-) breast cancer Stages 0-III. Blood and breast adipose tissue specimens were collected every 3 months for biomarker analyses including fatty acids by gas chromatography, oxylipins by LC-MS/MS, and DNA methylation by reduced-representation bisulfite sequencing (RRBS)., Results: A total of 51 participants completed the 12-month intervention. Study treatments were generally well-tolerated. While both doses increased n-3 PUFAs from baseline in breast adipose, erythrocytes, and plasma, the 5g/d supplement was more potent (n =51, p <0.001). The 5g/d dose also reduced plasma triglycerides from baseline (p =0.008). Breast adipose oxylipins at 0, 6, and 12 months showed dose-dependent increases in unesterified and esterified DHA and EPA metabolites (n =28). Distinct DNA methylation patterns in adipose tissue after 12 months were identified, with effects unique to the 5g/d dose group (n =17)., Conclusions: Over the course of 1 year, EPA+DHA dose-dependently increased concentrations of these fatty acids and their derivative oxylipin metabolites, producing differential DNA methylation profiles of gene promoters involved in metabolism-related pathways critical to ERPR(-) breast cancer development and progression. These data provide evidence of both metabolic and epigenetic effects of n-3 PUFAs in breast adipose tissue, elucidating novel mechanisms of action for high-dose EPA+DHA-mediated prevention of ERPR(-) breast cancer., Competing Interests: The authors declare no potential conflicts of interest.

Chronic myeloid leukemia (CML) is initiated and maintained by BCR::ABL which is clinically targeted using tyrosine kinase inhibitors (TKIs). TKIs can induce long-term remission but are also not curative. Thus, CML is an ideal system to test our hypothesis that transcriptome-based state-transition models accurately predict cancer evolution and treatment response. We collected time-sequential blood samples from tetracycline-off (Tet-Off) BCR::ABL-inducible transgenic mice and wild-type controls. From the transcriptome, we constructed a CML state-space and a three-well leukemogenic potential landscape. The potential's stable critical points defined observable disease states. Early states were characterized by anti-CML genes opposing leukemia; late states were characterized by pro-CML genes. Genes with expression patterns shaped similarly to the potential landscape were identified as drivers of disease transition. Re-introduction of tetracycline to silence the BCR::ABL gene returned diseased mice transcriptomes to a near healthy state, without reaching it, suggesting parts of the transition are irreversible. TKI only reverted the transcriptome to an intermediate disease state, without approaching a state of health; disease relapse occurred soon after treatment. Using only the earliest time-point as initial conditions, our state-transition models accurately predicted both disease progression and treatment response, supporting this as a potentially valuable approach to time clinical intervention even before phenotypic changes become detectable.