Transcriptome free energy can serve as a dynamic patient-specific biomarker in acute myeloid leukemia.

Acute myeloid leukemia (AML) is prevalent in both adult and pediatric patients. Despite advances in patient categorization, the heterogeneity of AML remains a challenge. Recent studies have explored the use of gene expression data to enhance AML diagnosis and prognosis, however, alternative approaches rooted in physics and chemistry may provide another level of insight into AML transformation. Utilizing publicly available databases, we analyze 884 human and mouse blood and bone marrow samples. We employ a personalized medicine strategy, combining state-transition theory and surprisal analysis, to assess the RNA transcriptome of individual patients. The transcriptome is transformed into physical parameters that represent each sample's steady state and the free energy change (FEC) from that steady state, which is the state with the lowest free energy.We found the transcriptome steady state was invariant across normal and AML samples. FEC, representing active molecular processes, varied significantly between samples and was used to create patient-specific barcodes to characterize the biology of the disease. We discovered that AML samples that were in a transition state had the highest FEC. This disease state may be characterized as the most unstable and hence the most therapeutically targetable since a change in free energy is a thermodynamic requirement for disease progression. We also found that distinct sets of ongoing processes may be at the root of otherwise similar clinical phenotypes, implying that our integrated analysis of transcriptome profiles may facilitate a personalized medicine approach to cure AML and restore a steady state in each patient.

State-transition modeling of blood transcriptome predicts disease evolution and treatment response in chronic myeloid leukemia.

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.

Targeting PRMT9-mediated arginine methylation suppresses cancer stem cell maintenance and elicits cGAS-mediated anticancer immunity.

Current anticancer therapies cannot eliminate all cancer cells, which hijack normal arginine methylation as a means to promote their maintenance via unknown mechanisms. Here we show that targeting protein arginine N-methyltransferase 9 (PRMT9), whose activities are elevated in blasts and leukemia stem cells (LSCs) from patients with acute myeloid leukemia (AML), eliminates disease via cancer-intrinsic mechanisms and cancer-extrinsic type I interferon (IFN)-associated immunity. PRMT9 ablation in AML cells decreased the arginine methylation of regulators of RNA translation and the DNA damage response, suppressing cell survival. Notably, PRMT9 inhibition promoted DNA damage and activated cyclic GMP-AMP synthase, which underlies the type I IFN response. Genetically activating cyclic GMP-AMP synthase in AML cells blocked leukemogenesis. We also report synergy of a PRMT9 inhibitor with anti-programmed cell death protein 1 in eradicating AML. Overall, we conclude that PRMT9 functions in survival and immune evasion of both LSCs and non-LSCs; targeting PRMT9 may represent a potential anticancer strategy.

State-transition Modeling of Blood Transcriptome Predicts Disease Evolution and Treatment Response in Chronic Myeloid Leukemia.

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.

Acquired miR-142 deficit in leukemic stem cells suffices to drive chronic myeloid leukemia into blast crisis.

The mechanisms underlying the transformation of chronic myeloid leukemia (CML) from chronic phase (CP) to blast crisis (BC) are not fully elucidated. Here, we show lower levels of miR-142 in CD34+CD38- blasts from BC CML patients than in those from CP CML patients, suggesting that miR-142 deficit is implicated in BC evolution. Thus, we create miR-142 knockout CML (i.e., miR-142-/-BCR-ABL) mice, which develop BC and die sooner than miR-142 wt CML (i.e., miR-142+/+BCR-ABL) mice, which instead remain in CP CML. Leukemic stem cells (LSCs) from miR-142-/-BCR-ABL mice recapitulate the BC phenotype in congenic recipients, supporting LSC transformation by miR-142 deficit. State-transition and mutual information analyses of "bulk" and single cell RNA-seq data, metabolomic profiling and functional metabolic assays identify enhanced fatty acid ß-oxidation, oxidative phosphorylation and mitochondrial fusion in LSCs as key steps in miR-142-driven BC evolution. A synthetic CpG-miR-142 mimic oligodeoxynucleotide rescues the BC phenotype in miR-142-/-BCR-ABL mice and patient-derived xenografts.

Proteomics and mathematical modeling of longitudinal CSF differentiates fast versus slow ALS progression.

OBJECTIVE: Amyotrophic lateral sclerosis (ALS) is a heterogeneous disease with a complex etiology that lacks biomarkers predicting disease progression. The objective of this study was to use longitudinal cerebrospinal fluid (CSF) samples to identify biomarkers that distinguish fast progression (FP) from slow progression (SP) and assess their temporal response. METHODS: We utilized mass spectrometry (MS)-based proteomics to identify candidate biomarkers using longitudinal CSF from a discovery cohort of SP and FP ALS patients. Immunoassays were used to quantify and validate levels of the top biomarkers. A state-transition mathematical model was created using the longitudinal MS data that also predicted FP versus SP. RESULTS: We identified a total of 1148 proteins in the CSF of all ALS patients. Pathway analysis determined enrichment of pathways related to complement and coagulation cascades in FPs and synaptogenesis and glucose metabolism in SPs. Longitudinal analysis revealed a panel of 59 candidate markers that could segregate FP and SP ALS. Based on multivariate analysis, we identified three biomarkers (F12, RBP4, and SERPINA4) as top candidates that segregate ALS based on rate of disease progression. These proteins were validated in the discovery and a separate validation cohort. Our state-transition model determined that the overall variance of the proteome over time was predictive of the disease progression rate. INTERPRETATION: We identified pathways and protein biomarkers that distinguish rate of ALS disease progression. A mathematical model of the CSF proteome determined that the change in entropy of the proteome over time was predictive of FP versus SP.

Comparison of cell state models derived from single-cell RNA sequencing data: graph versus multi-dimensional space.

Single-cell sequencing technologies have revolutionized molecular and cellular biology and stimulated the development of computational tools to analyze the data generated from these technology platforms. However, despite the recent explosion of computational analysis tools, relatively few mathematical models have been developed to utilize these data. Here we compare and contrast two cell state geometries for building mathematical models of cell state-transitions with single-cell RNA-sequencing data with hematopoeisis as a model system; (i) by using partial differential equations on a graph representing intermediate cell states between known cell types, and (ii) by using the equations on a multi-dimensional continuous cell state-space. As an application of our approach, we demonstrate how the calibrated models may be used to mathematically perturb normal hematopoeisis to simulate, predict, and study the emergence of novel cell states during the pathogenesis of acute myeloid leukemia. We particularly focus on comparing the strength and weakness of the graph model and multi-dimensional model.

Arsenic Trioxide and Venetoclax Synergize against AML Progenitors by ROS Induction and Inhibition of Nrf2 Activation.

Venetoclax (VEN) in combination with hypomethylating agents induces disease remission in patients with de novo AML, however, most patients eventually relapse. AML relapse is attributed to the persistence of drug-resistant leukemia stem cells (LSCs). LSCs need to maintain low intracellular levels of reactive oxygen species (ROS). Arsenic trioxide (ATO) induces apoptosis via upregulation of ROS-induced stress to DNA-repair mechanisms. Elevated ROS levels can trigger the Nrf2 antioxidant pathway to counteract the effects of high ROS levels. We hypothesized that ATO and VEN synergize in targeting LSCs through ROS induction by ATO and the known inhibitory effect of VEN on the Nrf2 antioxidant pathway. Using cell fractionation, immunoprecipitation, RNA-knockdown, and fluorescence assays we found that ATO activated nuclear translocation of Nrf2 and increased transcription of antioxidant enzymes, thereby attenuating the induction of ROS by ATO. VEN disrupted ATO-induced Nrf2 translocation and augmented ATO-induced ROS, thus enhancing apoptosis in LSCs. Using metabolic assays and electron microscopy, we found that the ATO+VEN combination decreased mitochondrial membrane potential, mitochondria size, fatty acid oxidation and oxidative phosphorylation, all of which enhanced apoptosis of LSCs derived from both VEN-sensitive and VEN-resistant AML primary cells. Our results indicate that ATO and VEN cooperate in inducing apoptosis of LSCs through potentiation of ROS induction, suggesting ATO+VEN is a promising regimen for treatment of VEN-sensitive and -resistant AML.

MicroRNA networks in FLT3-ITD acute myeloid leukemia.

MiR-126 and miR-155 are key microRNAs (miRNAs) that regulate, respectively, hematopoietic cell quiescence and proliferation. Herein we showed that in acute myeloid leukemia (AML), the biogenesis of these two miRNAs is interconnected through a network of regulatory loops driven by the FMS-like tyrosine kinase 3-internal tandem duplication (FLT3-ITD). In fact, FLT3-ITD induces the expression of miR-155 through a noncanonical mechanism of miRNA biogenesis that implicates cytoplasmic Drosha ribonuclease III (DROSHA). In turn, miR-155 down-regulates SH2-containing inositol phosphatase 1 (SHIP1), thereby increasing phosphor-protein kinase B (AKT) that in turn serine-phosphorylates, stabilizes, and activates Sprouty related EVH1 domain containing 1 (SPRED1). Activated SPRED1 inhibits the RAN/XPO5 complex and blocks the nucleus-to-cytoplasm transport of pre-miR-126, which cannot then complete the last steps of biogenesis. The net result is aberrantly low levels of mature miR-126 that allow quiescent leukemia blasts to be recruited into the cell cycle and proliferate. Thus, miR-126 down-regulation in proliferating AML blasts is downstream of FLT3-ITD­dependent miR-155 expression that initiates a complex circuit of concatenated regulatory feedback (i.e., miR-126/SPRED1, miR-155/human dead-box protein 3 [DDX3X]) and feed-forward (i.e., miR-155/SHIP1/AKT/miR-126) regulatory loops that eventually converge into an output signal for leukemic growth.

Disruption of dNTP homeostasis by ribonucleotide reductase hyperactivation overcomes AML differentiation blockade.

Differentiation blockade is a hallmark of acute myeloid leukemia (AML). A strategy to overcome such a blockade is a promising approach against the disease. The lack of understanding of the underlying mechanisms hampers development of such strategies. Dysregulated ribonucleotide reductase (RNR) is considered a druggable target in proliferative cancers susceptible to deoxynucleoside triphosphate (dNTP) depletion. Herein, we report an unanticipated discovery that hyperactivating RNR enables differentiation and decreases leukemia cell growth. We integrate pharmacogenomics and metabolomics analyses to identify that pharmacologically (eg, nelarabine) or genetically upregulating RNR subunit M2 (RRM2) creates a dNTP pool imbalance and overcomes differentiation arrest. Moreover, R-loop-mediated DNA replication stress signaling is responsible for RRM2 activation by nelarabine treatment. Further aggravating dNTP imbalance by depleting the dNTP hydrolase SAM domain and HD domain-containing protein 1 (SAMHD1) enhances ablation of leukemia stem cells by RRM2 hyperactivation. Mechanistically, excessive activation of extracellular signal-regulated kinase (ERK) signaling downstream of the imbalance contributes to cellular outcomes of RNR hyperactivation. A CRISPR screen identifies a synthetic lethal interaction between loss of DUSP6, an ERK-negative regulator, and nelarabine treatment. These data demonstrate that dNTP homeostasis governs leukemia maintenance, and a combination of DUSP inhibition and nelarabine represents a therapeutic strategy.

Dynamic patterns of microRNA expression during acute myeloid leukemia state-transition.

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.

Programmable siRNA pro-drugs that activate RNAi activity in response to specific cellular RNA biomarkers.

Since Paul Ehrlich's introduction of the "magic bullet" concept in 1908, drug developers have been seeking new ways to target drug activity to diseased cells while limiting effects on normal tissues. In recent years, it has been proposed that coupling riboswitches capable of detecting RNA biomarkers to small interfering RNAs (siRNAs) to create siRNA pro-drugs could selectively activate RNA interference (RNAi) activity in specific cells. However, this concept has not been achieved previously. We report here that we have accomplished this goal, validating a simple and programmable new design that functions reliably in mammalian cells. We show that these conditionally activated siRNAs (Cond-siRNAs) can switch RNAi activity against different targets between clearly distinguished OFF and ON states in response to different cellular RNA biomarkers. Notably, in a rat cardiomyocyte cell line (H9C2), one version of our construct demonstrated biologically meaningful inhibition of a heart-disease-related target gene protein phosphatase 3 catalytic subunit alpha (PPP3CA) in response to increased expression of the pathological marker atrial natriuretic peptide (NPPA) messenger RNA (mRNA). Our results demonstrate the ability of synthetic riboswitches to regulate gene expression in mammalian cells, opening a new path for development of programmable siRNA pro-drugs.

Roadmap on plasticity and epigenetics in cancer.

The role of plasticity and epigenetics in shaping cancer evolution and response to therapy has taken center stage with recent technological advances including single cell sequencing. This roadmap article is focused on state-of-the-art mathematical and experimental approaches to interrogate plasticity in cancer, and addresses the following themes and questions: is there a formal overarching framework that encompasses both non-genetic plasticity and mutation-driven somatic evolution? How do we measure and model the role of the microenvironment in influencing/controlling non-genetic plasticity? How can we experimentally study non-genetic plasticity? Which mathematical techniques are required or best suited? What are the clinical and practical applications and implications of these concepts?

Targeting miR-126 in inv(16) acute myeloid leukemia inhibits leukemia development and leukemia stem cell maintenance.

Acute myeloid leukemia (AML) harboring inv(16)(p13q22) expresses high levels of miR-126. Here we show that the CBFB-MYH11 (CM) fusion gene upregulates miR-126 expression through aberrant miR-126 transcription and perturbed miR-126 biogenesis via the HDAC8/RAN-XPO5-RCC1 axis. Aberrant miR-126 upregulation promotes survival of leukemia-initiating progenitors and is critical for initiating and maintaining CM-driven AML. We show that miR-126 enhances MYC activity through the SPRED1/PLK2-ERK-MYC axis. Notably, genetic deletion of miR-126 significantly reduces AML rate and extends survival in CM knock-in mice. Therapeutic depletion of miR-126 with an anti-miR-126 (miRisten) inhibits AML cell survival, reduces leukemia burden and leukemia stem cell (LSC) activity in inv(16) AML murine and xenograft models. The combination of miRisten with chemotherapy further enhances the anti-leukemia and anti-LSC activity. Overall, this study provides molecular insights for the mechanism and impact of miR-126 dysregulation in leukemogenesis and highlights the potential of miR-126 depletion as a therapeutic approach for inv(16) AML.

Targeting miR-126 disrupts maintenance of myelodysplastic syndrome stem and progenitor cells.

BACKGROUND: Myelodysplastic syndrome (MDS) arises from a rare population of aberrant hematopoietic stem and progenitor cells (HSPCs). These cells are relatively quiescent and therefore treatment resistant. Understanding mechanisms underlying their maintenance is critical for effective MDS treatment. METHODS: We evaluated microRNA-126 (miR-126) levels in MDS patients' sample and in a NUP98-HOXD13 (NHD13) murine MDS model along with their normal controls and defined its role in MDS HSPCs' maintenance by inhibiting miR-126 expression in vitro and in vivo. Identification of miR-126 effectors was conducted using biotinylated miR-126 pulldown coupled with transcriptome analysis. We also tested the therapeutic activity of our anti-miR-126 oligodeoxynucleotide (miRisten) in human MDS xenografts and murine MDS models. RESULTS: miR-126 levels were higher in bone marrow mononuclear cells from MDS patients and NHD13 mice relative to their respective normal controls (P < 0.001). Genetic deletion of miR-126 in NHD13 mice decreased quiescence and self-renewal capacity of MDS HSPCs, and alleviated MDS symptoms of NHD13 mice. Ex vivo exposure to miRisten increased cell cycling, reduced colony-forming capacity, and enhanced apoptosis in human MDS HSPCs, but spared normal human HSPCs. In vivo miRisten administration partially reversed pancytopenia in NHD13 mice and blocked the leukemic transformation (combination group vs DAC group, P < 0.0001). Mechanistically, we identified the non-coding RNA PTTG3P as a novel miR-126 target. Lower PTTG3P levels were associated with a shorter overall survival in MDS patients. CONCLUSIONS: MiR-126 plays crucial roles in MDS HSPC maintenance. Therapeutic targeting of miR-126 is a potentially novel approach in MDS.

Treatment-induced arteriolar revascularization and miR-126 enhancement in bone marrow niche protect leukemic stem cells in AML.

BACKGROUND: During 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). METHODS: BM 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. RESULTS: In 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. CONCLUSIONS: Treatment-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.

Cytoplasmic DROSHA and non-canonical mechanisms of MiR-155 biogenesis in FLT3-ITD acute myeloid leukemia.

We report here on a novel pro-leukemogenic role of FMS-like tyrosine kinase 3-internal tandem duplication (FLT3-ITD) that interferes with microRNAs (miRNAs) biogenesis in acute myeloid leukemia (AML) blasts. We showed that FLT3-ITD interferes with the canonical biogenesis of intron-hosted miRNAs such as miR-126, by phosphorylating SPRED1 protein and inhibiting the "gatekeeper" Exportin 5 (XPO5)/RAN-GTP complex that regulates the nucleus-to-cytoplasm transport of pre-miRNAs for completion of maturation into mature miRNAs. Of note, despite the blockage of "canonical" miRNA biogenesis, miR-155 remains upregulated in FLT3-ITD+ AML blasts, suggesting activation of alternative mechanisms of miRNA biogenesis that circumvent the XPO5/RAN-GTP blockage. MiR-155, a BIC-155 long noncoding (lnc) RNA-hosted oncogenic miRNA, has previously been implicated in FLT3-ITD+ AML blast hyperproliferation. We showed that FLT3-ITD upregulates miR-155 by inhibiting DDX3X, a protein implicated in the splicing of lncRNAs, via p-AKT. Inhibition of DDX3X increases unspliced BIC-155 that is then shuttled by NXF1 from the nucleus to the cytoplasm, where it is processed into mature miR-155 by cytoplasmic DROSHA, thereby bypassing the XPO5/RAN-GTP blockage via "non-canonical" mechanisms of miRNA biogenesis.

State-Transition Analysis of Time-Sequential Gene Expression Identifies Critical Points That Predict Development of Acute Myeloid Leukemia.

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.