Dynamic combinatorial interactions of RUNX1 and cooperating partners regulates megakaryocytic differentiation in cell line models.

Specific interactions of transcription factors (TFs) with their targets are crucial for specifying gene expression programs during cell differentiation. How specificity is maintained despite limited selectivity of individual TF-DNA interactions is not fully understood. RUNX1 TF is among the most frequently mutated genes in human leukemia and an important regulator of megakaryopoiesis. We used megakaryocytic cell lines to characterize the network of RUNX1 targets and cooperating TFs in differentiating megakaryocytes and demonstrated how dynamic partnerships between RUNX1 and cooperating TFs facilitated regulatory plasticity and specificity during this process. After differentiation onset, RUNX1 directly activated a large number of genes through interaction with preexisting and de novo binding sites. Recruitment of RUNX1 to de novo occupied sites occurred at H3K4me1-marked preprogrammed enhancers. A significant number of these de novo bound sites lacked RUNX motif but were occupied by AP-1 TFs. Reciprocally, AP-1 TFs were up-regulated by RUNX1 after 12-O-tetradecanoylphorbol-13-acetate induction and recruited to RUNX1-occupied sites lacking AP-1 motifs. At other differentiation stages, additional combinatorial interactions occurred between RUNX1 and its coregulators, GATA1 and ETS. The findings suggest that in differentiating megakaryocytic cell lines, RUNX1 cooperates with GATA1, AP-1, and ETS to orchestrate cell-specific transcription programs through dynamic TF partnerships.

Arterial Thromboembolism in Patients With AF and CHA2DS2-VASc Score 0-2 With and Without Cancer.

Background: It is unclear whether newly diagnosed cancer adds to the risk of arterial thromboembolism (ATE) in patients with atrial fibrillation/flutter (AF). This is especially relevant for AF patients with low to intermediate CHA2DS2-VASc scores in whom the risk-benefit ratios between ATE and bleeding are delicately balanced. Objectives: The objectives were to evaluate the ATE risk in AF patients with a CHA2DS2-VASc score of 0 to 2 with and without cancer. Methods: A population-based retrospective cohort study was performed. Patients with a CHA2DS2-VASc score of 0 to 2 not receiving anticoagulation at cancer diagnosis (or the matched index date) were included. Patients with embolic ATE or cancer before study index were excluded. AF patients were categorized into AF and cancer and AF and no cancer cohorts. Cohorts were matched for multinomial distribution of age, sex, index year, AF duration, CHA2DS2-VASc score, and low/high/undefined ATE risk cancer. Patients were followed from study index until the primary outcome or death. The primary outcome was acute ATE (ischemic stroke, transient ischemic attack, or systemic ATE) at 12 months using International Classification of Diseases-Ninth Revision codes from hospitalization. The Fine-Gray competing risk model was used to estimate the HR for ATE with death as a competing risk. Results: The 12-month cumulative incidence of ATE was 2.13% (95% CI: 1.47-2.99) in 1,411 AF patients with cancer and 0.8% (95% CI: 0.56-1.10) in 4,233 AF patients without cancer (HR: 2.70; 95% CI: 1.65-4.41). The risk was highest in men with CHA2DS2-VASc = 1 and women with CHA2DS2-VASc = 2 (HR: 6.07; 95% CI: 2.45-15.01). Conclusions: In AF patients with CHA2DS2-VASc scores of 0 to 2, newly diagnosed cancer is associated with an increased incidence of stroke, transient ischemic attack, or systemic ATE compared with matched controls without cancer.

Personalized lab test models to quantify disease potentials in healthy individuals.

Standardized lab tests are central for patient evaluation, differential diagnosis and treatment. Interpretation of these data is nevertheless lacking quantitative and personalized metrics. Here we report on the modeling of 2.1 billion lab measurements of 92 different lab tests from 2.8 million adults over a span of 18 years. Following unsupervised filtering of 131 chronic conditions and 5,223 drug-test pairs we performed a virtual survey of lab tests distributions in healthy individuals. Age and sex alone explain less than 10% of the within-normal test variance in 89 out of 92 tests. Personalized models based on patients' history explain 60% of the variance for 17 tests and over 36% for half of the tests. This allows for systematic stratification of the risk for future abnormal test levels and subsequent emerging disease. Multivariate modeling of within-normal lab tests can be readily implemented as a basis for quantitative patient evaluation.

Cell-autonomous function of Runx1 transcriptionally regulates mouse megakaryocytic maturation.

RUNX1 transcription factor (TF) is a key regulator of megakaryocytic development and when mutated is associated with familial platelet disorder and predisposition to acute myeloid leukemia (FPD-AML). We used mice lacking Runx1 specifically in megakaryocytes (MK) to characterized Runx1-mediated transcriptional program during advanced stages of MK differentiation. Gene expression and chromatin-immunoprecipitation-sequencing (ChIP-seq) of Runx1 and p300 identified functional Runx1 bound MK enhancers. Runx1/p300 co-bound regions showed significant enrichment in genes important for MK and platelet homeostasis. Runx1 occupied genomic regions were highly enriched in RUNX and ETS motifs and to a lesser extent in GATA motif. Megakaryocytic specificity of Runx1/P300 bound enhancers was validated by transfection mutagenesis and Runx1/P300 co-bound regions of two key megakaryocytic genes Nfe2 and Selp were tested by in vivo transgenesis. The data provides the first example of genome wide Runx1/p300 occupancy in maturating primary FL-MK, unravel the Runx1-regulated program controlling MK maturation in vivo and identify a subset of its bona fide regulated genes. It advances our understanding of the molecular events that upon RUNX1mutations in human lead to the predisposition to familial platelet disorders and FPD-AML.