Sequential drug treatment targeting cell cycle and cell fate regulatory programs blocks non-genetic cancer evolution in acute lymphoblastic leukemia.

BACKGROUND: Targeted therapies exploiting vulnerabilities of cancer cells hold promise for improving patient outcome and reducing side-effects of chemotherapy. However, efficacy of precision therapies is limited in part because of tumor cell heterogeneity. A better mechanistic understanding of how drug effect is linked to cancer cell state diversity is crucial for identifying effective combination therapies that can prevent disease recurrence. RESULTS: Here, we characterize the effect of G2/M checkpoint inhibition in acute lymphoblastic leukemia (ALL) and demonstrate that WEE1 targeted therapy impinges on cell fate decision regulatory circuits. We find the highest inhibition of recovery of proliferation in ALL cells with KMT2A-rearrangements. Single-cell RNA-seq and ATAC-seq of RS4;11 cells harboring KMT2A::AFF1, treated with the WEE1 inhibitor AZD1775, reveal diversification of cell states, with a fraction of cells exhibiting strong activation of p53-driven processes linked to apoptosis and senescence, and disruption of a core KMT2A-RUNX1-MYC regulatory network. In this cell state diversification induced by WEE1 inhibition, a subpopulation transitions to a drug tolerant cell state characterized by activation of transcription factors regulating pre-B cell fate, lipid metabolism, and pre-BCR signaling in a reversible manner. Sequential treatment with BCR-signaling inhibitors dasatinib, ibrutinib, or perturbing metabolism by fatostatin or AZD2014 effectively counteracts drug tolerance by inducing cell death and repressing stemness markers. CONCLUSIONS: Collectively, our findings provide new insights into the tight connectivity of gene regulatory programs associated with cell cycle and cell fate regulation, and a rationale for sequential administration of WEE1 inhibitors with low toxicity inhibitors of pre-BCR signaling or metabolism.

Oral and non-oral lichen planus show genetic heterogeneity and differential risk for autoimmune disease and oral cancer.

Lichen planus (LP) is a T-cell-mediated inflammatory disease affecting squamous epithelia in many parts of the body, most often the skin and oral mucosa. Cutaneous LP is usually transient and oral LP (OLP) is most often chronic, so we performed a large-scale genetic and epidemiological study of LP to address whether the oral and non-oral subgroups have shared or distinct underlying pathologies and their overlap with autoimmune disease. Using lifelong records covering diagnoses, procedures, and clinic identity from 473,580 individuals in the FinnGen study, genome-wide association analyses were conducted on carefully constructed subcategories of OLP (n = 3,323) and non-oral LP (n = 4,356) and on the combined group. We identified 15 genome-wide significant associations in FinnGen and an additional 12 when meta-analyzed with UKBB (27 independent associations at 25 distinct genomic locations), most of which are shared between oral and non-oral LP. Many associations coincide with known autoimmune disease loci, consistent with the epidemiologic enrichment of LP with hypothyroidism and other autoimmune diseases. Notably, a third of the FinnGen associations demonstrate significant differences between OLP and non-OLP. We also observed a 13.6-fold risk for tongue cancer and an elevated risk for other oral cancers in OLP, in agreement with earlier reports that connect LP with higher cancer incidence. In addition to a large-scale dissection of LP genetics and comorbidities, our study demonstrates the use of comprehensive, multidimensional health registry data to address outstanding clinical questions and reveal underlying biological mechanisms in common but understudied diseases.

Distinct and shared genetic architectures of gestational diabetes mellitus and type 2 diabetes.

Gestational diabetes mellitus (GDM) is a common metabolic disorder affecting more than 16 million pregnancies annually worldwide1,2. GDM is related to an increased lifetime risk of type 2 diabetes (T2D)1-3, with over a third of women developing T2D within 15 years of their GDM diagnosis. The diseases are hypothesized to share a genetic predisposition1-7, but few studies have sought to uncover the genetic underpinnings of GDM. Most studies have evaluated the impact of T2D loci only8-10, and the three prior genome-wide association studies of GDM11-13 have identified only five loci, limiting the power to assess to what extent variants or biological pathways are specific to GDM. We conducted the largest genome-wide association study of GDM to date in 12,332 cases and 131,109 parous female controls in the FinnGen study and identified 13 GDM-associated loci, including nine new loci. Genetic features distinct from T2D were identified both at the locus and genomic scale. Our results suggest that the genetics of GDM risk falls into the following two distinct categories: one part conventional T2D polygenic risk and one part predominantly influencing mechanisms disrupted in pregnancy. Loci with GDM-predominant effects map to genes related to islet cells, central glucose homeostasis, steroidogenesis and placental expression.

Genome-Wide Association Study Identifies 4 Novel Risk Loci for Small Intestinal Neuroendocrine Tumors Including a Missense Mutation in LGR5.

BACKGROUND & AIMS: Small intestinal neuroendocrine tumor (SI-NET) is a rare disease, but its incidence has increased over the past 4 decades. Understanding the genetic risk factors underlying SI-NETs can help in disease prevention and may provide clinically beneficial markers for diagnosis. Here the results of the largest genome-wide association study of SI-NETs performed to date with 405 cases and 614,666 controls are reported. METHODS: Samples from 307 patients with SI-NETs and 287,137 controls in the FinnGen study were used for the identification of SI-NET risk-associated genetic variants. The results were also meta-analyzed with summary statistics from the UK Biobank (n = 98 patients with SI-NET and n = 327,529 controls). RESULTS: We identified 6 genome-wide significant (P < 5 × 10-8) loci associated with SI-NET risk, of which 4 (near SEMA6A, LGR5, CDKAL1, and FERMT2) are novel and 2 (near LTA4H-ELK and in KIF16B) have been reported previously. Interestingly, the top hit (rs200138614; P = 1.80 × 10-19) was a missense variant (p.Cys712Phe) in the LGR5 gene, a bona-fide marker of adult intestinal stem cells and a potentiator of canonical WNT signaling. The association was validated in an independent Finnish collection of 70 patients with SI-NETs, as well as in the UK Biobank exome sequence data (n = 92 cases and n = 392,814 controls). Overexpression of LGR5 p.Cys712Phe in intestinal organoids abolished the ability of R-Spondin1 to support organoid growth, indicating that the mutation perturbed R-Spondin-LGR5 signaling. CONCLUSIONS: Our study is the largest genome-wide association study to date on SI-NETs and reported 4 new associated genome-wide association study loci, including a novel missense mutation (rs200138614, p.Cys712Phe) in LGR5, a canonical marker of adult intestinal stem cells.

Overlap of Genetic Loci for Central Serous Chorioretinopathy With Age-Related Macular Degeneration.

Importance: Central serous chorioretinopathy (CSC) is a serous maculopathy of unknown etiology. Two of 3 previously reported CSC genetic risk loci are also associated with AMD. Improved understanding of CSC genetics may broaden our understanding of this genetic overlap and unveil mechanisms in both diseases. Objective: To identify novel genetic risk factors for CSC and compare genetic risk factors for CSC and AMD. Design, Setting, and Participants: Using International Classification of Diseases, Ninth (ICD-9) and Tenth (ICD-10) Revision code-based inclusion and exclusion criteria, patients with CSC and controls were identified in both the FinnGen study and the Estonian Biobank (EstBB). Also included in a meta-analysis were previously reported patients with chronic CSC and controls. Data were analyzed from March 1 to September 31, 2022. Main Outcomes and Measures: Genome-wide association studies (GWASs) were performed in the biobank-based cohorts followed by a meta-analysis of all cohorts. The expression of genes prioritized by the polygenic priority score and nearest-gene methods were assessed in cultured choroidal endothelial cells and public ocular single-cell RNA sequencing data sets. The predictive utility of polygenic scores (PGSs) for CSC and AMD were evaluated in the FinnGen study. Results: A total of 1176 patients with CSC and 526 787 controls (312 162 female [59.3%]) were included in this analysis: 552 patients with CSC and 343 461 controls were identified in the FinnGen study, 103 patients with CSC and 178 573 controls were identified in the EstBB, and 521 patients with chronic CSC and 3577 controls were included in a meta-analysis. Two previously reported CSC risk loci were replicated (near CFH and GATA5) and 3 novel loci were identified (near CD34/46, NOTCH4, and PREX1). The CFH and NOTCH4 loci were associated with AMD but in the opposite direction. Prioritized genes showed increased expression in cultured choroidal endothelial cells compared with other genes in the loci (median [IQR] of log 2 [counts per million], 7.3 [0.6] vs 4.7 [3.7]; P = .004) and were differentially expressed in choroidal vascular endothelial cells in single-cell RNA sequencing data (mean [SD] fold change, 2.05 [0.38] compared with other cell types; P < 7.1 × 10-20). A PGS for AMD was predictive of reduced CSC risk (odds ratio, 0.76; 95% CI, 0.70-0.83 per +1 SD in AMD-PGS; P = 7.4 × 10-10). This association may have been mediated by loci containing complement genes. Conclusions and Relevance: In this 3-cohort genetic association study, 5 genetic risk loci for CSC were identified, highlighting a likely role for genes involved in choroidal vascular function and complement regulation. Results suggest that polygenic AMD risk was associated with reduced risk of CSC and that this genetic overlap was largely due to loci containing complement genes.

Inflammatory and infectious upper respiratory diseases associate with 41 genomic loci and type 2 inflammation.

Inflammatory and infectious upper respiratory diseases (ICD-10: J30-J39), such as diseases of the sinonasal tract, pharynx and larynx, are growing health problems yet their genomic similarity is not known. We analyze genome-wide association to eight upper respiratory diseases (61,195 cases) among 260,405 FinnGen participants, meta-analyzing diseases in four groups based on an underlying genetic correlation structure. Aiming to understand which genetic loci contribute to susceptibility to upper respiratory diseases in general and its subtypes, we detect 41 independent genome-wide significant loci, distinguishing impact on sinonasal or pharyngeal diseases, or both. Fine-mapping implicated non-synonymous variants in nine genes, including three linked to immune-related diseases. Phenome-wide analysis implicated asthma and atopic dermatitis at sinonasal disease loci, and inflammatory bowel diseases and other immune-mediated disorders at pharyngeal disease loci. Upper respiratory diseases also genetically correlated with autoimmune diseases such as rheumatoid arthritis, autoimmune hypothyroidism, and psoriasis. Finally, we associated separate gene pathways in sinonasal and pharyngeal diseases that both contribute to type 2 immunological reaction. We show shared heritability among upper respiratory diseases that extends to several immune-mediated diseases with diverse mechanisms, such as type 2 high inflammation.

Genetic predictors of lifelong medication-use patterns in cardiometabolic diseases.

Little is known about the genetic determinants of medication use in preventing cardiometabolic diseases. Using the Finnish nationwide drug purchase registry with follow-up since 1995, we performed genome-wide association analyses of longitudinal patterns of medication use in hyperlipidemia, hypertension and type 2 diabetes in up to 193,933 individuals (55% women) in the FinnGen study. In meta-analyses of up to 567,671 individuals combining FinnGen with the Estonian Biobank and the UK Biobank, we discovered 333 independent loci (P < 5 × 10-9) associated with medication use. Fine-mapping revealed 494 95% credible sets associated with the total number of medication purchases, changes in medication combinations or treatment discontinuation, including 46 credible sets in 40 loci not associated with the underlying treatment targets. The polygenic risk scores (PRS) for cardiometabolic risk factors were strongly associated with the medication-use behavior. A medication-use enhanced multitrait PRS for coronary artery disease matched the performance of a risk factor-based multitrait coronary artery disease PRS in an independent sample (UK Biobank, n = 343,676). In summary, we demonstrate medication-based strategies for identifying cardiometabolic risk loci and provide genome-wide tools for preventing cardiovascular diseases.

Recurrent Germline Variant in RAD21 Predisposes Children to Lymphoblastic Leukemia or Lymphoma.

Somatic loss of function mutations in cohesin genes are frequently associated with various cancer types, while cohesin disruption in the germline causes cohesinopathies such as Cornelia-de-Lange syndrome (CdLS). Here, we present the discovery of a recurrent heterozygous RAD21 germline aberration at amino acid position 298 (p.P298S/A) identified in three children with lymphoblastic leukemia or lymphoma in a total dataset of 482 pediatric cancer patients. While RAD21 p.P298S/A did not disrupt the formation of the cohesin complex, it altered RAD21 gene expression, DNA damage response and primary patient fibroblasts showed increased G2/M arrest after irradiation and Mitomycin-C treatment. Subsequent single-cell RNA-sequencing analysis of healthy human bone marrow confirmed the upregulation of distinct cohesin gene patterns during hematopoiesis, highlighting the importance of RAD21 expression within proliferating B- and T-cells. Our clinical and functional data therefore suggest that RAD21 germline variants can predispose to childhood lymphoblastic leukemia or lymphoma without displaying a CdLS phenotype.

Germline POT1 Deregulation Can Predispose to Myeloid Malignancies in Childhood.

While the shelterin complex guards and coordinates the mechanism of telomere regulation, deregulation of this process is tightly linked to malignant transformation and cancer. Here, we present the novel finding of a germline stop-gain variant (p.Q199*) in the shelterin complex gene POT1, which was identified in a child with acute myeloid leukemia. We show that the cells overexpressing the mutated POT1 display increased DNA damage and chromosomal instabilities compared to the wildtype counterpart. Protein and mRNA expression analyses in the primary patient cells further confirm that, physiologically, the variant leads to a nonfunctional POT1 allele in the patient. Subsequent telomere length measurements in the primary cells carrying heterozygous POT1 p.Q199* as well as POT1 knockdown AML cells revealed telomeric elongation as the main functional effect. These results show a connection between POT1 p.Q199* and telomeric dysregulation and highlight POT1 germline deficiency as a predisposition to myeloid malignancies in childhood.

Expression of BCL6 in paediatric B-cell acute lymphoblastic leukaemia and association with prognosis.

B-cell lineage acute lymphoblastic leukaemia (B-ALL) is the most common paediatric malignancy. Transcription factor B-cell lymphoma 6 (BCL6) is essential to germinal centre formation and antibody affinity maturation and plays a major role in mature B-cell malignancies. More recently, it was shown to act as a critical downstream regulator in pre-BCR+ B-ALL. We investigated the expression of the BCL6 protein in a population-based cohort of paediatric B-ALL cases and detected moderate to strong positivity through immunohistochemistry in 7% of cases (8/117); however, only two of eight BCL6 cases (25%) co-expressed the ZAP70 protein. In light of these data, the subtype with active pre-BCR signalling constitutes a rare entity in paediatric B-ALL. In three independent larger cohorts with gene expression data, high BCL6 mRNA levels were associated with the TCF3-PBX1, Ph-like, NUTM1, MEF2D and PAX5-alt subgroups and the 'metagene' signature for pre-BCR-associated genes. However, higher-than-median BCL6 mRNA level alone was associated with favourable event free survival in the Nordic paediatric cohort, indicating that using BCL6 as a diagnostic marker requires careful design, and evaluation of protein level is needed alongside the genetic or transcriptomic data.

IGF2BP3 Associates with Proliferative Phenotype and Prognostic Features in B-Cell Acute Lymphoblastic Leukemia.

The oncofetal protein insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) belongs to a family of RNA-binding proteins involved in localization, stability, and translational regulation of target RNAs. IGF2BP3 is used as a diagnostic and prognostic marker in several malignancies. Although the prognosis of pediatric B-cell acute lymphoblastic leukemia (B-ALL) has improved, a subgroup of patients exhibits high-risk features and suffer from disease recurrence. We sought to identify additional biomarkers to improve diagnostics, and we assessed expression of IGF2BP3 in a population-based pediatric cohort of B-ALL using a tissue microarray platform. The majority of pediatric B-ALL cases were positive for IGF2BP3 immunohistochemistry and were associated with an increased proliferative phenotype and activated STAT5 signaling pathway. Two large gene expression data sets were probed for the expression of IGF2BP3-the highest levels were seen among the B-cell lymphomas of a germinal center origin and well-established (KMT2A-rearranged and ETV6-RUNX1) and novel subtypes of B-ALL (e.g., NUTM1 and ETV6-RUNX1-like). A high mRNA for IGF2BP3 was associated with a proliferative "metagene" signature and a high expression of CDK6 in B-ALL. A low expression portended inferior survival in a high-risk cohort of pediatric B-ALL. Overall, our results show that IGF2BP3 shows subtype-specificity in expression and provides prognostic utility in high-risk B-ALL.

Single cell characterization of B-lymphoid differentiation and leukemic cell states during chemotherapy in ETV6-RUNX1-positive pediatric leukemia identifies drug-targetable transcription factor activities.

BACKGROUND: Tight regulatory loops orchestrate commitment to B cell fate within bone marrow. Genetic lesions in this gene regulatory network underlie the emergence of the most common childhood cancer, acute lymphoblastic leukemia (ALL). The initial genetic hits, including the common translocation that fuses ETV6 and RUNX1 genes, lead to arrested cell differentiation. Here, we aimed to characterize transcription factor activities along the B-lineage differentiation trajectory as a reference to characterize the aberrant cell states present in leukemic bone marrow, and to identify those transcription factors that maintain cancer-specific cell states for more precise therapeutic intervention. METHODS: We compared normal B-lineage differentiation and in vivo leukemic cell states using single cell RNA-sequencing (scRNA-seq) and several complementary genomics profiles. Based on statistical tools for scRNA-seq, we benchmarked a workflow to resolve transcription factor activities and gene expression distribution changes in healthy bone marrow lymphoid cell states. We compared these to ALL bone marrow at diagnosis and in vivo during chemotherapy, focusing on leukemias carrying the ETV6-RUNX1 fusion. RESULTS: We show that lymphoid cell transcription factor activities uncovered from bone marrow scRNA-seq have high correspondence with independent ATAC- and ChIP-seq data. Using this comprehensive reference for regulatory factors coordinating B-lineage differentiation, our analysis of ETV6-RUNX1-positive ALL cases revealed elevated activity of multiple ETS-transcription factors in leukemic cells states, including the leukemia genome-wide association study hit ELK3. The accompanying gene expression changes associated with natural killer cell inactivation and depletion in the leukemic immune microenvironment. Moreover, our results suggest that the abundance of G1 cell cycle state at diagnosis and lack of differentiation-associated regulatory network changes during induction chemotherapy represent features of chemoresistance. To target the leukemic regulatory program and thereby overcome treatment resistance, we show that inhibition of ETS-transcription factors reduced cell viability and resolved pathways contributing to this using scRNA-seq. CONCLUSIONS: Our data provide a detailed picture of the transcription factor activities characterizing both normal B-lineage differentiation and those acquired in leukemic bone marrow and provide a rational basis for new treatment strategies targeting the immune microenvironment and the active regulatory network in leukemia.

Immunogenomic Landscape of Hematological Malignancies.

Understanding factors that shape the immune landscape across hematological malignancies is essential for immunotherapy development. We integrated over 8,000 transcriptomes and 2,000 samples with multilevel genomics of hematological cancers to investigate how immunological features are linked to cancer subtypes, genetic and epigenetic alterations, and patient survival, and validated key findings experimentally. Infiltration of cytotoxic lymphocytes was associated with TP53 and myelodysplasia-related changes in acute myeloid leukemia, and activated B cell-like phenotype and interferon-γ response in lymphoma. CIITA methylation regulating antigen presentation, cancer type-specific immune checkpoints, such as VISTA in myeloid malignancies, and variation in cancer antigen expression further contributed to immune heterogeneity and predicted survival. Our study provides a resource linking immunology with cancer subtypes and genomics in hematological malignancies.

Clinicopathological features and prognostic value of SOX11 in childhood acute lymphoblastic leukemia.

Acute lymphoblastic leukemia is marked by aberrant transcriptional features that alter cell differentiation, self-renewal, and proliferative features. We sought to identify the transcription factors exhibiting altered and subtype-specific expression patterns in B-ALL and report here that SOX11, a developmental and neuronal transcription factor, is aberrantly expressed in the ETV6-RUNX1 and TCF3-PBX1 subtypes of acute B-cell leukemias. We show that a high expression of SOX11 leads to alterations of gene expression that are typically associated with cell adhesion, migration, and differentiation. A high expression is associated with DNA hypomethylation at the SOX11 locus and a favorable outcome. The results indicate that SOX11 expression marks a group of patients with good outcomes and thereby prompts further study of its use as a biomarker.

Predicting residential radon concentrations in Finland: Model development, validation, and application to childhood leukemia.

Objectives Inhaled radon gas is a known alpha-emitting carcinogen linked especially to lung cancer. Studies on higher concentrations of indoor radon and childhood leukemia have conflicting but largely negative results. In this study, we aimed to create a sophisticated statistical model to predict indoor radon concentrations and apply it to a Finnish childhood leukemia case-control dataset. Methods Prediction was based on ~80 000 indoor radon measurements, which were linked to national registries for potential indoor radon predictors based on the literature. In modelling, we used classical methods, random forests and deep neural networks. We had 1093 cases and 3279 controls from a nationwide case-control study. We estimated odds ratio (OR) for childhood leukemia using conditional logistic regression adjusted for potential confounders. Results The r 2of the final log-linear model was 0.21 for houses and 0.20 for apartments. Using random forest method, we were able to obtain slightly better fit for both houses (r 2= 0.28) and apartments (r 2= 0.23). In a risk analysis based on the case-control data with log-linear model, we observed a non-significant (P=0.54) increase with predicted radon concentrations [OR for the 2 ndquartile 1.08, 95% confidence interval (CI) 0.77-1.50, OR 1.10 with 95% CI 0.79-1.53 for the 3 rd, and 1.29 with 95% CI 0.93-1.77 for the highest quartile]. Conclusions Our modelling and the previously published models performed similarly but involves major uncertainties, and the results should be interpreted with caution. We observed a slight non-significant increase in risk of childhood leukemia related to higher average indoor radon concentrations.

Semisupervised Generative Autoencoder for Single-Cell Data.

Single-cell transcriptomics offers a tool to study the diversity of cell phenotypes through snapshots of the abundance of mRNA in individual cells. Often there is additional information available besides the single-cell gene expression counts, such as bulk transcriptome data from the same tissue, or quantification of surface protein levels from the same cells. In this study, we propose models based on the Bayesian deep learning approach, where protein quantification, available as CITE-seq counts, from the same cells is used to constrain the learning process, thus forming a SemI-SUpervised generative Autoencoder (SISUA) model. The generative model is based on the deep variational autoencoder (VAE) neural network architecture.

Data-driven characterization of molecular phenotypes across heterogeneous sample collections.

Existing large gene expression data repositories hold enormous potential to elucidate disease mechanisms, characterize changes in cellular pathways, and to stratify patients based on molecular profiles. To achieve this goal, integrative resources and tools are needed that allow comparison of results across datasets and data types. We propose an intuitive approach for data-driven stratifications of molecular profiles and benchmark our methodology using the dimensionality reduction algorithm t-distributed stochastic neighbor embedding (t-SNE) with multi-study and multi-platform data on hematological malignancies. Our approach enables assessing the contribution of biological versus technical variation to sample clustering, direct incorporation of additional datasets to the same low dimensional representation, comparison of molecular disease subtypes identified from separate t-SNE representations, and characterization of the obtained clusters based on pathway databases and additional data. In this manner, we performed an integrative analysis across multi-omics acute myeloid leukemia studies. Our approach indicated new molecular subtypes with differential survival and drug responsiveness among samples lacking fusion genes, including a novel myelodysplastic syndrome-like cluster and a cluster characterized with CEBPA mutations and differential activity of the S-adenosylmethionine-dependent DNA methylation pathway. In summary, integration across multiple studies can help to identify novel molecular disease subtypes and generate insight into disease biology.

Hemap: An Interactive Online Resource for Characterizing Molecular Phenotypes across Hematologic Malignancies.

Large collections of genome-wide data can facilitate the characterization of disease states and subtypes, permitting pan-cancer analysis of molecular phenotypes and evaluation of disease context for new therapeutic approaches. We analyzed 9,544 transcriptomes from more than 30 hematologic malignancies, normal blood cell types, and cell lines, and showed that disease types could be stratified in a data-driven manner. We then identified cluster-specific pathway activity, new biomarkers, and in silico drug target prioritization through interrogation of drug target databases. Using known vulnerabilities and available drug screens, we highlighted the importance of integrating molecular phenotype with drug target expression for in silico prediction of drug responsiveness. Our analysis implicated BCL2 expression level as an important indicator of venetoclax responsiveness and provided a rationale for its targeting in specific leukemia subtypes and multiple myeloma, linked several polycomb group proteins that could be targeted by small molecules (SFMBT1, CBX7, and EZH1) with chronic lymphocytic leukemia, and supported CDK6 as a disease-specific target in acute myeloid leukemia. Through integration with proteomics data, we characterized target protein expression for pre-B leukemia immunotherapy candidates, including DPEP1. These molecular data can be explored using our publicly available interactive resource, Hemap, for expediting therapeutic innovations in hematologic malignancies. SIGNIFICANCE: This study describes a data resource for researching derailed cellular pathways and candidate drug targets across hematologic malignancies.

Analysis of primary microRNA loci from nascent transcriptomes reveals regulatory domains governed by chromatin architecture.

Changes in mature microRNA (miRNA) levels that occur downstream of signaling cascades play an important role during human development and disease. However, the regulation of primary microRNA (pri-miRNA) genes remains to be dissected in detail. To address this, we followed a data-driven approach and developed a transcript identification, validation and quantification pipeline for characterizing the regulatory domains of pri-miRNAs. Integration of 92 nascent transcriptomes and multilevel data from cells arising from ecto-, endo- and mesoderm lineages reveals cell type-specific expression patterns, allows fine-resolution mapping of transcription start sites (TSS) and identification of candidate regulatory regions. We show that inter- and intragenic pri-miRNA transcripts span vast genomic regions and active TSS locations differ across cell types, exemplified by the mir-29a∼29b-1, mir-100∼let-7a-2∼125b-1 and miR-221∼222 clusters. Considering the presence of multiple TSS as an important regulatory feature at miRNA loci, we developed a strategy to quantify differential TSS usage. We demonstrate that the TSS activities associate with cell type-specific super-enhancers, differential stimulus responsiveness and higher-order chromatin structure. These results pave the way for building detailed regulatory maps of miRNA loci.