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      LSD1 defines erythroleukemia metabolism by controlling the lineage-specific transcription factors GATA1 and C/EBPα

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          Abstract

          Acute myeloid leukemia (AML) is a heterogenous malignancy characterized by distinct lineage subtypes and various genetic/epigenetic alterations. As with other neoplasms, AML cells have well-known aerobic glycolysis, but metabolic variations depending on cellular lineages also exist. Lysine-specific demethylase-1 (LSD1) has been reported to be crucial for human leukemogenesis, which is currently one of the emerging therapeutic targets. However, metabolic roles of LSD1 and lineage-dependent factors remain to be elucidated in AML cells. Here, we show that LSD1 directs a hematopoietic lineage-specific metabolic program in AML subtypes. Erythroid leukemia (EL) cells particularly showed activated glycolysis and high expression of LSD1 in both AML cell lines and clinical samples. Transcriptome, chromatin immunoprecipitation–sequencing, and metabolomic analyses revealed that LSD1 was essential not only for glycolysis but also for heme synthesis, the most characteristic metabolic pathway of erythroid origin. Notably, LSD1 stabilized the erythroid transcription factor GATA1, which directly enhanced the expression of glycolysis and heme synthesis genes. In contrast, LSD1 epigenetically downregulated the granulo-monocytic transcription factor C/EBPα. Thus, the use of LSD1 knockdown or chemical inhibitor dominated C/EBPα instead of GATA1 in EL cells, resulting in metabolic shifts and growth arrest. Furthermore, GATA1 suppressed the gene encoding C/EBPα that then acted as a repressor of GATA1 target genes. Collectively, we conclude that LSD1 shapes metabolic phenotypes in EL cells by balancing these lineage-specific transcription factors and that LSD1 inhibitors pharmacologically cause lineage-dependent metabolic remodeling.

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          Most cited references64

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          Fast and accurate short read alignment with Burrows–Wheeler transform

          Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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            Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities.

            Genome-scale studies have revealed extensive, cell type-specific colocalization of transcription factors, but the mechanisms underlying this phenomenon remain poorly understood. Here, we demonstrate in macrophages and B cells that collaborative interactions of the common factor PU.1 with small sets of macrophage- or B cell lineage-determining transcription factors establish cell-specific binding sites that are associated with the majority of promoter-distal H3K4me1-marked genomic regions. PU.1 binding initiates nucleosome remodeling, followed by H3K4 monomethylation at large numbers of genomic regions associated with both broadly and specifically expressed genes. These locations serve as beacons for additional factors, exemplified by liver X receptors, which drive both cell-specific gene expression and signal-dependent responses. Together with analyses of transcription factor binding and H3K4me1 patterns in other cell types, these studies suggest that simple combinations of lineage-determining transcription factors can specify the genomic sites ultimately responsible for both cell identity and cell type-specific responses to diverse signaling inputs. Copyright 2010 Elsevier Inc. All rights reserved.
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              The Emerging Hallmarks of Cancer Metabolism.

              Tumorigenesis is dependent on the reprogramming of cellular metabolism as both direct and indirect consequence of oncogenic mutations. A common feature of cancer cell metabolism is the ability to acquire necessary nutrients from a frequently nutrient-poor environment and utilize these nutrients to both maintain viability and build new biomass. The alterations in intracellular and extracellular metabolites that can accompany cancer-associated metabolic reprogramming have profound effects on gene expression, cellular differentiation, and the tumor microenvironment. In this Perspective, we have organized known cancer-associated metabolic changes into six hallmarks: (1) deregulated uptake of glucose and amino acids, (2) use of opportunistic modes of nutrient acquisition, (3) use of glycolysis/TCA cycle intermediates for biosynthesis and NADPH production, (4) increased demand for nitrogen, (5) alterations in metabolite-driven gene regulation, and (6) metabolic interactions with the microenvironment. While few tumors display all six hallmarks, most display several. The specific hallmarks exhibited by an individual tumor may ultimately contribute to better tumor classification and aid in directing treatment.
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                Author and article information

                Contributors
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                Journal
                Blood Advances
                American Society of Hematology
                2473-9529
                2473-9537
                May 11 2021
                May 11 2021
                April 30 2021
                : 5
                : 9
                : 2305-2318
                Affiliations
                [1 ]Department of Medical Cell Biology, Institute of Molecular Embryology and Genetics, and
                [2 ]Department of Pediatrics, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan;
                [3 ]Biological Data Science Research Group, Cellular and Molecular Biotechnology Research Institute, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan; and
                [4 ]Division of Bioinformatics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan
                Article
                10.1182/bloodadvances.2020003521
                33929501
                cff1d92a-5b04-4a0d-b416-feae4e983429
                © 2021
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