1
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Proteogenomic analysis reveals cytoplasmic sequestration of RUNX1 by the acute myeloid leukemia–initiating CBFB::MYH11 oncofusion protein

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Several canonical translocations produce oncofusion genes that can initiate acute myeloid leukemia (AML). Although each translocation is associated with unique features, the mechanisms responsible remain unclear. While proteins interacting with each oncofusion are known to be relevant for how they act, these interactions have not yet been systematically defined. To address this issue in an unbiased fashion, we fused a promiscuous biotin ligase (TurboID) in-frame with 3 favorable-risk AML oncofusion cDNAs ( PML::RARA, RUNX1::RUNX1T1, and CBFB::MYH11) and identified their interacting proteins in primary murine hematopoietic cells. The PML::RARA- and RUNX1::RUNX1T1-TurboID fusion proteins labeled common and unique nuclear repressor complexes, implying their nuclear localization. However, CBFB::MYH11-TurboID–interacting proteins were largely cytoplasmic, probably because of an interaction of the MYH11 domain with several cytoplasmic myosin-related proteins. Using a variety of methods, we showed that the CBFB domain of CBFB::MYH11 sequesters RUNX1 in cytoplasmic aggregates; these findings were confirmed in primary human AML cells. Paradoxically, CBFB::MYH11 expression was associated with increased RUNX1/2 expression, suggesting the presence of a sensor for reduced functional RUNX1 protein, and a feedback loop that may attempt to compensate by increasing RUNX1/2 transcription. These findings may have broad implications for AML pathogenesis.

          Abstract

          Abstract

          <p>The CBFB::MYH11 fusion protein that initiates Acute Myeloid Leukemia sequesters RUNX1 in the cytoplasm, reducing its activity&nbsp;and initiating a feedback loop&nbsp;that increases RUNX1 expression.</p>

          Related collections

          Most cited references112

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

          Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Near-optimal probabilistic RNA-seq quantification.

            We present kallisto, an RNA-seq quantification program that is two orders of magnitude faster than previous approaches and achieves similar accuracy. Kallisto pseudoaligns reads to a reference, producing a list of transcripts that are compatible with each read while avoiding alignment of individual bases. We use kallisto to analyze 30 million unaligned paired-end RNA-seq reads in <10 min on a standard laptop computer. This removes a major computational bottleneck in RNA-seq analysis.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia.

              Many mutations that contribute to the pathogenesis of acute myeloid leukemia (AML) are undefined. The relationships between patterns of mutations and epigenetic phenotypes are not yet clear. We analyzed the genomes of 200 clinically annotated adult cases of de novo AML, using either whole-genome sequencing (50 cases) or whole-exome sequencing (150 cases), along with RNA and microRNA sequencing and DNA-methylation analysis. AML genomes have fewer mutations than most other adult cancers, with an average of only 13 mutations found in genes. Of these, an average of 5 are in genes that are recurrently mutated in AML. A total of 23 genes were significantly mutated, and another 237 were mutated in two or more samples. Nearly all samples had at least 1 nonsynonymous mutation in one of nine categories of genes that are almost certainly relevant for pathogenesis, including transcription-factor fusions (18% of cases), the gene encoding nucleophosmin (NPM1) (27%), tumor-suppressor genes (16%), DNA-methylation-related genes (44%), signaling genes (59%), chromatin-modifying genes (30%), myeloid transcription-factor genes (22%), cohesin-complex genes (13%), and spliceosome-complex genes (14%). Patterns of cooperation and mutual exclusivity suggested strong biologic relationships among several of the genes and categories. We identified at least one potential driver mutation in nearly all AML samples and found that a complex interplay of genetic events contributes to AML pathogenesis in individual patients. The databases from this study are widely available to serve as a foundation for further investigations of AML pathogenesis, classification, and risk stratification. (Funded by the National Institutes of Health.).
                Bookmark

                Author and article information

                Contributors
                Journal
                J Clin Invest
                J Clin Invest
                J Clin Invest
                The Journal of Clinical Investigation
                American Society for Clinical Investigation
                0021-9738
                1558-8238
                7 December 2023
                15 February 2024
                7 December 2023
                : 134
                : 4
                : e176311
                Affiliations
                [1 ]Section of Stem Cell Biology, Division of Oncology, Department of Internal Medicine, and
                [2 ]Division of Endocrinology, Metabolism and Lipid Research, Department of Internal Medicine, Washington University School of Medicine, St. Louis, Missouri, USA.
                Author notes
                Address correspondence to: Timothy J. Ley, Section of Stem Cell Biology, Division of Oncology, Department of Internal Medicine, Washington University School of Medicine, 660 South Euclid Avenue Box 8007, St. Louis, Missouri 63110, USA. Phone: 314.362.8831; Email: timley@ 123456wustl.edu .
                Author information
                http://orcid.org/0000-0002-4376-4663
                http://orcid.org/0000-0002-7522-1946
                http://orcid.org/0000-0003-4266-6700
                http://orcid.org/0000-0002-9913-0520
                Article
                176311
                10.1172/JCI176311
                10866659
                38061017
                e5728f62-3205-498a-928c-d2262c624aa5
                © 2023 Day et al.

                This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 10 October 2023
                : 6 December 2023
                Funding
                Funded by: National Institutes of Health, https://doi.org/10.13039/100000002;
                Award ID: K12CA167570
                Funded by: National Institutes of Heath
                Award ID: CA211782
                Funded by: National Institutes of Health, https://doi.org/10.13039/100000002;
                Award ID: CA101937
                Funded by: National Institutes of Health, https://doi.org/10.13039/100000002;
                Award ID: CA197561
                Funded by: Barnes Jewish Hospital Foundation
                Award ID: N/A
                Funded by: Washington University Institute of Clinical and Translational Sciences
                Award ID: NCATS UL1 TR000448
                Funded by: National Institutes of Health, https://doi.org/10.13039/100000002;
                Award ID: NIGMS P41 GM103422
                Award ID: R24GM136766
                Funded by: National Institutes of Health, https://doi.org/10.13039/100000002;
                Award ID: NCI P30 CA091842
                To RBD
                To CAM
                To TJL
                To TJL
                To TJL
                To RRT
                Mass Spectrometry Research Resource, to RRT
                Siteman Comprehensive Cancer Center Support Grant
                Categories
                Research Article

                oncology,epigenetics,leukemias,proteomics
                oncology, epigenetics, leukemias, proteomics

                Comments

                Comment on this article