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Candia J, Cherukuri S, Guo Y, Doshi KA, Banavar JR, Civin CI, Losert W. Uncovering low-dimensional, miR-based signatures of acute myeloid and lymphoblastic leukemias with a machine-learning-driven network approach. CONVERGENT SCIENCE PHYSICAL ONCOLOGY 2015; 1. [PMID: 27274862 DOI: 10.1088/2057-1739/1/2/025002] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Complex phenotypic differences among different acute leukemias cannot be fully captured by analyzing the expression levels of one single molecule, such as a miR, at a time, but requires systematic analysis of large sets of miRs. While a popular approach for analysis of such datasets is principal component analysis (PCA), this method is not designed to optimally discriminate different phenotypes. Moreover, PCA and other low-dimensional representation methods yield linear or non-linear combinations of all measured miRs. Global human miR expression was measured in AML, B-ALL, and TALL cell lines and patient RNA samples. By systematically applying support vector machines to all measured miRs taken in dyad and triad groups, we built miR networks using cell line data and validated our findings with primary patient samples. All the coordinately transcribed members of the miR-23a cluster (which includes also miR-24 and miR-27a), known to function as tumor suppressors of acute leukemias, appeared in the AML, B-ALL and T-ALL centric networks. Subsequent qRT-PCR analysis showed that the most connected miR in the B-ALL-centric network, miR-708, is highly and specifically expressed in B-ALLs, suggesting that miR-708 might serve as a biomarker for B-ALL. This approach is systematic, quantitative, scalable, and unbiased. Rather than a single signature, our approach yields a network of signatures reflecting the redundant nature of biological signaling pathways. The network representation allows for visual analysis of all signatures by an expert and for future integration of additional information. Furthermore, each signature involves only small sets of miRs, such as dyads and triads, which are well suited for in depth validation through laboratory experiments. In particular, loss-and gain-of-function assays designed to drive changes in leukemia cell survival, proliferation and differentiation will benefit from the identification of multi-miR signatures that characterize leukemia subtypes and their normal counterpart cells of origin.
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Affiliation(s)
- Julián Candia
- Center for Human Immunology, Autoimmunity and Inflammation, National Institutes of Health, Bethesda, MD 20892, USA; Department of Physics, University of Maryland, College Park, MD 20742, USA; Center for Stem Cell Biology & Regenerative Medicine, Departments of Pediatrics and Physiology, University of Maryland School of Medicine, Baltimore MD 21201, USA
| | - Srujana Cherukuri
- Center for Stem Cell Biology & Regenerative Medicine, Departments of Pediatrics and Physiology, University of Maryland School of Medicine, Baltimore MD 21201, USA; Noble Life Sciences, 22 Firstfield Rd, Gaithersburg, MD 20878, USA
| | - Yin Guo
- Center for Stem Cell Biology & Regenerative Medicine, Departments of Pediatrics and Physiology, University of Maryland School of Medicine, Baltimore MD 21201, USA
| | - Kshama A Doshi
- Center for Stem Cell Biology & Regenerative Medicine, Departments of Pediatrics and Physiology, University of Maryland School of Medicine, Baltimore MD 21201, USA
| | - Jayanth R Banavar
- Department of Physics, University of Maryland, College Park, MD 20742, USA
| | - Curt I Civin
- Center for Stem Cell Biology & Regenerative Medicine, Departments of Pediatrics and Physiology, University of Maryland School of Medicine, Baltimore MD 21201, USA
| | - Wolfgang Losert
- Department of Physics, University of Maryland, College Park, MD 20742, USA
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Heiser D, Tan YS, Kaplan I, Godsey B, Morisot S, Cheng WC, Small D, Civin CI. Correlated miR-mRNA expression signatures of mouse hematopoietic stem and progenitor cell subsets predict "Stemness" and "Myeloid" interaction networks. PLoS One 2014; 9:e94852. [PMID: 24747944 PMCID: PMC3991639 DOI: 10.1371/journal.pone.0094852] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2013] [Accepted: 03/19/2014] [Indexed: 12/15/2022] Open
Abstract
Several individual miRNAs (miRs) have been implicated as potent regulators of important processes during normal and malignant hematopoiesis. In addition, many miRs have been shown to fine-tune intricate molecular networks, in concert with other regulatory elements. In order to study hematopoietic networks as a whole, we first created a map of global miR expression during early murine hematopoiesis. Next, we determined the copy number per cell for each miR in each of the examined stem and progenitor cell types. As data is emerging indicating that miRs function robustly mainly when they are expressed above a certain threshold (∼100 copies per cell), our database provides a resource for determining which miRs are expressed at a potentially functional level in each cell type. Finally, we combine our miR expression map with matched mRNA expression data and external prediction algorithms, using a Bayesian modeling approach to create a global landscape of predicted miR-mRNA interactions within each of these hematopoietic stem and progenitor cell subsets. This approach implicates several interaction networks comprising a "stemness" signature in the most primitive hematopoietic stem cell (HSC) populations, as well as "myeloid" patterns associated with two branches of myeloid development.
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Affiliation(s)
- Diane Heiser
- Center for Stem Cell Biology and Regenerative Medicine, Departments of Pediatrics and Physiology, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Yee Sun Tan
- Center for Stem Cell Biology and Regenerative Medicine, Departments of Pediatrics and Physiology, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Ian Kaplan
- Center for Stem Cell Biology and Regenerative Medicine, Departments of Pediatrics and Physiology, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Brian Godsey
- Center for Stem Cell Biology and Regenerative Medicine, Departments of Pediatrics and Physiology, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Sebastien Morisot
- Center for Stem Cell Biology and Regenerative Medicine, Departments of Pediatrics and Physiology, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Wen-Chih Cheng
- Center for Stem Cell Biology and Regenerative Medicine, Departments of Pediatrics and Physiology, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Donald Small
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Curt I. Civin
- Center for Stem Cell Biology and Regenerative Medicine, Departments of Pediatrics and Physiology, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
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