Transcriptome characterization by RNA sequencing identifies a major molecular and clinical subdivision in chronic lymphocytic leukemia

  1. Roderic Guigó1,2,14
  1. 1Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), 08003 Barcelona, Catalonia, Spain;
  2. 2Universitat Pompeu Fabra (UPF), 08003 Barcelona, Catalonia, Spain;
  3. 3Unitat d'Hematopatologia, Servei d'Anatomia Patològica, Hospital Clínic, Universitat de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Spain;
  4. 4Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), Spanish National Bioinformatics Institute, 28029 Madrid, Spain;
  5. 5Research Unit on Biomedical Informatics, Department of Experimental and Health Sciences, University Pompeu Fabra, 08003 Barcelona, Catalonia, Spain;
  6. 6Departamento de Bioquímica y Biología Molecular, Instituto Universitario de Oncología, Universidad de Oviedo, 33006 Oviedo, Spain;
  7. 7Gene Regulation Stem Cells and Cancer Programme, Centre for Genomic Regulation (CRG), 08003 Barcelona, Catalonia, Spain;
  8. 8Centro Nacional de Análisis Genómico, PCB, 08028 Barcelona, Spain;
  9. 9Departamento de Anatomía Patológica, Farmacología y Microbiología, Universitat de Barcelona, 08036 Barcelona, Spain;
  10. 10Institució Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain;
  11. 11Servei de Hematologia, Hospital Clínic, IDIBAPS, 08036 Barcelona, Spain
    1. 13 These authors contributed equally to this work.

    • 12 Present address: Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland

    Abstract

    Chronic lymphocytic leukemia (CLL) has heterogeneous clinical and biological behavior. Whole-genome and -exome sequencing has contributed to the characterization of the mutational spectrum of the disease, but the underlying transcriptional profile is still poorly understood. We have performed deep RNA sequencing in different subpopulations of normal B-lymphocytes and CLL cells from a cohort of 98 patients, and characterized the CLL transcriptional landscape with unprecedented resolution. We detected thousands of transcriptional elements differentially expressed between the CLL and normal B cells, including protein-coding genes, noncoding RNAs, and pseudogenes. Transposable elements are globally derepressed in CLL cells. In addition, two thousand genes—most of which are not differentially expressed—exhibit CLL-specific splicing patterns. Genes involved in metabolic pathways showed higher expression in CLL, while genes related to spliceosome, proteasome, and ribosome were among the most down-regulated in CLL. Clustering of the CLL samples according to RNA-seq derived gene expression levels unveiled two robust molecular subgroups, C1 and C2. C1/C2 subgroups and the mutational status of the immunoglobulin heavy variable (IGHV) region were the only independent variables in predicting time to treatment in a multivariate analysis with main clinico-biological features. This subdivision was validated in an independent cohort of patients monitored through DNA microarrays. Further analysis shows that B-cell receptor (BCR) activation in the microenvironment of the lymph node may be at the origin of the C1/C2 differences.

    Footnotes

    • 14 Corresponding author

      E-mail roderic.guigo{at}crg.cat

    • [Supplemental material is available for this article.]

    • Article published online before print. Article, supplemental material, and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.152132.112.

      Freely available online through the Genome Research Open Access option.

    • Received November 15, 2012.
    • Accepted November 12, 2013.

    This article, published in Genome Research, is available under a Creative Commons License (Attribution-NonCommercial 3.0 Unported), as described at http://creativecommons.org/licenses/by-nc/3.0/.

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