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Exploring the nature of prediagnostic blood transcriptome markers of chronic lymphocytic leukemia by assessing their overlap with the transcriptome at the clinical stage
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art%3A10.1186%2Fs12864-017-3627-4.pdf | Published version | 1.07 MB | Adobe PDF | View/Open |
Title: | Exploring the nature of prediagnostic blood transcriptome markers of chronic lymphocytic leukemia by assessing their overlap with the transcriptome at the clinical stage |
Authors: | Vlaanderen, J Leenders, M Chadeau-Hyam, M Portengen, L Kyrtopoulos, SA Bergdahl, IA Johansson, A-S Hebels, DDGAJ De Kok, TMCM Vineis, P Vermeulen, RCH |
Item Type: | Journal Article |
Abstract: | Background: We recently identified 700 genes whose expression levels were predictive of chronic lymphocytic leukemia (CLL) in a genome-wide gene expression analysis of prediagnostic blood from future cases and matched controls. We hypothesized that a large fraction of these markers were likely related to early disease manifestations. Here we aim to gain a better understanding of the natural history of the identified markers by comparing results from our prediagnostic analysis, the only prediagnostic analysis to date, to results obtained from a meta-analysis of a series of publically available transcriptomics profiles obtained in incident CLL cases and controls. Results: We observed considerable overlap between the results from our prediagnostic study and the clinical CLL signals (p-value for overlap Bonferroni significant markers 0.01; p-value for overlap nominal significant markers < 2.20e-16). We observed similar patterns with time to diagnosis and similar functional annotations for the markers that were identified in both settings compared to the markers that were only identified in the prediagnostic study. These results suggest that both gene sets operate in similar pathways. Conclusion: An overlap exists between expression levels of genes predictive of CLL identified in prediagnostic blood and expression levels of genes associated to CLL at the clinical stage. Our analysis provides insight in a set of genes for which expression levels can be used to follow the time-course of the disease; providing an opportunity to study CLL progression in more detail in future studies. |
Issue Date: | 20-Mar-2017 |
Date of Acceptance: | 14-Mar-2017 |
URI: | http://hdl.handle.net/10044/1/46024 |
DOI: | https://dx.doi.org/10.1186/s12864-017-3627-4 |
ISSN: | 1471-2164 |
Publisher: | BIOMED CENTRAL LTD |
Journal / Book Title: | BMC GENOMICS |
Volume: | 18 |
Issue: | 1 |
Copyright Statement: | © 2017 The Author(s). Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
Keywords: | Science & Technology Life Sciences & Biomedicine Biotechnology & Applied Microbiology Genetics & Heredity B-cell lymphoma Chronic lymphocytic leukemia Transcriptomics Prediagnostic study Public data GENE-EXPRESSION DATA MOLECULAR EPIDEMIOLOGY MULTIPLE-MYELOMA T-CELLS OPPORTUNITIES UPDATE CANCER CLL Bioinformatics 06 Biological Sciences 11 Medical And Health Sciences 08 Information And Computing Sciences |
Publication Status: | Published |
Article Number: | ARTN 239 |
Appears in Collections: | School of Public Health |