Exploring the nature of prediagnostic blood transcriptome markers of chronic lymphocytic leukemia by assessing their overlap with the transcriptome at the clinical stage.
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.



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.



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.
Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands.
Jelle
0000-0002-9096-692X
J
Vlaanderen
Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands.
Max
M
Leenders
Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands.|Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
Marc
M
Chadeau-Hyam
Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands.
Lützen
L
Portengen
Institute of Biology, Medicinal Chemistry and Biotechnology, National Hellenic Research Foundation, Athens, Greece.
Soterios A
SA
Kyrtopoulos
Department of Biobank Research, University of Umeå, Umeå, Sweden.
Ingvar A
IA
Bergdahl
Department of Oncology, University of Umeå, Umeå, Sweden.
Ann-Sofie
AS
Johansson
Department of Toxicogenomics, Maastricht University, Maastricht, The Netherlands.
Dennie D G A J
DD
Hebels
Department of Toxicogenomics, Maastricht University, Maastricht, The Netherlands.
Theo M C M
TM
de Kok
Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.|Molecular and Genetic Epidemiology, Human Genetics Foundation (HuGeF), Turin, Italy.
Paolo
P
Vineis
Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands. r.c.h.vermeulen@uu.nl.|Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK. r.c.h.vermeulen@uu.nl.|Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands. r.c.h.vermeulen@uu.nl.
Roel C H
RC
Vermeulen
D014408:Biomarkers, Tumor; D019295:Computational Biology / Q000379:methods; D020869:Gene Expression Profiling; D006801:Humans; D015451:Leukemia, Lymphocytic, Chronic, B-Cell / Q000097:blood / Q000175:diagnosis* / Q000235:genetics*; D009367:Neoplasm Staging; D011379:Prognosis; D059467:Transcriptome
D014408:Biomarkers, Tumor
B-cell lymphoma; Chronic lymphocytic leukemia; Prediagnostic study; Public data; Transcriptomics