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Clinics in Oncology
2016 | Volume 1 | Article 1118 1
Introduction
e Myelodysplastic Syndromes (MDS) are a heterogeneous group of clonal disorders in
the haematopoietic system. Characteristic for MDS is an ineffective haematopoiesis, dysplasia,
various degrees of cytopenia and a risk to evolve in Acute Myeloid Leukaemia (AML). For risk
calculation the international prognostic scoring system (IPSS) [1] is used and, recently, the IPSS-R
has been introduced [2]. In this new IPSS-R, the patients are divided into five risk groups for AML
transformation and survival (very low, low, intermediate, high and very high), depending on clinical
parameters and the karyotype, being the parameter with the strongest impact [2,3,4]. In both
systems, the IPSS and IPSS-R, a cytogenetic normal karyotype oſten leads to the allocation into a
better (good or int-1) risk group and 40-50% of the patients show a normal bone marrow karyotype.
Classical cytogenetic analyses are limited by their resolution and the need of mitotic cells, which
is not always successful in MDS. erefore, array CGH and SNP microarrays were used to analyze
Bioinformatic Evaluation and Comparison of Parallel
aSNP and aCGH Analyses of Myelodysplastic Syndromes
Patients with Normal Karyotype
OPEN ACCESS
*Correspondence:
Brigitte Royer-Pokora, Institute of
Human Genetics, Heinrich-Heine
University of Duesseldorf, Postfach
101007, D40001 Duesseldorf,
Germany, Tel: +49 211 8111230; Fax:
+49 211 8112538;
E-mail: royer@uni-duesseldorf.de
Received Date: 06 Sep 2016
Accepted Date: 26 Sep 2016
Published Date: 19 Oct 2016
Citation:
Claßen-von Spee S, Mallo M, Beier
M, de Leve S, Arenillas L, Pedro C,
et al. Bioinformatic Evaluation and
Comparison of Parallel aSNP and
aCGH Analyses of Myelodysplastic
Syndromes Patients with Normal
Karyotype. Clin Oncol. 2016; 1: 1118.
Copyright © 2016 Royer-Pokora
B. This is an open access article
distributed under the Creative
Commons Attribution License, which
permits unrestricted use, distribution,
and reproduction in any medium,
provided the original work is properly
cited.
Research Article
Published: 19 Oct, 2016
Abstract
To study MDS bone marrow samples for tumor specific alterations two different microarray
platforms, aSNP and aCGH, have been widely used. e purpose of this study was 1) to compare the
two array methods and 2) evaluate the usefulness of different aCGH algorithms for the identification
of authentic alterations in tumoral samples.
Parallel aSNP and aCGH analyses were performed on the same 21 bone marrow DNA samples
from karyotypically normal MDS patients. FISH and Q-PCR methods were used to verify several
alterations. e aSNP data were evaluated using Genotyping Console Soſtware; aCGH data were
analyzed with the ADM-2 setting of the Agilent Genomic Workbench program, followed by three
additional algorithms, haarseq, lawsglad and dnacopy. 404 alterations were seen with aSNP of these
74 were also seen with aCGH with at least the ADM-2 algorithm. With the ADM-2 setting, 237
imbalances were detected, of these 72 were seen with all four aCGH algorithms. Among the latter
aberrations were two tumour specific deletions, a TET2 deletion and a larger deletion containing
DNMT3A, present in a high percentage of cells. One tumour specific telomeric 16p gain only seen
with aCGH was confirmed with FISH in 7.5% of the cells. As expected, uniparental disomies (UPDs)
were only detected with aSNP; in one case at 3q and in the other case two UPDs at 4q and 5p. e
discrepancies between both methods and the algorithms are discussed in detail.
Our results show that 72/237 (30%) aCGH alterations were predicted with all four algorithms. Of the
74 alterations seen with both platforms 31 were seen with all algorithms. 18% of the aSNP alterations
and 31% of the aCGH alterations were also seen with the other platform. Of 15 selected aberrations
detected with aSNP only and with the highest deviation from normal 50% could be confirmed by
Q-PCR, whereas all 10 selected imbalances detected with aCGH only were confirmed by Q-PCR.
erefore, using several algorithms for aCGH analysis, increases the number of true alterations.
aSNP data should be interpreted with caution and another verification method is advisable.
Keywords: aSNP; aCGH; Karyotypically normal MDS; Bioinformatic evaluation
Sabrina Claßen-von Spee
1
, Mar Mallo
2
, Manfred Beier
1
, Simone de Leve
1
, Leonor Arenillas
3
,
Carmen Pedro
4
, Francesc Solé
2
and Brigitte Royer-Pokora
1
*
1
Institute of Human Genetics, Heinrich-Heine University, Duesseldorf, Germany
2
MDS Research Group, Institut de Recerca Contra la Leucèmia Josep Carreras, Barcelona, Spain
3
Laboratori de Citologia Hematològica Servei de Patologia, Hospital del Mar, Barcelona, Spain
4
Servei d'Hematologia Clínica, Hospital del Mar, Barcelona, Spain