Využití techniky komparativní genomové hybridizace na oligonukleotidových čipech jako diagnostického nástroje u pacientů s mnohočetným myelomem
Mnohočetný myelom (MM) je hematologické onemocnění způsobené maligní proliferací klonálních plazmatických buněk (PCs), které se vyznačuje značnou klinickou a biologickou variabilitou. Identifikace chromozomových změn v genomu PCs hraje klíčovou roli v patogenezi MM a má také důležitý prognostický význam u pacientů s MM. Z genetického hlediska lze MM rozdělit na dva subtypy. Hyperdiploidní MM (H-MM), který se vyskytuje u 50 % případů, je charakterizován častou incidencí trizomií chromozomů 3, 5, 7, 9, 11, 15, 19 a 21 a dále nízkým výskytem translokací IgH. Téměř polovina případů je klasifikována jako non-hyperdiploidní MM (NH-MM), u kterého lze často najít jednu z pěti rekurentních translokací IgH: 4p16 (FGFR3 a MMSET), 6p21 (CCND3), 11q13 (CCND1), 16q23 (MAF), 20q12 (MAFB) a který je asociován s nepříznivou prognózou onemocnění. Rozvoj a rozšířené využívání nových technologií, jako je technika celogenomové komparativní genomové hybridizace na oligonukleotidových čipech (aCGH), výrazně posunula výzkum genomových změn u MM, jelikož umožňuje v rámci jedné reakci analýzou chromozomových změn v celém genomu, a tak představuje ideální nástroj pro studium nádorové genetiky a je vhodnou aplikací pro rutinní analýzy v klinické praxi. Technika aCGH významně překonává běžně používané cytogenetické techniky (G-pruhování, FISH), a to jak v možnostech minimálního rozlišení chromozomových změn, tak i v kvalitě a množství získaných genomických dat nezbytných pro další analýzy a klinické aplikace. Technika aCGH je nyní používána k lepšímu pochopení molekulárního fenotypu nádorových buněk, pro studium vlivu chromozomových změn na citlivost na určitá chemoterapeutika a prognózu onemocnění. Tento dokument přináší stručný metodický a literární přehled použití techniky oligonukleotidové aCGH v diagnostice MM.
Tato práce byla podpořena granty Ministerstva školství, mládeže a tělovýchovy (MSM0021622434, LC06027), Ministerstva zdravotnictví (IGA granty NS10207, NS10406, NS10408) a GAČR GAP304/10/1395.
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J. Smetana1,2; J. Fröhlich1,2; V. Vranová2; A. Mikulášová1,2; P. Kuglík1,2; R. Hájek1,3,4
Authors place of work:
Babak Myeloma Group, Department of Pathological Physiology, Faculty of Medicine, Masaryk University, Czech Republic1; Institute of Experimental Biology, Faculty of Science, Masaryk University, Brno, Czech Republic2; Department of Internal Medicine – Hematooncology, University Hospital Brno, Czech Republic3; Laboratory of Experimental Hematology and Cell Immunotherapy, Department of Clinical Hematology, University Hospital Brno, Czech Republic4
Published in the journal:
Klin Onkol 2011; 24(Supplementum 1): 43-48
Multiple myeloma (MM) is a hematological disease caused by malignant proliferation of clonal plasma cells (PCs) known for its clinical and biological heterogeneity. Identification of chromosomal changes in genome of PCs plays a key role in MM pathogenesis and is supposed to have important prognostic significance for MM patients. There are two major genetic entities in MM. Hyperdiploid tumors (H-MM), which include about 50% of MM tumors, often have multiple trisomies involving chromosomes 3, 5, 7, 9, 11, 15, 19, and 21 and a substantially lower prevalence of IgH translocations. Nearly half of tumors are non-hyperdiploid (NH-MM), and mostly have one of five recurrent IgH translocations: 11q13 (CCND1), 6p21 (CCND3), 16q23 (MAF), 20q12 (MAFB), and 4p16 (FGFR3 and MMSET). The development and expanded use of new technologies, such as genome-wide array-based comparative genomic hybridization (aCGH) has accelerated genomic research in MM. This technique is a powerful tool to globally analyze recurrent copy number changes in tumor genome in a single reaction and to study cancer biology and clinical behaviors. It widely overcame routinely used cytogenetic techniques (G-banding, FISH) both in minimal resolution of chromosomal changes and amount of obtained genomic data important for further analyses and clinical applications. Array CGH technique is now used to better understanding of molecular phenotypes, sensitivity to particular chemotherapeutic agents, and prognosis of these diseases. This paper brings brief literature and methodic overview of oligonucleotide-based array-CGH technique in MM diagnosis.
This study was supported by grants of The Ministry of Education, Youth and Sports (MSM0021622434, LC06027), Ministry of Health (IGA grants NS10207, NS10406, NS10408) and GACR GAP304/10/1395.
The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study.
The Editorial Board declares that the manuscript met the ICMJE “uniform requirements” for biomedical papers.
of specific chromosomal aberrations (CHA) in genome of malignant
plasma cells (PCs) is considered to be one of the most important
independent prognostic factors for patients with MM . These
changes are often observed in chromosomal areas where tumor
suppressor genes or oncogenes are located . It is well established
that loss of tumor suppressor genes or copy gains of oncogenes are
essential events in developmental process of malignant PCs [3,4].
Several studies show that incidence of specific CHA is an important
prognostic factor often connected with response to chemotherapy or
bone marrow transplantation [5,6]. Thus, detection of CHA is an
essential step in determination of a given MM patient
pathogenesis. Effective detection of these changes by means of
standard karyotyping using G-banding cytogenetic techniques is
limited (about 30% of cases) due to low resolution (5–10 Mb) and
low proliferation of PCs. This limitation can be overcome by newer
techniques, such as fluorescent in
(FISH). However, this technique detects only a limited number of
target sequences in the genome. Using FISH, overall detection rate of
CHA reaches over 90% of all cases [7,8]. In MM patients, routine
application of FISH in clinical practice is mainly focused on
identifying specific chromosomal aberrations. Several studies
described prognostic significance of del(13)(q14)/loss of chromosome
13, del(17)(p13), gain(1)(q21) and IgH
translocations [7,8–10], but current understanding of MM
pathogenesis together with development of modern genome-wide
screening techniques proves that FISH is insufficient for description
of MM genetic heterogeneity. Introduction of microarray-based
comparative genomic hybridization (aCGH) technique by Solinas-Toldo
et al  gives researches an ideal molecular cytogenetic tool,
allowing detection of CHA including deletions and duplications in
a single experiment.
Oligonucleotide-based aCGH is
a robust modern technique, which allows detecting of CHA of size
as low as 2kb in a single reaction during 40 hours depending on
array platform (Tab. 1). Such resolution gives us a possibility
for detection of CHA on exon level [12,13], which dramatically
improves our investigations of chromosomal rearrangements in genome
of malignant cells. Moreover, with help of modern, sophisticated
statistic tools for CHA evaluation, it is possible to interpret data
mined from aCGH technique quite fast and easy, correlate these data
with other techniques or with clinical features. Thus, aCGH technique
and genomic copy number analyses with SNP genotyping arrays are
proving particularly effective for investigations of important CHA
connected with cancer diseases in molecular level .
of Oligonucleotide-based aCGH Technique
many hematological malignancies, aCGH technique has been often
successfully used for detection of genomic alterations [15–17]. An
essential issue in the implementation and optimization of aCGH
technique in our laboratory was obtaining sufficient amount of
genomic DNA (gDNA) from patients’ PCs samples. For successful aCGH
experiment and confident interpretation of aCGH results in MM
diagnosis, it is necessary to get purified gDNA from population of
a malignant clone of PCs, which is obtained by immunomagnetic
(MACS) or immunofluorescent (FACS) separation from patient’s bone
marrow. Malignant PCs are identified by surface antigenic markers of
CD 138+ CD45–[18,19]. For further differentiation of abnormal from
healthy PCs populations, CD38+, CD19+, CD56+ markers are used .
After sorting, samples of high purity with at least 0,5 × 106
PCs from abnormal population are obtained. For aCGH, minimum
infiltration of malignant PCs in the sample should be above 90%.
Minimum content of tumor cells represented in the sample for aCGH,
which is capable of distinguishing malignant from normal cells, is
around 20–30% . Then, isolation of gDNA can be made by typical
phenol-chloroform extraction or using a variety of commercially
available kits. In our laboratory, we commonly use Gentra Puregene
Core Kit A (Qiagen). Regardless of isolation method, it is
necessary to obtain high-quality gDNA as input. It minimizes the risk
of abnormal array background and generally is the cornerstone for
quality of whole genome analysis. As standard procedure, gDNA should
be checked using gel electrophoresis and measured for yield and
purity by a spectrophotometer. Recommendations according to
Agilent protocol suggest the ratio of absorbance 260 nm/280 nm in the
range of 1.75 to 1.90 and 260/230 greater than 2.0. As standard,
minimum amount of gDNA for aCGH experiment is 0.5 μg. In our
laboratory, we use 4x44K format 1 μg of gDNA. Concentration of
input gDNA should be between 200–400 ng/μl.
In our laboratory, we use
genome-wide oligonucleotide-based aCGH 4x44K
(Human HD-CGH 4x44K, Agilent Technologies) platform together with
complete hardware and software equipment required for aCGH technique
from Agilent (Agilent Technologies, Santa Clara, USA). The principle
of aCGH is hybridization between the “probe” and DNA fragments
(60 bp DNA fragments defined) “spotted” using photolithography on
a glass matrix (= array) . Probe DNA is prepared from the
DNA sample and healthy control DNA. DNA fragments of known sequence
are located on exact spots on the array, and each probe is associated
with specific position in the genome. Genomic DNA is obtained from
various sources of material (cultured cells, tissues, blood) cut by
restriction enzymes and labeled with fluorescent dyes of different
color, typically red and green. Samples and DNA controls are
cohybridised, incorrectly linked probes removed during wash step and
complementary probes that remained attached to the array provide the
fluorescent signal, which is acquired by a sensitive scanner.
Acquired digital “picture” from scanner is the analyzed by
appropriate software. Flow-chart of typical aCGH experiment is shown
Routine aCGH experiment begins
with digestion step, where gDNA is digested by restriction enzymes
(Alu1, Rsa1, DNaseI) into fragment size of 200–2,000 bp. For
fluorescent labeling of sample and control DNA, several commercially
available kits can be used. Specific activities (= measuring of
labeling effectiveness of DNA fragments) will slightly vary according
to the manufacturer and type of fluorescent dyes. We use Bioprime
Total Genomic Labeling System (Invitrogen) with specific fluorescent
dyes Alexa3 and Alexa5. According to manufacturer’s protocol,
specific activity of labeling with 1 μg gDNA as input should be in
the range of 90–100 pmol/μg for
Alexa3 and 70–90 pmol/μg for Alexa5. Total DNA yield is expected
between 4–7 μg. Labeled samples and controls of the same sex and
similar specific activity are mixed together, reaction and
hybridization buffer together with unmarked human Cot-1 DNA are then
added into reaction and after denaturation and incubation at 95 C/3
min and 30 min/37 C respectively, mixed solution is applied onto the
array. Hybridization process of 4x44K array lasts approximately
24 hours at 65 C. After hybridization, array undergoes washing
procedures (Wash buffer 1 and 2, Agilent Technologies), and then it
is ready for scanning in appropriate scanner. The output of the
scanner is a data file, which is further processed by software
(Agilent Feature Extraction 9.5.3), which visualizes the data for
checking of overall array quality and converts raw data from the
scanner into a format suitable for further software applications
designed to detect and analyzing genomic changes, such as Agilent
Genomic Workbench. The rate of gain or loss of genetic material is
obtained by analysing the ratio of green and red fluorescence from
the probes (fixed base modal ratio) and selected on the basis of
statistical methods (Z-score, ADM, HMM, CBS). Genome without CHA
is characterized by yellow fluorescence (log2 = 0). Areas with gained
genetic material are characterized by log2 > 0, whereas the values
0 are considered as loss of genetic material. Graphical image of
analysis of CHA using aCGH software are shown in Fig. 2.
of aCGH Technique in
introduction of new molecular cytogenetic techniques (FISH, aCGH)
brought new possibilities for detection of CHA in MM. Using FISH and
especially designed probes, the most frequently CHA were observed in
90% of patients [4,5–8]. According
to the International Myeloma Working group (IMWG), current minimal
clinical panel of CHA proposed for testing by FISH in MM patients
includes 3 aberrations
((del(17)(p13), t(4;14)(p16;q32), t(14;16)(q32;q23))
with known negative effect on MM prognosis. Expanded panel of FISH
markers includes hyperdiploidy (trisomies of chromosome 5, 9 and 15),
del(13)(q14)/monosomy 13, gain(1)(q21) and t(11;14)(q13;q32)
. However, with given heterogeneity of MM, it seems insufficient.
Moreover, several studies proved 100% occurrence of chromosomal
aberrations in MM when aCGH technique was used [21,25] and therefore
utilization of genome-wide techniques in clinical practice is already
taken under consideration in IMWG recommendations for cytogenetic
analyses used in MM diagnostics.
New technologies, especially
oligonucleotide-based comparative genome hybridization, have
dramatically changed human genomic analysis by combining the targeted
high-resolution aspects of FISH and the genome-wide scale of
karyotyping. The first whole genome studies in MM performed by
conventional CGH revealed new changes undetectable by G-banding and
pointed out aberrations studied by FISH. The most frequent
aberrations were: gain 1q, 3q, 9q, 11q, 15q, loss of 6q21, 13q, 14q,
16q [26,27]. The German group  for the first time evaluated
sensitivity (80.7%) and specificity (97.7%) between CGH and FISH in
MM diagnosis. Gutieréz et al  found a significantly shorter
overall survival for MM patients with deletions in the genome
compared to patients with gain of genetic material. The first use of
array-based CGH in MM was published by Largo et al , who have
verified previous studies made by conventional CGH, clarified the
definition of both hyperdiploid and non-hyperdiploid MM subtypes
according to FISH and further defined two genetically different
subclasses of the H-MM according to the incidence of 7p gain. Using
aCGH and GEP (gene expression profiling) analysis and subsequent
integration of the results from both techniques, Carrasco et al 
described two subclasses of H-MM with different prognosis among
cohort of 67 newly diagnosed patients with MM. In patients with
a combination of hyperdiploidy and trisomy of chromosome 11,
a trend for better prognosis was found in contrast to patients
without trisomy 11. Moreover, within H-MM subgroup without +11,
statistically significant difference for the incidence of 1q gain and
-13 (p < 0.001, p
= 0.019, respectively) compared to the subgroup with +11 was found.
These results confirmed previously published data about importance of
1q gain as an independent prognostic factor in MM . Deletions of
several genes involved in NF-kB pathway were described by Keats et al
. Genome-wide analysis of 155 patients brought interesting
findings that highlight the importance of NF-kB pathway in the
pathogenesis of MM. The paper presents findings of 14q32 deletion,
which included potential
target genes TRAF3, AMN
The authors describe two other less frequent areas with biallelic
deletions: 16q12 with genes CARD15,
CYLD, and 11q22 with
BIRC3/cIAP2. It was
interesting that 5 of 13 (38.5%) identified homozygous deletion of
genes (TRAF3, cIAP1,
cIAP2, and CYLD)
that are involved in negative regulation of NF-kB. To confirm
homozygous deletions, they performed FISH investigations and GEP
analyses. The paper further develops the impact of absence of TRAF3
gene product in overall prognosis and response to drugs used in MM
treatment. Authors showed that deletion of TRAF3
is associated with poor response to dexamethasone, but rather a good
therapeutic response to proteasome inhibitors. Furthermore, the
authors proposed that TRAF3
is a tumor suppressor gene, which was verified by reintroduction
of functional copies of genes in adenovirus vector into myeloma cell
lines. Cell lines with increased activity NF-kB showed a subsequent
reduction in growth and increased apoptosis. In contrast, in cell
lines with inactive NF-kB, the introduction of the common TRAF3
showed no change. Study by Chng et al  of a group of 131
patients focused on identifying new prognostic regions using aCGH and
GEP arrays. Combined GEP and aCGH analysis identified areas with
possible prognostic impact. Patients with deletions at 1p31–1p32 or
20p12.3–12.1 were found to have significantly shorter overall
survival compared to patients without these deletions (24.5 months
vs. 40 months p = 0.01; 20.6 months vs. 40
months p = 0.06, respectively). Survival after relapse was also
significantly reduced, but due to a small number of patients,
results were not quite statistically significant. Deletion
20p12.3–12.1 was also significantly associated with deletion 17p13
and also showed a strong trend to associate with t(11;14)
detected by FISH.
Our preliminary data from
a cohort of 84 MM patients performed on Agilent 4x44K arrays so
far confirmed previously published data. We found several new genetic
events in MM patients and abnormalities of candidate genes. Data from
our study will be published elsewhere.
remains incurable even today. Introduction of new types of drugs
(bortezomib, lenalidomide, thalidomide) and therapeutic strategies
significantly prolonged survival of patients with MM and their
quality of life during treatment . Similarly to many other types
of hematologic malignancies, MM is characterized by numerous
structural and numerical CHA involving many oncogenes, tumor
suppressor genes or genes involved in signaling pathways important
for cell cycle, apoptosis etc. Detection of CHA is one of the most
important independent prognostic markers in MM pathogenesis and
prognosis for patients . Oligonucleotide-based aCGH technique
provides both qualitative and quantitative information about CHA in
the genome of malignant PCs in a single experiment. In MM
pathogenesis, it is valuable diagnostic and scientific instrument
suitable for description of genetic heterogeneity typical for MM
providing new opportunities for identification of new biomarkers
capable of discerning prognosis.
During the last decade, several
important genetic events in MM pathogenesis using conventional CGH or
aCGH were described and verified [21,24,29–31]. Presented
data emphasize the strengths of
high-resolution aCGH results in the detection of genomic alterations
associated with development of disease and prognosis of MM patients.
However, it is now clear that there is a need for correlation of
aCGH findings with other advanced techniques (GEP, methylation
analysis). Moreover, newly developed techniques have relegated the
importance of aCGH into the background. Recent publications show the
new trend in development, leading to sequencing of the second and
third generation [34,35], which provides information in a much
larger scale than aCGH platform, which is currently available and
thus allow us more precise insight into genetic changes in pathology
of all malignant diseases.
Jan Smetana Babak
Myeloma Group Department
of Pathological Physiology Faculty
00 Brno Czech
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