Gene expression profiling of B-CLL in Ukrainian patients in post-Chernobyl period
Background: Genetic mechanisms that result in the development and progression of B-cell chronic lymphocytic leukemia (B-CLL) are mainly unknown. We have analyzed gene expression patterns in Ukrainian B-CLL patients with the aim of identifying B-CLL involved / associated genes in order to shed light...
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Інститут експериментальної патології, онкології і радіобіології ім. Р.Є. Кавецького НАН України
2012
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| Цитувати: | Gene expression profiling of B-CLL in Ukrainian patients in post-Chernobyl period / H. Savli, D. Sunnetci, N. Cine, D.F. Gluzman, M.P. Zavelevich, L.M. Sklyarenko, V.A. Nadgornaya, S.V. Koval // Experimental Oncology. — 2012. — Т. 34, № 1. — С. 57-63. — Бібліогр.: 47 назв. — англ. |
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irk-123456789-1387172018-06-20T03:06:16Z Gene expression profiling of B-CLL in Ukrainian patients in post-Chernobyl period Savli, H. Sunnetci, D. Cine, N. Gluzman, D.F. Zavelevich, M.P. Sklyarenko, L.M. Nadgornaya, V.A. Koval, S.V. Original contributions Background: Genetic mechanisms that result in the development and progression of B-cell chronic lymphocytic leukemia (B-CLL) are mainly unknown. We have analyzed gene expression patterns in Ukrainian B-CLL patients with the aim of identifying B-CLL involved / associated genes in order to shed light on the biology of this pathological entity. Material and methods: The samples of the peripheral blood and bone marrow of 44 Ukrainian B-CLL patients with no characteristics indicative of unfavorable course of the disease such as CD38 were analyzed morphologically and immunocytochemically according to the new WHO classification. Total RNA was isolated, and gene expression levels were determined by microarray method comparing with the sample from 17 healthy donors. Results: We investigated interactions using the Ingenuity Pathway Analysis (IPA) software and found 1191 network eligible up-regulated genes and 3398 Functions/Pathways eligible up-regulated genes, 1225 network eligible down-regulated genes and 2657 Functions/Pathways eligible down-regulated genes. Conclusion: In B-CLL patients, gene networks around MYC, HNF1A and HNF4A, YWHAG, NF-κB1 and SP1 are identified as up-regulated; CEBPA, YWHAG, SATB1 and RB1 — as down-regulated. G protein coupled receptor signaling, arachidonic acid and linoleic acid metabolisms, calcium signaling, metabolism of xenobiotics by cytochrome P450 are found out as significant up-regulated pathways. EIF2 and Cdc42 signaling, regulation of eIF4 and p70S6k signaling, protein ubiquitination pathway and oxidative phosphorylation are the most significant down-regulated pathways obtained in our study. The involvement of NF-κB gene network and upregulated levels of G protein coupled receptor signaling pathway, which has an important role in transcription of NF-κB, are important and need further examination. 2012 Article Gene expression profiling of B-CLL in Ukrainian patients in post-Chernobyl period / H. Savli, D. Sunnetci, N. Cine, D.F. Gluzman, M.P. Zavelevich, L.M. Sklyarenko, V.A. Nadgornaya, S.V. Koval // Experimental Oncology. — 2012. — Т. 34, № 1. — С. 57-63. — Бібліогр.: 47 назв. — англ. 1812-9269 http://dspace.nbuv.gov.ua/handle/123456789/138717 en Experimental Oncology Інститут експериментальної патології, онкології і радіобіології ім. Р.Є. Кавецького НАН України |
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English |
| topic |
Original contributions Original contributions |
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Original contributions Original contributions Savli, H. Sunnetci, D. Cine, N. Gluzman, D.F. Zavelevich, M.P. Sklyarenko, L.M. Nadgornaya, V.A. Koval, S.V. Gene expression profiling of B-CLL in Ukrainian patients in post-Chernobyl period Experimental Oncology |
| description |
Background: Genetic mechanisms that result in the development and progression of B-cell chronic lymphocytic leukemia (B-CLL) are mainly unknown. We have analyzed gene expression patterns in Ukrainian B-CLL patients with the aim of identifying B-CLL involved / associated genes in order to shed light on the biology of this pathological entity. Material and methods: The samples of the peripheral blood and bone marrow of 44 Ukrainian B-CLL patients with no characteristics indicative of unfavorable course of the disease such as CD38 were analyzed morphologically and immunocytochemically according to the new WHO classification. Total RNA was isolated, and gene expression levels were determined by microarray method comparing with the sample from 17 healthy donors. Results: We investigated interactions using the Ingenuity Pathway Analysis (IPA) software and found 1191 network eligible up-regulated genes and 3398 Functions/Pathways eligible up-regulated genes, 1225 network eligible down-regulated genes and 2657 Functions/Pathways eligible down-regulated genes. Conclusion: In B-CLL patients, gene networks around MYC, HNF1A and HNF4A, YWHAG, NF-κB1 and SP1 are identified as up-regulated; CEBPA, YWHAG, SATB1 and RB1 — as down-regulated. G protein coupled receptor signaling, arachidonic acid and linoleic acid metabolisms, calcium signaling, metabolism of xenobiotics by cytochrome P450 are found out as significant up-regulated pathways. EIF2 and Cdc42 signaling, regulation of eIF4 and p70S6k signaling, protein ubiquitination pathway and oxidative phosphorylation are the most significant down-regulated pathways obtained in our study. The involvement of NF-κB gene network and upregulated levels of G protein coupled receptor signaling pathway, which has an important role in transcription of NF-κB, are important and need further examination. |
| format |
Article |
| author |
Savli, H. Sunnetci, D. Cine, N. Gluzman, D.F. Zavelevich, M.P. Sklyarenko, L.M. Nadgornaya, V.A. Koval, S.V. |
| author_facet |
Savli, H. Sunnetci, D. Cine, N. Gluzman, D.F. Zavelevich, M.P. Sklyarenko, L.M. Nadgornaya, V.A. Koval, S.V. |
| author_sort |
Savli, H. |
| title |
Gene expression profiling of B-CLL in Ukrainian patients in post-Chernobyl period |
| title_short |
Gene expression profiling of B-CLL in Ukrainian patients in post-Chernobyl period |
| title_full |
Gene expression profiling of B-CLL in Ukrainian patients in post-Chernobyl period |
| title_fullStr |
Gene expression profiling of B-CLL in Ukrainian patients in post-Chernobyl period |
| title_full_unstemmed |
Gene expression profiling of B-CLL in Ukrainian patients in post-Chernobyl period |
| title_sort |
gene expression profiling of b-cll in ukrainian patients in post-chernobyl period |
| publisher |
Інститут експериментальної патології, онкології і радіобіології ім. Р.Є. Кавецького НАН України |
| publishDate |
2012 |
| topic_facet |
Original contributions |
| url |
http://dspace.nbuv.gov.ua/handle/123456789/138717 |
| citation_txt |
Gene expression profiling of B-CLL in Ukrainian patients in post-Chernobyl period / H. Savli, D. Sunnetci, N. Cine, D.F. Gluzman, M.P. Zavelevich, L.M. Sklyarenko, V.A. Nadgornaya, S.V. Koval // Experimental Oncology. — 2012. — Т. 34, № 1. — С. 57-63. — Бібліогр.: 47 назв. — англ. |
| series |
Experimental Oncology |
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2025-07-10T06:26:13Z |
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2025-07-10T06:26:13Z |
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1837240398338064384 |
| fulltext |
Experimental Oncology ��� ������ ���� ��arc����� ������ ���� ��arc�� ��arc�� ��
GENE EXPRESSION PROFILING OF B-CLL IN UKRAINIAN PATIENTS
IN POST-CHERNOBYL PERIOD
H. Savli1,*, D. Sunnetci1, N. Cine1, D.F. Gluzman2, M.P. Zavelevich2,
L.M. Sklyarenko2, V.A. Nadgornaya2, S.V. Koval2
1Medical Genetics Department, Medicine Faculty of Kocaeli University, Turkey
2R.E. Kavetsky Institute of Experimental Pathology, Oncology and Radiobiology, NAS of Ukraine, Kyiv, Ukraine
Background: Genetic mechanisms that result in the development and progression of B-cell chronic lymphocytic leukemia (B-CLL) are
mainly unknown. We have analyzed gene expression patterns in Ukrainian B-CLL patients with the aim of identifying B-CLL involved /
associated genes in order to shed light on the biology of this pathological entity. Material and methods: The samples of the peripheral blood
and bone marrow of 44 Ukrainian B-CLL patients with no characteristics indicative of unfavorable course of the disease such as CD38 were
analyzed morphologically and immunocytochemically according to the new WHO classification. Total RNA was isolated, and gene expression
levels were determined by microarray method comparing with the sample from 17 healthy donors. Results: We investigated interactions using
the Ingenuity Pathway Analysis (IPA) software and found 1191 network eligible up-regulated genes and 3398 Functions/Pathways eligible
up-regulated genes, 1225 network eligible down-regulated genes and 2657 Functions/Pathways eligible down-regulated genes. Conclusion:
In B-CLL patients, gene networks around MYC, HNF1A and HNF4A, YWHAG, NF-κB1 and SP1 are identified as up-regulated; CEBPA,
YWHAG, SATB1 and RB1 — as down-regulated. G protein coupled receptor signaling, arachidonic acid and linoleic acid metabolisms,
calcium signaling, metabolism of xenobiotics by cytochrome P450 are found out as significant up-regulated pathways. EIF2 and Cdc42 sig-
naling, regulation of eIF4 and p70S6k signaling, protein ubiquitination pathway and oxidative phosphorylation are the most significant
down-regulated pathways obtained in our study. The involvement of NF-κB gene network and upregulated levels of G protein coupled recep-
tor signaling pathway, which has an important role in transcription of NF-κB, are important and need further examination.
Key Words: B-CLL, gene expression profiling, microarray analysis, gene networks.
Ionizing radiation �IR� is one of t�e most studied
carcinogens in t�e development of multiple myeloma�
primary myelofibrosis� polycyt�emia vera� non-Hodg-
kin’s lymp�omas� myelodysplastic syndromes and
some forms of acute and c�ronic leukemia� especially
in acute myelogenous leukemia �A�L� [�� �]. Until re-
cently� c�ronic lymp�ocytic leukemia �CLL� �as not been
considered as a radiation-associated leukemia. Nev-
ert�eless� current understanding of radiation-induced
tumorigenesis and t�e etiology of lymp�atic neoplasia
s�ow t�at IR exposure increases CLL risk [�].
After C�ernobyl nuclear accident� people living
in t�e contaminated areas of Ukraine are still exposed
to low doses of IR. Analysis of t�e patients wit� various
forms of t�e malignancies of �ematopoietic and lym-
p�oid tissues �as not revealed t�e differences in B-CLL
percentage among C�ernobyl clean-up wor kers and
Ukrainian population in w�ole. B-CLL was s�own
to be a predominant form of �ematopoietic malignancies
in clean-up workers as well as in general population [�].
Genetic mec�anisms t�at result in t�e development and
progression of CLL are mainly unknown [�]. Gene expres-
sion profiling by microarray is useful to understand B-CLL
origin and development [�]. T�e analysis of t�e molecular
genetic features s�ould be advantageous in elucidating
t�e putative association of IR and B-CLL.
Earlier� we �ave studied gene expressions of seve-
ral apoptosis related genes in different types of tumors
of �ematopoietic and lymp�oid tissues in �89 patients
including t�ose wit� B-CLL living in areas of Ukraine
contaminated wit� radionuclides in post-C�ernobyl
period [�]. In t�e present study� we �ave analyzed gene
expression patterns in samples from �� B-CLL Ukrainian
patients in post-C�ernobyl period wit� t�e aim of iden-
tifying t�e genes related to or involved in t�is pat�ology
in order to s�ed lig�t on t�e biology of B-CLL.
MATERIAL AND METHODS
T�e samples of t�e perip�eral blood of B-CLL patients
were obtained from R.E. Kavetsky Institute of Experimen-
tal Pat�ology� Oncology and Radiobio logy of t�e National
Academy of Sciences of Ukraine. All t�e patients were
referred to Reference Laboratory of Immunocytoc�em-
istry and Onco�ematology Department of t�e Institute for
verifying t�e diagnosis. Bone marrow and perip�eral blood
smears stained by �ay-Grunwald-Giemsa were studied
morp�ologically. Immunocytoc�emical tec�niques �APAAP�
LSAB-AP� and a broad panel of monoclonal antibodies
against lineage specific� differentiation and activation
antigens of leukocytes were employed for immunop�e-
notyping pat�ological cells in blood and bone marrow.
T�e main forms and cytological variants of �ematological
malignancies were diagnosed according to new WHO clas-
sification [8]. All t�e samples were immunop�enotyped�
and only �� samples from CD�8-negative B-CLL patients
out of ��� diagnosed patients wit� B-CLL/B-cell lymp�oma
from small lymp�ocytes [�] were included in t�e study.
Control group comprised perip�eral blood samples from
�� �ealt�y donors. T�e et�ic committees of bot� collaborat-
ing researc� institutions approved t�e design of t�e study.
Total RNA isolation. Total RNA was isolated from
mononuclear cells for eac� patient using QIAamp RNA
Blood �ini Kit �QIAGEN� Valencia� CA� USA� and treated
Received: February 2, 2012.
*Correspondence: E-mail: hakansavli@yahoo.com
Abbreviations used: AML — acute myelogenous leukemia;
B-CLL — B-cell chronic lymphocytic leukemia; IPA — Ingenuity
Pathway Analysis; IR — ionizing radiation.
Exp Oncol ����
��� �� �����
�8 Experimental Oncology ��� ������ ���� ��arc��
wit� DNase I according to t�e manufacturer’s instruc-
tions. T�e quality of t�e RNA was assessed by loading
��� ng of total RNA onto an RNA Labc�ip �Agilent Tec�-
nologies� Waldbronn� Germany�� followed by analysis
�A���� Bioanalyzer; Agilent Tec�nologies�. An RNA
integrity value �RIN� of �.� was considered acceptable.
RNAs from �� B-CLL patients and �� �ealt�y donors
were pooled seperately. Pooling process was performed
in t�e way t�at ��� ng RNA sample was used from eac�
B-CLL patient/�ealt�y donor. Eac� RNA pool was pre-
pared as t�ree replicates.
Microarray analysis. �icroarray analysis was
performed using t�e W�ole Human Genome Oligo �i-
croarray �Agilent Tec�nologies�� encompassing more
t�an ������ �uman DNA probes. T�e full list of cDNAs
is available online �www.agilent.com�. Protocols for
sample preparation and �ybridization of t�e mononuclear
cells were adaptations of t�ose in t�e Agilent Tec�nical
�anual. In s�ort� first strand cDNA was trans cribed from
��� ng of total RNA using T�-Oligo�dT� Promoter Primer.
Samples were transcribed in vitro and Cy-�-labelled
by using a Quick-A�P labeling kit �Agilent Tec�nologies�.
Following a furt�er clean-up round �Qiagen�� cRNA was
fragmented into pieces ranging from �� to ��� bases
in size. Fragmented cRNA samples ��.�� mg� were �ybrid-
ized onto c�ips by means of �� � of incubation at ��°C wit�
constant rotation� followed by a two-step microarray was�
of � min in two was�ing buffers �Agilent Tec�nologies�. Hy-
bridized microarrays were scanned in a Agilent Tec�nolo-
gies Scanner �model G����B� and numerical results were
extracted wit� Feature Extraction version 9.�.�.� using
���8��_D_F_�����8�� grid� GE�-v�_9�_Feb�� protocol
and GE�_QC�_Feb�� QC metric set.
T�e microarray data were analyzed using GeneSpring
software version 9.� �Agilent Tec�nologies� Santa Clara�
CA�. T�e fold c�anges were analyzed by filtering t�e
dataset using P-value < �.�� and a signal-to-noise ratio
>� for use in T-test statistical analysis. Additional filter-
ing �minimum �-fold c�ange� was applied to extract t�e
most t�ese genes� w�ic� were analyzed using Ingenuity
Pat�way Analysis �IPA� software �Ingenuity Systems�
Redwood City� CA�. T�ose genes wit� known gene sym-
bols �HUGO� and t�eir corresponding expression values
were uploaded into t�e software. Eac� gene symbol was
mapped to its corresponding gene object in t�e Ingenu-
ity Pat�ways Knowledge Base. Networks of t�ese genes
were algorit�mically generated based on t�eir connec-
tivity and assigned a score. T�e score is a numerical
value used to rank Networks according to �ow relevant
t�ey are to t�e genes in t�e input dataset but may not
be an indication of t�e quality or significance of t�e net-
work. T�e score takes into account t�e number of focus
genes in t�e network and t�e size of t�e network to ap-
proximate �ow relevant t�is network is to t�e original list
of focus genes. T�e network identified is t�en presented
as a grap� indicating t�e molecular relations�ips between
genes/gene products. Genes are represented as nodes�
and t�e biological relations�ip between two nodes is rep-
resented as an edge �line�. T�e intensity of t�e node color
indicated t�e degree of up- or down-regulation. T�e node
s�apes are disclosed in corresponding figure legends.
Canonical pat�way analysis identified t�e pat�ways from
t�e IPA library of canonical pat�ways� w�ic� were most
significant to t�e input data set. T�e significance of t�e
association between t�e data set and t�e canonical pat�-
way was determined based on two parameters: ��� A ratio
of t�e number of genes from t�e data set t�at map to t�e
pat�way divided by t�e total number of genes t�at map
to t�e canonical pat�way and ��� a P value calculated
using Fisc�er’s exact test determining t�e probability t�at
t�e association between t�e genes in t�e data set and
t�e canonical pat�way is due to c�ance alone.
Quantitative real-time PCR (Q-RT-PCR). cDNA
was synt�esized using RevertAid First Strand cDNA
Synt�esis Kit �Fermentas Inc.� �aryland� USA�. Q-RT-
PCR was performed as we described previously for
determination of MYC� BAX� BCL-2 and FAS1 gene ex-
pressions [9� ��]. Standard curves were obtained using
serial dilutions of t�e beta-globulin gene �DNA Control
Kit� Roc�e�. Gene-specific primers �Table �� were ob-
tained from Integrated DNA Tec�nologies �Iowa� USA�.
Obtained gene expression values were normalized us-
ing a �ousekeeping gene of beta� microglobulin. Gene
expression ratios were compared in patient and control
groups using REST �Relative Expression Software Tool�.
Table 1. List of the primers used for the quantitative RT-PCR
Genes Primer sequences
Beta2 microglobulin (F) 5’ TGA CTT TGT CAC AGC CCA AGA TA 3’
(R) 5’ AAT CCA AAT GCG GCA TCT TC 3’
BAX (F) 5’ TGC TTC AGG GTT TCA TCC AG 3’
(R) 5’ GGC GGC AAT CAT CCT CTG 3’
MYC (F) 5’ GGC AAA AGG TCA GAG TCT GG 3’
(R) 5’ GTG CAT TTT CGG TTG TTG C 3’
FAS1 (F) 5’ CAA GGG ATT GGA ATT GAG CA 3’
(R) 5’ GAC AAA GCC ACC CCA AGT TA 3’
BCL-2 (F) 5’ AGG AAG TGA ACA TTT CGG TGA C 3’
(R) 5’ GCT CAG TTC CAG GAC CAG GC 3’
RESULTS
Differentially expressed genes are s�own in two
separate tables. T�e ��� most up-regulated genes are
s�own in Table �. T�e ��� most down-regulated genes
are s�own in Table �. Bot� sets of results were obtained
based on minimum �-fold c�ange using GeneSpring
software version 9.� �Agilent Tec�nologies� Santa Clara�
CA�. In Table � t�e gene expression results of four genes
�MYC� BAX� BCL-2 and FAS1� obtained by real-time PCR
and microarray met�ods are compared. Real-time PCR
results of MYC� BCL-2 and BAX are in a good agreement
wit� microarray expression rates.
Table 4. Summarized real-time PCR confirmation results of the four genes
Genes Ratios obtained by RT-PCR Ratios obtained by arrays
BAX 5.0265 (Up-regulated) 2.592 (Up-regulated)
BCL-2 16.696 (Up-regulated) 1.747 (Up-regulated)
MYC 4.15 (Up-regulated) 2.794 (Up-regulated)
FAS1 4.536 (Up-regulated) 2.460 (Down-regulated)
We investigated interactions using IPA software and
found ��9� network eligible up-regulated genes and
��98 Functions/Pat�ways eligible up-regulated genes.
Fig. � s�ows t�e most significant four gene networks
of over-expressed genes in B-CLL samples. Top func-
tions of t�ese genes are related to �ematopoiesis� lipid
metabolism� small molecule bioc�emistry� cancer� infec-
Experimental Oncology ��� ������ ���� ��arc����� ������ ���� ��arc�� ��arc�� �9
tious diseases� cell cycle� cardiovascular system deve-
lopment and function� gene expression� embryonic de-
velopment� tissue morp�ology� inflammatory response.
Up-regulated gene networks are identified around MYC�
HNF1A and HNF4A� YWHAG� NF-κB1 and SP1.
We also found ���� network eligible down-regulated
genes� and ���� Functions/Pat�ways eligible down-regu-
lated genes. Fig. � s�ows four gene networks of down-
regulated genes in B-CLL. T�e main functions of t�e genes
are related to cellular functions and maintenance� protein
synt�esis� dermatological diseases and conditions� cell
deat�� gene expression� inflammatory disease� cellular
growt� and proliferation� post-translational modification�
cancer� infectious diseases� cell morp�ology� and deve-
lopment. Down-regulated gene networks are identified
around CEBPA� YWHAG� SATB1 and RB1.
DISCUSSION
B-CLL is a �eterogeneous disease and a predominant
form of �ematopoietic malignancies. Despite new molecu-
lar met�ods identifying important prognostic and diagnostic
genetic markers� genetic mec�anisms involved in B-CLL
origin are mainly unknown. A number of novel prognostic
markers suc� as Bcl-�� �AP-kinase� NF-κB� ZAP-�� were
identified applying gene expression profiling before [��� ��].
We �ave analyzed gene expression patterns in sam-
ples from �� B-CLL Ukrainian patients in post-C�ernobyl
period to identify genes associated wit� t�is form of lym-
p�oproliferative malignancy. Our study �as demon-
strated new genetic networks and biological pat�ways
in bot� up- and down-regulated gene expression levels.
Analysis using IPA software revealed ��9� network
eligible up-regulated genes and ��98 Functions/Pat�-
ways eligible up-regulated genes. T�e individual genes
are found in multiple categories of functions related
to �ematopoiesis� lipid metabolism� small molecule
bioc�emistry� cancer� infectious diseases� cell cycle�
development and function of cardiovascular system�
gene expression� embryonic development� tissue
morp�ology� inflammatory response.
One important gene network is identified around
t�e up-regulated MYC and SP1 genes �Fig. �� a�. MYC�
a strong proto-oncogene� plays very important roles in cell
proliferation �by upregulating cyclins� downregulating
p���� controlling cell growt� �by upregulating ribosomal
RNA and proteins�� apoptosis �by downregulating BCL-
Table 2. The 100 most up-regulated genes in B-CLL
Fold Change Gene
9.971721 CB162722
9.893506 THC2579650
9.856071 IRX5
9.828577 SAPS1
9.718567 THC2671344
9.659609 LRRC2
9.598212 PIGR
9.52783 BX119852
9.385712 FMOD
9.34002 CGB1
9.180631 VPS18
9.170944 RAPH1
9.11223 RNF150
9.11183 RAP1GAP
9.109504 RPA4
9.073619 THC2672701
9.049471 CD86
9.029652 RBM22
8.81397 AA704712
8.759307 AA479896
8.743843 AKAP12
8.691222 CCDC66
8.670482 ABCA4
8.608516 CV575560
8.573189 GRAMD1C
8.567822 EFTUD1
8.518443 LOC389043
8.484631 S71486
8.467656 BTC
8.455834 SMARCA4
8.4216795 MGC39584
8.39463 BF368414
8.346779 C1orf173
8.317559 NDP
8.281372 BI826226
8.207127 RPTN
8.186712 PRRX1
8.142795 BQ286187
8.100048 L5
8.054283 ATXN3L
8.05317 AK098548
8.044337 TEF
8.034349 WDR33
8.031527 CASKIN2
8.008858 FLJ25770
7.9823356 THC2686753
7.9713397 KLHL23
7.9610386 POLR2J2
7.9588156 STARD13
7.950879 MLL
Fold Change Gene
7.9061837 TTC23
7.886104 SFRP1
7.8818917 FLJ32679
7.8160353 MMP14
7.798868 MEGF10
7.7877035 WDR21C
7.775479 BU587941
7.7426653 BCR
7.7220807 THC2676656
7.706189 AI089002
7.6771984 WNT3
7.648338 UCP3
7.647829 NFE2L1
7.6217384 C1orf168
7.6014295 TMPRSS3
7.6004906 WNT2B
7.5972705 TUSC5
7.5422063 TEX12
7.522491 MGC88374
7.4850636 ST6GAL1
7.4668427 LOC645478
7.4543867 KIAA0672
7.4285965 NAV2
7.419999 THC2537502
7.419809 KIAA1946
7.3947935 BX647159
7.3545713 BG190682
7.3339643 RUNDC2B
7.3178434 GBP6
7.2903414 ZNF713
7.2862663 ASB16
7.2639813 THC2530551
7.2611523 PPM1F
7.2371364 MYOC
7.228985 LOC643401
7.2250643 KALRN
7.215619 MYCNOS
7.1989717 CRISPLD2
7.1989717 CRISPLD2
7.192935 ADIPOQ
7.192935 ADIPOQ
7.1847763 SLC44A5
7.1847763 SLC44A5
7.1711025 ZCCHC13
7.135996 SLC27A1
7.1255236 ZNF2
7.122238 MSTP9
7.0874977 PSPH
7.048849 PYY2
7.032443 AD7C-NTP
Table 3. The 100 most down-regulated genes in B-CLL
Fold Change Gene
-9.467819 THC2588392
-8.866756 HBG1
-8.638458 SELENBP1
-8.50988 HBA2
-8.47693 HBG1
-7.8862677 SAT1
-7.8419037 FCGR3A
-7.80179 RGS2
-7.7845144 SLC25A39
-7.7299724 ALAS2
-7.686287 KRT1
-7.6433597 SRGN
-7.6020937 PROK2
-7.5707283 S100P
-7.5505257 TNFRSF10C
-7.475219 MXD1
-7.389961 HBD
-7.376893 CLEC4E
-7.297138 CMTM6
-7.2936077 FTL
-7.292986 PAIP2
-7.2235703 ALAS2
-7.182671 HBD
-7.1385164 LGALS3
-7.1038146 IFIT2
-7.0883236 ANXA1
-7.055394 AQP9
-7.054615 LOC552891
-6.935093 C6orf32
-6.9139557 PDZK1IP1
-6.892113 FBXL5
-6.8429413 CMTM2
-6.823658 HBQ1
-6.8207946 BNIP3L
-6.7675858 CLC
-6.7639685 AP1S2
-6.7029543 ALOX5AP
-6.678584 ACTG1
-6.6524496 GIMAP7
-6.643402 GCA
-6.632475 CSTA
-6.6212616 PBEF1
-6.5431356 LIMK2
-6.537367 SOD2
-6.535038 TP53INP1
-6.5181375 IFIT1
-6.475131 BID
-6.470724 HIST1H2AC
-6.470461 DUSP1
-6.461632 MNDA
Fold Change Gene
-6.4505854 BCL2A1
-6.4489126 TTRAP
-6.3537326 TNFAIP2
-6.341367 IL1R2
-6.3040967 FYB
-6.26194 S100A12
-6.2470803 TLR2
-6.2420635 SNCA
-6.2413063 PBEF1
-6.2392893 THC2586959
-6.231715 CAMP
-6.2299414 S100A8
-6.2271876 KRT23
-6.193751 DYNLT1
-6.171741 SLC31A2
-6.153518 RGS18
-6.139215 SIPA1L1
-6.125804 CCR1
-6.0938168 ADD3
-6.021562 NFE2
-6.0161657 QPCT
-5.994034 ITM2B
-5.9857407 YPEL5
-5.9691944 IFNGR1
-5.955679 IL8RB
-5.950643 C20orf24
-5.9466496 GLUL
-5.9364004 NINJ1
-5.9354315 C5orf32
-5.9249115 VPS4B
-5.9206657 FLJ10357
-5.9169197 HSD17B11
-5.904073 UBB
-5.895618 FTL
-5.894103 SAT1
-5.8842864 CKLF
-5.8623157 MYL4
-5.8620443 FBXO7
-5.8529325 LCP1
-5.8372726 SNN
-5.8210387 BNIP3L
-5.8020077 MTPN
-5.7948103 COPS5
-5.7918744 NGFRAP1
-5.782423 MFSD1
-5.7802 MPP1
-5.7671204 HIPK1
-5.7636905 PBEF1
-5.746536 PAG1
-5.7328815 APOBEC3A
�� Experimental Oncology ��� ������ ���� ��arc��
2�� differentiation and stem cell self-renewal. �utations�
overexpression� rearrangement and translocation of MYC
�ave been associated wit� a variety of �ematopoietic
tumors� leukemias and lymp�omas� including Burkitt
lymp�oma [��]. Hig� expression level of MYC �as been
reported in more aggressive and apoptosis resistant forms
of B-CLL and mig�t be used as molecular marker specific
of resistant B-CLL subsets [��� ��]. SP�� a zinc finger
transcription factor� is involved in cell differentiation� cell
growt�� apoptosis� immune response� response to DNA
damage� and c�romatin remodeling. SP1 and MYC are
involved cooperatively in telomerase activation� w�ic�
is a critical step in cellular immortalization and carcinogen-
esis. Kyo et al. �ave suggested t�at t�e level of SP� ex-
pression mig�t be a critical determinant of telomerase
activity bot� in cancer and normal cells [��].
Anot�er network is identified around NF-κB1 gene
�Fig. �� b�. NF-κB regulates several genes t�at mediate
tumorigenesis and metastasis and also plays an im-
portant role in pat�ogenesis of B-cell neoplasms. Car-
cinogens� tumor promoters� inflammatory cytokines�
and c�emot�erapeutic agents activate NF-κB and
t�is activation can suppress apoptosis� t�us pro-
moting c�emoresistance and tumorigenesis. B�arti
et al. suggested t�at NF-κB mig�t be an ideal target
for c�emoprevention and c�emosensitization [���
�8]. In addition� we �ave found NF-κB gene centered
around two up- and down-regulated networks in our
previous study on prostate cancer [�9].
Canonical pat�way analysis revealed t�at G-protein
coupled receptor �GPCR� signaling is an important
pat�way modulated by t�e up-regulated genes
in B-CLL. It is known t�at GPCRs regulate proliferation�
differentiation� c�emotaxis and also t�ey play an im-
portant role in inflammatory diseases and cancer [��].
GPCRs are involved in control of transcription factors
suc� as STAT�� NF-κB and CREB by G protein sub-
families [��]. En�anced viability of CLL cells by t�e
STAT� p�osp�orylation and interaction between �epa-
tocyte growt� factor and its receptor �c-�ET�� w�ic�
a b
dc
Fig. 1. Significant up-regulated gene networks identified around MYC and SP1 genes �a�� NF-κB1 gene �b�� HNF1A and HNF4A
genes �c�� YWHAG gene �d� in B-CLL samples. T�e node s�apes denote enzymes � �� p�osp�atases � �� kinases � �� peptidases
� �� G-protein coupled receptor � �� transmembrane receptor � �� cytokines � �� growt� factor � �� ion c�annel � �� transporter � ��
translation factor � �� nuclear receptor � �� transcription factor � � and ot�er � �.T�e intensity of t�e node color-�red� indicated
t�e degree of up-regulation
Experimental Oncology ��� ������ ���� ��arc����� ������ ���� ��arc�� ��arc�� ��
was found up-regulated in our study� was reported
before [��]. CREB �cA�P response element binding
protein� �ad been found overexpressed in bone mar-
row samples from patients wit� acute lymp�oid and
myeloid leukemia and associated wit� a poor outcome
in A�L patients according to previous studies [��].
A network is also identified around HNF1A and HNF4A
�Fig. �� c�. HNF�A is a transcription factor required for t�e
expression of several liver-specific genes and t�e expres-
sion of t�is gene is controlled by HNF�A� w�ic� may play
role in development of t�e liver� kidney and intestines.
Anot�er significant signaling pat�way is calcium
signaling involved in many processes suc� as cell sur-
vival/apoptosis� cell cycle progression� differentiation�
cross-talk between intracellular compartments �ER�
mitoc�ondria�� general metabolism and telomerase activ-
ity. T�e calcineurin/NFAT signaling pat�way is important
in lymp�oma/leukemogenesis [��]. Deregulation of t�is
signaling and/or abnormal expression of its components
�as been reported in solid tumors of epit�elial origin� lym-
p�oma and lymp�oid leukemia. �ouse models of �uman
T-ALL/lymp�oma s�owed t�e pro-oncogenic effect of ac-
tive calcineurin/NFAT signaling in vivo [��]. NFAT tran-
scription factors form four calcium signaling responsive
members: NFATc�� NFATc�� NFATc� and NFATc�. Among
t�ese members NFATc� and NFATc�� w�ic� are found up-
regulated in our study� were reported to be involved in t�e
development� differentiation and functioning of multiple
T-and B-cell subsets in previous studies. NFATc� was
found to be expressed in a majority of aggressive B-cell
lymp�omas. On t�e ot�er �and� NFATc� activation was
s�own to be responsible in B-CLL� in cooperation wit�
STAT�� for t�e �ig� expression of CD�� [��].
�etabolism of xenobiotics by cytoc�rome P��� pat�-
way �as been s�own as �ig�ly significant in our study.
T�e en�anced expression of several P���s like CYP�A�
CYP�C and CYP�A� t�at are up-regulated in our study�
was reported in tumor cells elsew�ere [��].
Arac�idonic acid and linoleic acid metabolisms are
t�e ot�er significant pat�ways modulated by t�e up-
regulated genes in our study.
Analysis using IPA software revealed ���� network
eligible down-regulated genes� and ���� Functions/
Pat�ways eligible down-regulated genes. T�ese individual
a b
dc
Fig.2. A significant down-regulated gene network identified around RB1 gene �a�� SATB1 gene �b� in B-CLL samples� CEBPA gene
�c�� YWHAG gene �d� in B-CLL samples. T�e keys to t�e node s�apes are t�e same as in Fig. �. T�e intensity of t�e node color-
�green� indicates t�e degree of down-regulation
�� Experimental Oncology ��� ������ ���� ��arc��
genes are related to cell functions and maintenance� protein
synt�esis� dermatological diseases and conditions� cell
deat�� gene expression� inflammatory disease� cell growt�
and proliferation� post-translational modification� cancer�
infectious diseases� cell morp�ology� and development.
One important down-regulated network is identified
around RB1 gene �Fig. �� a�. T�e role of RB1 in B-CLL �as
been reported based on cytogenetic data [��]. RB1 dele-
tions involved in ��q�� abnormalities �ave been reported
in B-CLL before [�8].
Anot�er down-regulated network is identified around
SATB1 gene �Fig. �� b�. SATB1 is a new type of gene regulator
expressing in various �uman cancers and t�oug�t to be re-
lated to t�e malignant potential. Overexpression of t�is gene
�as been reported as a predictor of poor prognosis in lung
and gastric cancers [�9� ��].
An important network is identified around CEBPA
gene �Fig. �� c�. CEBPA is a critical transcriptional factor
and regulates t�e balance between cell proliferation and
differentiation during early �ematopoietic development
and myeloid differentiation [��]. CEBPA �as a tumor-
suppressor function in leukemogenesis and bot� loss
of function and gain of function �ave leukemogenic
potential. It was reported t�at overexpression of CEBPA
could contribute to B-ALL and loss of function could con-
tribute to A�L [��]. On t�e ot�er �and� down-regulated
CEBPA was found in acute promyelocytic leukemia stem
cells in animal models [��].
Canonical pat�way analysis revealed t�at oxidative
p�osp�orylation is an important pat�way modulated by t�e
down-regulated genes in B-CLL. In fact� previous studies
suggested t�at t�e oxidative p�osp�orylation �OXPHOS�
system is severely compromised in various cancers [��].
EIF� signaling is anot�er significant pat�way. Suppres-
sion of �ead and neck� colorectal carcinoma and multiple
myeloma tumor growt� and/or survival by p�osp�orylation
of eIF�α was reported before [��].
IPA reveals regulation of eIF� and p��s�K signa ling
pat�way. eIF�E down-regulated in our study plays an im-
portant role in tumor initiation and progression w�en its
overexpression cooperates wit� oncogenes to acceler-
ate transformation in cell lines and animal models [��].
p��s�K is a serine/t�reonine kinase and its target sub-
strate is S� ribosomal protein [��]. In�ibition of p��s�K
was related to cell cycle arrest at G�/G� p�ase in �uman
cancer cells before [�8].
Protein ubiquitination is anot�er pat�way found signifi-
cant in our study. Ubiquitination of key signaling molecules
by E� ubiquitin ligases forms an important regulatory
mec�anism for NF-κB signaling. Deubiquitinases �DUBs�
counteract E� ligases and play a substantial role in down-
regulation of NF-κB signaling and �omeostasis [�9].
Cdc�� signaling is a �ig�ly significant pat�way.
Cdc�� promotes or in�ibits tumor progression depending
on t�e cellular context and contributes to cancer develop-
ment t�roug� its different roles in intracellular trafficking�
cell cycle regulation and survival� polarity� migration and
transcriptional control [��]. Cdc�� is also important in t�e
development and progression of lymp�oma. Genetic
knockdown or p�armacological in�ibition of Cdc�� result-
ing in a cell cycle arrest and apoptosis of anaplastic large
cell lymp�oma cells �as been reported [��].
An important network is identified around bot� down-
regulated and up-regulated YWHAG gene in our study
�Fig. � and Fig. ��. T�is gene encoding for ����-� protein
gamma was found �ig�ly expressed in skeletal and �eart
muscles. It �as been suggested t�at t�is protein �as an im-
portant role in muscle tissue [��� ��]. ����-� proteins play
critical regulatory roles in signaling pat�ways in cell division
and apoptosis [��]. Furt�er investigations are required
to establis� t�e function of YWHAG gene in B-CLL.
Real-time PCR confirmation results of four genes
�MYC� FAS1� BAX and BCL-2� s�ow t�at only MYC� BAX
and BCL-2 expressions are in agreement wit� microar-
ray results. Up-regulation of MYC is compatible wit� our
expectations.
Previous studies indicate t�at �ig� ratio of Bcl-� to Bax
proteins confers a poor prognosis wit� decreased rates
of complete remission and overall survival [��]. In our study�
BCL-2 upregulation level is superior to t�at of BAX in real-
time PCR results but not in microarrays being analyzed.
FAS1 expression was found up-regulated in real-time
PCR but down-regulated in microarrays in our study.
It �as been reported t�at Fas expression is not very �ig�
in B-CLL [��] t�at coincides wit� our fin dings of relatively
small up-regulation by real-time PCR. It s�ould be noted
t�at Fas was mentioned as apoptosis regulator [��] in CLL
cells exposed to IR.
NF-κB gene network was conspicuous in terms of being
determined also in our previous studies of gene expression
in prostate cancer. In addition� upregulated levels of G protein
coupled receptor signaling pat�way� w�ic� �as an important
role in transcription of NF-κB� need advanced examinations.
In t�is sense� NF-κB gene w�ic� is important in bot� cell cycle
regulation and cancer progression deserves furt�er study.
Our study �as presented t�e gene expression profil-
ing in B-CLL patients of Ukrainian population as w�ole.
We believe t�at t�e contribution of IR as t�e putative factor
in t�e origin of B-CLL s�ould be furt�er evaluated using
suc� molecular genetic approac�.
ACKNOWLEDGEMENTS
T�e study was financed wit�in t�e framework of t�e
joint researc� project �/������8 “Cytomorp�ological�
immunocytoc�emical and molecular biological features
of leukemias in persons exposed to ionizing radiation” ac-
cording to t�e Agreement between t�e �inistry of Education
and Science of Ukraine and t�e Scientific and Tec�nical
Researc� Council of Turkey �TUBITAK�.
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