FIZIOLOGIA
physiology
FOUNDING EDITORCHIEF EDITOR
CO-CHIEF EDITORSASSOCIATE EDITORSEXECUTIVE EDITORSFRANCISC SCHNEIDERCARMEN PANAITESCUCARMEN TATUFLORINA BOJINMIHAI NECHIFORSORIN RIGAGABRIELA TANASIEDACIANA NISTORMARIUS GEORGESCUEDITORIAL BOARD
ARDELEAN AURELBĂDĂRĂU ANCA
BENEDEK GYORGYBENGA GHEORGHECOJOCARU MANOLEGĂLUȘCAN ATENAIANCAU MARIAMIHALAŞ GEORGETA
MUNTEAN DANINAMUREŞAN ADRIANANESTIANU VALERIUOPREA TUDORPANAITESCU CARMEN(Arad)(Bucureşti)(Szeged)(Cluj)(Bucureşti)(Timișoara)(Craiova)(Timişoara)(Timişoara)(Cluj)(Craiova)(New Mexico)(Timişoara)PĂUNESCU VIRGILPETROIU ANAPODARIU ANGELA CODRUTA
RÂCZ OLIVERRIGA DANSABĂU MARIUS
SAULEA I. AURELSIMIONESCU MAIASWYNGHEDAUW BERNARDTANGUAY M. ROBERTTATU ROMULUS FABIANVLAD AURELIANVOICU VICTORZĂGREAN LEON

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Fiziologia - Physiology • 2019.29.2(98)CONTENTS
Experimental Electrophysiological Device for the Appreciation of the Cardiac Systolic Function – A Pilot Study ...4
Ordodi V, Matiu-Iovan L, Barbulescu G, Bonciog D, Nistor D, Crisnic D, Tanasie G
Modern Application of Next-Generation Sequencing (NGS) ............................................................................................9Popa L, Crisnic D, Nistor D, Plesca D, Tatu C, Tanasie G, Zogorean R, Gavriliuc O, Anghel S, Bojin F, Paunescu V
Modified Langendorff Device For Rat Heart Decellularization ......................................................................................17
Bonciog D, Matiu-Iovan L, Barbulescu G, Burian C, Goje D, Buica P, Paunescu V, Ordodi V
B*08:01 HLA Class I and Class II Alleles And Haplotypes Frequencies Patients with Hematological Diseases
in the Western Part of Romania ........................................................................................................................................21
Gai E, Lungeanu D, Arghirescu S, Calma CL, Paunescu V
Experimental Electrocardiograph for Telemedicine .......................................................................................................35
Susman F, Lascu M, Ordodi V
EGF-Induced Chemotaxis of SK-BR3 Tumor Cells In Vitro Using Holographic Imaging ............................................38
Plesca D, Crisnic D, Nistor D, Tatu C, Tanasie G, Zogorean R, Anghel S, Gavriliuc O, Bojin F, Paunescu V

CUPRINS
Dispozitiv experimental electrofiziologic pentru evaluarea funcției sistolice cardiace – studiu pilot .........................4
Ordodi V, Matiu-Iovan L, Barbulescu G, Bonciog D, Nistor D, Crisnic D, Tanasie G
Aplicații moderne ale secvențierii de nouă generație (NGS) ...........................................................................................9Popa L, Crisnic D, Nistor D, Plesca D, Tatu C, Tanasie G, Zogorean R, Gavriliuc O, Anghel S, Bojin F, Paunescu
Dispozitiv Langendorff modificat pentru decelularizarea inimii de șobolan ................................................................17
Bonciog D, Matiu-Iovan L, Barbulescu G, Burian C, Goje D, Buica P, Paunescu V, Ordodi V
B*08:01 HLA clasa I, alelele MHC clasa II și frecvența haplotipurilor la pacienții cu afecțiuni hematologiceîn vestul României .............................................................................................................................................................21
Gai E, Lungeanu D, Arghirescu S, Calma CL, Paunescu V
Dispozitiv electrocardiografic pentru telemedicină ........................................................................................................35
Susman F, Lascu M, Ordodi V
Evaluarea in vitro a chemotaxiei celulelor tumorale SK-BR3 indusă de EGF prin imagistică holografică ...............38
Plesca D, Crisnic D, Nistor D, Tatu C, Tanasie G, Zogorean R, Anghel S, Gavriliuc O, Bojin F, Paunescu V

Fiziologia - Physiology • 2019.29.2(98)3EXPERIMENTAL ELECTROPHYSIOLOGICAL DEVICEFOR THE APPRECIATION OF THE CARDIAC SYSTOLICFUNCTION – A PILOT STUDYVALENTIN ORDODI1,2, LILIANA MÂȚIU-IOVAN1, GRETA BĂRBULESCU2,3,
DANIEL BONCIOG1, DACIANA NISTOR2,3, DANIELA CRÎSNIC2,4, GABRIELATĂNASIE2,3
1 Politehnica University of Timișoara, 2 Victoriei Square, RO-300006, Timișoara, România
2 OncoGen Research Center, Pius Bânzeu Clinical Emergency Hospital, 156 Liviu Rebreanu Bv, RO-300723, Timișoara România
3 University of Medicine and Pharmacy ”Victor Babeș” Timișoara, 2 Eftimie Murgu Square RO-300041, Timișoara, România
4 SC Biodim SRL, 59 Porumbescu St, RO-300239, Timișoara, România

ABSTRACTIn this paper we propose the design and implementation of an electrophysiological experimental device capable of acquiring
in real time three cardiovascular parameters: an electrocardiographic derivation (DII), the phonocardiogram and the
peripheral photoplestismogram pulse wave at the level of a finger from the upper limb. These parameters allow us tomeasure systolic parameters with the help of appropriate software and mathematical relationships to calculate theBlumberger hemodynamic index and ejection fraction of the left ventricle. The method is completely noninvasive, simple toperform than the classic polyphysiogram that involved recording the carotid sphygmogram and allows the assessment of
the systolic function of the left ventricle in the family doctor's office or of general medicine that does not have the equipment
and skills necessary to perform the echocardiographic examination. The preliminary results show a good correlation
between the ejection fraction measured echocardiographically (72%) and the value determined with the presented device(77%), which recommends testing the device on significant batches of patients with various cardiovascular pathologies.
Keywords: electrophysiological, non-invasive, cardiac systolic function

INTRODUCTION
Hypertensive, ischemic and valvular cardiovascularpathology is currently the most important cause of morbidity
and mortality worldwide and the age of onset of these
diseases is increasingly reduced. The instrumental
exploration of the cardiovascular function is a stage ofmaximum importance for specifying a correct diagnosis,
respectively prescribing the appropriate treatment. The
range of investigations that can explore the cardiovascularsystem is extremely extensive due to the development ofelectronics, computers and computers, biophotonics,
imaging, etc. In addition to modern imaging techniques:
echocardiography,
coronarography,
radioisotopic
exploration of cardiac and pulmonary function, computer
tomography and nuclear magnetic resonance, the traditional
methods: electrocardiography, phonocardiography andphotoplethysmography are widely available which provide

important data for an accurate cardiological diagnosis. Heart
failure is a syndrome that occurs during many ischemic or
non-ischemic heart conditions. Left and congestive heart
failure are more commonly encountered in medical practicecompared to isolated right heart failure.
The assessment of the systolic-diastolic function of theleft ventricle and of the heart as a whole is performed at thepresent time with high accuracy using echocardiography.
The left ventricle is considered to have normal systolic
function if the ejection fraction is greater than 50% and if its
volume index is below 97 ml / m2 body surface area.
Systolic times are defined as the durations of the various
phases of ventricular systole. They are important markers in
the evaluation of cardiac performance, which can be
determined simply, quickly and noninvasively with the helpof the polyphysiogram. Traditionally, three parameters arerecorded simultaneously: ECG, phonocardiogram andcarotid artery pulse (Figure 1):

Received September 20th 2019. Accepted November 24th 2019. Address for correspondence: Valentin Ordodi, PhD, Politehnica Universityof Timișoara, 2 Victoriei Square, RO-300006, Timișoara, România; phone: +40-256-404219; e-mail: vali.medtm99@gmail.com

4

Fiziologia - Physiology • 2019.29.2(98)Where:- EJ - ejection period (s)- PEJ - pre-ejection period (s)EXPERIMENTAL DEVICE

Fig. 1. The classic polyphysiogram. Systolic times. (According to
Dan Dobreanu UMF Tg Mureș)The experimental device acquires, amplifies, processes
and displays simultaneously the following biosignals
generated during heart activity: cardiac electrical activity(electrocardiogram) by recording with surface electrodes,
using the standard bipolar derivatives of the limbs, thephonocardiogram is recorded in the mitral, erb or aortic areaand photopletismogram generated by the pulse wave,
recorded at the level of a finger by the hand by the techniqueof reflection of the light radiation on the surface of the skin.
The experimental device (Figure 2) contains three mainparts:- The acquisition and amplification module of theelectrical and mechanical signals generated during
the cardiac revolution- The power supply of the amplifier for thephonocardiogram- Analog-numerical conversion module of these signals
as well as the interface with the computer (Arduino
UNO R3 acquisition board)

Usually the following systolic times are determined:a) Electromechanical systole (QZ2). It is measured
from the beginning of the Q wave on theelectrocardiogram and up to the beginning of thesecond noise on the phonocardiogram.
b) The ejection period (EJ) is measured on the
carotid sphygmogram. It is measured
from the base of the anacrotic wave tothe dichroic incision.
c) The pre-ejection period (PEJ) represents
the difference between theelectromechanical systole and theejection period.
If contractile dysfunction of the left ventricle
appears, there is an increase in pre-ejection
duration (PEJ) and a reduction in ejection duration(EJ) with relatively unchanged electromechanicalsystole (QZ2) duration. The Blumberger
Fig. 2.The experimental device - overview (2A), respectively block diagram (2B).
hemodynamic index can be defined as:
𝐸𝐽
𝐵𝑙𝑢𝑚𝑏𝑒𝑟𝑔𝑒𝑟 ℎ𝑒𝑚𝑜𝑑𝑦𝑛𝑎𝑚𝑖𝑐 𝑖𝑛𝑑𝑒𝑥 =𝑃𝐸𝐽
Where:‐ EJ - ejection period (s)‐ PEJ - pre-ejection period (s)This parameter more accurately assesses the systolic
dysfunction of the left ventricle compared to the twoparameters considered separately.
Using systolic times we can calculate the ejection
fraction of the left ventricle (Fej) using the relation:
Fej = ( 1.125 – 1.350 ∙Fiziologia - Physiology • 2019.29.2(98)

𝑃𝐸𝐽
𝐸𝐽) ∙ 100

The ECG module uses an integrated AD8232
instrumentation amplifier produced by Analog Devices. It
is designed for recording a single bipolar ECG derivation,
the configuration used in the experimental device uses the
DII derivation because in most individuals the amplitude of
the waves in this derivation is maximum (the projection of
the cardiac electric vector in the Einthoven triangle). The
ECG module uses an integrated AD8232 instrumentation
amplifier produced by Analog Devices. It is designed forrecording a single bipolar ECG derivation, theconfiguration used in the experimental device uses the D II
derivation because in most individuals the amplitude of the
waves in this derivation is maximum (the projection of the
cardiac electric vector in the Einthoven triangle). The block5

diagram of this circuit is shown in figure 3A.
The acquisition of ECG biopotentials was
performed using suction-type electrodes
attached to the root of the upper limbs (rightand left) and to the root of the lower left limb
in accordance with the standard bipolar
limb derivatives. The conventional colors
for the electrodes were observed. The
connection cable between the electrodes
and the ECG amplifier is shielded toprevent the penetration of electromagnetic
parasites.
The audio frequency amplifier for thephonocardiogram uses a simple transistor
amplifier schematic with three transistors
adapted for the electret microphone. The
device contains a "low down" filter tomitigate parasitic noise from the outsideenvironment. Figure 3B shows the principle
diagram of this amplifier. For theacquisition of cardiac sounds, a common
stethoscope was used, which was adapted
to the electret microphone (Figure 3C). The
Fig. 3. The modules of the experimental device. A – ECG instrumentation amplifierconnection between the microphone andblock diagram, B – phonocardiogram amplifier principle diagram, C – modified
the amplifier was made through a wellstethoscope with electret microphone, D – power supply for phonocardiogramshielded audio cable. Since the amplifier
amplifier principle diagram, E – photopletismograph principle diagram and overview,for phonocardiography requires a supply
F – Arduino UNO R3 data board overview.
voltage of + 9V, it was necessary to include
a booster voltage regulator from + 5V to + 9V. Figure 3D
For all data acquisition we used ”Serial Oscilloscope”
shows the principle diagram of the device.
open source software.
The instrumentation amplifier for recording theelectrocardiogram and the audio frequency amplifier forthe recording of the phonocardiogram are mounted
RESULTS AND DISCUSSION – CASE STUDYshielded in Faraday cages to be protected fromelectromagnetic interference.
A preliminary experiment using the proposed
experimental device was performed on a male subject 44
The photoplethysmograph (Figure 3E) used to detect
years old, without cardiovascular pathology evaluatedthe volume variation synchronous with the cardiac activity
cardiologically. Echocardiography determines the ejectionof a finger from the upper limb was used an optical sensor
fraction = 72%.
based on the principle of light ray reflection on the surface
The signal acquisition was made in clinostatism, in a roomof the tegument. This sensor has included the amplification
witha temperature of 220 C, after a rest of 10 minutes undermodule so that the useful signal is obtained directly at thethe usual conditions of any routine electrocardiographic
output. The sensor was included in the housing of a
examination. For the electrocardiogram the bipolar derivationcommon defective pulseoximetry sensor. The connectionof the DII was chosen, the phonocardiogram was recorded bywith the acquisition board was made by shielded cableplacing the stethoscope in the Erb area, and thewhich also ensures the + 5V supply of the module.
photoplethysmogram was recorded at the level of the left
Acquisition board Arduino UNO R3 (Figure 3F)
hand index.
provides interface with the computer, respectively thePreviously blood pressure was measured by listening
analog-digital conversion of the biosignals from themethod and a standard electrocardiogram was recorded withpatient. It is a flexible structure, programmable in C ++ andelectrocardiograph Innomed HS80G – L.
The recording of the biosignals and the marking of the
upload in Arduino IDE, provided with a USB port thatsystolic times is shown in Figure 4.
allows connection to any computer.

6

Fiziologia - Physiology • 2019.29.2(98)CONCLUSION
The case study shows that the proposed working
hypothesis is correct and can be carried out to carry out
extensive studies on batches of patients that reach thestatistical significance for each type of pathology, so that theexperimental device and the working method can bevalidated.

REFERENCES

Fig. 4. Experimental polyphysiogram. Systolic times.

Since all the parameters that enter into the calculation
equations have the same units of measurement and areused as mathematical (dimensionless) reports we canmeasure directly on the record in mm, these sizes. Thus wewill have:- QZ2 (electromechanical systole) = 25.8 mm- EJ (ejection period) = 20.5 mm
We calculate the PEJ (pre-ejection period) with therelation:
PEJ = QZ2 – EJ = 25,8 mm – 20,5 mm = 5,3 mm
Knowing these data we can calculate the Bumberger
hemodynamic index and ejection fraction (Fej) with theformulas:Blumberger hemodinamic index =Fej = ( 1.125 – 1.350 ∙

𝑷𝑬𝑱
𝑬𝑱

𝑬𝑱
𝑷𝑬𝑱

=

𝟐𝟎,𝟓
𝟓,𝟑

= 3.86) ∙ 100 = (1.125 – 1.350 ∙

𝟓,𝟑
𝟐𝟎.𝟓

) ∙ 100

Fej = 77 %Table I presents the experimental data obtained in thecase study:
Table I. Case Study. Experimental data.
Parameter
Blumberger
hemodinami
c indexEjection
fraction (%)

Echocardiography-Experimnet
al device
3.86

Norma
l value
2.5 - 5

72

77

>50

Fiziologia - Physiology • 2019.29.2(98)

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balneofiziokinetoterapie. Ed. Mirton Timișoara, 2006.
5. Diaconu C. Explorări funcționale în medicina internă. Ed. All,
București, 2016.
6. Ordodi LV, Păunescu V, Mic AA, Ionac M, Săndesc D, Mic FA.
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DISPOZITIV EXPERIMENTAL ELECTROFIZIOLOGICPENTRU EVALUAREA FUNCȚIEI SISTOLICECARDIACE – STUDIU PILOTREZUMATÎn lucrarea de față ne propunem proiectarea și realizarea unui dispozitiv experimental electrofiziologic de tip polifiziograf
capabil să achiziționeze în timp real trei parametrii cardiovasculari: o derivație electrocardiografică (DII), fonocardiogramași fotoplestismograma periferică la nivelul unui deget de la membrul superior. Acești parametri ne permit să măsurăm timpii
sistolici și cu ajutorul unui software adecvat și a unor relații matematice să calculăm indicele hemodinamic Blumberger șifracția de ejecție a ventriculului stâng. Metoda este complet noninvazivă, mai simplu de executat decât polifiziogramaclasică care presupunea înregistrarea sfigmogramei carotidiene și permite aprecierea funcției sistolice a ventriculului stângîn cabinetul medicului de familie sau de medicină generală care nu posedă echipamentul și competențele necesare
efectuării examenului ecocardiografic. Rezultatele preliminare arata o bună corelație între fracția de ejecție masurată
ecocardiografic (72%) și valoarea determinata cu dispozitivul prezentat (77%), fapt care recomanda testarea dispozitivului
pe loturi semnificative de pacienti cu diverse patologii cardiovasculare.
Cuvinte cheie: electrofiziologic, noninvaziv, funcția sistolică cardiacă.

8

Fiziologia - Physiology • 2019.29.2(98)MODERN APPLICATION OF NEXT-GENERATIONSEQUENCING (NGS)LAURA POPA, DANIELA CRISNIC, DACIANA NISTOR, PLESCA DANA,CARMEN TATU, GABRIELA TANASIE, ROXANA ZOGOREAN, OANA GAVRILIUC,
SIMONA ANGHEL, FLORINA BOJIN, VIRGIL PAUNESCU
Clinical Emergency County Hospital “Pius Brinzeu” Timisoara, Centre for Gene and Cellular Therapies in Cancer Treatment - OncoGen
Department of Functional Sciences, “Victor Babes” University of Medicine and Pharmacy Timisoara

ABSTRACTDNA sequencing refers to determine the correct order of nucleotide bases in a DNA macromolecule using sequencing
machines. The first sequencing method based on enzymatic synthesis or Sanger method, opened the way in revolutionizing
the field of genomics and other scientific fields.
Over the past ten years, massively parallel DNA sequencing platforms were released. The appearance on Next Generation
Sequencing has changed the view of the analysis and understanding of living bodies. The progress accelerated biologicaland biomedical research by bringing together the DNA sequencing, epigenetic sequencing, fragment analysis, genotyping
and genomic profiling. Longer read lengths, shorter time to result also a lower overall cost of DNA sequencing, made it
widely accessible and more efficient.
In this review, we present a brief evolution of sequencing methods from the beginning to nowadays and the board range ofapplications for NGS technologies.
Keywords: DNA, sequencing, Sanger method, molecules, nucleotides

INTRODUCTION
Genetic sequencing or DNA sequencing refers to any
method or technology that is used to determine the order ofthe four bases: adenine (A), guanine (G), cytosine (C) andthymine (T) - in a DNA strand. Being able to read the orderof nucleic acid is our opportunity to uncover the hereditaryand biochemical properties of terrestrial life [1].
At the present time there are several sequencing
methods, ranked according to when they were discovered,in classical or first generation methods and second
generation (next generation) methods. The first category isrepresented by the chemical method of Maxam and Gilbert
and the enzymatic method also called Sanger method which
is based on enzymatic synthesis. The next generation ofsequencing, also known as high-throughput sequencing
uses modern technologies, represented by Illumina (Solexa)
sequencing, Roche 454 sequencing and Ion Torrent Proton/ PGM sequencing.
Deoxyribonucleic acid (DNA) was demonstrated as thegenetic material by Oswald Theodore Avery in 1944 [2]. In
1953 James Watson and Francis Crick have published theirlatest discovery: the molecular structure of DNA- the double
helix [1, 3]. Their discovery was based on Rosalind Franklin
and Maurice Wilkins’ X-ray diffraction of DNA. In 1962
Watson, Crick and Wilkins shared the Nobel Prize in
Medicine.
Robert Holley and colleagues were able to produce thevery first whole nucleic acid sequence, that of alanine tRNA
from Saccharomyces cerevisiae in 1965. Robert William
Holley was awarded with the Nobel Prize in 1968 fordescribing the structure of alanine transfer RNA, linking DNA
and protein synthesis [4].
The methods of determining the nucleotide sequence ofDNA fragments were discovered in 1970, independently byWalter Gilbert (the chemical degradation technique) andFrederick Sanger (the enzymatic synthesis technique). BothGilbert and Sanger were awarded with the Nobel Prize for
Chemistry in 1980 [5].
The first whole genome of an organism, the virus
Phange-Phi X174, was sequenced in 1977. In 1988, The
Human Genome Project began, and it was completed in
2003.

Received September 16th 2019. Accepted November 20th 2019. Address for correspondence: Laura Popa, MD, Clinical Emergency County
Hospital “Pius Brînzeu” Timișoara, Centre for Cellular and Gene Therapies in the Treatment of Cancer – OncoGen; Liviu Rebreanu Street No.
156, RO-300723, Timisoara, Romania; phone: +40743129395; e-mail: laura.claudia21@yahoo.com

Fiziologia - Physiology • 2019.29.2(98)9The chemical degradation sequencing techniqueIn the chemical DNA sequencing method end-labelled
DNA is partially cleaved at each of the four nucleotide bases
in four different reactions. The fragments are ordered by size
by gel electrophoresis and the sequence read-off anautoradiograph by noting which base-specific agent cleaved
at each successive nucleotide along the strand [6].
Chemical method uses chemicals to break the DNA
molecules into certain nucleotides. After marking the heads
5` with 32P, the sequenced DNA is distorted (it becomes asingle-wire) and is divided into four samples. Each of thefour samples is treated (with piperidine) to produce rupturesat nucleotides with specific bases that are also chemicallymodified in a certain way. The conditions are so regulated
that the ruptures cannot occur to all nucleotides in such afragment that populations are obtained of different fragment
sizes for each sample, some marked at the end 5`. The
fragments are separated by electrophoresis and are
identified by autoradiography. The autoradiograph is apolyacrylamide gel, where the nucleotides are displayed
from the site of label. This method was used to sequenceoligonucleotides (short nucleotide polymers, usually smaller
than 50 base-pairs in length). Molecules labeled at the 3'
end can be sequenced up to 100-200 bases from the labeledtermination [7].

The Sanger method of sequencing“... [A] knowledge of sequences could contribute much to
our understanding of living matter.”Frederick Sanger

In 1977, Frederick Sanger developed a new techniquefor DNA sequencing based on the chain termination method.
For this method, Sanger was awarded in 1980 with a second
Nobel Prize in Chemistry [9]. Also called “first generation
sequencing”, the technique means to synthesize the DNA
chains on a template strand, but chain growth will stop when
one of four possible dideoxy nucleotides, which lack a 3’hydroxyl group, will became incorporated, thereby
preventing the addition of another nucleotide [10].

Fig.2. The enzymatic synthesis sequencing technique
Legend: In a tube, the DNA fragment to be sequenced is mixed
with a primer, DNA polymerase, DNA nucleotides and the four dyelabeled chain-terminating dideoxy nucleotide. The mixture will beheated, cooled and then heated again, to denaturate the DNA andto help DNA polymerase to synthesize new DNA. At the end thetube will contain different lengths fragments. The ends of thefragments are labeled with dyes. Then the fragments are run
through capillary gel electrophoresis. The detector records thefluorescence intensity and displays the result as a chromatogram.
Adapted from Khan Academy [10].

Fig. 1. Maxam–Gilbert sequencing method
Legend: The DNA fragment, marked at the 5’ end with 32P isbroken into different size nucleotides. The resulted fragments areordered by size in an electrophoresis gel. Sequencing is obtainedby autoradiography. Adapted from Maxam, A. M., & Gilbert, W.
(1977) 74(2), 560–564 [8]10The enzymatic synthesis technique. In a tube we
combine the primer, DNA polymerase, DNA nucleotides(dATP, dTTP, dGTP and dCTP) with the DNA sample which
is about to be sequenced. In the next step, the four dyelabeled, chain terminating dideoxy nucleotides are added.
First, the template DNA needs to be denaturated, whichmeans to separate each strands, so the mixture will beheated. After denaturation, the mixture will be cooled, sothat the primer can bind to the single stranded template.
Once the primer has bound, the temperature is raised
again, so that the DNA polymerase will synthesize new DNA,
starting from the primer. DNA polymerase will continue
Fiziologia - Physiology • 2019.29.2(98)adding nucleotides to the chain until it adds a dideoxy
nucleotide instead of a normal one. At this point, when adideoxy nucleotide is added, no other nucleotides can be
added, so this will be the last nucleotide from the given
strand. This process is repeated in a number of cycles, andso in the end, different lengths fragments will be found in the
tube. The ends of the fragments will be labeled with dyes.
The last step is to transfer the fragments to the capillary
gel electrophoresis, where the short fragments will movequickly through the pores of the gel, while the long ones will
move more slowly.
The detector records the data, which consists in a series ofpeaksin fluorescence intensity, and it is called ‘a chromatogram’.
The DNA sequence can be read from the chromatogram.
Later on the manually method was replaced byautomated sequencing machines, in which the truncatedDNA molecules were labeled with fluorescent tags and thenwere separated by size within thin glass capillaries anddetected by laser excitation.
Sanger sequencing is used for relatively long stretchesof DNA (up to about 900 base pairs). It is usually used tosequence individual pieces of DNA, such as bacterial
plasmids or DNA copied in PCR, becoming a standard
method in clinical genetics [10].
The automated Sanger method had dominated theindustry for almost two decades and led to the only finishedgrade human genome sequence.
Second-generation DNA sequencing
As the time passed by, for sequencing large numbers ofhuman genomes, the Sanger method showed a need oftechnological improvement, despite its limitations [11].
In 2005 and the following years have marked theemergence of a new generation of sequencers, which werecheaper, more efficient and less time consumers. The newgeneration on sequencers can be divided by their working
principle into: microelectrophoretic methods, sequencing by
hybridization, real-time observation of single molecules andcyclic-array sequencing [12].
Within only a few days or hours, NGS technologies cansequence in parallel millions to billions of reads in a single
run and the time required to generate the GigaBase sized
reads. With fast development and wide applications, thenext-generation sequencing is becoming better than the first
generation such as Sanger sequencing [13].
The main characteristics of second generation sequencing
technology are:‐ generation of many millions of short reads in parallel‐ speed up of sequencing the process compared to
the first generation‐ low cost of sequencing‐ sequencing output is directly detected without theneed for electrophoresis [14].
The first commercial next-generation DNA sequencing
systems was launched by Roche’s 454 technology in 2005,
Fiziologia - Physiology • 2019.29.2(98)being able to produce sequences with very high throughput
and at much lower cost than the previous technologies [14].
Today, the dominant second-generation sequencing
platforms are HiSeq from Illumina and SOLiD from Life
Technologies, as reported at AGBT [15].
Third-generation DNA sequencing
The third generations of sequencers is represented by
Pacific Biosciences and Oxford Nanopore platforms. Pacific
Biosciences uses fluorescent labelling (with different colors)
as the previous technologies, and detects the signals in realtime, as they are emitted every time the incorporation of thenucleotides occur. During the sequencing reaction, the DNA
fragment is incorporated by the DNA polymerase withfluorescent labeled nucleotides. When a nucleotide isincorporated, it releases a luminous signal that is recordedby sensors. The detection of the labeled nucleotides is theequivalent of the determination of the DNA sequence [14].
The fundamental technology on which the third
generation of sequencers is based on is SBS(sequencing by synthesis) by degradation, or direct physicalinspection of the DNA molecule. It has a moderate current
raw read accuracy, 1000 bp or longer current read length,
moderate current throughput and a low cost per base. It
takes only few hours from the beginning of sequencing until
the primary result even if the data analysis is very complex
due to the large data volumes [2].
The basic advantages of third- generation sequencing
are: fast turn-around time, it requires minimal amounts ofreagents/sample, no PCR amplification needed, more than
1000bp average read lengths [16].

FUNDAMENTALS OF NGS
Ten years ago next-generation sequencing (NGS)
technologies appeared on the market, and since then,tremendous progress has been made.
All NGS platforms share a common feature, which is
massively parallel sequencing of clonally amplified or single
DNA molecules that are spatially separated in a flow gel [17].
An elementary step in each NGS workflow is a library
construction. An NGS library is a collection of similar size
DNA fragments and known adaptor sequences, added to the
5’ and 3’ ends of the DNA fragments. A library corresponds
to a single sample and multiple libraries, each with theirunique adaptor sequences. They can be sequenced in thesame sequencing run. This technique of preparing thelibrary is used in all types of NGS sequencing and involves
four steps: DNA fragmentation or target selection, ligation of
the adapters, size selection and library quantification and
QC (quality control) [18].
The first step is DNA fragmentation, where the isolated
double-strand DNA is fragmented in smaller pieces by11physical or enzymatic methods. These libraries are also
called “fragment libraries”. If the sequence of a specifictarget is known, PCR amplification is used to produce DNA
amplicons, which are called “amplicon libraries”.
The following step is to connect specific adaptors to the
5’ and 3’ end. These adaptors are between 20 to 40 bp
fragments and they contain known sequences. There are
two different types of adaptor. One adaptor sequence
contains the primer annealing site for the sequencing primer,while the second type of adaptor is used to anchor the DNA
fragment to a surface for sequencing (e.g. beads).
The next step is to select the library fragment sizes that
we need for our sequencing. Generally there two size
selection methods: gel electrophoresis and bead based size
selection. In the gel electrophoresis method the adaptor
library fragments are run in a gel to separate the fragments bysize, and band corresponding the size of interest is collected.
Using the bead based method, magnetic beads are used withbuffer solution to isolate the fragment size of interest.
The last step is library quantification and QC. Accurate
library quantification is important for successful template
preparation. There are few library quantification commonly
used. One of them is Bioanalyzer System; this method ismeasuring both library concentration and fragment size
information. The second method is qPCR, and brings themost accurate library quantification information, as it
measures only amplifiable library fragments but it doesn’t
provide any information about the fragments size.

transplant rejection, to detect pathogens and to determine
cancer treatment.
In microbiology the NGS determines the DNA sequence ofa complete bacterial genome in a single sequence run, andfrom these data, information on resistance and virulence. NGS
sequencing allows whole genome sequencing (WGS), wholetranscriptome shotgun sequencing (WTSS), RNA sequencing(RNA-seq), whole exome sequencing (WES), sequencing oftargeted genes (TS) or candidate genes (CGS), active
methylation and epigenetic markers [5].
Other clinical applications are: outbreak management,
molecular case finding, characterization and surveillance of
pathogens, rapid identification of bacteria, taxonomy,
metagenomics approaches on clinical samples, and thedetermination of the transmission of zoonotic microorganisms from animals to humans [19].
Improvements in technology have dramatically reduced
the cost of DNA sequencing. According to National Human
Genome Research Institute, the two following graphs show
the cost of DNA sequence using Sanger-based chemistries
and capillary-based instruments in 2001 and the cost of
DNA sequence using 'second-generation' platforms from the
beginning of 2008 [20].
In November 2008, the genomic company, Illumina
announced that it can bring the price of genome sequencing
below $100 in the next two years. It is expected that in few
years the genome sequencing will be affordable to themajority of population, which can faster lead to thedevelopment of personalized medicine.
GlobalData analysts are predicting that genomics
companies will become one day as big as the largest
pharmaceutical companies and probably will dominate thepharmaceutical industry.

Fig.4. The evolution of sequencing cost

Legend: Sequencing cost per Mb 2001- 2019. Adapted from National
Human Genome Research Institute [20]Fig.3. NGS library construction

Legend: The DNA fragment is broken into smaller fragments. Specific adaptors
are connected to the 5’ and 3’ end. The library fragments with the adaptors will
be run in a gel electrophoresis to arrange them by size and then run into
Polymerase chain reaction (PCR). Adapted from Kchouk, M., Gibrat , J. F., &Elloumi, M. (2017) [13]In contrary to Sanger sequencing, a NGS Sequencing
can use the same protocol for all pathogens for both
identification and typing applications [19].
There are no doubts that NGS brought a revolutionary
progress to the scientific world, so that today we can use thesequencing methods for prenatal testing, cancer detection,
12

Fig.5. The evolution of sequencing cost.

Legend: Sequencing cost per genome 2001- 2019. Adapted from National
Human Genome Research Institute [20]Fiziologia - Physiology • 2019.29.2(98)At the moment there are many competing sequencing
platforms on the market. According to “Labiotech” online
science magazine: Illumina controls 75% of this market with
its sequencing-by-synthesis (SBS) method. Its closest
competitor is Thermo Fisher, which works on ion
semiconductor sequencing (Ion Torrent), followed by Pacific
Biosciences’ single molecule real-time (SMRT) sequencing.
Together, Thermo Fisher and Pacific Life Sciences control
the remaining 25% of the market.
In April 2018, Genetic Engineering&Biotechnology
News has developed a classification of top 10 sequencing
companies:

PGM and ION S5 SYSTEM

In 2011, Life technologies began commercializing anddistributing the Ion Torrent Personal Genome Machine(PGM). Ion Torrent Personal Genome Machine or PGM is asequencing platform that works on measuring pH rather
than light to detect polymerisation events.
The PGM works on semi-conductor technology andion-sensitive transistors to sequence DNA using only
DNA polymerase and natural nucleotides, combining
semiconductor sequencing technology with natural
biochemistry. Ion Torrent semiconductor sequencing is using
a similar technology to 454 pyrosequencing, but it is based on
detection of the hydrogen ion released during the
10. Oxford Nanopore
5. Qiagensequencing process, instead of using fluorescent labeledTechnologies
nucleotides like other second generation technologies.
9. 10x Genomics
4. Agilent Technologies
The beginning of the sequencing is marked by the library
8. Genewiz
3. BGI Genomics
preparation, which is commonly used for all NGS
7. Pacific Biosciences of
2. Thermo Fisher
sequencers. After the library is ready, it is placed on a chip.
California (PacBio)
Scientific
The machine has a capacity of sequencing one chip per run.
6. Macrogen
1. Illumina
Every chip contains a set of micro wells, and each well has
In the following parts, we will discuss about the mosta bead with few identical fragments.
popular sequencing machines and the ones we work with inEvery time a fragment incorporates a nucleotide in the
our laboratory.
pearl, a hydrogen ion is released which will change the pHof the solution. A sensor attached on the bottom of the micro
Table I. Summary of NGS platforms and characteristics
well detects the change of pH, and converts
it into a voltage signal. This voltage signal is
Platform
Instrument
Reads per run
Avr
Read
Error type
Error
Data
Year
Read
type
rate
generated
proportional to the number of nucleotides
length(%)
per runincorporated.
(Gb)This sequencing technology is able toIllumina
MiniSeq
25M
150
SE,PE
missmatch
1
7.5 (max)
2013
read lengths which are longer and faster(maximum)than other SGS sequencers, which
Illumina
MiSeq
25M
300
SE,PE
missmatch
0.1
15 (max)
2011
represents its main advantage.
(maximum)A major disadvantage of this sequencer
Illumina
NextSeq
400M
150
SE,PE
missmatch1
120 (max)
2014
is the dificulty of interpreting the(maximum)homopolymer sequences, which will cause
Illumina
HiSeq
5B(maximum)
150
SE,PE
missmatch
0.1
1.5
Tb
2012
insertions and deletions (indel) [14].
(max)
The producer platform of PGM, Thermo
Illumina
HiSeq X
6B(maximum)
150
SE,PE
missmatch
0.1
1.8
Tb
2014
(max)
Fisher, provides the following applications ofIon
PGM 314400.000400
SE
indel
1
0.05 to2011
the sequencer: DNA sequencing, epigenetic
Torrent
chip v2
550.000
0.1
sequencing, fragment analysis, genotyping
Ion
PGM 315
2-3 M
200
SE
indel
1
0.5 to 1
2011
and genomic profiling, NGS, RNA
Torrent
chip v2
sequencing [21]. The Ion S5 systems areIon
PGM 315
4-5.5 M
400
SE
indel
1
1.2 to 2
2013
designed to enable a broad range of targeted
Torrent
Chip v2
next-generation
sequencing
(NGS)
Ion
Ion Proton
60-80 M
200
SE
indel
1
10
2012
applications
with
speed
and
scalability.
Torrent
The Ion S5 System, released in
Ion
Ion S5 XL
3-5 M
400
SE
indel
1
1.2 to 2
2015
September, 2015 is using the speed ofTorrent
520
semiconductor sequencing with impressive
Ion
Ion S5 XL
15-20 M
400
SE
indel
1
0.3 to 0.5
2015
Torrent
530
on-board computing power. Easy to use withIon
Ion S5 XL
16-80 M
400
SE
indel
1
NA
2015
cartridge-based reagents, and highTorrent
540
throughput sequencing applications. The Ion
Chef System provides automated template
Legend: Here we present the most popular sequencing platforms and their
preparation and reproducible chip loading forcharacteristics. Adapted from: Kchouk, M., Gibrat , J. F., & Elloumi, M. [13]semiconductor sequencing machines [22].

Fiziologia - Physiology • 2019.29.2(98)13

A clinical study for deafness mutations has concluded
that PGM is accurate for application to clinical diagnosis ofcommon causative mutations and efficiently identified rarecausative mutations and mutation candidates [23].
The main applications for PGM and Ion S5 are: microbial
and metagenomic sequencing, targeted re-sequencing(gene panels) and clinical sequencing.
Table II. The main clinical applications for PGM and Ion S5
sequencing
Cancerresearch

Gene
expression
analysis- genepanels for
SNPs- indels- copynumber- geneexpression- genefusionanalysis- wholetranscriptom
e RNA- Seq- targetedRNAsequencing- small RNA
sequencing

Microbiology/
Infectious
diseaseresearch- microbial
wholegenomes- microbial
typing- metagenomics

Inheriteddiseaseresearch

Reproductive
healthresearch- panelsfortargeted
gene or
whole
exome
analysis- aneuploidy
detection

ILLUMINA
Illumina is currently the leader in the NGS industry andmost library preparation protocols are compatible with theIllumina system [25].
Illumina sequencing technology was based onsequencing by synthesis (SBS) technology, and it was
founded in the Chemistry Department of Cambridge
University in the mid 90’s.
The new approach of sequencing was based on
Cambridge scientists Shankar Balasubramanian, Ph.D. andDavid Klenerman, Ph.D. research. In their research, they
were using fluorescently labeled nucleotides to observe themotion of a polymerase at the single molecule level as it
synthesized DNA immobilized to a surface [24].

Similar to the other methods, the DNA is first broken intofragments and run on a gel tray to separate them by size.
From all the fragments, a 200-300 base pair fragment isselected for further replication through PCR.
An automated cluster generation is used to distribute thefragment library to the surface of a flow cell, amongst theadaptors. A process called bridge amplification occurs,
creating copies of a specific molecule on the surface. As
each new base is added, a camera records the location ofeach cluster by capturing the fluorescent signal. The
sequence is actually the combination of these images. Even
though is seems to be a slow process, each flow cell
analyzes approximately 150 million of these clusters.
Table III. Illumina Benchtop Sequencers
iSeq
100
SystemMiniSeq
SystemMiSeq
Series

Large whole genome
sequencing (human,plant, animal)
Small whole genome
sequencing (microbe,
virus

X

X

X

X

X

X

X

Exome sequencing
Targeted genesequencing (amplicon,
gene panel)

14

X

Whole transcripom
sequencing

X

Gene expression
profiling with mRNAseq

X

Targeted gene
expression profiling

X

X

X

Long-range ampliconsequencing

X

X

X

miRNA and small RNA
analysis

X

X

X

X

X

X

Methilation
sequencing

Legend: The red and green spots are the adaptors. ‘P5’ and ‘P7’ are thesequences used for flow cell attachment and amplification. Adapted from
Li, J., Batcha, A. M. N., Gaining, B., & Mansmann, U. R. (2015) [26]X

X

DNA-protein
interaction analysis

Fig.6. Architecture of a standard Illumina NGS library

NextSeq
Series

16s metagenomic
sequencing

X
X

X

X

Legend: Applications of Illumina Benchtop Sequencers. Adapted from
Illumina website [24]Fiziologia - Physiology • 2019.29.2(98)Table IV. Illumina Large Scale Seqencers
NextSeq
Series

HiSeq
4000
SystemHiSeq
X
SeriesNovaSeq
6000
SystemLarge wholegenomesequencing(human, plant,
animal)

X

X

X

X

Small wholegenomesequencing(virus, microbe)

X

X

X

Exome
sequencing

X

X

X

Targeted genesequencing(amplicon, genepanel)

X

X

X

Whole
transcriptome
sequencing

X

X

X

Gene expression
profiling withmRNA Seq

X

X

X

miRNA and small
RNA analysis

X

X

X

DNA protein
interaction
analysis

X

X

X

Methylation
sequencing

X

X

X

Shotgunmetagenomics

X

X

X

Legend: Applications of Illumina Large Scale Sequencers. Adapted from
Illumina website [24]Illumina also offers the highest throughput of all
platforms and the lowest per-base cost. Read lengths of up
to 300 bp are compatible with almost all types of application.
Unfortunately, the sample loading is technicallychallenging; because of the random scattering of clusters
across the flow cells, the concentration of the library must
be strictly controlled. When it’s about 16S metagenomics,
libraries must be diluted or mixed with a reference PhiX
library to generate diversity [25].

CONCLUSION
The first method of sequencing came about half acentury ago and it marked the beginning of a new era. The
Sanger sequencing method lies at the heart of all otherFiziologia - Physiology • 2019.29.2(98)following methods. The evolution of sequencing has
undeniable helped the scientific life to study biologicalsystems at a higher level. Clinical laboratories have alreadystarted to use NGS as a diagnostic tool, while forensic
research is still at the beginning.
NGS technologies are characterized by an impressive
range of applications and high throughput, which gives us
the opportunity to produce millions of reads in a short periodof time and to use the obtained information in clinical andresearch use. We can conclude that since the first
sequencing machine was released, many improvements
have been made; starting with higher throughput, longer
reads lengths, lower costs and lower error rate.
The technological advances in the field of genomics
over the past quarter-century have led to substantial
reductions in the cost of genome sequencing and it ispredicted that in the following years will drop even more.
In this review, we presented a brief overview of thegenerations of sequencing technologies by beginning withthe first-generation to the third generation. In the following
years, many other sequencing platforms will appear,
analyzing a larger amount of data (Terabyte) and leading us
to a higher technological level, as the field of NGS
development and applications is a fast-moving area of
research
Acknowledgement: This work was supported by the grant“Chimeric Antigen Receptor Targeted Oncoimmunotherapy with
Natural Killer Cells (CAR-NK)”, POC 92/09/09/2016, ID: P_37_786,
MySMIS code: 103662.

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4. https://www.revolvy.com/page/Robert-W.-Holley
5. Mircea Covic. Medical Genetics, Third Edition, DNA
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Technologies: From First to Next Generation. Biology andMedicine, 2017; 9: 03.
14. Munroe DJ, Harris TJR. Third-generation sequencing
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15. Laura Moya Andérico. Ultrasequencing: Methods and Applicationsof the New Generation Sequencing Platforms, 2015.
16. Voelkerding KV, Dames SA, Durtschi JD. Next-Generation
Sequencing: From Basic Research to Diagnostics. Clinical
Chemistry, 2009; 55: 641-658.
17. Parson W, Strobl C, Huber G, Zimmermann B, Gomes SM, Souto
L, Irwin J. Evaluation of next generation mtGenome sequencing
using the Ion Torrent Personal Genome Machine (PGM). Forensic
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Massively Parallel Sequencing of Forensic STRs Using the Ion
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22. Nishio SY, Hayashi Y, Watanabe M, Usami SI. ClinicalApplication of a Custom AmpliSeq Library and Ion Torrent
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Application in Individualized Molecular Oncology. Cancer
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APLICAȚII MODERNE ALE SECVENȚIERIIDE NOUĂ GENERAȚIE (NGS)REZUMAT
Secvențierea ADN se referă la determinarea ordinii corecte a bazelor de nucleotide dintr-o macromoleculă de ADN folosind
tehnologii de secvențiere. Prima metodă de secvențiere bazată pe sinteza enzimatică sau metoda Sanger a deschis calea
revoluției în domeniul genomicii și a altor domenii științifice.
În ultimii zece ani, au fost lansate platforme de secvențiere ale ADNului care pot analiza un volum uriaş de informaţii întrun timp mult mai scurt. Apariția ultimelor generații de secvențe a schimbat viziunea analizei și a înțelegerii corpurilor vii.
Progresul a accelerat cercetarea biologică și biomedicală prin reunirea secvențializării ADN-ului, secvențierii epigenetice,analizei fragmentelor, genotipării și profilării genomice. Capacitatea aparatelor de a citi lungi secvenţe de nucleotide, timpul
mai scurt până la rezultatul analizei și un cost total mai mic al secvențierii ADN-ului, au făcut ca acesta să fie accesibil pescară largă și mult mai eficient.
În aceast review, prezentăm o scurtă evoluție a metodelor de secvențiere de la început până la zilele noastre și gama deaplicații de bază pentru tehnologiile NGS.
Cuvinte cheie: ADN, secvenţiere, metoda Sanger, molecule, nucleotide

16

Fiziologia - Physiology • 2019.29.2(98)MODIFIED LANGENDORFF DEVICEFOR RAT HEART DECELLULARIZATIONDANIEL BONCIOG1, LILIANA MÂȚIU-IOVAN1, GRETA BĂRBULESCU3,
CAIUS BURIAN2, DANIEL GOJE3, PAUL BUICĂ2, VIRGIL PĂUNESCU2,3,
VALENTIN ORDODI1,2
1Politehnica University of Timișoara, 2 Victoriei Square, RO-300006, Timișoara, România
2OncoGen Research Center, Pius Bânzeu Clinical Emergency Hospital, 156 Liviu Rebreanu Bv, RO-300723, Timișoara, România.
3University of Medicine and Pharmacy ”V. Babeș” Timișoara, 2 Eftimie Murgu Square RO-300041, Timișoara, România

ABSTRACTIn this paper we propose the design and implementation of a modified Langendorff experimental device, pressure controlled,
used to decellularize the heart with a sodium dodecyl sulfate (SDS) surfactant solution to obtain cardiac biomatrix. The
experimental device consists of two constructive parts: a hydraulic part that provides through a peristaltic pump and apressure transducer, infusion retrograde through the aorta of the heart under constant pressure regime, as well as anelectronic part that constitutes the regulator of the experimental device. The decellularization solution is recirculated during
the physico-chemical process, so that by serial spectrophotometric determinations of the concentration of deoxyribonucleic
acid (DNA) and proteins in this solution, the kinetics of the decellularization and can be determined, respectively, when it iscompleted.
Keywords: Langendorff, electronic pressure regulator, decellularization, cardiac biomatrix.

INTRODUCTION
In recent years we have witnessed a major developmentof the medical sciences, with a significant impact on theincrease of life expectancy. Thus, modern medicine has tosolve more and more cases with degenerative pathology oftissues and organs which demands finding viable
possibilities for their replacement [1,2,3]. Moderntransplantology involves two major problems: (i) the numberof potential organ and tissue donors is significantly lower
compared to the number of patients in need of suchtreatment, which leads to the formation of long waiting lists
and (ii) the issue of immune mediated rejection involving
treatments aggressive so as not to compromise therespective graft. To these problems are added those of amoral and religious aspects that further limit the possibilityof performing a transplant operation. Due to these aspects,
tissue engineering is looking for viable solutions for
obtaining in vitro functional tissues and organs that can betransplanted. One of the goals of bioengineering is theobtaining of biomaterials that allow the growth anddifferentiation of some cell types, thus being able to fulfill abasic requirement for the realization of a three-dimensional
cellular construct suitable for implantation in a human body[4,5]. The decellularization of an organ as a whole offers thebest three-dimensional biomaterial suitable forrecellularization with the recipient's own stem cells and thus
obtaining a functional and self-organ. In the case of theheart, to obtain a biomaterial with adequate threedimensional structure, several protocols were applied on
both large animals and small animals. Ott applied coronary
anterograde perfusion to the rat heart using threesurfactants for decellularization: sodium dodecyl sulfate(SDS), polyethylene glycol (PEG) and Triton X-100,
respectively enzyme-based methods: trypsin in thepresence of EDTA-Na2 and deoxycholic acid. The authors
observed that protocols that used SDS as a decellularizing
agent are superior to those that used PEG, Triton X-100 or
enzymes [6,7]. Anterograde coronary perfusion with SDS for
12 hours allowed to obtain a fully decellularized good quality
biomaterial. Most experimental devices used to decellularize
the various organs are based on the retrograde perfusion
principle described by Langendorff using the arterial systemof the respective organ. The purpose of this paper consisted

Received September 15th 2019. Accepted November 20th 2019. Address for correspondence: Valentin Ordodi, PhD, Politehnica University ofTimișoara, 2 Victoriei Square, RO-300006, Timișoara, România; phone: +40-256-404219; e-mail: vali.medtm99@gmail.com

Fiziologia - Physiology • 2019.29.2(98)17in the design and implementation of a pressure controlled
Langendorff type device for decellularizing the rat heart[8,9,10].

EXPERIMENTAL DEVICE
The experimental device respects the principle
described by Langendorff and from functional point ofview it is a pressure controlled device. It maintains constantcoronary perfusion pressure by varying the minut-volumerate of decellularization solution that enters in the aorta[11,12,13]. In figure 1.A. we observe the experimental
device as a whole, and in figure 1.B. its block diagram.

aspirated from decellularization chamber by the peristaltic
pump (Fig. 1B.7) and reintroduced into the heart via of thecannula. The manual valve (Fig. 1B.6) with which thecannula is provided, is used for the initial filling of thehydraulic circuit of the experimental device and theelimination of any air bubbles. The perfusion pressure of theheart is the pressure on the discharge branch of theperistaltic pump and is permanently monitored by thepressure resistive transducer (Fig. 1B.P). Additionally, it isread by the researcher on the mechanical manometer (Fig
1B.M). The operation of the peristaltic pump is controlled by
the automation system that brings together the following
modules: pressure amplifier (Fig. 1B.8) that processes thesignal generated by the resistive pressure transducer; thecomparator module (Fig. 1B.9), which receives both theamplified signal from the pressure transducer and areference voltage regulated by the researcher frompotentiometer (Fig. 1B.10). Its scale is directly graded in
mmHg. The output of this module reaches a power amplifier(Fig. 1B.11) and via a solid state relay (Fig. 1B.12) controls
the peristaltic pump function.

EXPERIMENTAL PROTOCOL

Fig. 1. A. Experimental device. B. Block diagram

The heart (Fig. 1B.5) prepared for decellularization isfixed to the tip of a special cannula (AD Instruments) (Fig.
1B.4) and inserted into a decellularization chamber (Fig.
1B.1) made of plastic material with the volume of 100 cubic
centimeters. It contains the decellularization solution: SDS
1% homogenized during the experiments by means of amagnetic stirrer (Fig. 1B.2 and 1B.3). Thus the compositionof the solution is constant at any point of the chamber at theone time, thus allowing the collection of samples forbiochemical determinations. The decellularization solution is
18

Testing and validation of the experimental device was
performed by decellularizing five Sprague Dawley rat rats
weighing between 350 and 400 g. The harvesting of hearts
was done in compliance with international law (The Guide
for the Care and Use of Laboratory Animals published by the
National Institute of Health no.85-23) and therecommendations of the Ethics Commission of UMF „VBabeș” Timișoara. In all cases, VIMA general anesthesia
with sevoflurane was used. induction was performed with
sevoflurane 8% in oxygen in a special chamber, andmaintenance was performed with sevoflurane 3.5% througha facial mask for rats until the heart was excised. In the firststep, the abdominal cavity is opened and the heparin
sodium is injected into the inferior vena cava 100 IU / Kg.
After 4-5 minutes, the thoracic cavity is opened by cutting
the ribs and the heart is rapidly excised with a fragment aslong as the aorta. It is inserted into a Petri dish with a cold
solution of heparinized physiological sodium chloride andthe dissection is continued until the cord and a fragment ofaorta about 1 cm long are prefectly isolated [14,15]. The
heart thus processed is fixed with a silk surgical thread on
the cannula of the Langendorff type device and infused for
600 minutes with a 1.5% SDS solution [16]. The solution
volume in the device was 120 cm3. At 30 min intervals, 30
uL samples were taken to determine the concentration of
nucleic acids and proteins in the decellularization solution.
These determinations were performed using the ultraviolet
spectrophotometric method. The proteins have a maximum
absorption at 280 nm at neutral pH. Nucleic acids under thesame conditions have a maximum absorption at 260 nm, sothat the two analytes can be determined simultaneously
Fiziologia - Physiology • 2019.29.2(98)without their separation [17,18,19]. A NanoDrop ND-1000
computerized microspectrophotometer was used. The
device performs the measurements directly, without theneed for other reagents, and the results are displayed in
ng/µL for nucleic acids and in mg/mL for proteins.

RESULTS AND DISCUSSIONS
Following the processing of the experimental data, thefinal moment of decellularization could be established,considered as the time when the concentration of the twodetermined analytes became constant. Figure 2 showsgraphically the average values of deoxyribonucleic acid andprotein concentration respectively for the five experiments
performed.

considered completed because the concentration of bothanalytes reaches a stable maximum.

CONCLUSIONSThe proposed experimental device and the method
presented are well suited for the decellularization of the rat
heart in order to obtain biomaterials that can then be
repopulated with autologous cardiac muscle cells obtainedby in vitro differentiation of mesenchymal stem cells.

REFERENCES
1. Peter MC, Thomas WG, Stephen FB. An overview of tissue
and whole organ decellularization processes. Biomaterials,
2011; 32: 3233-3243.
2. Hawkins JA, Hillman ND, Lambert LM, et al. Immunogenicity
of decellularized cryopreserved allografts in pediatric cardiac
surgery: comparison with standard cryopreserved allografts. J
Thorac Cardiovasc Surg, 2003; 126: 247-52.

Fig. 2. Evolution of DNA and protein concentration during theheart decellularization (median values).

The increase of the concentration of the two analytes is
described very well by the following polynomial equations oforder 3 (Correlation coefficient, R2 > 0.95 in both cases). We
can say that these equations apply to any experiment ofdecellularization of the rat heart under the conditions
presented.
C DNA [ng/µL] = - 4 ·10 -0,7 · t3 + - 0,000·t2 + 0,439·t + 3,007
CProtein [mg/mL] = - 2·10 -0,8 · t3 + 10-0,5·t2 0,003·t + 0,024
From the analysis of the experimental data it is observedthat at the minute 400 the decellularization can be

Fiziologia - Physiology • 2019.29.2(98)3. http://www.crestinortodox.ro/sanatate-si-stiinta/72679moartea-cerebrala.
4. Murray JE. Organ transplantation: the practical possibilities.
Boston ed., 1966; 54-67.
5. Gilbert TW, Sellaro TL, Badylak SF. Decellularization oftissues and organs. Biomaterials, 2006; 27: 3675-83.
6. Ott HC, Matthiesen TS, Goh SK, Black LD, Kren SM, Netoff
TI, Taylor DA. Perfusion decellularized matrix: using nature’s
platform to engineer a bioartificial heart. Nat Med, 2008; 14(2):213-21.
7. Nakayama KH, Batchelder CA, Lee CI, Tarantal AF.
Decellularized rhesus monkey kidney as a three-dimensional
scaffold for renal tissue engineering. Tissue Eng Part A
2010;16(7): 2207-16.
8. Weymann A, Loganathan S, Takahashi H, Schies C, Claus
B, Hirschberg K, et al. Development and evaluation of aperfusion decellularization porcine heart model-generation of
3-dimensional myocardial neoscaffolds. Circulation journal:
official journal of the Japanese Circulation Society 2011; 75(4):852-860.
9. Weymann A, Radovits T, Schmack B, Li S, Korkmaz S, Soós
P, et al. In vitro generation of atrioventricular heart valve
neoscaffolds. Artificial organs 2014; 38(7): E118-E128.
10. Badylak SF, Weiss DJ, Caplan A, Macchiarini P. Engineered
whole organs and complex tissues. Lancet, 2012; 379: 943.
11. Perju D, Suta M, Todincă T, Rusnac C. Echipamente deautomatizare pneumatice de joasa presiune. Aplicaţii.
Pneumatica Collection, Politehnica Timisoara Ed., 2001.
12. Perju D, Suta M, Rusnac C, Brusturean GA. Automatizarea
proceselor chimice. Aplicaţii. Pneumatica Collection,
Politehnica Timisoara Ed., 2005
19

13. Ionescu G et al. Traductoare pentru automatizări industriale.
Vol I. Ciclul manualului inginerului automatist. Tehnica
Bucharest Ed., 1985.
14. Blasig IE, Ebert B, Hennig C, Pali T, Tosaki A. Inverse
relationship between ESR spin-trapping of oxy-radicals anddegree of functional recovery during myocardial reperfusion in
isolated working rat heart. Cardiovasc Res 1990; 24: 263-270.
15. Chen Z, Li T, Zhang B. Morphine postconditioning protects
against reperfusion injury in the isolated rat hearts. J Surg Res
2008; 145: 287-294.

16. Mirica N, Luculescu M, Răducan A, Ordodi V, Duicu O, Borya
C, Fira–Mlădinescu O, Muntean D. Dichotomic effects of
Diayoxide and Cyclosporine A on contractile function andinfarct size in Langendorff perfused rat hearts. Proceedings of
8th International Congress on Coronary Artery Disease, Oct11-14 , 2009, Prague Czech Republic, Ed. Medimondinternational Proceedings, 21-26.
17. Manta I, Cucuianu M, Benga G, Hodârnău A. Metodebiochimice în laboratorul clinic. Ed. Dacia, Cluj-Napoca, 1976.
18. www.promega.ro/resources
19. www.nanodrop.com.

DISPOZITIV LANGENDORFF MODIFICAT PENTRU
DECELULARIZAREA INIMII DE ȘOBOLAN
REZUMATÎn lucrarea de față ne propunem proiectarea și realizarea unui dispozitiv experimental de tip Langendorff, controlat inpresiune, folosit pentru decelularizarea cordului cu o soluție tensioactivă de sodiu dodecil sulfat (SDS) în vederea obținerii
biomatricilor cardiace. Dispozitivul experimental este format din două părți constructive: o parte hidraulică care asigură prinintermediul unei pompe peristaltice și a unui traductor de presiune, perfuzia retrogradă prin aorta a cordului în regim
presional constant, precum și o parte electronică care constituie regulatorul dispozitivului experimental. Soluția dedecelularizare se recirculă pe parcursul procesului fizico-chimic, astfel încât prin determinări spectrofotometrice seriate aconcentrației de acid dezoxiribonucleic (ADN) și proteine din această soluție se poate determina cinetica decelularizării
respectiv momentul în care acesta este finalizată.
Cuvinte cheie: Langendorff, reglator electronic de presiune, decelularizare, biomatrice cardiacă

20

Fiziologia - Physiology • 2019.29.2(98)B*08:01 HLA CLASS I AND CLASS II ALLELES
AND HAPLOTYPES FREQUENCIES PATIENTS WITHHEMATOLOGICAL DISEASES IN THE WESTERNPART OF ROMANIAELENA GAI1, DIANA LUNGEANU2, SMARANDA ARGHIRESCU3,CRENGUTA LIVIA CALMA1,4, VIRGIL PAUNESCU1,4
1OncoGen - Centre for Gene and Cellular Therapies in Cancer, Emergency Clinical County Hospital "Pius Brînzeu" Timișoara
2Centre for Modelling Biological Systems and Data Analysis, Department of Functional Sciences, "Victor Babeș" University of Medicine andPharmacy, Timișoara, Romania
3Departement of Transplant, Emergency Clinical Hospital "Louis Ţurcanu",
4Department of Functional Sciences, "Victor Babeș" University of Medicine and Pharmacy, Timișoara, Romania

ABSTRACTThe present study was conducted between 2015 and 2018 and it aimed to investigate the haplotypes incidence in acutelymphoblastic leukemia (ALL), acute myeloid leukemia (AML) and aplastic anemia (AA) in Western Part of Romania.
Sequencing-based typing (SBT) technique using SeCore ONE LAMBDA kits was used to type HLA genes class I and II.
The frequencies of the alleles for the hematologic disease were calculated and compared.
Keywords: HLA genes class I and II, haplotypes, acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML),
aplastic anemia (AA), sequencing-based typing (SBT) technique

INTRODUCTION
The major histocompatibility complex (MHC) plays afundamental role in immune response [1][2] and it’s firstmentioned involvement in human affections was highlighted
in leukemia [3].
In humans, the major histocompatibility complex islocalized on chromosome 6 being expanded on about 4
centiMorgan (cM) of DNA (4 × 106 pairs of bases) andcomprising approximately 200 genes [4].
HLA (Human leukocyte antigen) represents the humanversion of MHC and encodes proteins on the surface ofantigen-presenting cells (APC) [5]. The HLA A, B, and C
genes correspond to the class I MHC exhibit intracellularpeptides, HLA DP, DM, DQA, DQB, and DR genes
correspond to the class II MHC exhibit extracellularpeptides while the HLA genes corresponding to MHC class
III coding part of the complement components system. Of
these, there are three genes containing α chains and arecalled class I (HLA-A, -B, and-C) and three pairs of genes
containing α and β chains and are called class II (HLADR,-DP, and-DQ) [6] [7].
Acuteleukemia
comprises
a
group
of
oncohaematological diseases with multifactorial origins. The
results of an epidemiological [8] study show that acutelymphoblastic leukemia (ALL) occurs mainly in children,
while acute myeloblastic leukemia (AML) is observed inyoung people, and its incidence increases with age [9].
Aplastic anemia (AA) is a rare condition that threatening
the existence of hematopoietic stem cells, anemia
characterized by peripheral blood cytopenia and hypoplasiaof the bone marrow. This occurs by destroying
hematopoiesis by cytotoxic T cells. Certain human leukocyte
antigen (HLA) alleles play a role in activating clones withautoreactive T lymphocytes in patients with AA [10].
The purpose of this study is to investigate the incidenceof haplotypes in patients with ALL, AML and AA.

Received July 10th 2019. Accepted October 12th 2019. Address for correspondence: Elena Gai, Biol. PhD, OncoGen - Centre for Gene andCellular Therapies in Cancer, Emergency Clinical County Hospital "Pius Brînzeu" Timișoara, Liviu Rebreanu Bvd. 156, RO-300723, Timisoara,
Romania; phone: +40356433282, +40374161282; e-mail: elagai@yahoo.com

Fiziologia - Physiology • 2019.29.2(98)21

MATERIALS AND METHODSPatients
HLA typing has been performed in the HLA departmentof OncoGen - Centre for Gene and Cellular Therapies inCancer, Emergency Clinical County Hospital "Pius Brînzeu"Timișoara, who has accreditation from the National
Transplant Agency to perform HLA-print.
In the current study, we included 554 records from which
264 were receptors. We identified 194 patients with one of
the three disorders analyzed (ALL, AML, and AA) who
underwent bone marrow transplantation. Of the 194 cases,
82 were diagnosed with acute lymphoid leukemia, 67 withacute myelogenous leukemia and 45 with aplastic anemia.
MethodThe studied samples were collected from 554 children
patient’s of Emergency Clinical Hospital "Louis Ţurcanu",
Departement of Transplant, between 2015 and 2018.
According to the norms of international and national ethics,
informed consent has been obtained from all the subjects
or their legal guardians regarding the use of data in thisstudy [11].
Collection, transport, and storage of specimens werecarried out in accordance with applicable regulatory
requirements. The whole blood samples were collected invacutainer tubes with 2 mL (3.6 mg) K3-EDTA
ethylendiaminotertraacetic from patients diagnosed with
LAL, LAM, and AA.
Extraction
The MagNA Pure LC automatic extraction was
performed using 2 mL of whole blood samples and the
MagnaPure LC Automatic DNA Extraction kit containing thewash buffer I, wash buffer II, lysis buffer, proteinase K andmagnetic glass particles suspension (MGPs). The extraction
kit and the instrument use magnetic ball technology to purify
genomic DNA from the bloodstream. Magnetic particles areused to capture DNA in the solution. The DNA on themagnetic particles is washed and then it is eluted from themagnetic particles in the solution for use.
The MagnaPure system required a 120-minute time forthe 100 μl protocol to complete the DNA isolation from 32
samples.
The verification of the DNA concentration extracted fromeach sample was carried out with the Qubit 3.0 Fluorometer.
HLA genotyping
HLA Genotyping was carried out using the sequencingbased typing (SBT) method, using SeCore ONE LAMBDA
kits to determine the class I and class II HLA allele.
Pre-amplification for class I was performed with a
specific Amplification Mix class I (A, B, C) and FastStart Taq
22using for each sample 20 mL mixture and 5 mL DNA. Preamplification for class II was performed with a special class
II Amplification Mix (DQB1 and DRB1) and FastStart Taq
using each case of 23 mL mixture and 2 mL DNA.
The samples thus prepared were introduced in
ThermoCycler GeneAmp Applied Biosystems 9700 program
SECORE PRE where the amplification was carried out
comprising several stages and cycles during the duration of
60 minutes. The amplification product has been checked byan agarose gel migration 2%. It then followed the purification
phase with EXO-SAP for the elimination of unincorporated
dNTP stage that was performed using ThermoCycler
GeneAmp Applied Biosystems 9700 program SECOREEXOSAP consisting of a cycle of 20 minutes at 37 °C and a
20-minute cycle at 80°C.
Post-amplification was performed using the specific kitsof each class I and class II and the corresponding
amplicons. The samples thus prepared were introduced in
the GeneAmp thermocycler Applied Biosystems 9700
program SECORE POST for the actual amplification.
The sequencing fragments were then purified by
precipitation with ethanol and skated using Hi-Di formamide
and PPT buffer. The denatured product has been detected by
the electrophoresis on 16 capers using the genetic Analyzer
of automatic sequencing genetically analyzer ABI 3130xL.
The obtained electropherograms were interpreted with
the HLA SBT uTYPE 7.0 program to process the data filesof DNA samples. Data files are generated from the samples
processed with SeCore sequencing kits and the Aplied
Genosystem Genetic Analyzer. Analysis and identificationof HLA genes was done by comparison with the IPD(Immuno Polymorphism Database) database-IMGT(International ImMunoGeneTics)/HLA [12] [13].
Data analysis
Univariate descriptive statistics included the observed
frequency counts (percentage). To investigate the statisticalsignificance of observed differences in allele frequences
within the analyzed groups, a Chi-square test [14] [15] or the
Fisher-exact test [16] were applied.
Furthermore, inter-haplotype correlation and exploratory
principal component analysis (PCA) was conducted toinvestigate the underlying associations of haplotypes in thethree blood disorders. Kaiser-Meyer-Olkin (KMO) test of
sampling adequacy and Bartlett's test of sphericity wereapplied to verify the data suitability for factor analysis. The
scree plots and the eigenvalues over 1 were considered as
criteria for deciding the appropriate number of factors to be
extracted. The resulting factors were used to explore thepossible underlying haplotype structure in the bloodconditions within the analyzed database.
The descriptive statistics (i.e. the frequency tables ofobserved alleles) include both four-digit HLA-typing (i.e.
high-resolution profiles with first two nomenclature fields)
and two-digit HLA-typing. The decision to neither drop the
Fiziologia - Physiology • 2019.29.2(98)two-digit records nor reduce all the records to two-digit
resolution was based on the consideration of the informative
character of these valuable data existing in this historical
database.
All reported probability values were two-tailed and a
0.05 level of significance was considered, while marking thehighly significant values, as well. Data analysis was
conducted with the statistical software IBM SPSS v.20 and
the R v.3.4.1 software packages.

RESULTS AND DISCUSSION
We identified 194 patients with one of the threedisorders analyzed (ALL, AML, or AA) who underwent bonemarrow transplantation. Of the 194 cases, 82 (31.1%) was
diagnosed with acute lymphoid leukemia, 67 (25.4%).with
acute myelogenous leukemia and 45 (17.0%) with aplastic
anemia. Table I shows the observed blood disorders in the
study population, with their respective frequencies andnumber of homozygous cases.

Table I. The observed types of blood disorder in the study population

Blood disorder

Observed
HLA-A
count
homozygotes
frequency (%)

HLA-Bhomozygotes

HLA-C
homozygotes

HLA-DRB1
homozygotes

HLA-DQB1
homozygotes

14

6

6

6

12

Acute lymphoblastic leukemia(ALL)

82 (31.1%)

Acute myeloid leukemia (AML)

67 (25.4%)

7

8

8

10

16

Aplastic anemia (AA)45 (17.0%)

5

2

2

7

8

Immunodeficiency

8 (3.0%)

‒

‒

‒

‒

Myelodysplastic syndrome

8 (3.0%)

‒

‒

‒

1

1

Wiskott–Aldrich syndrome

6 (2.3%)

‒

‒

1

‒

‒

Hodgkin's lymphoma

5 (1.9%)

3

‒

1

‒

1

Chronic granulomatous disease

4 (1.5%)

1

1

1

‒

‒

Neutropenia

4 (1.5%)

‒

‒

‒

‒

‒

Lymphoblastic lymphoma

3 (1.1%)

1

‒

‒

‒

1

Non-Hodgkin lymphoma

3 (1.1%)

‒

‒

‒

‒

‒

Medullary aplasia

2 (0.8%)

1

‒

‒

‒

‒

Paroxysmal nocturnal
hemoglobinuria

2 (0.8%)

‒

‒

‒

1

1

Lymphoma

2 (0.8%)

1

‒

‒

‒

‒

Myelofibrosis with myeloid
metaplasia (MMM)

2 (0.8%)

‒

‒

‒

‒

‒

Severe combined
immunodeficiency (SCID)

2 (0.8%)

1

‒

1

‒

‒

Purine nucleosidephosphorylase deficiency

1 (0.4%)

‒

‒

‒

‒

‒

Langerhans cell histiocytosis

1 (0.4%)

‒

‒

‒

‒

‒

Juvenile myelomonocytic
leukemia (JMML)

1 (0.4%)

‒

‒

‒

‒

‒

Myelomonocytic leukaemia

1 (0.4%)

‒

‒

‒

‒

‒

Multiple myeloma

1 (0.4%)

‒

‒

‒

‒

1

Lymphohistiocytosis

1 (0.4%)

1

‒

1

‒

‒

Anaplastic large cell lymphoma

1 (0.4%)

1

‒

‒

‒

‒

Fiziologia - Physiology • 2019.29.2(98)23Chronic lymphocytic leukemia

1 (0.4%)

‒

‒

‒

‒

‒

Chronic myelogenous leukemia(CML)

1 (0.4%)

‒

‒

‒

‒

‒

Chronic myelogenous leukemia
in the lymphoid blastic phase

1 (0.4%)

‒

‒

‒

‒

‒

Pancytopenia

1 (0.4%)

1

‒

‒

‒

‒

Idiopathic thrombocytopenic
purpura1 (0.4%)

‒

‒

‒

‒

‒

Refractory thrombotic
thrombocytopenic purpura

1 (0.4%)

‒

‒

1

‒

‒

Myeloid sarcoma

1 (0.4%)

‒

‒

‒

‒

‒

Shwachman-Diamondsyndrome

1 (0.4%)

‒

‒

‒

‒

‒

Griscelli syndrome

1 (0.4%)

‒

‒

‒

‒

‒

Nijmegen breakage syndrome

1 (0.4%)

‒

‒

‒

‒

‒

Thalassemia

1 (0.4%)

‒

‒

‒

‒

‒

Thrombocytopenia

1 (0.4%)

‒

‒

‒

‒

1

Total

264 (100%)

Tables II (a, b, c, d, e) present the synthesis with theallele groups identified within the three groups of disorders
analyzed ALL, AML, and AA. Each HLA type was counted
once for a case (i.e. the allele was counted once for thehomozygous cases).
One limitation of the present study is the resolution
discrepancy for the HLA-typing in the database, though wechose to keep the two-digit resolution data for theirinformative value in future studies. Another caveat is
generated by the limited number of cases in the databaseand subsequent relatively low frequency of observed alleles
and haplotypes, nevertheless bringing valuable information
for future studies on HLA patterns in blood conditions.
The frequency of the human leucocyte antigen (HLA)A*24:02 allele (22.0%), HLA-A*03:01 (20.7%) and HLAA*32:01 (18.3%) were significantly higher in patients with
ALL compared with AML and AA. Among patients with AML,
the frequency of the HLA-A11:01 allele (11.9%) was
significantly higher, whereas the frequency of the HLAA*02:01 allele (46.7%) was also significantly higher inpatients with AA and ALL- HLA-A*02:01 allele (42.7%).
This study indicated that the frequency of the HLA-B*08:01
allele (15.6%) and the HLA-B*14:02 (13.3%) allele may play24

a predisposing role in patients with AA. The frequency of the
HLA-B*18:01 (13.3% and HLA-B* 35:01 (13.4%) alleles may
be associated with high risk of AML vs. HLA-B* 44:02(12.2%) and HLA-B* 51:01 (15.9%) with high risk of ALL,
respectively.
Significant positive association with the AA disease wasfound for HLA-C* 07:01 (37.8%) and HLA-C* 06:02 (17.8%)
vs. HLA-C* 12:03 (20.9%). and HLA-C* 08:02 (11.9%)
association with AML and HLA-C* 04:01 (24.4%) and HLAB* 15:02 (9.8%)association with ALL.
HLA-DRB1* 01:01, HLA-DRB1* 03:01 and HLADRB1* 13:01 were the most frequent alleles in thepatients with AA (17,8%). HLA-DRB1* 07:01 (20.9%) andHLA-DRB1 *11:01 (14.9%) alleles were detected in AML
patients. HLA-DRB1* 11:04 (25.6%) and HLA-DRB1 16:01(17.1%) were the most frequent alleles in the ALL patients.
Three alleles including HLA-DQB1 03:01 (45.1%), HLADQB1 05:02 (23.2%) and HLA-DQB1 05:01 (19.5%) weresignificantly frequent in ALL patients. HLA-DQB1 02:01(22.2%), HLA-DQB1 03:02 (20.0%) and HLA-DQB1 06:03(20%) alleles were observed in AA and HLA-DQB1 02:02,
significantly less frequent, was present in patients with AML(17.9%).

Fiziologia - Physiology • 2019.29.2(98)Table II a. The frequencies of HLA-A* allele identified within ALL, AML, and AA.
HLA-A* allele
‒
01:XX
01:01
02:XX
02:01
02:05
02:07
02:11
02:17
03:XX
03:01
03:02
11:XX
11:01
23:XX
23:01
24:XX
24:02
24:03
24:07
25:XX
25:01
26:XX
26:01
29:01
29:02
30:XX
30:01
30:02
31:01
32:XX
32:01
33:XX
33:01
33:03
66:01
68:XX
68:01
68:02
74:01

Total(a)(b)(n=194)2 (1.0%)7 (3.6%)43 (22.2%)
10 (5.2%)
82 (42.3%)
2 (1.0%)2 (1.0%)4 (2.0%)2(1.0%)
4 (2.0%)28 (14.4%)
3 (1.5%)1 (0.5)28 (14.4%)
1 (0.5)7 (3.5%)8 (4.1%)32 (16.5%)
4 (2.0%)1 (0.5%)1 (0.5%)
13 (6.7%)
1 (0.5%)
11 (5.7%)
3 (1.5%)5 (2.5%)1 (0.5%)4 (2.0%)1 (0.5%)2 (1.0%)1 (0.5%)28 (14.4%)
1 (0.5%)5 (2.5%)2(1.0%)
1 (0.5%)1 (0.5%)6 (3.0%)3 (1.5%)1 (0.5%)ALL (a)(c)(n=82)
1 (1.2%)3 (3.7%)17 (20.7%)
3 (3.7%)35 (42.7%)
1 (1.2%)2 (2.4%)
1 (1.2%)
1 (1.2%)17 (20.7%)
1 (1.2%)9 (11.0%)
2 (2.4%)3 (3.7%)18 (22.0%)

1 (1.2%)
1 (1.2%)5 (6.1%)2 (2.4%)
1 (1.2%)

AML (a)(d) (n=67)

AA(a)(e) (n=45)

p-value (f)‒3 (4.5%)14 20.9%)5 (7.5%)26 (38.8%)
1 (1.5%)

1 (2.2%)1 (2.2%)12 (26.7%)
2 (4.4%)21 (46.7%)
1 (2.2%)1 (2.2%)

‒
0.89
0.71
0.60
0.71
‒
‒
‒
‒
0.45
0.075
‒
‒
0.47
‒
0.49
‒
0.21
‒
‒
‒
0.002**
‒
0.71
‒
0.45
‒
‒
‒
‒
‒
0.42
‒
0.77
‒
‒
‒
0.77
‒
‒

1 (1.5%)8 (11.9%)2 (3.0%)1 (1.5%)12 (17.9%)
1 (1.5%)2 (3.0%)5 (7.5%)8 (11.9%)

10 (14.9)
1 (1.5%)6 (9.0%)3 (4.5%)2 (2.4%)
1 (1.2%)2 (2.4%)2 (3.0%)15 (18.3%)

8 (11.9%)
1 (1.5%)
1 (1.5%)
1 (1.5%)2 (2.4%)
1 (1.2%)
1 (1.2%)
1 (1.2%)2 (2.4%)3 (4.5%)
1 (1.5%)
1 (1.5%)

1 (2.2%)2 (4.4%)3 (6.7%)7 (15.6%)
3 (6.7%)6 (13.3%)
4 (8.9%)1 (2.2%)2 (4.4%)2 (4.4%)1 (2.2%)1 (2.2%)1 (2.2%)1 (2.2%)5 (11.1%)
2(4.4%)

1 (2.2%)2 (4.4%)(a) observed frequency counts (%); (b) percentage out of 194 total; (c) percentage out of 82 total; (d)percentage out of 67 total; (e) percentage out of 45 total.
for each allele observed in all the three groups, either asymptotic Chi-square test or Fisher-exact test
was applied to investigate the statistical significance of observed differences in proportions, as
appropriate.
** statistically highly significant differences (p < 0.01)(f)

Fiziologia - Physiology • 2019.29.2(98)25

Table II b. The frequencies of HLA-B* allele identified within ALL, AML, and AA.
HLA-B* allele
‒
07:XX
07:02
07:05
08:XX
08:01
08:32
13:XX
13:02
14:01
14:02
15:XX
15:01
15:02
15:18
18:XX
18:01
18:03
18:05
27:XX
27:02
27:05
35:XX
35:01
35:02
35:03
35:08
37:XX
37:01
38:01
39:XX
39:01
39:10
40:XX
40:01
40:02
40:06
41:XX
41:01
41:02
44:XX
44:02
44:03
44:05
44:27
45:01
45:04
47:01
49:01
50:01
26

Total(a)(b)(n=194)4 (2.0%)5 (2.6%)13 (6.7%)
1 (05%)
2 (1.0%)24 (12.4%)
1 (05%)
1 (05%)
10 (5.2%)
2 (1.0%)17 (8.8%)
1 (05%)
5 (2.6%)
1 (05%)
3 (1.5%)5 (2.6%)33 (17.0%)
1 (05%)
1 (05%)
1 (05%)
5 (2.6%)9 (4.6%)2 (1.0%)22 (11.3%)
8 (4.1%)16 (8.2%)
3 (1.5%)
1 (05%)
3 (1.5%)
14 (7.2%)
2 (1.0%)3 (1.5%)
1 (05%)
4 (2.1%)6 (3.1%)10 (5.2%)5 (2.6%)
1 (05%)
4 (2.1%)
1 (05%)
4 (2.1%)18 (9.3%)
6 (3.1%)6 (3.1%)
1 (05%)
1 (05%)
1 (05%)
3 (1.5%)9 (4.6%)4 (2.1%)ALL (a)(c)(n=82)
2 (2.4%)2 (2.4%)4 (4.9%)1 (1.2%)8 (9.8%)1 (1.2%)3 (3.7%)5 (6.1%)1 (1.2%)4 (4.9%)1 (1.2%)3 (3.7%)14 (17.1%)
1 (1.2%)3 (3.7%)6 (7.3%)
1 (1.2%)
11 (13.4%)
5 (6.1%)5 (6.1%)2 (2.4%)4 (4.9%)1 (1.2%)2 (2.4%)2 (2.4%)4 (4.9%)3 (3.7%)
1 (1.2%)
1 (1.2%)3 (3.7%)10 (12.2%)
3 (3.7%)2 (2.4%)
1 (1.2%)

AML (a)(d) (n=67)

AA(a)(e) (n=45)

p-value (f)1 (1.5%)
1 (1.5%)5 (7.5%)
1 (1.5%)
1 (1.5%)9 (13.4%)

1 (2.2%)2 (4.4%)4 (8.9%)

‒
1
0.62
‒
‒
0.60
‒
‒
0.31
‒
0.39
‒
‒
‒
‒
‒
0.70
‒
‒
‒
0.85
0.25
‒
0.25
0.59
0.006**
‒
‒
‒
0.56
‒
‒
‒
‒
0.87
0.37
0.85
‒
0.83
‒
‒
0.57
0.66
0.87
‒
‒
‒
‒
0.56
1

6 (9.0%)2 (3.0%)6 (9.0%)7 (15.6%)1(2.2%)
1(2.2%)
6 (13.3%)

1 (1.5%)
1 (2.2%)2 (4.4%)2 (3.0%)13 (19.4%)
1 (1.5%)
1 (1.5%)
1 (1.5%)
1 (1.5%)
1 (1.5%)9 (13.4%)
2 (3.0%)2 (3.0%)1 (1.5%)
1 (1.5%)
1 (1.5%)6 (9.0%)1 (1.5%)
1 (1.5%)
1 (1.5%)3 (4.5%)2 (3.0%)2 (3.0%)1 (1.5%)
1 (1.5%)2 (3.0%)1 (1.5%)5 (7.5%)
1 (1.5%)2 (3.0%)6 (13.3%)

1 (2.2%)2 (4.4%)2 (4.4%)1 (2.2%)9 (20.0%)

2 (4.4%)4 (8.9%)1 (2.2%)2 (4.4%)4 (8.9%)1 (2.2%)1 (2.2%)3 (6.7%)2 (4.4%)2 (4.4%)1 (2.2%)4 (4.9%)2 (2.4%)

1 (1.5%)
1 (1.5%)2 (3.0%)1 (1.5%)2 (4.4%)3 (6.7%)
1 (2.2%)Fiziologia - Physiology • 2019.29.2(98)51:XX
51:01
51:09
52:XX
52:01
52:05
53:XX
53:05
55:01
56:01
57:XX
57:01
58:XX
58:01
78:XX

2 (1.0%)32 (16.5%)
1 (05%)
1 (05%)
9 (4.6%)
1 (05%)
1 (05%)
1 (05%)
4 (2.1%)
1 (05%)
2 (1.0%)5 (2.6%)
1 (05%)
2 (1.0%)1 (05%)

13 (15.9%)
1 (1.2%)2 (4.4%)5 (11.1%)

14 (20.9%)

‒
0.38
‒
‒
‒
‒
‒
‒
1
‒
‒
1
‒
‒
‒

1 (1.5%)7 (8.5%)
1 (1.2%)2 (4.4%)
1 (1.5%)2 (2.4%)2 (2.4%)2 (2.4%)
1 (1.2%)
1 (1.2%)1 (2.2%)1 (2.2%)

1 (1.5%)
1 (1.5%)2 (3.0%)1 (2.2%)

1 (1.5%)
1 (1.5%)(a) observed frequency counts (%); (b) percentage out of 194 total; (c) percentage out of 82 total; (d)percentage out of 67 total; (e) percentage out of 45 total.
for each allele observed in all the three groups, either asymptotic Chi-square test or Fisher-exact test
was applied to investigate the statistical significance of observed differences in proportions, as
appropriate.
** statistically highly significant differences (p < 0.01)(f)

Table II c. The frequencies of HLA-C* allele identified within ALL, AML, and AA.
HLA-C* allele
‒
01:02
02:XX
02:02
03:XX
03:02
03:03
03:04
04:XX
04:01
04:04
05:XX
05:01
06:XX
06:02
07:XX
07:01
07:02
07:04
07:12
08:XX
08:01
08:02
12:XX
12:02
12:03
14:XX

Total(a)(b)(n=194)13 (6.7%)
8 (4.1%)2 (1.0%)35 (18.0%)
2 (1.0%)1 (0.5%)8 (4.1%)7 (3.6%)2 (1.0%)44 (22.7%)
1 (0.5%)2 (1.0%)15 (7.7%)
2 (1.0%)25 (12.9%)
6 (3.1%)54 (27.8%)
15 (7.7%)
8 (4.1%)1 (0.5%)1 (0.5%)1 (0.5%)18 (9.3%)
4 (2.1%)16 (8.2%)
30 (15.5%)
2 (1.0%)Fiziologia - Physiology • 2019.29.2(98)ALL (a)(c)(n=82)
7 (8.5%)4 (4.9%)20 (24.4%)
1 (1.2%)
1 (1.2%)4 (4.9%)3 (3.7%)
1 (1.2%)20 (24.4%)

7 (8.5%)
1 (1.2%)8 (9.8%)2 (2.4%)20 (24.4%)
5 (6.1%)5 (6.1%)

AML (a)(d) (n=67)

AA(a)(e) (n=45)

p-value (f)4 (6.0%)4 (6.0%)2 (3.0%)6 (9.0%)1 (1.5%)2 (4.4%)‒‒‒0.047*
‒
‒
0.90
1
‒
0.49
‒
‒
1
‒
0.43
0.77
0.23
0.79
0.59
‒
‒
‒
0.39
‒
0.50
0.25
‒

2 (3.0%)2 (3.0%)1 (1.5%)12 (17.9%)
1 (1.5%)2 (3.0%)5 (7.5%)
1 (1.5%)9 (13.4%)
3 (4.5%)17 (25.4%)
6 (9.0%)2 (3.0%)9 (20.0%)

2 (4.4%)2 (4.4%)12 (26.7%)

3 (6.7%)8 (17.8%)
1 (2.2%)17 (37.8%)
4 (8.9%)1 (2.2%)1 (2.2%)

1 (1.5%)5 (6.1%)2 (2.4%)9 (11.0%)
9 (11.0%)

8 (11.9%)2 (3.0%)4 (6.0%)14 (20.9%)

1 (2.2%)5 (11.1%)
3 (6.7%)7 (15.6%)
2 (4.4%)27

14:02
15:XX
15:02
15:05
15:14
16:XX
16:01
16:02
16:04
17:01

6 (3.1%)1 (0.5%)17 (8.8%)
2 (1.0%)1 (0.5%)1 (0.5%)2 (1.0%)3 (1.5%)1 (0.5%)2 (1.0%)3 (3.7%)
1 (1.2%)8 (9.8%)1 (1.2%)2 (3.0%)1 (2.2%)6 (9.0%)1 (1.5%)3 (6.7%)

1
‒
0.90
‒
‒
‒
‒
‒
‒
‒

1 (2.2%)
1 (1.5%)
1 (1.2%)
1 (1.2%)
1 (1.2%)
1 (1.2%)1 (2.2%)2 (3.0%)1 (1.5%)(a) observed frequency counts (%); (b) percentage out of 194 total; (c) percentage out of 82 total; (d)percentage out of 67 total; (e) percentage out of 45 total.
for each allele observed in all the three groups, either asymptotic Chi-square test or Fisher-exact test
was applied to investigate the statistical significance of observed differences in proportions, as
appropriate.
* statistically significant differences ( p < 0.05)(f)

Table II d. The frequencies of HLA-DRB1* allele identified within ALL, AML, and AA.
HLA-DRB1*
allele
‒
01:XX
01:01
01:02
03:XX
03:01
03:03
04:XX
04:01
04:02
04:03
04:04
04:05
04:07
04:10
07:XX
07:01
08:01
08:02
09:01
10:01
10:02
11:XX
11:01
11:02
11:03
11:04
11:61
12:XX
12:01
13:XX
13:01

28

Total(a)(b)(n=194)3 (1.5%)2 (1.0%)29 (14.9%)9 (4.6%)2 (1.0%)31 (16.0%)
1 (0.5%)3 (1.5%)
12 (6.2%)
4 (2.1%)3 (1.5%)5 (2.6%)2 (1.0%)2 (1.0%)1 (0.5%)3 (1.5%)26 (13.4%)
5 (2.6%)2 (1.0%)2 (1.0%)2 (1.0%)1 (0.5%)
12 (6.2%)
26 (13,4%)
1 (0.5%)3 (1.5%)34 (17.5%)
1 (0.5%)2 (1.0%)6 (3.1)3 (1.5%)22 (11.3%)

ALL(a)(c)(n=82)
1 (1.2%)
1 (1.2%)
12 (14.6%)
4 (4.9%)1 (1.2%)13 (15.9%)
1 (1.2%)
1 (1.2%)4 (4.9%)2 (2.4%)
1 (1.2%)
1 (1.2%)
1 (1.2%)
1 (1.2%)

AML (a)(d) (n=67)
1 (1.5%)9 (13.4%)
2 (3.0%)1 (1.5%)10 (14.9%)
1 (1.5%)4 (6.0%)2 (3.0%)1 (1.5%)AA(a)(e) (n=45)

p-value (f)2 (4.4%)

‒
‒
0.81
0.56
‒
0.92
‒
1
0.69
‒
‒
0.16
‒
‒
‒
‒
0.077
‒
‒
‒
‒
‒
‒
0.60
‒
‒
0.033*
‒
‒
0.57
‒
0.20

8 (17.8%)
3 (6.7%)8 (17.8%)
1 (2.2%)4 (8.9%)2 (4.4%)3 (6.7%)
1 (2.2%)

1 (1.5%)
1 (2.2%)2 (2.4%)7 (8.5%)2 (2.4%)

1 (1.5%)14 (20.9%)
1 (1.5%)2 (2.4%)
1 (1.2%)
1 (1.2%)3 (3.7%)12 (14.6%)
1 (1.2%)21 (25.6%)
1 (1.2%)4 (4.9%)2 (2.4%)6 (7.3%)5 (11.1%)
3 (6.7%)
1 (2.2%)

1 (1.5%)9 (13.4%)
10 (14.9%)
3 (4.5%)9 (13.4%)
1 (1.5%)
1 (1.5%)
1 (1.5%)
1 (1.5%)8 (11.9%)4 (8.9%)4 (8.9%)1 (2.2%)8 (17.8%)

Fiziologia - Physiology • 2019.29.2(98)13:02
13:03
13:05
13:68
14:XX
14:01
14:02
14:04
14:07
14:54
15:XX
15:01
15:02
15:07
16:XX
16:01
16:02

5 (2.6%)4 (2.1%)1 (0.5%)1 (0.5%)1 (0.5%)6 (7.3%)1 (0.5%)5 (2.6%)
1 (0.5%)7 (3.6%)2 (1.0%)16 (8.2%)
9 (4.6%)
1 (0.5%)4 (2.1%)30 (15.5%)
7 (3.6%)3 (3.7%)
1 (1.2%)
1 (1.2%)
1 (1.2%)3 (3.7%)
1 (1.2%)2 (2.4%)
1 (1.2%)4 (4.9%)4 (4.9%)6 (7.3%)2 (2.4%)14 (17.1%)
5 (6.1%)2 (3.0%)3 (4.5%)

1 (1.5%)
1 (1.5%)2 (4.4%)2 (3.0%)1 (2.2%)3 (4.5%)
1 (1.5%)6 (9.0%)1 (1.5%)
11 (16.4%)
1 (1.5%)

1 (2.2%)6 (13.3%)
3 (6.7%)
1 (2.2%)1 (2.2%)5 (11.1%)
1 (2.2%)

‒
‒
‒
‒
‒
0.66
‒
1
‒
‒
‒
0.23
‒
‒
1
0.65
0.28

(a) observed frequency counts (%); (b) percentage out of 194 total; (c) percentage out of 82 total; (d)percentage out of 67 total; (e) percentage out of 45 total.
for each allele observed in all the three groups, either asymptotic Chi-square test or Fisher-exact
test was applied to investigate the statistical significance of observed differences in proportions, as
appropriate.
*statistically significant differences ( p < 0.05)(f)

Table II e. The frequencies of HLA-DQB1* allele identified within ALL, AML, and AA.
HLA-DQB1*
allele
‒
02:XX
02:01
02:02
03:XX
03:01
03:02
03:03
03:05
04:01
04:02
05:XX
05:01
05:02
05:03
05:04
05:05
06:XX
06:01
06:02
06:03
06:04
06:11
06:18

Total(a)(b)(n=194)3 (1.5%)4 (2.1%)33 (17.0%)
21 (10.8%)
16 (8.2%)
75 (38.7%)
21 (10.8%)8 (4.1%)1 (0.5%)1 (0.5%)8 (4.1%)
12 (6.2%)
32 (16.5%)
36 (18.6%)
16 (8.2%)
3 (1.5%)1 (0.5%)7 (3.6%)6 (3.1%)16 (8.2%)
23 (11.9%)
4 (2.1%)1 (0.5%)1 (0.5%)

Fiziologia - Physiology • 2019.29.2(98)ALL(a)(c)(n=82)
3 (3.7%)2 (2.4%)13 (15.9%)
5 (6.1%)5 (6.1%)37 (45.1%)
8 (9.8%)3 (3.7%)
1 (1.2%)2 (2.4%)5 (6.1%)16 (19.5%)
19 (23.2%)
8 (9.8%)1 (1.2%)5 (6.1%)3 (3.7%)5 (6.1%)6 (7.3%)2 (2.4%)

AML (a)(d) (n=67)
2 (3.0%)10 (14.9%)
12 (17.9%)
10 (14.9%)25 (37.3%)
4 (6.0%)3 (4.5%)
1 (1.5%)2 (3.0%)6 (9.0%)10 (14.9%)
11 (16.4%)
4 (6.0%)1 (1.5%)6 (9.0%)8 (11.9%)2 (3.0%)AA(a)(e) (n=45)

10 (22.2%)
4 (8.9%)1 (2.2%)13 (28.9%)9 (20.0%)
2 (4.4%)4 (8.9%)1 (2.2%)6 (13.3%)
6 (13.3%)
4 (8.9%)3 (6.7%)
1 (2.2%)3 (6.7%)5 (11.1%)
9 (20.0%)
1 (2.2%)

1 (1.5%)p-value (f)‒‒0.56
0.022*
0.05#
0.19
0.075
1
‒
‒
0.24
0.38
0.61
0.34
0.71
‒
‒
0.34
‒
0.57
0.11
‒
‒
‒

29

(a) observed frequency counts (%); (b) percentage out of 194 total; (c) percentage out of 82 total; (d)percentage out of 67 total; (e) percentage out of 45 total.
for each allele observed in all the three groups, either asymptotic Chi-square test or Fisher-exact
test was applied to investigate the statistical significance of observed differences in proportions, as
appropriate.
* statistically significant differences ( p < 0.05); # marginally statistical significance (p0.05)(f)

Table III (a and b) show the most frequent haplotypes ofclass I and class II HLA allele, respectively.
According to haplotypes analysis, A*02:01 B*18:01
C*07:01 and A*01:01 B*08:01 C*07:01 in AML patients,
A*02:01 B*35:03 C*04:01 in ALL and in AA patients,
frequencies were significantly high for class I HLA (7.5%, 4.5%
3.7%. and 6.7%, respectively). The most frequent haplotypes ofclass II HLA allele were DRB1*11:04 DQB1*03:01 (22.0%) in
ALL, DRB1*03:01 DQB1*02:01 and DRB1*11:01 DQB1*03:01
in AML and DRB1*03:01 DQB1*02:01 in AA.

According to haplotypes analysis, A*02:01 B*18:01
C*07:01 and A*01:01 B*08:01 C*07:01 in AML patients,
A*02:01 B*35:03 C*04:01 in ALL and in AA patients,
frequencies were significantly high for class I HLA (7.5%,
4.5% 3.7%. and 6.7%, respectively). The most frequent
haplotypes of class II HLA allele were DRB1*11:04
DQB1*03:01 (22.0%) in ALL, DRB1*03:01 DQB1*02:01 andDRB1*11:01 DQB1*03:01 in AML and DRB1*03:01
DQB1*02:01 in AA.

Table III a. The most frequent haplotypes of class I HLA allele identified within ALL, AML, and AA.
HLA-A* B* C*
A*01:01 B*08:01 C*07:01
A*02:01 B*35:03 C*04:01
A*02:01 B*18:01 C*07:01
A*01:01 B*08:01 C*02:02
A*01:01 B*08:01 C*04:01
A*02:01 B*13:02 C*06:02

Total(a)(b)(n=194)7 (3.6%)7 (3.6%)6 (3.1%)3 (1.5%)3 (1.5%)3 (1.5%)ALL(a)(c)(n=82)
2 (2.4%)3 (3.7%)
1 (1.2%)‒2 (2.4%)
1 (1.2%)

AML (a)(d)(n=67)
3 (4.5%)
1 (1.5%)5 (7.5%)
1 (1.5%)‒2(3.0%)

AA(a)(e)(n=45)
2 (4.4%)3 (6.7%)‒2 (4.4%)1 (2.2%)‒p-value (f)
0.69
0.425
0.059
0.106
0.454
0.606

(a) observed frequency counts (%); (b) percentage out of 194 total; (c) percentage out of 82 total; (d)percentage out of 67 total; (e) percentage out of 45 total.
for each haplotype, either asymptotic Chi-square test or Fisher-exact test was applied to investigate thestatistical significance of observed differences in proportions, as appropriate.
(f)Table III b. The most frequent haplotypes of class II HLA allele identified within ALL, AML, and AA.
HLA-DRB1* DQB1*
DRB1*11:04 DQB1*03:01
DRB1*03:01 DQB1*02:01
DRB1*11:01 DQB1*03:01
DRB1*16:01 DQB1*05:02
DRB1*07:01 DQB1*02:02
DRB1*01:01 DQB1*05:01
DRB1*13:01 DQB1*06:03

30

Total(a)(b)(n=194)ALL(a)(c)(n=82)AML (a)(d)(n=67)

AA(a)(e)(n=45)

p-value (f)28(14.4%)
25(12.9%)
20(10.3%)
20(10.3%)
17(8.8%)
15(7.7%)
13(6.7%)

18(22.0%)
9(11.0%)

8 (11.9%)2 (4.4%)0.021*

9 (13.4%)

7(15.6%)

0.752

8 (9.8%)9 (13.4%)

3 (6.7%)0.547

10(12.2%)

6 (9.0%)4 (8.9%)0.832

3 (3.7%)10(14.9%)

4 (8.9%)0.041*

6 (7.3%)5 (7.5%)4 (8.9%)0.943

3 (3.7%)4 (6.0%)6(13.3%)

0.134

Fiziologia - Physiology • 2019.29.2(98)(a) observed frequency counts (%); (b) percentage out of 194 total; (c) percentage out of 82 total; (d)percentage out of 67 total; (e) percentage out of 45 total.
for each haplotype, either asymptotic Chi-square test or Fisher-exact test was applied to investigate
the statistical significance of observed differences in proportions, as appropriate.
* statistically significant differences ( p < 0.05);(f)

The inter-haplotype correlation analysis was applied,with results in Table IV. The highly significant correlations
were emphasized in bold, though all the significant

correlation values were marked as well. The Bartlett's test of
sphericity was highly significant (p< 0.001), so the Principal
Component Analysis (PCA) was subsequently applied.

Table IV. Inter-haplotypes correlations. Highly significant correlations are in bold.

(i)

(ii)

HLA haplotype

(i)

(ii)

(iii)

(iv)

(v)

(vi)

(vii)

(viii)

(ix)

(x)

(xi)

(xii)

(xiii)

A*01:01 B*08:01 C*07:01

1.0

-.037

-.035

-.024

-.024

-.024

-.079

.256**

-.066

-.066

-.060

-.056

-.052

1.0

-.035

-.024

-.024

-.024

.235**

.008

-.066

.025

-.060

-.056

-.052

1.0

-.022

-.022

.219**.181**

-.069

.037

.037

.155*

-.052

-.048

1.0

-.016

-.016

-.051

.326**

.095

-.042

-.039

.120

-.034

1.0

-.016

.067

.201**

-.042

-.042

.109

-.036

-.034

1.0

.186**

-.048

.095

-.042

.404**

-.036

-.034

1.0

.017

.005

.102

.080

-.009

.066

1.0

.123*

-.130*

-.065

-.054

-.103

1.0

-.059

.075

-.098

.045

1.0

.015

-.098

-.091

1.0

-.090

-.083

1.0

.077

A*02:01 B*35:03 C*04:01(iii)

A*02:01 B*18:01 C*07:01(iv)

A*01:01 B*08:01 C*02:02(v)

A*01:01 B*08:01 C*04:01(vi)

A*02:01 B*13:02 C*06:02(vii)

DRB1*11:04 DQB1*03:01(viii)

DRB1*03:01 DQB1*02:01(ix)

DRB1*11:01 DQB1*03:01(x)

DRB1*16:01 DQB1*05:02(xi)

DRB1*07:01 DQB1*02:02(xii)

DRB1*01:01 DQB1*05:01(xiii)

DRB1*13:01 DQB1*06:03

1.0

Kaiser-Meyer-Olkin measure = 0.492
Bartlett's test of sphericity: Chi-square=163.212 (df=78), p<0.001
Statistical significance: * p<0.05; ** p<0.01

Table V presents the PCA results. Based on the screeplot (Figure 1) and the criterion of eigenvalues greater than1, seven factors were extracted explaining more than 68%
of the total variance. For each extracted factor, the main
contributive haplotypes are emphasized in bold. The
haplotypes' patterns of the factors for the three types of

Fiziologia - Physiology • 2019.29.2(98)anemia proved to be indistinct. Figure 2 shows the matrix ofthe two-factor correlations for the three blood conditiondiseases. Nevertheless, the seven factors account for the
structure analysis of the frequently observed haplotypes, as
shown in the diagram constructed based on data in Table 5
and Figure 3.

31

Table V. Principal component analysis (PCA) and factor loading for the HLA haplotypes.
The main contributive haplotypes for each factor are in bold.
Extracted factors
HLA haplotype

F1

F2

F3

F4

F5

F6

F7

A*01:01 B*08:01 C*07:01

-.269

.320

.179

-.378

.177

-.237

.591

A*02:01 B*35:03 C*04:01

.083

-.117

.647

.372

-.064

-.128

.131

A*02:01 B*18:01 C*07:01

.533

.104

-.035

.032

-.090

.102

.294

A*01:01 B*08:01 C*02:02

-.265

.499

-.102

.384

-.338

.398

.001

A*01:01 B*08:01 C*04:01

.024

.341

.233

-.015

.580

.057

-.593

A*02:01 B*13:02 C*06:02

.680

.284

-.209

.025

.090

.028

.224

DRB1*11:04 DQB1*03:01

.465

.020

.436

.508

.078

-.112

.082

DRB1*03:01 DQB1*02:01

-.333

.756

.241

.097

-.007

-.036

.015

DRB1*11:01 DQB1*03:01

.118

.360

-.298

.138

-.514

-.415

-.248

DRB1*16:01 DQB1*05:02

.191

-.286

.355

-.196

-.409

.303

-.207

DRB1*07:01 DQB1*02:02

.646

.282

-.188

-.189

.165

.121

-.107

DRB1*01:01 DQB1*05:01

-.209

-.139

-.325

.465

.283

.490

.222

DRB1*13:01 DQB1*06:03

-.064

-.238

-.329

.434

.187

-.519

-.053

Eigenvalue

1.738

1.511

1.272

1.195

1.082

1.047

1.030

Variance (%)

13.367%

11.626%9.783%

9.190%

8.324%

8.054%

7.921%

Cumulative of variance (%)

13.367%24.992%34.775%43.966%52.290%60.344%68.265%

Fig. 1. The scree plot for the 13 most frequent haplotypes
considered in the principal component analysis (PCA). Based on
the criterion of eigenvalue >1, seven factors were chosen,
accounting for more than 68% of the total variance.

32

Fig. 2. Matrix of the two-factor correlations for the three bloodcondition diseases: 1 ‒ ALL, 2 ‒ AML, 3 ‒ AA. F1 to F7 are theseven factors resulted from the principal component analysis(PCA).

Fiziologia - Physiology • 2019.29.2(98)3.Ozdilli K, Oguz FS, Anak S, Kekik C, Carin
M, Gedikoglu G. The frequency of HLAclass I and II alleles in turkish childhood
acute leukaemia patients. J. Int. Med. Res.,
2010; 38(5): 1835-1844.
4.Janeway CA Jr, Travers P, Walport M, etal. The Major Histocompatibility Complex
and Inflammation, in Immunobiology: The
Immune System in Health and Disease, 5thEd., New York: Garland Science, 2001.
5.Marsh SGE, et al. Nomenclature forfactors of the HLA system. Tissue Antigens,2010; 75(4): 291-455.
6.Matzaraki V, Kumar V, Wijmenga C,
Fig. 3. Diagram of the underlying structure of frequently observed haplotypes within the threeblood conditions analyzed, based on the seven factors resulted from the principal component
Zhernakova A. The MHC locus and genetic
analysis (PCA).
susceptibility to autoimmune and infectious
diseases. Genome Biol., 2017; 18(1): 76.
7. Wieczorek M, et al. Major Histocompatibility Complex (MHC)
Class I and MHC Class II Proteins: Conformational Plasticity in
CONCLUSIONS
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8.
Fernández-Torres J, Flores-Jiménez D, Arroyo-Pérez A,
This study found that the most frequent haplotypes in a
Granados J, López-Reyes A. HLA-B*40 Allele Plays a Role instudied population group of 194 patients with one of thethe Development of Acute Leukemia in Mexican Population: A
three disorders analyzed (ALL, AML, and AA) were A*02:01
Case-Control Study. Biomed Res. Int., 2013; 2013; 1-6.
B*13:02 C*06:02 DRB1*07:01 DQB1*02:02, A*01:01 B*
9. Patiroglu T, Akar HH. Relationships of Human Leukocyte
08:01 C*02:02 DRB1*03:01 DQB1*02:01, A*01:01 B*08:01
Antigen-A, -B, -DRB1 Alleles, and Haplotypes in 129 Ethnic
C*07:01 DRB1*03:01 DQB1*02:01, A*02:01 B*35:03
C*04:01 DRB1*11:04 DQB1*03:01, A*02:01 B*13:02
Turkish Patients With Acute Myeloblastic Leukemia. Lab. Med.,
C*06:02 DRB1*11:04 DQB1*03:01 and A*02:01 B*18:01
2015; 46(3): 195-199.
C*07:01 DRB1*11:04 DQB1*03:01.
10. Pui CH, Carroll WL, Meshinchi S, Arceci RJ. Biology, Risk
The analysis of the study shows that there is no
Stratification, and Therapy of Pediatric Acute Leukemias: An
haplotype to be considered a risk factor in the development
Update. J. Clin. Oncol., 2011; 29(5): 551-565.
of a haematological disease, but these results can be further
11. Schroter S, Plowman R, Hutchings A, Gonzalez A. Reportingused in a larger study.
ethics committee approval and patient consent by study design
The most common alleles susceptibile to be consideredin five general medical journals. J. Med. Ethics, 2006; 32(12):as a risk factor in the development of hematological
718–23.
diseases in patients in the western part of Romania are
12. Robinson J, Mistry K, McWilliam H, Lopez R, Marsh SGE. IPD-A*02:01 in AA but also ALL, A*24:02 in ALL, B*18:01 in AML
the Immuno Polymorphism Database. Nucleic Acids Res., 2010;
but also ALL and AA, B*08:01 in AA, C*02:02 in ALL,
38: D863-9.
C*04:01 in ALL and AML, DRB1*03:01 in AA and ALL,
13. Robinson J, Halliwell JA, McWilliam H, Lopez R, Parham P,
DRB1*07:01 in AML, DRB1*11:04 in ALL, DQB1*03:01 in
Marsh SGE. The IMGT/HLA database. Nucleic Acids Res.,ALL and AML.
2013; 41: D1222-7.
14. Hansen AM, Jeske D, Kirsch W. A Chi-Square Goodness-of-Fit
ACKNOWLEDGMENTS
Test for Autoregressive Logistic Regression Models withThis work was supported by the National Transplant Program.
Applications to Patient Screening. J. Biopharm. Stat., 2015;25(1): 89-108.
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understanding of MHC class I and MHC class II antigen
16. Chen Q, Wang W, Lin P, Zhong Q, Yu S. Application of Excel
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2. Benacerraf B. Role of MHC gene products in immune regulation.
Fang Yi Ke Da Xue Xue Bao, 2009; 29(4): 791-3.
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Fiziologia - Physiology • 2019.29.2(98)33

B*08:01 HLA CLASA I, ALELELE MHC CLASA II ȘI
FRECVENȚA HAPLOTIPURILOR LA PACIENȚII CU
AFECȚIUNI HEMATOLOGICE ÎN VESTUL ROMÂNIEIREZUMAT
Studiul de față s-a desfășurat între 2015 și 2018, având ca scop investigarea incidenței haplotipurilor în leucemia acută
limfoblastică (ALL), leucemia acută mieloidă (AML) și anemia aplastică (AA) în partea de vest a României. A fost utilizată
tehnica de secvențializare de tip SBT (sequencing-based typing), folosind kiturile SeCore ONE LAMBDA, cu ajutorul cărora
au fost tipizate genele HLA clasa I și II. Ulterior, a fost analizată și comparată frecvența alelelor pentru bolile hematologice.
Cuvinte cheie: gene HLA clasa I și II, leucemie acută limfoblastică (ALL), leucemie acută mieloidă (AML), anemie aplastică(AA), tehnica de tipizare prin secvențiere (SBT)

34

Fiziologia - Physiology • 2019.29.2(98)EXPERIMENTAL ELECTROCARDIOGRAPH
FOR TELEMEDICINEFLORIN ȘUȘMAN1, MIHAELA LASCU1, VALENTIN ORDODI1,2
1Politehnica University of Timișoara, 2 Victoriei Square, RO-300006, Timișoara, România
2OncoGen Research Center, Pius Brânzeu Clinical Emergency Hospital, 156 Liviu Rebreanu Bv, RO-300723, Timișoara, România.

ABSTRACTThis article describes a simple electrocardiographic device that allows via the mobile phone network the real-timemonitoring of the electrocardiogram at the patient's home. The experimental device is realized by coupling some miniatureelectronic modules, it is powered by a 9 V alkaline battery which gives it a long operating autonomy and which allows therecording of a standard ECG derivation. The electrocardiogram is transmitted in real time through a wireless device to thepatient's mobile phone. It has the possibility to save the respective recording, to transmit it to the cardiologist or to the family
physician, either in real time or at a later date, through appropriate software.
Key words: ECG machine, mobile phone network, telemedicine

INTRODUCTION
Cardiovascular disease is currently the leading cause ofmorbidity and mortality worldwide. Countries with a highstandard of living have a true epidemic of cardiovasculardiseases, especially ischemic. The sudden death of thesepatients is quite difficult to avoid in medical practice, as it isdue in most cases to heart rhythm disorders that are mostoften electrocardiographic [1,2,3]. Telemedicine, aseemingly new branch of medicine, involves remotephysician-patient communication [4]. The main contributionof the present telemedicine is the monitoring of somephysiological and biochemical parameters of the humanbody and the transmission of the data collected through anelectronic system of remote communications to thespecialist doctor. Cardiology benefits greatly from thedevelopment of these technologies, the essential
cardiovascular parameters: peripheral pulse, oxygen
saturation, blood pressure, electrocardiogram, being easy torecord with the usual electronic devices and thus the patient
can transmit this data to the doctor in a very simple way fromhome [5,6,7]. The first remote transmissions of anelectrocardiogram were made more than half a century ago.
Currently, the existing technologies both in terms of theacquisition and amplification of the ECG signal as well as
the analogical numerical conversion of the data, respectively

their transmission via mobile telephony, make this mode of
consultation widely used [8,9].
Experimental device
The experimental device acquires, amplifies andprocesses, displays and transmits the ECG signal to amobile phone via Bluetooth device. The electrocardiogramis sent in real time through a specialized software to thecardiologist or can be saved on the mobile device and sent
later or archived. The power supply of the experimental
device is provided by a 9 V alkaline battery. In figure 1 wecan see the modules from which the device is made.

Fig.1. A. Experimental device (overview); B. Block diagram

Received August 20th 2019. Accepted October 12th 2019. Address for correspondence: Valentin Ordodi, PhD, Politehnica University ofTimișoara, 2 Victoriei Square, RO-300006, Timișoara, România; phone: +40-256-404219; e-mail: vali.medtm99@gmail.com

Fiziologia - Physiology • 2019.29.2(98)35‐ The acquisition and amplification module of the ECG
signal. AD8232 is an integrated circuit whose design is
specific to ECG applications, but also to other applications
that use biopotential measurements. It has been modeled
to extract, amplify and filter small biopotential signals
under noise conditions. This design incorporates a very
low power ADC converter along with an integrated µC foreasy signal acquisition. The configuration used in theexperimental device uses the DII derivation because inmost individuals the amplitude of the waves in thisderivation is maximum (the projection of the cardiac
electric vector in the Einthoven triangle) [10].
‐ High-performance picoPower microchip microcontroller(Atmega 328p), based on 8-bit AVR RISC, combines ISP
flash memory with 32KB memory with real-time write
capabilities, EEPROM 1024B, SRK 2KB, 23 generalpurpose I / O lines, 32 purpose work registers general, /counters with comparison modes, internal and external
switches, USART programmable serial, two-wire serialinterface, SPI serial port, 10-bit 6-channel A / D converter, programmable monitoring timer with internal oscillator
and five selectable energy saving modes [11].
‐ Display is a blue light OLED type, of 0.96 inch. It is
having a resolution of 128x64. OLED is a self lightemitting technology composed of a thin, multi-layeredorganic film placed between an anode and cathode. In
contrast to LCD technology, OLED does not require abacklight. The display module can be interfaced with any
microcontroller using IIC protocols [12].
‐ Bluetooth module is HC-06 type. This module performs
the wireless connection between the experimental
device and the mobile phone. Is an Arduino compatible
device that establishes a bilateral serial connection on
the 2.4 GHz frequency [13].
The programming interface used to design the software
is Arduino IDE and is based on the C / C ++ language. Also
through Arduino IDE the driver for the OLED display was
downloaded [14].

RESULTS AND DISCUSSION
A preliminary experiment using the proposed
experimental device was performed on a male subject 24
years old. The bipolar DII standard derivation of the limbs
was recorded, connecting the negative pole of the
instrumentation amplifier at the level of the right shoulder,
and the positive one at the thoracic level in the spinal
projection area. Thus the cardiac electric vector will have amaximum
representation,
andtherecorded
electrocardiographic signal will be maximum. The
36

connection between the experimental device and the mobile
phone is established via Bluetooth, the graphical applicationis launched and the electrocardiogram is followed in realtime. Figure 2 shows the appearance of this recording on
the mobile phone.

Fig. 2. Electrocardiogram viewed on the mobile phone

The heart rate and the ECG aspect are transmitted inreal time to the cardiologist, using the appinventor.mit.edu
application available online. Also the recordings can be
stored in the memory of the mobile phone and comparedlater [15].

CONCLUSIONSThe presented experimental device is simple,
inexpensive, very accessible and easy to use by mostpatients. The recorded electrocardiogram corresponds
qualitatively to the requirements for a correct diagnosis in
the case of rhythm disorders, and even of ischemic
episodes, which recommends it for monitoring the cardiac
activity at home and transmitting data directly to theattending physician. The patient's safety is ensured by theuse of a 9 V battery. There is absolutely no physicalconnection between the experimental device and anotherelectronic device: computer, cable telephone line, etc.,
avoiding the risk of accidents.

REFERENCES
1. Bunu C. Fiziologia aparatului cardiovascular. Ed. Orizonturi
Universitare, Timișoara, 2003.
2. Noveanu L, Mihalaș G. Fiziologie Practică. Vol II. Ed. MirtonTimișoara, 2005.
3. Diaconu C. Explorări funcționale în medicina internă. Ed. All,
București, 2016.
4. Bashshur RL, Armstrong PA, and Youssef 21, Telemedicine;
Explorations in the use of telecommunications in health care,Charles C. Thomas, Springfield, IL, 1975.
5. Economakos G, Nikolaidis L, and Papakonstantinou G.
Animation techniques for real time ECG monitoring, inFiziologia - Physiology • 2019.29.2(98)Computers in Cardiology 1998, Cleveland, OH, USA,
September 1998, IEEE.
6. Brunetti ND, De Gennaro L, Dellegrottaglie G, Amoruso
D,Antonelli G, Di Biase M. A regional prehospitalelectrocardio-gram network with a single telecardiology ‘‘hub’’for public emergency medical service: technical requirements,
logis-tics, manpower, and preliminary results. Telemed J E
Health, 2011; 17: 72-33.
7. Brunetti ND, Dellegrottaglie G, Di Giuseppe G, LoprioreC,
Gardini G, Patruno S, et al. YOUng Football Italianamateur
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Transactions on Information Technology in Biomedicine, 2001;
5(1):13-16.
9. Chang CC, Yang YC, Teng WC, et al. An SCP compatible 12lead electrocardiogram database for signal transmission,storage and analysis. J Computer in Cardiology, 2004, 31:621624.
10. www.analog.com/media/en/technical-documentation/datasheets/ad8232.pdf
11. www.microchip.com/downloads/en/DeviceDoc/Atmel-7810Automotive-Microcontrollers-ATmega328P_Datasheet.pdf
12. http://www.farnell.com/datasheets/1718446.pd
13. https://www.olimex.com/Products/Components/RF/BLUETOOTH-SERIAL-HC-06/resources/hc06.pdf
14. https://www.arduino.cc/en/main/software
15. http://appinventor.mit.edu

DISPOZITIV ELECTROCARDIOGRAFICPENTRU TELEMEDICINĂREZUMATÎn prezentul articol este descris un dispozitiv electrocardiografic simplu, care permite via reteaua de telefonie mobila
monitorizarea in timp real a electrocardiogramei la domiciliul pacientului. Dispozitivul experimental este realizat prin
cuplarea unor module electronice miniaturale, este alimentat de la o baterie alcalina de 9 V ceea ce ii confera o autonomie
de functionare indelungata si care permite inregistrarea unei derivatii ECG standard. Electrocardiograma este transmisa intimp real prin intermediul unui dispozitiv fara fir catre telefonul mobil al pacientului. Acesta are posibilitatea sa salveze
inregistrarea respectiva, sa o transmita medicului specialist cardiolog sau medicului de familie, fie in timp real fie la o dataulterioara prin intermediul unei software adecvat.
Cuvinte cheie: dispozitiv ECG, rețea de telefonie mobilă, telemedicină

Fiziologia - Physiology • 2019.29.2(98)37

EGF-INDUCED CHEMOTAXIS OF SK-BR3 TUMORCELLS IN VITRO USING HOLOGRAPHIC IMAGINGDANA PLEȘCA1, DANIELA CRÎSNIC1,2,3, DACIANA NISTOR1,2, CARMEN TATU1,2,
GABRIELA TANASIE1,2, ROXANA ZOGOREAN2, SIMONA ANGHEL1,2,
OANA GAVRILIUC1,2, FLORINA BOJIN1,2, VIRGIL PĂUNESCU1,2
1Department of Functional Sciences, „Victor Babes” University of Medicine and Pharmacy Timisoara, Romania
2OncoGen-Centre for Gene and Cellular Therapies in the Treatment of Cancer, „Pius Brinzeu” Clinical Emergency County Hospital Timisoara,

Romania
3SC Biodim SRL, 59 Porumbescu St, RO-300239, Timișoara, România

ABSTRACTIn this study we evaluated the ability for induction of chemotaxia in vitro, for a tumor cell line of breast adenocarcinoma,
SK-BR3. This cell line was evaluated for the morphological and phenotypic characteristics, and for expression of receptors
involved in chemotaxis. SK-BR3 cell line expresses epidermal growth factor receptor (EGFR), so that we used EGF(epidermal growth factor) in our studies, as chemotaxis inducer. Chemotaxis was studied in specific µ-slides, using aholographic imaging system – Holomonitor M4.
From the morphological point of view, tumor cells have a polygonal shape, with a cellular size of 15-20 µm. The chemotactic
effects of EGF on SK-BR3 were evaluated by motility, migration and migration speed, parameters which were monitored
for 24 hours. Cultured on fibronectin-coated plates, SK-BR3 cells in presence of EGF exhibited an increased motility
compared to native SK-BR3 (818.1 m  sd, and 673.7 m  sd, respectively). Migration speed is 2 times higher for thetumor cells in presence of EGF, while the migration is similar, but is unidirectional.
This in vitro study is very important for invasion and tumor metastasis and provides a targeted image about these processes
for SK-BR3 tumor cell line, mainly due to the investigation methods using Holomonitor M4 and holographic images analysis
by Hstudio software. These investigations could be further extended to analysis of other tumor cells and several different
chemotaxis inducers.
Key words: chemotaxia, tumor cells, Holomonitor M4, EGF

INTRODUCTION
Chemotaxis represents directed cellular movement inresponse to a chemical gradient from the extracellularenvironment. The process is important for initiation andmaintenance of the inflammatory processes, while incancer it accounts for tumor cells dissemination andprobably distant metastases. In tumors, chemotaxis ofcarcinoma cells and stromal cells is mediated bychemokines, chemokine receptors, growth factors andgrowth factors receptors, some of them presented in Table
I [1]. Tumor cells can move both randomly and directionally,
efficient migration being accomplished when cells havedirected movement [2].

For chemotactic movement, cells should pass throughthree individual steps: sensing the chemical compound,polarization and locomotion. Single tumor cells are involvedin two different types of directed movement: amoeboid andmesenchymal migration. In our study, we were interested in
the mesenchymal type of tumor cell migration, which ischaracterized by elongated cellular morphology,
establishing cellular polarity and low velocity of migration(0.1-1 µm/min) (Table II) [3]. Mesenchymal migration is alsoa characteristic of most carcinomas or cells undergoing
epithelial to mesenchymal transition (EMT) [4-9]. However,amoeboid and mesenchymal migration can interconvert,
both in vivo and in vitro.

Received 12th of October 2019. Accepted 11th of November 2019. Address for correspondence: Florina Bojin, MD, PhD, Department of
Functional Sciences, „Victor Babes” University of Medicine and Pharmacy Timisoara, Eftimie Murgu Square No. 2A, RO-300041, Romania;
phone/fax: +40256490507; e-mail: florinabojin@umft.ro38

Fiziologia - Physiology • 2019.29.2(98)Signaling regulation is very important for chemotaxis oftumor cells, thus making important studying chemotaxis inphysiological relevant conditions, within the tumor
microenvironment. Several studies showed that a complex
chemokine network initiates and regulates chemotaxis oftumor cells. This network can also regulate several otherintracellular processes, such as tumor development,
angiogenesis, tumor evasion, senescence, survival andmetastatic progression, at this moment more than 50
different chemokines and chemokine receptors being
involved in cancer, and more than 30% of them being also
involved in chemotaxis.

Table II. Types of directed cellular migration
Unicellular migration

Multicellular migration

Movement
type

Amoeboid

Mesenchymal

Colective or
chain migration

Streaming

Cellular typeWBC

Fibroblasts

Tumor cells

Tumor cells

Tumor cells

Cells involved
in gastrulation,wound healing
and cancer

Microenviron
ment factors
influencing
migration

Chemokine
gradient andgrowthfactors

Chemokine
gradient andgrowth factors

Chemokine
gradient andgrowth factors,
extracellularmatrixreorganization

Chemokine
gradient andgrowth factors,
extracellularmatrixreorganization

Change ofcellularmorphology

Amoeboid tomesenchymalMesenchymal
to amoeboid,
mesenchymal
to colective

Colective tounicellularmigration

Undetermined

Processes
involving
cellular
movement

Immuneresponse

Development

Development
andmorphogenesis

Development

Table I. Growth factors involved in cancer cells chemotaxia
Chemokines andgrowth factors

Receptors

Experimental
data

EGF, TGFa,
betacellulin,
HBEGF

EGFR (ERBB1),
Transwell assay
ERBB2 (Her2),
ERBB3 and ERBB4 3D invasion
In vivo invasion

Cancer types

Breast, lung,colorectal,
gastric cancers,
glioblastoma

Intravital imaging
FGF

PDGF

FGFR1-4

PDGFR

IGF1

TGFβR1 and
TGFβR2

IGF1R

Transwell assay

VEGFA and
VEGFC

CSF1R

VEGFR1-3

Tumor invasion

Breast cancer,
glioblastoma,
melanoma

Breast, lung,squamous cellandoesophageal
Intravital imaging cancers
Wound-healing
assay

Transwell assay

Breast cancer,
sarcoma,multiplemyeloma,lymphoma,melanomaTranswell assay Breast, ovarian,endometrial,
3D invasion
prostate andIn vivo invasion gastric cancers
and leukemia
Intravital imaging
Transwell assay Melanoma,prostate cancer,
3D culturesarcoma,meningioma andleukemia

Fiziologia - Physiology • 2019.29.2(98)Tumor invasion

Neovasculariza
tion
Tissue healing
Tumor invasion

Cancer type

Breast andprostate
cancer,melanoma

Breast andprostate
cancer,melanoma,lung carcinoma

Breast,prostate, lung,colorectal
cancer,melanoma andsquamous
carcinoma

Breast cancer

References

7-15

7, 16, 17

7, 18-24

25-29

Transwell assay

Wound healing

CSF1

Immuneresponse

Transwell assay Breast, ovarian,pancreatic, renal
cancers,
glioblastoma

3D culture

TGFβ

Tumor
invasion

Cells involved
in developmentof neural crest

In this study, we evaluated the capacity of inducing
chemotaxis on a tumor cell line – SK-BR3 breast
adenocarcinoma. This cell line expresses epidermal growth
factor receptors (EGFR), so that we used epidermal growth
factor (EGF) as chemotaxis agent.

MATERIALS AND METHODS
SK-BR3 cell culture
For the SK-BR3 cell line, the producer recommends thecomplete culturing medium, which contains ATCCformulated McCoy's 5a Medium Modified, supplemented
with 10% Fetal Calf Serum (FCS). Subculturing is
recommended to be 1:2, medium replacement 2-3
times/week. Cells are expanded in adherent culture plates,in cell incubators with humidity and 5% CO2.

39

Chemotaxia protocol
The protocol for cells seeding in chemotaxia slides was
as follows:- 10,000 cells in suspension in 50 µl complete culture
medium were pipeted in the central channel;- Cells were left to adhere 30 minutes in incubator;- EGF was added in lateral chamber in concentration of
10 ng/µl;- the chemotaxis plates were placed on the Holomonitor
M4 and monitored for 24 hours in a time-lapse
manner;- images were obtained at 10 minutes interval andanalyzed with Hstudio software.
The SK-BR3 cells were monitored using the Holomonitor
M4 as follows: a. without any adhesion substrate, evaluating
motility of native cells; b. in fibronectin-coated culture plates; c.
in presence of EGF (chemotaxis inductor) on special slides.
Results were analyzed using the HStudio software.

Fig.2. Morphological aspects of SK-BR3 cells cultured on
fibronection-coated plates, optic microscopy, Ob. 4x, 10x, 20x.

In Figure 3, SK-BR3 cells are monitored with
Holomonitor M4 while being cultivated in chemotaxia plates,
in presence of EGF. The figure presents moments 1, 50 and
97 from the time-lapse recording. For further datainterpretation we used the HStudio software, which canprovide data regarding directed cellular motility.

RESULTS AND DISCUSSION
SK-BR3 cells were monitored for 24 hours with
Holomonitor M4. The images were taken every 30 minutes
and are represented as holograms of cultured tumor cells,
adherent to the plastic surface. The 3D images are
represented based on the occupied area and cellular height.
Depending on the 3D image of the recorded event, thedevice can provide information related to cellular viability.
Figure 1 shows the 3D holographic aspect of SK-BR3
cells at moments 1, 50 and 99 from the 24-hours time-lapse.
After 24 hours of continuous monitoring, the focus of thedevice becomes less accurate, so the experiment was
stopped, also this is a transitory phenomenon.

Fig.1. Time-lapse monitoring of SK-BR3 cells. Laser profilometry
using Holomonitor M4. SK-BR3 were monitored for 24 hours infibronectin-coated 6-well cell culture plates, images taken every 30
minutes. Ob. 20x

SK-BR3 tumor cells were first verified from themorphological point of view when cultured on semisolid
matrices, such as fibronectin. Cells were seeded at a cellulardensity of 10,000 cells/cm2 and monitored in optic
microscopy for at least 24 hours before adding chemotactic
substance.

40

Fig.3. Time-lapse monitoring of SK-BR3 cells moving towards EGF
gradient in fibronectin-coated chemotaxis plates. Holomonitor M4
images, Ob. 20x.

Fig.4. Motility graph of SK-BR3 cells represented for 10 cells (leftpanel) and average cellular population (right panel) without
chemotactic factors, monitored in chemotaxis microplates
fibronectin-coated.

The biaxial movement of cells is represented in Figure
4. Individual movement of 10 cells is represented on the left
panel, while the average cell movement is represented on
the right panel. The above images are automatically
Fiziologia - Physiology • 2019.29.2(98)generated by the HStudio software after identification ofeach holographic element as a cell. Biaxial representationof cellular movement and motility shows a disorganizedpattern, but the average motility is clearly oriented towards
the left part of the starting point.
When using the chemotaxia slides, the cells have amore directed movement in presence of EGF, whicle theaverage cell graph (right panel) shows a directness towards
the positive end of the ox axis, which is towards thechemotactic factor (Figure 5).

Fig.5. Motility graph of SK-BR3 cells represented for 10 cells (leftpanel) and average cellular population (right panel) with EGF as
chemotactic factor, monitored in chemotaxis microplates
fibronectin-coated.

Using the HStudio Holomonitor M4 specific software, wewere able to evaluate motility, migration and migration
speed for both SK-BR3 cells with or without EGF as
chemotactic factor. On the left part of the Figure 6 we
represented the parameters of the untreated cells, while theright panel represents the same parameters in presence of
EGF gradient. All these parameters are quantitatively
defined in Table III

Fiziologia - Physiology • 2019.29.2(98)41CONCLUSIONSThis in vitro study is very important for invasion andtumor metastasis and provides a targeted image about
these processes for SK-BR3 tumor cell line, mainly due tothe investigation methods using Holomonitor M4 andholographic images analysis by HStudio software. These
investigations could be further extended to analysis of othertumor cells and several different chemotaxis inducers.

Fig.6. Graphical representation of parameters analyzed with
HStudio software related to motility of native cells (left panel) and
EGF – chemoatracted SK-BR3 tumor cells (right panel).
Table III. Comparative analysis of motility characteristics for
SK-BR3 cells
SK-BR3

SK-BR3 EGF

Motility (m)

673.7

818.1

Migration (m)

81.5

142.2

Migration speed (m/h)

20.1

21.3

Considering the importance of chemotaxia in cancer,
development of drug therapies targeting different steps inchemotaxis became a purpose of the recent scientificresearch. Recently, autonomous devices for monitoring
chemotaxis, which can be implanted in vivo at tumor level,
will help to a precise definition of the specific chemotactic
signals involved in tumor cells migration [30]. Moreover,different compounds have been developed for a multitude ofchemotactic factors, some of them being already in clinicaluse, others in clinical trials.
These studies present an in vitro model for studying thechemotactic ability of tumor cells (SK-BR3 breast cancer cellline) in the presence of EGF, a growth factor withchemotactic abilities. This is one of the first studies related
to chemotaxia which involves holographic imaging using theHolomonitor M4.
Depending on the movement type, the cells thus
monitored were included in a specific category of directedmovement: unicellular, mesenchymal, which is very frequent
in many cancers, including breast cancer. The migration
speed (0.35 µm/min) (Table III) is also in accordance withthe definition of the mesenchymal movement, according to
Roussos ET et al. [4], which propose a range between 0.11 µm/min for this parameter.

42

Acknowledgement: This work was supported by the grant“Chimeric Antigen Receptor Targeted Oncoimmunotherapy with
Natural Killer Cells (CAR-NK)”, POC 92/09/09/2016, ID: P_37_786,
MySMIS code: 103662.

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EVALUAREA IN VITRO A CHEMOTAXIEICELULELOR TUMORALE SK-BR3 INDUSĂ
DE EGF PRIN IMAGISTICĂ HOLOGRAFICĂREZUMATÎn acest studiu am evaluat capacitatea de inducere a chemotaxiei pe linia celulară tumorală SK-BR3, o linie celulară deadenocarcinom mamar. Această linie celulară a fost investigată morfologic, fenotipic și din punct de vedere al expresiei
receptorilor pentru inductori ai chemotaxiei. Linia celulară SK-BR3 prezintă expresie de receptor pentru factorul de creștere
epidermal (EGFR), în studiile noastre fiind utilizat EGF (factorul de creștere epidermal) ca factor inductor al chemotaxiei.
Chemotaxia a fost studiată în plăci speciale pentru chemotaxie, utilizând un sistem de imagistică de tip holografic –Holomonitor M4.
Din punct de vedere morfologic, celulele tumorale ale celor 2 linii celulare investigate prezintă o formă poligonală,dimensiunile celulare sunt relativ mici, de aproximativ 15-20 µm. Efectele chemotactice la nivelul celulelor SK-BR3 indusede EGF au fost evidențiate prin evaluarea motilității, vitezei de deplasare, migrării și direcției de deplasare, parametri
monitorizați timp de 24h. Celulele SK-BR3 cultivate pe fibronectină în prezența EGF, prezintă o motilitate crescută
comparativ cu SK-BR3 fără factori de creștere (818,1 m  sd, respectiv 673,7 m sd). Viteza de deplasare este maimare de aproximativ 2 ori pentru SK-BR3 în prezenta EGF, migrarea este similară cu SK-BR3 fără factori, dar este
unidirecțională.
Considerăm că acest studiu in vitro de o importanța deosebită în ceea ce privește invazia și metastazarea tumorală, carene oferă o imagine țintită despre aceste procese pe linia celulară de adenocarcinom mamar SK-BR3, în special prinutilizarea Holomonitor M4 și analiza imaginilor holografice cu soft-ul Hstudio. Aceste investigații ar putea fi extinse în viitor
prin studiul altor celule tumorale, în prezența altor factori inductori ai chemotaxiei.
Cuvinte cheie: chemotaxie, celule tumorale, Holomonitor M4, EGF

Fiziologia - Physiology • 2019.29.2(98)

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Fiziologia - Physiology • 2019.29.2(98)