Kshivets O. Lung Cancer Surgery
-
Upload
oleg-kshivets -
Category
Health & Medicine
-
view
1.275 -
download
0
Transcript of Kshivets O. Lung Cancer Surgery
LYMPH NODE METASTASES OF LUNG LYMPH NODE METASTASES OF LUNG CANCER AND IMMUNE SYSTEMCANCER AND IMMUNE SYSTEM
Oleg Kshivets, MD, PhDOleg Kshivets, MD, PhD Siauliai Cancer Center, Siauliai, LithuaniaSiauliai Cancer Center, Siauliai, LithuaniaThe Second International Chicago Symposium on
Malignancies of The Chest and Head & NeckChicago, Illinois, The USA, 2001
Abstract:Abstract: LYMPH NODE METASTASES OF LUNG CANCER AND IMMUNE SYSTEMLYMPH NODE METASTASES OF LUNG CANCER AND IMMUNE SYSTEM Oleg Kshivets Siauliai Cancer Center, Siauliai, Lithuania Oleg Kshivets Siauliai Cancer Center, Siauliai, Lithuania Purpose: Significance of immune cell and humoral circuit in terms of detection of lung cancer (LC) patients (LCP) with lymph node metastases was investigated. Methods: In trial (1987-1998) consecutive cases after surgery, monitored 533 LCP (males – 472, females – 61; age=57.40.4 years; pneumonectomies -181, upper lobectomies - 138, lower lobectomies - 67, upper/lower bilobectomies - 24, middle lobectomies – 6, segmentectomies – 76, exploratory thoracotomies and biopsies - 41) with pathologic stage I-IV (stage I – 48, stage II – 47, stage III - 321; stage IV – 117; squamous cell LC - 294, adenocarcinoma - 171, large cell LC – 48, small cell LC - 20; T1 - 116, T2 - 168, T3 – 125, T4 - 124; N0 – 148, N1 - 144, N2 - 159; N3 – 82; G1 – 88, G2 – 166, G3 – 279; M0 – 438; M1 - 95) were reviewed. Variables selected for study were input levels of immunity blood parameters, sex, age, TNMG. Thawed aliquoted samples were evaluated for IgG, IgM, IgA, natural antibodies, circulating immune complexes. The percentage, absolute count and total population number (per human organism) of T-lymphocytes (CD3), B-lymphocytes (CD19), helper T-lymphocytes (CD4), suppressor/cytotoxic T-lymphocytes (CD8), killer cells (O-cells, K-cells or CD16), precursor T-cells (CD1), activated T-cells (CDw26), monocytes (CD64, CD13), helper/inducer T-lymphocytes (CD4+2H), contrsuppressor T-lymphocytes (CD8+VV), CD4/CD8, leukocytes, lymphocytes, polymorphonuclear and sticknuclear leukocytes were estimated. The laboratory blood studies also included input levels of NST (tests of oxygen dependent metabolism of neutrophils spontaneous and stimulated by Staphylococcus aureus or by Streptococcus pyogenes), index of stimulation of leukocytes by Staphylococcus aureus or Streptococcus pyogenes, index of thymus function, phagocytic number, phagocyte index, index of complete phagocytosis. Differences between groups were evaluated using multiple regression analysis, multi-factor clustering, structural equation modelling and Monte Carlo simulation. Results: It was revealed that separation of LCP with lymph node metastases (males – 343, females – 42; age=57.2±0.4 years; T1-4N1-3M0-1; tumor size=6.1±0.1 cm; n=385) from LCP without metastases (males – 129, females – 19; age=57.9±0.6 years; T1-3N0M0, tumor size=3.5±0.2 cm; n=148) significantly (P=0.000000) depended on: 1) level of immune cell circuit (2=31263.7; Df=560); 2) value of monocyte and macrophage circuit (2=233.9; Df=14); 3) level of humoral immunity (2=183.66; Df=9); 4) neutrophils circuit (2=7261.35; Df=77); 5) value of cell ratio factors (ratio of LC cell population to immune cell subpopulations in integral LCP organism) (2=6907.08; Df=104); 6) LC characteristics (T1-4, M0-1,G1-3, histology, tumor size) (2=1103.58; Df=27). It was also founded that most important factors of metastases of LC in lymph nodes were cell ratio factors (T=-5.761; P=0.0000000) and LC characteristics (T=9.666; P=0.0000000).
Key words: Lung Cancer, Immunity, Lymph Node Metastases
The Main Characteristics of The Main Characteristics of The Study PopulationsThe Study Populations
Lung Cancer Patients (males – 472, females – 61; age=57.40.4 years)…..533
Stage I…………..……………………...48Stage II…………………..……………..47Stage III……………………………….321Stage IV……………………………….117
Procedures (n=533)Procedures (n=533)Pneumonectomy………………………181Upper Lobectomy…………………….138Lower Lobectomy.……………………..67Upper/Lower Bilobectomy…….………24Middle Lobectomy………………………6Segmentectomy.……………………..…76Exploratory Thoracotomy, Biopsy…...41 Combined & Extensive Procedures with Resection of
Pericardium, Left Atrium, Aorta, Vena Cava Superior, Vena Azygos, Carina, Trachea, Diaphragm, Chest Wall, Ribs, etc. ………………….…………….55
Lung Cancer Patients Lung Cancer Patients Characteristics (n=533)Characteristics (n=533)
Squamous Cell……..294 Adenocarcinoma…...171 Large Cell……………48 Small Cell…………….20 T1.…………………..116 T2……………………168 T3……………………125 T4……………………124 N0……………………148
N1…………………...144 N2…………………...159 N3………………….…82 G1…………………….88 G2…………………...166 G3…………………...279 M0…………………...438 M1…………………….95
Immune Testing:Immune Testing:
Significant Immune Data in Detection of Lung Cancer Lymph Node Significant Immune Data in Detection of Lung Cancer Lymph Node Metastases (n=533)Metastases (n=533)
NN Factors N0 n=148 N1-3 n=385 P Mean SD Mean SD 1 2
B-cells (abs)*109/l B-cells (tot)*109
0.36 1.76
0.37 1.84
0.31 1.48
0.18 0.92
0.027* 0.020*
3 CD4+2H (abs)*109/l CD4+2H (tot) *109
0.59 2.83
0.41 1.89
0.51 2.46
0.34 1.78
0.018* 0.037*
4 5
CD8 (%) CD8 (tot) *109
14.03 1.17
8.20 0.89
12.50 1.01
7.79 0.78
0.045* 0.045*
6 Lymphocytes (%) 30.57 10.78 27.07 11.10 0.001* 7 8
NST spontaneous NST stimulated Streptococcus Pyogenes
7.33 9.55
6.30 8.63
9.16 11.73
9.15 9.71
0.026*
0.017* 9 Index Stimulation by Streptococcus
pyogenes 1.46
1.23
1.87
1.87
0.013*
10 11 12 13
Leukocytes (abs)*109/l Segmented Neutrophils (%) Segmented Neutrophils (abs)*109/l Segmented Neutrophils (tot)*109
5.94 61.78 3.69 17.84
2.32 11.14 1.60 8.20
6.45 65.17 4.25 20.12
2.53 11.49 1.96 9.30
0.031* 0.002* 0.002* 0.009*
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29
T-cells/Cancer Cells B-cells/Cancer Cells K-cells/Cancer Cells CD1/Cancer Cells CDw26/Cancer Cells CD4+2H/Cancer Cells CD8+VV/Cancer Cells CD4/Cancer Cells CD8/Cancer Cells Leukocytes/Cancer Cells Eosinophils/Cancer Cells Lymphocytes/Cancer Cells Monocytes/Cancer Cells Stick Neutrophils/Cancer Cells Segmented Neutrophils/Cancer Cells
1.76 0.73 1.02 0.31 0.19 1.11 1.13 1.40 0.47 10.99 0.31 3.43 0.40 0.12 6.72
1.60 1.24 1.79 0.52 0.33 1.08 1.36 1.29 0.58 8.72 0.37 3.94 0.50 0.20 5.25
0.78 0.28 0.47 0.14 0.09 0.47 0.47 0.64 0.19 5.62 0.31 1.52 0.18 0.08 3.65
0.62 0.22 0.43 0.21 0.14 0.41 0.49 0.57 0.17 3.09 0.27 1.09 0.21 0.14 2.09
0.000000* 0.000000* 0.000000* 0.000000* 0.000002* 0.000000* 0.000000* 0.000000* 0.000000* 0.000000* 0.000053* 0.000000* 0.000000* 0.004333* 0.000000*
Results of Logistic Regression Modeling in Detection of Lymph Node Results of Logistic Regression Modeling in Detection of Lymph Node
Metastases of Lung Cancer (n=533)Metastases of Lung Cancer (n=533) NN Significant Immune Factors: 2=47.281; Df=14;
P=0.00002; n=533; Estimate
1 2 3 4 5 6 7 8 9 10 11 12 13 14
Const.B0 CD4+2H (abs)*109/l CD4+2H (tot)*109 CD8 (%) CD8 (tot) *109 B-cells (abs)*109/l B-cells (tot)*109 NST spontaneous NST stimulated Streptococcus pyogenes Index Stimulation by Streptococcus pyogenes Leukocytes (abs)*109/l Lymphocytes (%) Segmented Neutrophils (%) Segmented Neutrophils (abs)*109/l Segmented Neutrophils (tot)*109
-2.60217 -4.62834
0.82 -0.01852 -0.04143 1.64540 -0.62571 0.06071 -0.02167 0.26358
0.48 0.01332 0.03823 -0.02550 -0.09027
ExpectedNormal
Frequency Distribution (Residuals): Lung Cancer Patients with Stage I-IVLogistic Regression (N0-N1-3---Immune System)
Chi2=47.28; Df=14; P=0.00002; n=533
No
of o
bs
0
20
40
60
80
100
120
140
160
180
200
220
240
-1,2 -1,0 -0,8 -0,6 -0,4 -0,2 0,0 0,2 0,4 0,6 0,8 1,0
Correlation between Lymph Node Metastasis & Lung Cancer Characteristics (n=533)Correlation between Lymph Node Metastasis & Lung Cancer Characteristics (n=533)
13,545 26,991 40,436 53,882 67,327 80,773 94,218 107,664 121,109 134,555 above
Bivariate Histogram: Lung Cancer Cell Population & Lymph Node MetastasesLung Cancer Patients with Stage I-IV, n=533
r=0.50; P=0.0000
-0,083 0,034 0,151 0,268 0,384 0,501 0,618 0,735 0,852 0,969 above
Quadratic SurfaceLung Cancer Cell Population vs. G1-3 vs. NO---N1-3
r (Lung Cancer Cell Population vs. NO---N1-3)=0.50; P=0.000 r (Lung Cancer Cell Population vs. G1-3)=0.27; P=0.000
r(G1-3 vs. NO---N1-3)=0.31; P=0.000
T- & B-cell Circuit in Detection of Lung T- & B-cell Circuit in Detection of Lung Cancer Lymph Node Metastases (n=533)Cancer Lymph Node Metastases (n=533)
CD8- & CD4-cell Circuit in Detection of Lung CD8- & CD4-cell Circuit in Detection of Lung Cancer Lymph Node Metastases (n=533)Cancer Lymph Node Metastases (n=533)
Lymphocytes & Monocytes Circuit in Detection Lymphocytes & Monocytes Circuit in Detection of Lung Cancer Lymph Node Metastasesof Lung Cancer Lymph Node Metastases (n=533) (n=533)
K-cells Circuit & Cancer Cells Number in K-cells Circuit & Cancer Cells Number in Detection of Lung Cancer Lymph Node Detection of Lung Cancer Lymph Node
Metastases (n=533)Metastases (n=533)
Segmented Neutrophils & CD4+2H-cells Circuit Segmented Neutrophils & CD4+2H-cells Circuit in Detection of Lung Cancer Lymph Node in Detection of Lung Cancer Lymph Node
Metastases (n=533)Metastases (n=533)
Cancer Cells Number & G1-3 in Detection of Cancer Cells Number & G1-3 in Detection of Lung Cancer Lymph Node Metastases (n=533)Lung Cancer Lymph Node Metastases (n=533)
Humoral Immunity in Detection of Lung Humoral Immunity in Detection of Lung Cancer Lymph Node Metastases (n=533)Cancer Lymph Node Metastases (n=533)
Cancer Cells Number & Cancer Cells Number & Lymphocytes Lymphocytes in in Detection of Lung Cancer Lymph Node Detection of Lung Cancer Lymph Node
Metastases (n=533)Metastases (n=533)
Role of Cell Ratio Factors in Lymph Node Metastases of Role of Cell Ratio Factors in Lymph Node Metastases of Lung Cancer (n=533)Lung Cancer (n=533)
Pareto Chart of t-Values for Coefficients; df=502Variable: NO---N1-N3 (Multiple R=0.529; P=0.00000)Sigma-restricted parameterization: Cell Ratio Factors
Lung Cancer Patients with Stage I-IV (T1-4N0-3M0-1), n=533
t-Value (for Coefficient;Absolute Value)
.0017443.3030983.3379894.3759631
.5061909.56716.5855403.6148093
.7795556
.7844907.7909309.8093222.8143432.8234021
.93423771.0256651.0449641.059058
1.1895431.225681.251766
1.4075021.457586
1.6227741.738972
1.9701382.216493
2.8545283.320651
3.893053
p=.05
Eosinophils/CC^2Leucocytes/CC^2
CD8+VV/CCB-cells/CC^2
Segm.Neutrophils/CC^Monocytes/CC^2
Stick Neutrophils/CCMonocytes/CC
CDw26/CCSegm.Neutrophils/CC
T-cells/CC^2Leucocytes/CC
Stick Neutrophils/CCCD8+VV/CC^2Eosinophils/CC
K-cells/CCLymphocytes/CC
Lymphocytes/CC^2CDw26/CC^2
T-cells/CCB-cells/CC
CD4+2H/CC^2K-cells/CC^2
CD1/CC^2CD8/CC^2
CD1/CCCD4+2H/CC
CD4/CC^2CD4/CCCD8/CC
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5
Results of Multi-Factor Clastering of Immune Results of Multi-Factor Clastering of Immune Factors in Detection of Lung Cancer Lymph Factors in Detection of Lung Cancer Lymph
Node Metastases (n=533)Node Metastases (n=533)
Networks between Factors of Immune Cell and Networks between Factors of Immune Cell and Humoral Circuit and LC Characteristics (n=533)Humoral Circuit and LC Characteristics (n=533)
SEPATH Modeling of System Lumph Node SEPATH Modeling of System Lumph Node Metastases--Immune System of Lung Metastases--Immune System of Lung
Cancer Patients (n=533)Cancer Patients (n=533)
N0--N1-3--T-, B-, K-Cell Circuit-Humoral Immunity-Macrophage Circuit--Neutrophil Circuit-Cell Ratio Factors-Lung Cancer
Global Model: Normalized Residuals (Lymph Node Metastases)Chi2=73226.4; Df=3154; P=0.000000; n=533
Value
Expe
cted
Nor
mal
Val
ue
-5
-3
-1
1
3
5
-25 -15 -5 5 15 25 35
Results of Monte Carlo Simulation (n=533)Results of Monte Carlo Simulation (n=533)
-1,849 -1,277 -0,706 -0,134 0,437 1,009 1,580 2,152 2,723 3,295 above
Monte Carlo Simulation: Lung Cancer Patients with Stage I-IV, n=533Model: N0---N1-3--T-, B-, K-cell Circuit--Humoral Immunity--Monocyte/Macrophage
--Neutrophils Circuit--Cell Ratio Factors--Cancer CharacteristicsP=0.000000
-3,675 -3,349 -3,024 -2,699 -2,374 -2,048 -1,723 -1,398 -1,073 -0,747 -0,422 -0,097 0,229 0,554 0,879 1,204 1,530 above
Monte Carlo Data Simulation: Lung Cancer Patients with Stage I-IV, n=533Model: N0---N1-3--T-, B-, K-cell Circuit--Humoral Immunity--Monocyte/Macrophage
Neutrophils Circuit-Cell Ratio Factors--Cancer CharacteristicsP=0.000000
-0,972 -0,475 0,022 0,520 1,017 1,514 2,011 2,508 3,006 3,503 above
Monte Carlo Simulation: Lung Cancer Patients with Stage I-IV, n=533Model: N0---N1-3--T-, B-, K-cell Circuit--Humoral Immunity--Monocyte/Macrophage
--Neutrophils Circuit--Cell Ratio Factors--Cancer CharacteristicsP=0.000000
-2,376 -1,739 -1,101 -0,464 0,174 0,812 1,449 2,087 2,725 3,362 above
Monte Carlo Simulation: Lung Cancer Patients with Stage I-IV, n=533Model: N0---N1-3--T-, B-, K-cell Circuit--Humoral Immunity--Monocyte/Macrophage
Neutrophils Circuit--Cell Ratio Factors--Cancer CharacteristicsP=0.000000
Immune Networks in Detection of Lymph Node Immune Networks in Detection of Lymph Node Metastasis in Lung Cancer Patients (n=533)Metastasis in Lung Cancer Patients (n=533)
0 2 4 6 8 10 122
0
2
4
6Model "Early Cancer---Immune System"
Lung Cancer Cell Population
Imm
une
Cyt
otox
ic C
ell P
opul
atio
ns
5.072
2.072
X1 3
X2 3
X3 3
X4 3
10.0590.235 X1 2 X2 2
X3 2 X4 2
0 5 10 15 200
5
10Model "Early Cancer---Immune System"
Time
Cel
l Pop
ulat
ion
Dyn
amic
s
5.884
0.306
X1 2
X1 3
200 X1 1
0 5 10 15 20 25 3010
5
0
5
10Model "Invasive Cancer---Immune System"
Lung Cancer Cell Population
Imm
une
Cyt
otox
ic C
ell P
opul
atio
ns
10.187
8.334
X1 3
X2 3
X3 3
X4 3
25.4662.403 10 14 X1 2 X2 2
X3 2 X4 2
0 5 100
10
20
30Model "Invasive Cancer---Immune System"
Time
Cel
l Pop
ulat
ion
Dyn
amic
s
25.07
8.691 10 14
X4 2
X4 3
100 X4 1
Lotka-Volterra Models of Lung Cancer Cell Population Lotka-Volterra Models of Lung Cancer Cell Population and Cytotoxic Cell Population Dynamicsand Cytotoxic Cell Population Dynamics
Holling-Tenner Models of Lung Cancer Cell Population Holling-Tenner Models of Lung Cancer Cell Population and Cytotoxic Cell Population Dynamics and Cytotoxic Cell Population Dynamics
0 5 100
2
4
6Model "Early Cancer---Immune System"
Lung Cancer Cell Population
Imm
une
Cyt
otox
ic C
ell P
opul
atio
ns
4.266
0.414
X1 3
X2 3
X3 3
X4 3
100.103 X1 2 X2 2
X3 2 X4 2
0 50 100 150 200 2500
2
4
6Model "Early Cancer---Immune System"
Time
Cel
l Pop
ulat
ion
Dyn
amic
s
4.266
0.103
X1 2
X1 3
2000 X1 1
0 5 10 15 200
5
10
15Model "Invasive Cancer---Immune System"
Lung Cancer Cell Population
Imm
une
Cyt
otox
ic C
ell P
opul
atio
ns
13.007
1
X1 3
X2 3
X3 3
X4 3
19.5124 X1 2 X2 2
X3 2 X4 2
0 20 40 600
10
20Model "Invasive Cancer---Immune System"
Time
Cel
l Pop
ulat
ion
Dyn
amic
s
19.51
1
X4 2
X4 3
500 X4 1
Neural Networks in Detection of Lymph Node Metastases by Immune Factors & Neural Networks in Detection of Lymph Node Metastases by Immune Factors & Tumor Characteristics of Lung Cancer Patients (n=533)Tumor Characteristics of Lung Cancer Patients (n=533)
N0 N1-3 N0 N1-3 N0 N1-3Total 73 194 32 101 43 90Correct 55 159 30 77 34 73Wrong 18 35 2 24 9 17Unknown 0 0 0 0 0 0N0 55 35 30 24 34 17N1-3 18 159 2 77 9 73
T. Back PropagationV. Back PropagationT. Con.Gradient DescV. Con.Gradient DescT. Quasi-newtonV. Quasi-newton
Training Error Graph (Sum-squared)Lung Cancer Patients with Stage I-IV (T1-4N0-3M0-1), n=533
Neural Network (Linear): Immune System---Lymph Node Metastases
Epoch
Erro
r
0.0
0.2
0.4
0 100 200 300 400 500
ROC
Receiver Operating Characteristic (ROC) curveLung Cancer Patients with Stage I-IV (T1-4N0-3M0-1), n=533
Neural Network (Linear): Immune System---Lymph Node Metastases
1-Specificity
Sens
itivi
ty
0.0
0.5
1.0
0.0 0.5 1.0
T. Levenberg-MarquarV. Levenberg-MarquarT. Quick PropagationV. Quick PropagationT. Delta Bar DeltaV. Delta Bar Delta
Training Error Graph (Sum-squared)Lung Cancer Patients with Stage I-IV (T1-4N0-3M0-1), n=533
Neural Network (Linear): Immune System---Lymph Node Metastases
Epoch
Erro
r
0.0
0.2
0.4
0.6
0.8
0 100 200 300 400 500
Neural Networks in Detection of Lymph Node Metastases by Immune Neural Networks in Detection of Lymph Node Metastases by Immune Factors of Lung Cancer Patients (n=533)Factors of Lung Cancer Patients (n=533)
N0 N1-3 N0 N1-3 N0 N1-3 Total 69 198 28 105 51 82 Correct 59 159 21 78 34 59 Wrong 10 39 7 27 17 23 Unknown 0 0 0 0 0 0 N0 59 39 21 27 34 23 N1-3 10 159 7 78 17 59
Training Error Graph (Sum-squared)
Lung Cancer Patients with Stage I-IV (t1-4N0-3M0-1), n=533
Neural Network (Linear): Immune System---Lymph Node Metastases
Epoch
Err
or
0.0
0.2
0.4
0.6
0.8
0 100 200 300 400 500 600
T. Back PropagationV. Back PropagationT. Levenberg-MarquarV. Levenberg-MarquarT. Quick PropagationV. Quick PropagationT. Delta Bar DeltaV. Delta Bar Delta
ROC
Receiver Operating Characteristic (ROC) curveLung Cancer Patients with Stage I-IV (T1-4N0-3M0-1), n=533
Neural Network (Linear): Immune System---Lymph Node Metastases
1-Specificity
Sens
itivi
ty
0.0
0.5
1.0
0.0 0.5 1.0 N0N1-3
Cluster Diagram (NO---N1-3)Lung Cancer Patients with Stage I-IV (T1-4N0-3M0-1), n=533
Neural Network (Linear), Layer 1: Immune System---Lymph Node Metastases
T-cell Population
Cel
l Rat
io F
acto
r (L
euco
cyte
s/Can
cer
Cel
ls)
0
10
20
30
40
50
60
0 4 8 12 16
Training & Verification of Neural Networks in Recognition of Lymph Node Training & Verification of Neural Networks in Recognition of Lymph Node Metastases by Immune Factors of Lung Cancer Patients (n=533)Metastases by Immune Factors of Lung Cancer Patients (n=533)
N0 N1-3 N0 N1-3 N0 N1-3 Total 86 247 26 74 36 64 Correct 84 245 15 57 18 55 Wrong 2 2 11 17 18 9 Unknown 0 0 0 0 0 0 N0 84 2 15 17 18 9 N1-3 2 245 11 57 18 55 ---------------------------------------------------------------------------------------------------------------------------------------------- Genetic N0-N1-3 CD4+2H PhN S% Lym% E/CC S/CC M/CC Algorithm Yes Yes Yes Yes Yes Yes Yes Selection Useful T/CC CD4+2H/CC CD1/CC CD8/CC Yes Yes Yes Yes ----------------------------------------------------------------------------------------------------------------------------------------------
Training Error Graph (Sum-squared)Lung Cancer Patients with Stage I-IV (T1-4N0-3M0-1), n=533
Neural Network (PNN): Immune System---N0-N1-3
Epoch
Err
or
0.0
0.2
0.4
0.6
0.8
0 50 100 150 200 250 300
Training by Levenberg-MarquardtVerification by Levenberg-Marquardt
Lung Cancer DynamicsLung Cancer Dynamics
Conclusions:Conclusions: It was revealed that separation of lung cancer
patients with lymph node metastases from patients without metastases significantly depended on:
1) level of immune cell circuit; 2) value of monocyte and macrophage circuit; 3) level of humoral immunity; 4) neutrophils circuit; 5) value of cell ratio factors; 6) lung cancer characteristics.
Address:Address:
Oleg Kshivets, M.D., Ph.D. Thoracic Surgeon Department of Surgery Siauliai Cancer Center Tilzes:42-16, 5400 Siauliai, Lithuania Tel. (37041)416614 [email protected] [email protected] http//:myprofile.cos.com/Kshivets