DISTANT METASTASES OF LUNG DISTANT METASTASES OF LUNG CANCER AND IMMUNE SYSTEMCANCER AND IMMUNE SYSTEM

Oleg Kshivets, MD, PhD Oleg Kshivets, MD, PhD Department of SurgeryDepartment of Surgery

Siauliai Cancer Center, Siauliai, LithuaniaSiauliai Cancer Center, Siauliai, LithuaniaInternational Conference on Lung Cancer “Lung Cancer, Standards International Conference on Lung Cancer “Lung Cancer, Standards

and New Trends”, 22-24 May, 2003, Vilnius, Lithuaniaand New Trends”, 22-24 May, 2003, Vilnius, Lithuania

AbstractAbstract• DISTANT METASTASES OF LUNG CANCER AND IMMUNE SYSTEMDISTANT METASTASES OF LUNG CANCER AND IMMUNE SYSTEM • Oleg Kshivets Dept. of Surgery, Siauliai Cancer Center, Siauliai, LithuaniaOleg Kshivets Dept. of Surgery, Siauliai Cancer Center, Siauliai, Lithuania• Purpose:Purpose: Significance of immune data in terms of detection of lung cancer (LC) patients (LCP) with Significance of immune data in terms of detection of lung cancer (LC) patients (LCP) with

distant metastases was investigated. distant metastases was investigated. • Methods:Methods: In trial (1987-2003) consecutive cases after surgery, monitored 533 LCP (males – 472, In trial (1987-2003) consecutive cases after surgery, monitored 533 LCP (males – 472,

females – 61; age=57.4±0.4 years; females – 61; age=57.4±0.4 years; • pneumonectomies -181, upper lobectomies - 138, lower lobectomies - 67, upper/lower bilobectomies - pneumonectomies -181, upper lobectomies - 138, lower lobectomies - 67, upper/lower bilobectomies -

24, middle lobectomies – 6, segmentectomies – 76, exploratory thoracotomies and biopsies - 41) with 24, middle lobectomies – 6, segmentectomies – 76, exploratory thoracotomies and biopsies - 41) with pathologic stage I-IV (squamous cell LC - 294, adenocarcinoma - 171, large cell LC – 48, small cell LC - pathologic stage I-IV (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, 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 G3 – 279; M0 – 438; M1 - 95) were reviewed. Variables selected for study were input levels of immunity blood parameters (IgG, IgM, IgA, natural antibodies, circulating immune complexes, percentage, absolute blood parameters (IgG, IgM, IgA, natural antibodies, circulating immune complexes, percentage, absolute count and total population number of T-lymphocytes, B-cells, CD4, CD8, K-cells, CD1, CDw26, count and total population number of T-lymphocytes, B-cells, CD4, CD8, K-cells, CD1, CDw26, monocytes, CD4+2H, CD8+VV, CD4/CD8, leukocytes, lymphocytes, polymorphonuclear and monocytes, CD4+2H, CD8+VV, CD4/CD8, leukocytes, lymphocytes, polymorphonuclear and sticknuclear leukocytes, NST-tests, indexes of stimulation of leukocytes, index of thymus function, sticknuclear leukocytes, NST-tests, indexes of stimulation of leukocytes, index of thymus function, phagocytic number, phagocyte index, index of complete phagocytosis), sex, age, TNMG. Differences phagocytic number, phagocyte index, index of complete phagocytosis), sex, age, TNMG. Differences between groups were evaluated using multiple regression analysis, multi-factor clustering, discriminant between groups were evaluated using multiple regression analysis, multi-factor clustering, discriminant analysis, structural equation modeling, Monte Carlo simulation and neural networks computing. analysis, structural equation modeling, Monte Carlo simulation and neural networks computing.

• Results:Results: It was revealed that recognition of LCP with distant metastases (males=76, females=19; It was revealed that recognition of LCP with distant metastases (males=76, females=19; age=56.6±1.0 years; T1-4N1-3M1; tumor size=6.2±0.2 cm; n=95) from LCP without distant metastases age=56.6±1.0 years; T1-4N1-3M1; tumor size=6.2±0.2 cm; n=95) from LCP without distant metastases (males=396, females=42; age=57.6±1.0 years; T1-3N0-3M0, tumor size=5.2±0.1 cm; n=438) (males=396, females=42; age=57.6±1.0 years; T1-3N0-3M0, tumor size=5.2±0.1 cm; n=438) significantly depended on: 1) level of B-cell circuit (P=0.00000); 2) value of K-cell circuit (P=0.0004); 3) significantly depended on: 1) level of B-cell circuit (P=0.00000); 2) value of K-cell circuit (P=0.0004); 3) level of humoral immunity (P=0.033); 4) neutrophils circuit (P=0.00000); 5) value of cell ratio factors level of humoral immunity (P=0.033); 4) neutrophils circuit (P=0.00000); 5) value of cell ratio factors (ratio of LC cell population to immune cell subpopulations in integral LCP organism) (P=0.00000); 6) (ratio of LC cell population to immune cell subpopulations in integral LCP organism) (P=0.00000); 6) LC characteristics (T1-4, N0-3,G1-3, histology, tumor size) (P=0.000000); 7) anthropometric data LC characteristics (T1-4, N0-3,G1-3, histology, tumor size) (P=0.000000); 7) anthropometric data (P=0.004). Correct classification of LCP with M1 from LCP with M0 was 91.8% by logistic regression, (P=0.004). Correct classification of LCP with M1 from LCP with M0 was 91.8% by logistic regression, 88.2% by discriminant analysis and 97.0% by neural by neural networks computing.88.2% by discriminant analysis and 97.0% by neural by neural networks computing.

The Main Characteristics of The Study PopulationsThe Main Characteristics of The Study Populations• Lung Cancer Patients……………………..Lung Cancer Patients……………………..533533 • Age=Age=57.457.40.4 0.4 years;years; Male=Male=472472; Female=; Female=6161

• Lung Cancer Patients with M0..................Lung Cancer Patients with M0..................438438• Age=Age=57.657.61.01.0 years; Male= years; Male=396396; Female=; Female=4242• Tumor Size= Tumor Size= 5.25.20.1 0.1 cmcm

• Lung Cancer Patients with M1……………Lung Cancer Patients with M1……………9595• Age=Age=56.656.61.01.0 years; Male= years; Male=7676; Female=; Female=1919• Tumor Size= Tumor Size= 6.26.20.20.2 cm cm

ProceduresProcedures• Pneumonectomy…………………….………..Pneumonectomy…………………….………..181181• Upper Lobectomy…….……………………...Upper Lobectomy…….……………………...138138• Lower Lobectomy.…………….………............Lower Lobectomy.…………….………............6767• Upper/Lower Bilobectomy……………………Upper/Lower Bilobectomy……………………2424• Middle Lobectomy……………..……….………Middle Lobectomy……………..……….………66• Segmentectomy.……………………………….Segmentectomy.……………………………….7676• Exploratory Thoracotomy, Biopsy..………….Exploratory Thoracotomy, Biopsy..………….4141 • Combined & Extensive Procedures with Resection of Combined & Extensive Procedures with Resection of

Pericardium, Left Atrium, Aorta, V.Cava Superior, Pericardium, Left Atrium, Aorta, V.Cava Superior, V.Azygos, Carina, Trachea, Diaphragm, Chest Wall, Ribs, V.Azygos, Carina, Trachea, Diaphragm, Chest Wall, Ribs, etc. …………..etc. …………..5555

Lung Cancer Patients Lung Cancer Patients CharacteristicsCharacteristics

• Squamous Cell…...Squamous Cell…...294294• Adenocarcinoma....Adenocarcinoma....171171• Large Cell….………Large Cell….………4848• Small Cell………….Small Cell………….2020• T1.………….……..T1.………….……..116116• T2…………………T2…………………168168• T3…………………T3…………………125125• T4…………………T4…………………124124

• N0…………………N0…………………148148• N1…….…………...N1…….…………...144144• N2…………….…...N2…………….…...159159• N3………………..…N3………………..…8282• G1……………….….G1……………….….8888• G2………………....G2………………....166166• G3………………....G3………………....279279• M0………………...M0………………...438438• M1………………….M1………………….9595

Immune Testing:Immune Testing:

Table 1. Factors of T-, B- and K-cell Circuit between LCP with M0 (n=438) and Table 1. Factors of T-, B- and K-cell Circuit between LCP with M0 (n=438) and LCP with M1 (n=95) in terms of Detection of Distant MetastasesLCP with M1 (n=95) in terms of Detection of Distant Metastases

Mean

LCP, M0 n=438

Mean LCP,M1

N=95 t-value df p

Std.Dev. LCP,M0

n=438

Std.Dev. LCP,M1

N=95 Tumor Size (cm) 5,239726 6,215789 -3,72159 531 0,000219 2,396178 1,908342

CDw26+ (%) 5,605023 8,105263 -3,20919 531 0,001412 6,667430 7,810895 CDw26+(abs) 0,090411 0,130842 -2,70226 531 0,007107 0,127010 0,154036

IS2 1,680274 2,128421 -2,30640 531 0,021473 1,532526 2,393994 IgM 1,586963 1,721895 -2,07756 531 0,038230 0,537765 0,718151

Eosinophils (abs) 0,201237 0,286726 -2,11400 531 0,034981 0,193518 0,739662 CDw26+(tot) 0,440413 0,617791 -2,36629 531 0,018325 0,645086 0,737137

Leucocytes/Cancer Cells 7,506118 5,301781 3,38944 531 0,000752 6,182328 2,972705 Segm.Neutrophils/Cancer Cells 4,729750 3,460669 3,17607 531 0,001580 3,776131 2,029899

Lymphocytes/Cancer Cells 2,191886 1,389798 2,94362 531 0,003386 2,616236 0,960459 Monocytes/Cancer Cells 0,258301 0,178361 2,14404 531 0,032483 0,348875 0,217287

T-cells/Cancer Cells 1,130815 0,711234 3,45057 531 0,000604 1,150247 0,608045 B-cells/Cancer Cells 0,433972 0,253099 2,26493 531 0,023919 0,773206 0,181743 K-cells/Cancer Cells 0,664727 0,415835 2,11953 531 0,034509 1,136055 0,284653

CD4+2H+/Cancer Cells 0,687676 0,444601 2,99092 531 0,002910 0,764786 0,440009 CD8+VV+/Cancer Cells 0,692672 0,460807 2,33704 531 0,019808 0,929459 0,569794

CD8+/Cancer Cells 0,285175 0,180585 2,57284 531 0,010357 0,387765 0,172482 CD4+/Cancer Cells 0,909451 0,576432 3,28217 531 0,001098 0,950611 0,582158

Table 2. Results of Logistic Regression Modeling in Recognition of Table 2. Results of Logistic Regression Modeling in Recognition of LCP with Distant Metastases (n=95) from LCP with M0 (n=438)LCP with Distant Metastases (n=95) from LCP with M0 (n=438)

Variables in the Equation

-.309 .142 4.763 1 .029 .734 .556 .969-2.202 1.070 4.233 1 .040 .111 .014 .901

47.923 4 .000-6.452 1.310 24.256 1 .000 .002 .000 .021-3.450 .634 29.571 1 .000 .032 .009 .110-1.758 .458 14.738 1 .000 .172 .070 .4239.580 4.058 5.572 1 .018 14470.437 5.082 4.1E+07.064 .025 6.675 1 .010 1.066 1.015 1.118

-.118 .059 3.979 1 .046 .888 .791 .998.102 .043 5.608 1 .018 1.107 1.018 1.204.061 .029 4.414 1 .036 1.063 1.004 1.125.194 .094 4.263 1 .039 1.214 1.010 1.460

-.897 .382 5.514 1 .019 .408 .193 .862.606 .277 4.784 1 .029 1.833 1.065 3.153

1.399 .713 3.852 1 .050 4.051 1.002 16.3791.511 .726 4.328 1 .037 4.530 1.091 18.8052.966 2.309 1.651 1 .199 19.422

Tumor SizeT1N0-N3N0N2N3T-cells (abs)CDw26+cells (%)CD1+cells (%)B-cells (%)NST-spont.IS-2ICPIgMCD1+cells (tot)CD8+VV+/Cancer CellsConstant

Step1

B S.E. Wald df P Exp(B) Lower Upper95.0% C.I.for EXP(B)

Table 3. Results of Discriminant Analysis in Recognition of LCP Table 3. Results of Discriminant Analysis in Recognition of LCP with Distant Metastases (n=95) from LCP with M0 (n=438)with Distant Metastases (n=95) from LCP with M0 (n=438)

Discriminant Analysis: LCP with M1 (n=95)---LCP with M0 (n=438)

,975 13,850 1 531 ,000,981 10,299 1 531 ,001,986 7,302 1 531 ,007,992 4,316 1 531 ,038,992 4,469 1 531 ,035,990 5,600 1 531 ,018,979 11,488 1 531 ,001,981 10,087 1 531 ,002,984 8,665 1 531 ,003,991 4,595 1 531 ,033,978 11,906 1 531 ,001,990 5,131 1 531 ,024,992 4,493 1 531 ,034,983 8,951 1 531 ,003,990 5,463 1 531 ,020,988 6,620 1 531 ,010,980 10,773 1 531 ,001

Tumor Size (cm)CDw26+cells (%)CDw26-cells (abs)IgMEosinophils (abs)CDw26+cells (tot)Leucocytes/Lung Cancer CellsSegmented Neutrophils/Lung Cancer CellsLymphocytes/Lung Cancer CellsMonocytes/Lung Cancer CellsT-cells/Lung Cancer CellsB-cells/Lung Cancer CellsK-cells/Lung Cancer CellsCD4+2H+cells/Lung Cancer CellsCD8+VV+cells/Lung Cancer CellsCD8/Lung Cancer CellsCD4/Lung Cancer Cells

Wilks'Lambda F

df1

df2 P

Results of Discriminant Analysis in Detection Results of Discriminant Analysis in Detection Lung Cancer Distant Metastases (n=533)Lung Cancer Distant Metastases (n=533)

6,005,50

5,004,50

4,003,50

3,002,50

2,001,50

1,00,500,00

-,50-1,00

Canonical Discriminant Function 1

MTS = 130

20

10

0

Std. Dev = 1,05

Mean = ,92

N = 95,00

3,252,75

2,251,75

1,25,75,25-,25

-,75-1,25

-1,75-2,25

-2,75-3,25

-3,75

Canonical Discriminant Function 1

MTS = 060

50

40

30

20

10

0

Std. Dev = ,99

Mean = -,20

N = 438,00

Results of General Discriminant Analysis in Detection Lung Cancer Distant Metastases (n=533)Results of General Discriminant Analysis in Detection Lung Cancer Distant Metastases (n=533)

General Discriminant AnalysisIg M vs. I g A vs. M0 -- M1

(Analysis sample)

0,8 0,6 0,4 0,2

General Discriminant AnalysisT-cell Population vs. B-cell Population vs. M0--M1

(Analysis sample)

2,5 2 1,5 1 0,5 0 -0,5

General Discriminant AnalysisCD8 vs. CD4 vs. M0--M1

(Analysis sample)

1,4 1,2 1 0,8 0,6 0,4 0,2

General Discriminant Analysis S egmented Neutrophils vs. E osinophils vs. M0 -- M1

(Analysis sample)

4 3 2 1 0

Classification of Lung Cancer Patients Classification of Lung Cancer Patients with M0 with M0 (n=(n=438438) ) from from Lung Cancer Lung Cancer Patients with Patients with M1 M1 (n=(n=9595))

• Classification of Cases by Logistic RegressionClassification of Cases by Logistic Regression• Observed Observed Pred.LC Pred.LC M0M0 Pred. Pred.LCLCPP M1 M1 CorrectCorrect• LCPLCP with M0 with M0 425 425 13 13 9797..00%%• LCP with M1LCP with M1 3300 65 65 6868..44%%• Total Total 455 78 455 78 91.8%91.8%• Classification of Cases by Discriminant AnalysisClassification of Cases by Discriminant Analysis• Observed Observed Pred.LC Pred.LC M0M0 Pred. Pred.LCLCPP M1 M1 CorrectCorrect• LCPLCP with M0 with M0 415 415 23 23 9494..77%%• LCP with M1LCP with M1 40 40 55 55 5757..99%%• Total Total 455 78 455 78 88.2%88.2% • Classification of Cases by Classification of Cases by General General Discriminant AnalysisDiscriminant Analysis• Observed Observed Pred.LC Pred.LC M0M0 Pred. Pred.LCLCPP M1 M1 CorrectCorrect• LCPLCP with M0 with M0 425 425 13 13 9797..00%%• LCP with M1LCP with M1 18 18 77 77 8181..11%%• Total Total 443 90 443 90 94.2%94.2%

T-cell & B-cell Circuit in T-cell & B-cell Circuit in Detection of LungDetection of Lung CancerCancer Distant Distant Metastases (n=533)Metastases (n=533)

CD8-cell & CD4-cell Circuit in CD8-cell & CD4-cell Circuit in Detection of Detection of LungLung Cancer Cancer Distant Distant Metastases (n=533)Metastases (n=533)

Monocyte & Lymphocyte Circuit in Monocyte & Lymphocyte Circuit in Detection Detection of Lungof Lung Cancer Cancer Distant Distant Metastases (n=533)Metastases (n=533)

CDw26-cell & K-cell Circuit in CDw26-cell & K-cell Circuit in Detection of Detection of LungLung Cancer Cancer Distant Distant Metastases (n=533)Metastases (n=533)

Segmented Neutrophil & Eosinophil Circuit in Segmented Neutrophil & Eosinophil Circuit in Detection Detection of Lungof Lung Cancer Cancer Distant Distant Metastases (n=533)Metastases (n=533)

IgM & T-cells/Cancer Cells Ratio in IgM & T-cells/Cancer Cells Ratio in Detection Detection of Lungof Lung Cancer Cancer Distant Distant Metastases (n=533)Metastases (n=533)

CCirculate Immune Complexes and irculate Immune Complexes and Leucocytes/Cancer Cells Ratio in Leucocytes/Cancer Cells Ratio in Detection of LungDetection of Lung

CancerCancer Distant Distant Metastases (n=533)Metastases (n=533)

Results of Multi-Factor Clastering of Immune Factors in Detection Results of Multi-Factor Clastering of Immune Factors in Detection of Lung Cancer Distant Metastases (n=533)of Lung Cancer Distant 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 Networks in Detection of Lung SEPATH Networks in Detection of Lung Cancer Distant Metastases (n=533)Cancer Distant Metastases (n=533)

Neural Networks in Recognition of LCP with M1 (n=95) from LCP with M0 (n=438)Neural Networks in Recognition of LCP with M1 (n=95) from LCP with M0 (n=438)

• M0M0 M1M1 Baseline Errors=0.091Baseline Errors=0.091• TotalTotal 438438 95 95 Correct Classification=97%Correct Classification=97%

• CorrectCorrect 436436 92 92 Area Under ROC Curve=0.978Area Under ROC Curve=0.978• WrongWrong 2 2 3 3• UnknownUnknown 0 0 0 0• M0M0 436436 3 3• M1M1 2 2 92 92 Genetic Algorithm SelectionGenetic Algorithm Selection• Useful for M1Useful for M1 D N T CD4+2H(abs,t) CDw26(%,abs,t) CD8+VV(%,abs,t) CD4(abs) D N T CD4+2H(abs,t) CDw26(%,abs,t) CD8+VV(%,abs,t) CD4(abs) • Recognition Recognition Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes • IS-2 PI ICP IgA Weight E(abs,t) SN(t) B (t)IS-2 PI ICP IgA Weight E(abs,t) SN(t) B (t)• Yes Yes Yes Yes Yes Yes Yes YesYes Yes Yes Yes Yes Yes Yes Yes

M0M1

Cluster DiagramRecognition LCP with M1 (n=95) from LCP with M0 (n=438)

Neural Network (MLP): Error=0.091;Area Under ROC Curve=0.978; Correct Classification Rate=0.97

Tumor Size (cm)

B-ce

lls (%

)

0

10

20

30

40

50

0 2 4 6 8 10 12 14 16

Optimal Neural Networks in Recognition of LCP with M1 (n=95) from LCP with M0 Optimal Neural Networks in Recognition of LCP with M1 (n=95) from LCP with M0 (n=438)(n=438)

• M0M0 M1M1 Baseline Errors=0.000018Baseline Errors=0.000018• TotalTotal 438438 95 95 Correct Classification=100%Correct Classification=100% • CorrectCorrect 438438 95 95 Area Under ROC Curve=1.00Area Under ROC Curve=1.00• WrongWrong 00 00• UnknownUnknown 00 00• M0M0 438438 00• M1M1 00 9595

• Genetic Algorithm SelectionGenetic Algorithm Selection• Useful for M1Useful for M1 N G T CDw26(%) CDw26(abs) B(%) IS-2 PhN ICP Weight StN/CCN G T CDw26(%) CDw26(abs) B(%) IS-2 PhN ICP Weight StN/CC• Recognition Recognition Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes YesYes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

M0M1

Cluster DiagramRecognition LCP with M1 (n=95) from LCP with M0 (n=438)

Neural Network (MLP)

T-cells (%)

B-ce

lls (%

)

0

10

20

30

40

50

10 20 30 40 50 60 70 80 90 100

Training Error Graph (Sum-squared)Recognition LCP with M1 (n=95) from LCP with M0 (n=438)

Neural Network (MLP):Error=0.0000118; Area Under ROC Curve=1.00;Correct Classification Rate=1.00

Epoch

Erro

r

0.0

0.2

0.4

0.6

0 100 200 300 400 500 600 700

Train by Levenberg-Marquardt

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

0.01 0.1 1 10 100

0.1

10

100

Early LCLC with T1-4N0M0LC with T1-4N1-3M0LC with T1-4N0-3M1

Model "Distant MTS---Cytotoxic K-cells"

Lung Cancer Cell Population

Cyt

otox

ic K

-cel

l Pop

ulat

ions X1 3

X2 3

X3 3

X4 3

X1 2 X2 2

X3 2 X4 2

LC with T1-4N0-3M0LC with T1-4N0-3M1

Model "Distant MTS---Cytotoxic K-cells"

Time

Cel

l Pop

ulat

ion

Dyn

amic

s

X1 2

X1 3

X1 1

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

0.1 1 10 100

0.1

10

Early Lung CancerLC with T1-4N0M0LC with T1-4N0-3M0LC with T1-4N0-3M1

Model "Distant MTS ---Cytotoxic K-cells"

Lung Cancer Cell Population

Cyt

ooto

xic

K-c

ell P

opul

atio

ns X1 3

X2 3

X3 3

X4 3

X1 2 X2 2

X3 2 X4 2

0.1 1 10 1000.1

1

10

100

LC with T1-4N0-3M0LC with T1-4N0-3M1

Model "Distant MTS---Cytotoxic K-cells"

Time

Cel

l Pop

ulat

ion

Dyn

amic

s

X4 2

X4 3

X4 1

Lung Cancer DynamicsLung Cancer Dynamics

SUPERONCOIMMUNOLOGY-1.0

IMMUNODIAGNOSIS-1 IMMUNODIAGNOSIS-2

IMMUNODEFICIENCY NORMMALIGNANT NEOPLASM

POPULATION PHASE TRANSITION IMMUNOSTAGING

N M G

EARLY CANCER INVASIVE CANCER

Conclusions:Conclusions:• It was revealed that recognition of lung cancer patients with It was revealed that recognition of lung cancer patients with

distant metastases from lung cancer patients without distant distant metastases from lung cancer patients without distant metastases significantly depended on: metastases significantly depended on:

• 1) level of B-cell circuit; 1) level of B-cell circuit; • 2) value of K-cell circuit; 2) value of K-cell circuit; • 3) level of humoral immunity; 3) level of humoral immunity; • 4) neutrophils circuit; 4) neutrophils circuit; • 5) value of cell ratio factors (ratio of cancer cell population to 5) value of cell ratio factors (ratio of cancer cell population to

immune cell subpopulations in integral patient organism); immune cell subpopulations in integral patient organism); • 6) lung cancer characteristics (T1-4, N0-3,G1-3, histology, tumor 6) lung cancer characteristics (T1-4, N0-3,G1-3, histology, tumor

size); size); • 7) anthropometric data. 7) anthropometric data.

• Correct classification of lung cancer patients with M1 from lung Correct classification of lung cancer patients with M1 from lung cancer patients with M0 was 91.8% by logistic regression, 88.2% cancer patients with M0 was 91.8% by logistic regression, 88.2% by discriminant analysis and 97.0% by neural by neural by discriminant analysis and 97.0% by neural by neural networks computing.networks computing.

Patents:Patents: Kshivets O.Kshivets O. Method of Immunodiagnosis ofMethod of Immunodiagnosis of

Distant Metastases of OncopatientsDistant Metastases of Oncopatients.. Patent from 06.10.95.-N2107295.-8pp. Patent from 06.10.95.-N2107295.-8pp. Kshivets O.Kshivets O. Method of Immunodiagnosis of Method of Immunodiagnosis of

Generalization of OncopatientsGeneralization of Oncopatients.. Patent from 09.10.95.-N2107294.-12pp. Patent from 09.10.95.-N2107294.-12pp.

• Oleg Kshivets, M.D., Ph.D. Oleg Kshivets, M.D., Ph.D. Thoracic/Abdominal Surgeon, Department of SurgeryThoracic/Abdominal Surgeon, Department of Surgery

• Siauliai Cancer Center, Tilzes:42-16, LT5400 Siauliai, LithuaniaSiauliai Cancer Center, Tilzes:42-16, LT5400 Siauliai, Lithuania• Tel. (37041)416614; Fax (37041)526430Tel. (37041)416614; Fax (37041)526430

• okshivets@yahoo.comokshivets@yahoo.com kshivets@hotmail.comkshivets@hotmail.com• http//:myprofile.cos.com/Kshivetshttp//:myprofile.cos.com/Kshivets