Kshivets O. Lung Cancer Surgery

LYMPH NODE METASTASES OF LUNG CANCER AND IMMUNE SYSTEM Oleg Kshivets, MD, PhD Siauliai Cancer Center, Siauliai, Lithuania The Second International Chicago Symposium on Malignancies of The Chest and Head & Neck Chicago, Illinois, The USA, 2001

Abstract: LYMPH NODE METASTASES OF LUNG CANCER AND IMMUNE SYSTEM 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=57.40.4 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 Study Populations
Lung Cancer Patients (males – 472, females – 61; age=57.4  0.4 years) … .. 533
Stage I…………..……………………... 48
Stage II…………………..…………….. 47
Stage III………………………………. 321
Stage IV………………………………. 117

Procedures (n=533)
Pneumonectomy……………………… 181
Upper Lobectomy……………………. 138
Lower Lobectomy.…………………….. 67
Upper/Lower Bilobectomy…….……… 24
Middle Lobectomy……………………… 6
Segmentectomy.……………………..… 76
Exploratory 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 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:

Significant Immune Data in Detection of Lung Cancer Lymph Node Metastases (n=533)

Results of Logistic Regression Modeling in Detection of Lymph Node Metastases of Lung Cancer (n=533)

Correlation between Lymph Node Metastasis & Lung Cancer Characteristics (n=533)

T- & B-cell Circuit in Detection of Lung Cancer Lymph Node Metastases (n=533)

CD8- & CD4-cell Circuit in Detection of Lung Cancer Lymph Node Metastases (n=533)

Lymphocytes & Monocytes Circuit in Detection of Lung Cancer Lymph Node Metastases (n=533)

K-cells Circuit & Cancer Cells Number in Detection of Lung Cancer Lymph Node Metastases (n=533)

Segmented Neutrophils & CD4+2H-cells Circuit in Detection of Lung Cancer Lymph Node Metastases (n=533)

Cancer Cells Number & G1-3 in Detection of Lung Cancer Lymph Node Metastases (n=533)

Humoral Immunity in Detection of Lung Cancer Lymph Node Metastases (n=533)

Cancer Cells Number & Lymphocytes in Detection of Lung Cancer Lymph Node Metastases (n=533)

Role of Cell Ratio Factors in Lymph Node Metastases of Lung Cancer (n=533)

Results of Multi-Factor Clastering of Immune Factors in Detection of Lung Cancer Lymph Node Metastases (n=533)

Networks between Factors of Immune Cell and Humoral Circuit and LC Characteristics (n=533)

SEPATH Modeling of System Lumph Node Metastases--Immune System of Lung Cancer Patients (n=533)

Results of Monte Carlo Simulation (n=533)

Immune Networks in Detection of Lymph Node Metastasis in Lung Cancer Patients (n=533)

Lotka-Volterra Models of Lung Cancer Cell Population and Cytotoxic Cell Population Dynamics

Holling-Tenner Models of Lung Cancer Cell Population and Cytotoxic Cell Population Dynamics

Neural Networks in Detection of Lymph Node Metastases by Immune Factors & Tumor Characteristics of Lung Cancer Patients (n=533) N0 N1-3 N0 N1-3 N0 N1-3 Total 73 194 32 101 43 90 Correct 55 159 30 77 34 73 Wrong 18 35 2 24 9 17 Unknown 0 0 0 0 0 0 N0 55 35 30 24 34 17 N1-3 18 159 2 77 9 73

Neural Networks in Detection of Lymph Node Metastases by Immune 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 & Verification of Neural Networks in Recognition of Lymph Node 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
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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
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Lung Cancer Dynamics

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:
Oleg Kshivets, M.D., Ph.D.
Thoracic Surgeon
Department of Surgery
Siauliai Cancer Center
Tilzes:42-16, 5400 Siauliai, Lithuania
Tel. (37041)416614
[email_address] [email_address]
http//:myprofile.cos.com/Kshivets

Kshivets O. Lung Cancer Surgery

by Oleg Kshivets

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