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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 ,[object Object],[object Object],[object Object],[object Object],[object Object]
Procedures (n=533) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Lung Cancer Patients Characteristics (n=533) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
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) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Training & Verification of Neural Networks in Recognition of Lymph Node Metastases by Immune Factors of Lung Cancer Patients (n=533)   ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Lung Cancer Dynamics
Conclusions: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Address: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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Kshivets O. Lung Cancer Surgery

  • 1. 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
  • 2. 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
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  • 7. Significant Immune Data in Detection of Lung Cancer Lymph Node Metastases (n=533)
  • 8. Results of Logistic Regression Modeling in Detection of Lymph Node Metastases of Lung Cancer (n=533)
  • 9. Correlation between Lymph Node Metastasis & Lung Cancer Characteristics (n=533)
  • 10. T- & B-cell Circuit in Detection of Lung Cancer Lymph Node Metastases (n=533)
  • 11. CD8- & CD4-cell Circuit in Detection of Lung Cancer Lymph Node Metastases (n=533)
  • 12. Lymphocytes & Monocytes Circuit in Detection of Lung Cancer Lymph Node Metastases (n=533)
  • 13. K-cells Circuit & Cancer Cells Number in Detection of Lung Cancer Lymph Node Metastases (n=533)
  • 14. Segmented Neutrophils & CD4+2H-cells Circuit in Detection of Lung Cancer Lymph Node Metastases (n=533)
  • 15. Cancer Cells Number & G1-3 in Detection of Lung Cancer Lymph Node Metastases (n=533)
  • 16. Humoral Immunity in Detection of Lung Cancer Lymph Node Metastases (n=533)
  • 17. Cancer Cells Number & Lymphocytes in Detection of Lung Cancer Lymph Node Metastases (n=533)
  • 18. Role of Cell Ratio Factors in Lymph Node Metastases of Lung Cancer (n=533)
  • 19. Results of Multi-Factor Clastering of Immune Factors in Detection of Lung Cancer Lymph Node Metastases (n=533)
  • 20. Networks between Factors of Immune Cell and Humoral Circuit and LC Characteristics (n=533)
  • 21. SEPATH Modeling of System Lumph Node Metastases--Immune System of Lung Cancer Patients (n=533)
  • 22. Results of Monte Carlo Simulation (n=533)
  • 23. Immune Networks in Detection of Lymph Node Metastasis in Lung Cancer Patients (n=533)
  • 24. Lotka-Volterra Models of Lung Cancer Cell Population and Cytotoxic Cell Population Dynamics
  • 25. Holling-Tenner Models of Lung Cancer Cell Population and Cytotoxic Cell Population Dynamics
  • 26. 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
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