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PRECISE EARLY DETECTION OF LUNG CANCER AND IMMUNE CIRCUIT
Oleg Kshivets
Kaluga Cancer Center, Russia,
nd SSO Annual Cancer Symposium, March 12-16, 2014, Phoenix, AZ, the USA
67
Bootstrap Simulation: n=450

Number of Samples=3333

Early Lung Cancer=48; Norm=120;

Kendall Tau-A

Error=0.0: Area Under ROC Curve=1.0; n=450):

P<

Rank Sensitivit
y

Monocytes

Rank

Neural Networks Simulation (Correct Classification=100%;

1

1496.65

Objective: Significance of immune circuit in terms of early detection of lung cancer (LC) was inestigated.

Non-Malignant Pathology =282

Methods: In trial (1987-2013) consecutive cases after surgery, monitored 48 LC patients (LCP) (m=40, f=8;
lobectomies=48) with pathologic stage IA (tomor size=1.6±0.4 cm; squamous=21, adenocarcinoma=25,
large cell=2; T1N0M0=48; G1=16, G2=21, G3=11, 5-year survival=100%), 282 patients with lung nonmalignant pathology (NMP) (m=188, f=94; pneumonectomies=5, lobectomies=179, segmentectomies=98;
non-malignant tumors=100; abscess=112; tuberculoma=70) and 120 healthy donors (HD) (m=69, f=51)
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 discriminant analysis, clustering, nonlinear
estimation, structural equation modeling, Monte Carlo, bootstrap simulation and neural networks
computing.

B-Cells

1

-0.041

0.05

CD4+2H+Cells

2

1369.02

Segmented Neutrophils

2

-0.041

0.05

B-cells

3

1354.34

Leucocytes

3

-0.040

0.05

CD8+VV+Cells

4

1340.32

CD8+VV+Cells

4

-0.034

0.05

CD4+Cells

5

545.32

Monocytes

5

-0.028

0.05
CD16+Cells

6

348.67

Results: It was revealed that early detection of LC from NMP and HD (n=402) significantly depended on:
CD4+2H, CD8+VV, CD4, B, CD16, monocytes (P=0.017-0.000).
Neural networks computing, genetic algorithm selection and bootstrap simulation revealed
relationships of early detection of LC and monocytes (rank=1), CD4+2H (rank=2), CD19 (3), CD8+VV (4),
CD4 (5), CD16 (6).
Correct detection of early LCP was 100% by neural networks computing (error=0.000; area under ROC
curve=1.0).

P=0.023

T

P

r^2=0.039149654 DF Adj r^2=0.019495897 FitStdErr=0.30565814 Fstat=2.246057
a=0.64898982 b=0.19674838 c=-0.060515312 d=0.0044941272 e=-9.6163077e-05
f=0.10192687 g=-0.018714273 h=0.0012173861 i=-2.3777096e-05

-2.70302

0.007132

Monocytes

-3.07382

0.002242

B-cells

-4.32866

0.000019

CD16+cells

-2.23547

0.025879

CD8+VV+cells

-2.09551

-2.94928

1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
17.5 15 2.5 0
1
1 7.5
T-Cells

5 2.5

1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
15 0
10 12.5
ls
5 7.5
+Cel
2.5
8+VV
0 0
CD

0.036687

Leucocytes

Early Cancer---NMP, HD

Segmented Neutrophils

Early Cancer---NMP, HD

Significant Factors:

z=a+b/x+c/x^2+d/x^3+e/x^4+fy+gy^2+hy^3+iy^4

0.003352

Discriminant Function Analysis Summary No. of vars in model: 10; Wilks' Lambda:
.89179 approx. F (10,439)=5.3266 p< .0000
Wilks' - Lambda

P

CD4+Cells

0.902078

0.024945

CD8+VV+Cells

0.902549

0.021866

CD4+2H+Cells

0.903516

0.016712

B-Cells

0.939965

0.000002

T-Cells

0.909554

0.003277

Monocytes

0.910621

0.002473

Lymphocytes

0.905700

0.009192

Stimulation Index by Staphylococcus aureus

0.903661

0.016058

NST stimulated by Staphylococcus aureus

0.907671

0.005407

NST spontaneous

0.901417

0.030056

Poster #331
PRECISE EARLY DETECTION OF LUNG CANCER AND IMMUNE CIRCUIT
Oleg Kshivets

Conclusion: Early detection of LC from NMP and HD significantly depended on immune cell circuit.

Poster #331

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PRECISE EARLY DETECTION OF LUNG CANCER AND IMMUNE CIRCUIT

  • 1. PRECISE EARLY DETECTION OF LUNG CANCER AND IMMUNE CIRCUIT Oleg Kshivets Kaluga Cancer Center, Russia, nd SSO Annual Cancer Symposium, March 12-16, 2014, Phoenix, AZ, the USA 67 Bootstrap Simulation: n=450 Number of Samples=3333 Early Lung Cancer=48; Norm=120; Kendall Tau-A Error=0.0: Area Under ROC Curve=1.0; n=450): P< Rank Sensitivit y Monocytes Rank Neural Networks Simulation (Correct Classification=100%; 1 1496.65 Objective: Significance of immune circuit in terms of early detection of lung cancer (LC) was inestigated. Non-Malignant Pathology =282 Methods: In trial (1987-2013) consecutive cases after surgery, monitored 48 LC patients (LCP) (m=40, f=8; lobectomies=48) with pathologic stage IA (tomor size=1.6±0.4 cm; squamous=21, adenocarcinoma=25, large cell=2; T1N0M0=48; G1=16, G2=21, G3=11, 5-year survival=100%), 282 patients with lung nonmalignant pathology (NMP) (m=188, f=94; pneumonectomies=5, lobectomies=179, segmentectomies=98; non-malignant tumors=100; abscess=112; tuberculoma=70) and 120 healthy donors (HD) (m=69, f=51) 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 discriminant analysis, clustering, nonlinear estimation, structural equation modeling, Monte Carlo, bootstrap simulation and neural networks computing. B-Cells 1 -0.041 0.05 CD4+2H+Cells 2 1369.02 Segmented Neutrophils 2 -0.041 0.05 B-cells 3 1354.34 Leucocytes 3 -0.040 0.05 CD8+VV+Cells 4 1340.32 CD8+VV+Cells 4 -0.034 0.05 CD4+Cells 5 545.32 Monocytes 5 -0.028 0.05 CD16+Cells 6 348.67 Results: It was revealed that early detection of LC from NMP and HD (n=402) significantly depended on: CD4+2H, CD8+VV, CD4, B, CD16, monocytes (P=0.017-0.000). Neural networks computing, genetic algorithm selection and bootstrap simulation revealed relationships of early detection of LC and monocytes (rank=1), CD4+2H (rank=2), CD19 (3), CD8+VV (4), CD4 (5), CD16 (6). Correct detection of early LCP was 100% by neural networks computing (error=0.000; area under ROC curve=1.0). P=0.023 T P r^2=0.039149654 DF Adj r^2=0.019495897 FitStdErr=0.30565814 Fstat=2.246057 a=0.64898982 b=0.19674838 c=-0.060515312 d=0.0044941272 e=-9.6163077e-05 f=0.10192687 g=-0.018714273 h=0.0012173861 i=-2.3777096e-05 -2.70302 0.007132 Monocytes -3.07382 0.002242 B-cells -4.32866 0.000019 CD16+cells -2.23547 0.025879 CD8+VV+cells -2.09551 -2.94928 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 17.5 15 2.5 0 1 1 7.5 T-Cells 5 2.5 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 15 0 10 12.5 ls 5 7.5 +Cel 2.5 8+VV 0 0 CD 0.036687 Leucocytes Early Cancer---NMP, HD Segmented Neutrophils Early Cancer---NMP, HD Significant Factors: z=a+b/x+c/x^2+d/x^3+e/x^4+fy+gy^2+hy^3+iy^4 0.003352 Discriminant Function Analysis Summary No. of vars in model: 10; Wilks' Lambda: .89179 approx. F (10,439)=5.3266 p< .0000 Wilks' - Lambda P CD4+Cells 0.902078 0.024945 CD8+VV+Cells 0.902549 0.021866 CD4+2H+Cells 0.903516 0.016712 B-Cells 0.939965 0.000002 T-Cells 0.909554 0.003277 Monocytes 0.910621 0.002473 Lymphocytes 0.905700 0.009192 Stimulation Index by Staphylococcus aureus 0.903661 0.016058 NST stimulated by Staphylococcus aureus 0.907671 0.005407 NST spontaneous 0.901417 0.030056 Poster #331
  • 2. PRECISE EARLY DETECTION OF LUNG CANCER AND IMMUNE CIRCUIT Oleg Kshivets Conclusion: Early detection of LC from NMP and HD significantly depended on immune cell circuit. Poster #331