1) The study investigated the significance of the immune system in the early detection of lung cancer by analyzing blood samples from 48 early-stage lung cancer patients, 282 patients with non-malignant lung conditions, and 120 healthy individuals. 2) Statistical analysis revealed that early detection of lung cancer depended significantly on levels of certain immune cells like CD4+2H, CD8+VV, CD4, B cells, CD16, and monocytes. 3) Neural network modeling correctly classified all lung cancer cases based on levels of monocytes, CD4+2H, B cells, CD8+VV, CD4, and CD16 in blood samples.

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