WO2018221820A1 - Procédé pour évaluer l'immunité et fournir des informations concernant l'apparition d'un cancer par l'utilisation d'une différence de distribution des cellules immunitaires entre le sang périphérique d'un patient atteint d'un cancer colorectal et celui d'une personne normale, et kit de diagnostic l'utilisant - Google Patents

Procédé pour évaluer l'immunité et fournir des informations concernant l'apparition d'un cancer par l'utilisation d'une différence de distribution des cellules immunitaires entre le sang périphérique d'un patient atteint d'un cancer colorectal et celui d'une personne normale, et kit de diagnostic l'utilisant Download PDF

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WO2018221820A1
WO2018221820A1 PCT/KR2018/000505 KR2018000505W WO2018221820A1 WO 2018221820 A1 WO2018221820 A1 WO 2018221820A1 KR 2018000505 W KR2018000505 W KR 2018000505W WO 2018221820 A1 WO2018221820 A1 WO 2018221820A1
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cells
value
ctls
cancer
patients
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이종균
최중범
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이종균
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
    • G01N33/57484—Immunoassay; Biospecific binding assay; Materials therefor for cancer involving compounds serving as markers for tumor, cancer, neoplasia, e.g. cellular determinants, receptors, heat shock/stress proteins, A-protein, oligosaccharides, metabolites
    • G01N33/57496—Immunoassay; Biospecific binding assay; Materials therefor for cancer involving compounds serving as markers for tumor, cancer, neoplasia, e.g. cellular determinants, receptors, heat shock/stress proteins, A-protein, oligosaccharides, metabolites involving intracellular compounds
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/14—Optical investigation techniques, e.g. flow cytometry
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/14—Optical investigation techniques, e.g. flow cytometry
    • G01N15/149—Optical investigation techniques, e.g. flow cytometry specially adapted for sorting particles, e.g. by their size or optical properties
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/569—Immunoassay; Biospecific binding assay; Materials therefor for microorganisms, e.g. protozoa, bacteria, viruses
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/569—Immunoassay; Biospecific binding assay; Materials therefor for microorganisms, e.g. protozoa, bacteria, viruses
    • G01N33/56966—Animal cells
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/58—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving labelled substances
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/58—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving labelled substances
    • G01N33/582—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving labelled substances with fluorescent label
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/14—Optical investigation techniques, e.g. flow cytometry
    • G01N2015/1486—Counting the particles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/70—Mechanisms involved in disease identification
    • G01N2800/7023—(Hyper)proliferation
    • G01N2800/7028—Cancer

Definitions

  • the onset was performed by assessing and evaluating peripheral blood immunity of cancer patients and colorectal cancer, including colorectal cancer, and finding markers that differ significantly between the two groups, and creating and applying a binary logistic regression algorithm based on a combination of these. To diagnose and provide criteria regarding immunotherapy.
  • Immunity is not determined by one factor, but by the net effect of various factors, such as the immune cells and proteins that make up the immune system. Therefore, the personal immunity (Personal immunity) is inevitably different and will change from time to time. This means that individualized immunotherapy requires tailored personal immunotherapy based on different immunity. In general, treatment or therapy is a process in which diagnosis of a disease is preceded by a diagnosis and then a treatment is determined. Immune diagnosis is also possible before the immunotherapy (Immune diagnosis) can be treated accordingly, most of the immunotherapy is carried out without accurate immunodiagnosis. This is because, as mentioned above, the individual's immunity is so complex that no methodological criteria or evidence for assessing and diagnosing it have been established.
  • An object of the present invention is to find markers that show differences in colorectal cancer patients and normal people among immune cells constituting peripheral blood immunity for diagnosing cancer immunity.
  • an object of the present invention is to establish a statistical algorithm through a combination of these and based on this individual cells by simply and easily measuring the cell activity of natural killer cells without counting the number of natural killer cells (NK cells) using a cell counter To diagnose the immune activity of the immune system is to provide.
  • NK cells natural killer cells
  • a method for evaluating the immunity of peripheral blood using the difference in the distribution of immune cells in peripheral blood of a colorectal cancer patient and a normal person and using the same to provide information on the presence or absence of colorectal cancer (A) peripheral blood immunity Classifying lymphocytes, monocytes, and granulocytes by analyzing the cellular size and wrinkles of the cells; (B) analyzing the distribution of immune cells in peripheral blood of cancer patients and normal persons by staining the markers of the three types of immune cells with at least one antibody combination; (C) determining a combination of differences in cancer markers and normal persons with statistically significant result values of the marker markers in the two cancer patients and normal populations so as to determine whether cancer has occurred; And (D) diagnosing the presence of colorectal cancer by measuring immunity per unit blood without counting natural killer cells using a flow cytometer or a cell counter using the label marker.
  • a computer readable recording medium having recorded thereon a computer program for executing the method.
  • a diagnostic kit for providing information on the presence of colorectal cancer by the method is provided.
  • a significant marker may be selected from immune cells contained in a blood sample, and analyzed using a flow cytometer to diagnose cancer immunity through a regression analysis algorithm.
  • This has the advantage of being very simple, quick to inspect, significant cost savings and sufficient accuracy compared to being overhauled in a preventive manner.
  • the reliability of the test can be improved by increasing reproducibility and stability, compared to an ELISA that measures and diagnoses a known tumor biomarker in blood.
  • FIG. 1 is a view for explaining the cell phenotype for NKC analysis according to an embodiment of the present invention.
  • Figure 2 is a diagram for explaining the cell phenotype for Th1 / Th2 analysis according to an embodiment of the present invention.
  • Figure 3 is a view for explaining the cell phenotype for analysis of Myeloid Derived Stem Cells (MDSCs) according to an embodiment of the present invention.
  • MDSCs Myeloid Derived Stem Cells
  • Figure 4 is a view for explaining the cell phenotype for the analysis of Regulatory T cells (Tregs) according to an embodiment of the present invention.
  • CTLs cytotoxic T cells
  • Figure 6 is a view for explaining the CD279 + TIGIT + in CTLs cell phenotype for Exhausted T cells (ETc) analysis according to an embodiment of the present invention.
  • FIG. 7 is a diagram illustrating a cell phenotype for Immune checkpoint (ICP) analysis according to a preferred embodiment of the present invention.
  • FIG. 8 is a view for explaining the CD3- ⁇ TCR + cell phenotype for Gamma-delta T cells (GDT) analysis according to an embodiment of the present invention.
  • FIG. 10 is a view showing a model for providing cancer immunity in three stages of E1 E2 E3 using two E score cut values according to an embodiment of the present invention.
  • Cell analysis in the present invention basically used a flow cytometer (Flow cytometer), the following six kinds of immune cells (WBC, Lymphocytes, Neutrophils, Monocytes, Basophils, Eosinophils) included in the white blood cell subtype (WBCS) was analyzed using an automatic hematology analyzer.
  • WBC flow cytometer
  • the present invention is based on the marker markers expressed in the nine kinds of immune cell populations in the blood of patients and normal people before colorectal cancer surgery, the distribution of the immune cells for each marker marker (%) and the number of cells (cells) / ⁇ L) and its ratio (Ratio), which can be classified into the following categories by the function and analysis method of immune cells.
  • NK cells 1) NK cells (NKC)
  • MDSCs Myeloid Derived Stem Cells
  • CTLs Cytotoxic T cells
  • the present invention classifies and organizes major cellular immune markers into significant groups.
  • the selected markers actually showed significant differences in expression levels between colorectal cancer patients and two normal groups even in peripheral blood immunity units and were useful as diagnostic markers.
  • statistically significant markers were actually confirmed by the present patients, these markers were single items that showed sufficient sensitivity and specificity to diagnose or distinguish colon cancer patients from normal individuals.
  • the algorithm was developed.
  • the mathematical model used in the present invention is based on binary logistic regression.
  • NK cells NK cells
  • Th1Th2 Th1Th2
  • MDSCs Myeloid Derived Stem Cells
  • Tregs Regulatory T cells
  • CTLs Cytotoxic T cells
  • Ec Exhausted T cells
  • ICP Immune checkpoint
  • GDT Gamma-delta T cells
  • the kinds of fluorescence used in the invention are seven kinds of FITC, Alexa Fluor 488, PE, PE-Cy5, PE-Cy7, PerCP, and APC.
  • Channel is the detector channel type of the flow cytometer
  • Tandem-dye is the type of fluorescence attached to the antibody
  • Marker is the type of marker marker
  • Marker location is the location of each marker. As described below, there may be a difference in the experimental method.
  • NK cells Channel Tandem-dye Marker Marker location Distributor Catalog # Lot # Volume / test FL1 FITC CD3 surface BD 555339 6125658 0.5 FL2 PE CD56 surface BD 555516 6054620 2.5 FL3 PE-Cy7 CD314 surface BD 562365 6140911 2.5 FL4 APC CD158b surface BioLegend 312612 B210467 0.5
  • Th1Th2 Channel Tandem-dye Target Marker location Distributor Catalog # Lot # Volume / test FL1 Alexa Fluor488 CD183 surface BD 558047 6155849 0.5 FL2 PE CD194 surface BD 551120 5107877 0.5 FL3 PE-Cy5 CD4 surface BD 555348 5037589 0.5 FL4 APC CD196 surface BD 560619 5135834 0.15
  • Regulatory T cells Channel Tandem-dye Target Marker location Distributor Catalog # Lot # Volume / test FL1 FITC CD4 surface BD 555346 5097644 0.5 FL2 PE CD25 surface BD 555432 6040885 2.5 FL3 PE-Cy7 CD152 intra BD 555854 5142830 2.5 FL4 APC CD279 surface BD 558694 6154800 2.5
  • Cytotoxic T cells Channel Tandem-dye Target Marker location Distributor Catalog # Lot # Volume / test FL1 FITC CD3 surface BD 555339 6125658 0.5 FL2 PE CD25 surface BD 555432 6040885 2.5 FL3 PE-Cy7 CD152 intra BD 555854 5142830 2.5 FL4 APC CD279 surface BD 558694 6154800 2.5
  • Exhausted T cells Channel Tandem-dye Target Marker location Distributor Catalog # Lot # Volume / test FL1 FITC CD3 surface BD 555339 6125658 0.5 FL2 PE TIGIT Surface eBioseience 12-9500-42 4310012 2.5 FL3 PerCP CD8 Surface eBioseience 46-0087-41 E10832-1634 2.5 FL4 APC CD279 Surface BD 558694 6154800 2.5
  • Immune checkpoint Channel Tandem-dye marker Marker location Distributor Catalog # Lot # Volume / test FL1 FITC CD3 Surface BD 555339 6125658 0.5 FL2 PE CD366 Intra BD 563422 5082811 One FL3 PerCP CD272 Intra R & D systems FAB3354C ABCC212071 One FL4 APC CD223 intra R & D systems FAB23193A ADXM0116041 2.5
  • Gamma-delta T cells Channel Tandem-dye marker Marker location Distributor Catalog # Lot # Volume / test FL1 FITC CD3 Surface BD 555339 6125658 0.5 FL2 PE ⁇ TCR surface BD 555717 5267944
  • the basic staining method was carried out as follows.
  • each antibody Dispense the volume per test (volume / test) of each antibody to be stained into a microcentrifuge tube of 1.8 mL volume using a micro pipette.
  • the combined volume of each antibody is prepared to be 10 ⁇ L per test.
  • the preparation of the antibody varies depending on whether the marker location to be stained is all the surface of the membrane or the combination of the surface and the cytoplasm. The basic staining is only the surface marker.
  • the cells are stained by combining antibodies for staining, fixation of cells, and then prepared by staining intracellular markers.
  • NK cells consisting of a combination of surface membranes for 10 tests (10 people), 5 ⁇ L (0.5 ⁇ L x 10 tests) of FITC mouse anti-human CD3 IgGs. ), 25 ⁇ L (2.5 ⁇ L ⁇ 10 tests) of PE mouse anti-human CD56 IgGs, 25 ⁇ L (2.5 ⁇ L ⁇ 10 tests) of PE-Cy7 mouse anti-human CD314 IgGs, 5 ⁇ L (0.5 ⁇ L of APC mouse anti-human CD158b IgG) x 10 tests) were put into each microcentrifuge tube to prepare 60 ⁇ L. Then, 40 ⁇ L of PBS (Phosphate-buffered saline) was added to the tube to make a final volume of 100 ⁇ L of antibody combination.
  • PBS Phosphate-buffered saline
  • Tregs consisting of a combination of the surface and the cytoplasm of the marker with 10 tests (10 persons).
  • the staining antibody of NK cells (NKC), Th1Th2 (TH), Myeloid Derived Stem Cells (MDSCs), Exhausted T cells (ETc), Gamma-delta T cells (GDT) consisting of a combination of cell membranes
  • NTC NK cells
  • Th1Th2 Th1Th2
  • MDSCs Myeloid Derived Stem Cells
  • Ec Exhausted T cells
  • GDT Gamma-delta T cells
  • Tums Regulatory T cells
  • CTLs Cytotoxic T cells
  • ICP Immune checkpoint
  • Constituent volume ratio of each antibody is as indicated through the volume / test ratio of Table 1 to Table 8, the antibody combination volume can be prepared by the same method as the above example.
  • the results obtained through flow cytometry are all obtained in the distribution (%), and the number of cells (cells / ⁇ L) according to each distribution is multiplied by the distribution using the differential of the white blood cells obtained using the automatic blood cell analyzer. It can be calculated as
  • FIGS. 1 to 8 The results of analyzing the markers of immune cells using the flow cytometer through the above experimental procedure are shown in FIGS. 1 to 8, and the statistical results of analyzing the colorectal cancer patients and normal persons are shown in Tables 9 to 18.
  • FIGS. 1 to 8 and 10 are rotated 90 degrees in the counterclockwise direction, it will be described below that the above drawings are based on the rotated 90 degrees in the clockwise direction.
  • Figure 1 is for the NKC analysis according to a preferred embodiment of the present invention 1 CD3-CD56 +, 2 CD3 + CD56 +, 3 CD314 + CD158b- in CD3-CD56 + cells (NK cells), 4 CD314-CD158b + in NK cells, 5 It provides six cell phenotypes: CD314-CD158b + in NK cells, 6 CD158b + in CD3 + CD56- (T cells).
  • cells when analyzing blood with a flow cytometer, cells can be classified into X-axis as FSC-H (relative size of cells) and Y-axis as SSC-H (cell wrinkles).
  • Blood immune cells can be classified into lymphocytes, monocytes, and granulocytes according to cell size and extent of wrinkles. The analysis was performed mainly on the lymphocytes (Lymphocytes) in the center of the graph, and this part was stained using an antibody attached to each marker.
  • the X-axis shows the presence of CD3 staining and the Y-axis shows the presence of CD56 staining.
  • the cross-shaped solid line inside the graph shows CD3- + on the left and CD56 + on the bottom.
  • the CD3-CD56 + part was designated as Q1, the CD3 + CD56 + part as Q2, the CD3 + CD56- part as Q3, and the CD3-CD56- part as Q4.
  • the lower left graph cells of the Q1 region were again classified according to the presence or absence of the CD314 and CD158 markers using antibodies, and the graph expression method was as described above.
  • the cells of the Q3 region of the upper right graph were again classified according to the presence or absence of the CD314 and CD158 markers using antibodies, and the expression method of the graph was as described above.
  • Figure 2 provides four cell phenotypes, such as 1 Th1, 2 Th2, 3 Th17, 4 Th1 / Th2 for Th1 / Th2 analysis according to a preferred embodiment of the present invention.
  • Figure 2 also shows the results of the analysis by using the cells of the lymphocyte site of Figure 1 by sorting the presence or absence of the staining of each marker CD4, CD183, CD194, CD196 sequentially or simultaneously, graph
  • the reaction between the X-axis and the Y-axis antibody was expressed as a numerical value, and each region was subdivided by a solid line in the graph.
  • the detailed method is as described with reference to FIG. 1.
  • the distribution of Th1, Th2, Th17 is obtained by the following equation (1).
  • Figure 3 provides a cell phenotype for analysis of Myeloid Derived Stem Cells (MDSCs) according to a preferred embodiment of the present invention.
  • MDSCs Myeloid Derived Stem Cells
  • Figure 4 provides three cell phenotypes, such as 1 CD4 + CD279 +, 2 CD4 + CD25 +, 3 CD4 + CD152 + for the analysis of Regulatory T cells (Tregs) according to an embodiment of the present invention. Since the representation of the graph shown through FIGS. 4 to 8 is the same as that described with reference to FIG. 1, a detailed description thereof will be omitted.
  • Figure 5 provides two cell phenotypes, such as 1 CD152 + in CTLs, 2 CD279 + in CTLs for the analysis of Cytotoxic T cells (CTLs) according to a preferred embodiment of the present invention.
  • CTLs Cytotoxic T cells
  • Figure 6 provides a CD279 + TIGIT + in CTLs cell phenotype for Exhausted T cells (ETc) analysis according to a preferred embodiment of the present invention.
  • FIG. 7 shows 1 CD3 + CD366 +, 2 CD3-CD366 +, 3 CD366 + in lymphocytes, 4 CD3 + CD272 +, 5 CD3-CD272 +, 6 CD272 + in lymphocytes, for Immune checkpoint (ICP) analysis according to a preferred embodiment of the present invention.
  • GDT Gamma-delta T cells
  • Table 9 is a table showing the average distribution and cell number of peripheral blood NKC of colorectal cancer patients and normal people.
  • Table 10 is a table showing the average distribution and cell number of peripheral blood TH of colorectal cancer patients and normal people.
  • Table 11 is a table showing the average distribution and cell number of peripheral blood MDSCs of colorectal cancer patients and normal people.
  • Table 12 is a table showing the average distribution and cell number of peripheral blood Tregs of colorectal cancer patients and normal people.
  • Table 13 is a table showing the average distribution and cell number of peripheral blood CTLs of colorectal cancer patients and normal people.
  • Table 14 is a table showing the average distribution and cell number of peripheral blood ETc of colorectal cancer patients and normal people.
  • Table 15 is a table showing the average distribution and cell number of peripheral blood ICP of colorectal cancer patients and normal people.
  • Table 16 is a table showing the average distribution and cell number of peripheral blood GDT of colorectal cancer patients and normal people.
  • Table 17 is a table showing the average distribution and cell number of peripheral blood WBCS of colorectal cancer patients and normal people.
  • Table 18 is a table showing the ratio of peripheral blood immune cells of colorectal cancer patients and normal people.
  • N is the number of experimental groups
  • Mean is the mean value
  • SD is the standard deviation
  • SE is the standard error
  • 95% Mean is calculated using only 95% by discarding 2.5% of the results at both ends of the group to reduce the error rate
  • the mean value, Median means the median value.
  • NKC CD3-CD56 + (NK)% Control 132 16.50 8.08 0.70 16.00 14.82 0.183 Patients 98 17.79 10.05 1.28 17.20 16.21 NKC CD3 + CD56 +% Control 132 5.00 4.17 0.36 4.45 3.77 0.065 Patients 98 3.67 2.50 0.32 3.49 3.00 NKC CD3-CD56 + cells / ⁇ L Control 132 342 198 17 325 313 0.284 Patients 98 345 206 26 330 304 NKC CD3 + CD56 + (NKT) cells / ⁇ L Control 132 108 109 10 93 76 0.129 Patients 98 76 64 8 70 56 NKC CD314 + CD158b - % in NK cells Control 132 56.19 16.45 1.48 56.60 57.14 0.030 Patients 98 47.04 18.02 2.29 47.12 49.41 NKC CD314 + CD158b- cells / ⁇ L in NK
  • peripheral blood immune cells of 132 normal and 98 patients were analyzed.
  • markers of immune cells showing a difference between the two groups at the significance level P value ⁇ 0.05 were found.
  • the bold and italicized parts of the table are significant markers of immune cells.
  • the difference in mean value between the two groups was analyzed using the statistical program SPSS. As the population follows the normal distribution and satisfies the equivariance condition, the statistical difference of the mean value was used by the T test student's t - test.
  • cancer colony-specific immune cell markers can be used to accurately classify colorectal cancer patients and normal persons, and cancer diagnosis through immunological tests may be possible.
  • a binary logistic regression model formulated to express the difference in peripheral blood immunity between colorectal cancer patients and normal people was applied to the diagnosis of cancer.
  • colorectal cancer patients and normal subjects were converted to 1 and 0, respectively, as dependent variables, and immune cell marker result values were used as independent variables as shown in Tables 9 to 18 above.
  • the items that best distinguish the two groups of 132 normal and 98 colorectal cancer patients were selected.
  • Table 19 above shows coefficients (B) and constants in a regression analysis model using 23 immune cell markers.
  • B is a B estimate and corresponds to a coefficient value in a regression model.
  • SE is the standard error value for the B estimate
  • Wald is the square of (the standard error value of the B estimate / B estimate).
  • Df means degrees of freedom
  • Sig Means significance, and the significance of each item in the model
  • Exp (B) means e B with natural logarithm of B , and each independent variable increases by 1. This is a statistic that indicates how many times the probability of belonging to a group having an internal value of 1 is greater than that of a group having an internal value of 0.
  • CD4 +% in CTLs 23.317-0.403 (CD4 +%)-0.468 (CD3 + CD8 +%) + 0.961 (CD4 + CD279 +%) + 0.646 (CD4 + CD25 +%) + 0.001 (CD4 + CD152 +%)-0.093 (CD279 +% in CTLs) +0.131 (CD152 +% in CTLs) +0.623 (CD3 + CD272 +%) + 0.479 (CD3 + CD223 +)-0.221 (Lymphocytes%)-0.174 (Neutrophils%)-1.056 (NLR) +4.576 (CTLs / Treg) -0.011 (CD314 + CD158b-% in NK cells) +0.739 (CD314-CD158b +% in NK cells) -0.140 (CD314 + in T cells) +0.450 (Th1%) + 0.074 (Th2%)-7.516 (TH1 / TH2) -0.001 (MDSCs cells / ⁇ L)+0.495 (monocytes%)
  • the result value can be largely influenced by the higher weight item, and the data for more factors are required. May act as an inhibitor in testing. Therefore, more preferably, the following logistic regression function consisting of a combination of 11 factors can be used.
  • each result value and the coefficient value are multiplied and summed together with a constant value to obtain a Logit (P) value.
  • Logit (P) a linear equation model value
  • Equation 3 the predictive Y value of colorectal cancer patients and normal subjects is e P Is obtained by denominator 1-e P as the denominator, and the probability Y value is named E score in the present invention.
  • Table 20 shows sensitivity, specificity, and Youden index values according to the E score result value.
  • cut values for sensitivity and specificity of the E score result value can be arbitrarily adjusted.
  • the cut value is 0.098
  • the sensitivity is 100% and the specificity is 78.4%.
  • the cut value is 0.684
  • the sensitivity is 83.1% and the specificity is 100%. This indicates that all of them are normal at E score ⁇ 0.098 and similarly diagnosed as colorectal cancer patients at 0.684 ⁇ E score.
  • FIG. 10 is a diagram showing a model for providing cancer immunity in three steps of E1 E2 E3 using two E score cut values according to an embodiment of the present invention.
  • the cut value of the E score may be divided into three sections based on 0.098 and 0.684, and the cancer immunity according to the E score result may be classified into three stages.
  • Section E socre ⁇ 0.098 is normal and named E1.
  • Section 0.098 ⁇ E score ⁇ 0.684 is a high-risk cancer group and is named E2.
  • 0.684 ⁇ E score is colorectal cancer patients.
  • a patient before surgery for colorectal cancer is diagnosed as a normal person (E1), a high risk group of cancer (E2), and a colorectal cancer patient (E3) using, for example, peripheral blood immunity.
  • E1 normal person
  • E2 high risk group of cancer
  • E3 colorectal cancer patient
  • the regression model made using 23 or 11 immune cell markers can maximize the usefulness of cancer diagnosis by increasing the sensitivity and specificity by using newly discovered markers, and the 23 or 11 proposed in the present invention.
  • New combinations, rather than branch items, can also be used to diagnose and regress models.

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Abstract

La présente invention concerne un procédé pour évaluer l'immunité du sang périphérique et fournir des informations sur l'apparition ou non d'un cancer colorectal par l'utilisation d'une différence de distribution de cellules immunitaires entre le sang périphérique de patients atteints d'un cancer colorectal et celui de personnes normales, le procédé comprenant les étapes consistant à : (A) analyser les cellules immunitaires du sang périphérique en termes de taille des cellules et de degré de rides pour classer les cellules en lymphocytes, monocytes et granulocytes ; (B) colorer un marqueur de marquage des trois types de cellules immunitaires avec au moins une combinaison d'anticorps pour analyser la distribution des cellules immunitaires dans des sangs périphériques de patients cancéreux et de personnes normales ; (C) différencier des ensembles dans lesquels les valeurs de résultat significatives du marqueur de marquage sont différentes entre les deux groupes de patients cancéreux et de personnes normales, avec une signification statistique, de façon à déterminer si l'apparition d'un cancer a eu lieu ou non parmi des patients cancéreux et des personnes normales ; et (D) mesurer l'immunité par unité de sang au moyen du marqueur de marquage pour diagnostiquer l'apparition d'un cancer colorectal, sans compter les cellules tueuses naturelles avec un cytomètre de flux ou un compteur de cellules.
PCT/KR2018/000505 2017-06-02 2018-01-11 Procédé pour évaluer l'immunité et fournir des informations concernant l'apparition d'un cancer par l'utilisation d'une différence de distribution des cellules immunitaires entre le sang périphérique d'un patient atteint d'un cancer colorectal et celui d'une personne normale, et kit de diagnostic l'utilisant WO2018221820A1 (fr)

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