MARKER FOR DIAGNOSING COLORECTAL CANCER AND METHOD FOR PROVIDING INFORMATION REQUIRED FOR DIAGNOSIS OF COLORECTAL CANCER

Abstract

The present invention relates to a marker for diagnosing colorectal cancer, a method for providing information required for the diagnosis of colorectal cancer by using same, and a method for providing information for monitoring the response to colorectal cancer therapy by using same.

Claims

1. A method for providing information required for the diagnosis of colorectal cancer, the method comprising: measuring the level of STAT3 phosphorylation in Th cells contained in a first sample; and measuring the level of STAT3 phosphorylation in Tc cells contained in a second sample.

2. The method of claim 1, wherein the first sample and the second sample include peripheral blood.

3. The method of claim 1, wherein the measuring of the level of STAT3 phosphorylation is performed using flow cytometry.

4. The method of claim 1, wherein the first sample is prepared by: a mononuclear cell isolation step of isolating mononuclear cells contained in blood; a cytokine treatment step of treating the isolated mononuclear cells with a cytokine; and a phosphorylation staining step of performing phosphorylation staining.

5. The method of claim 4, wherein the cytokine is IL-10.

6. The method of claim 4, wherein the concentration of the cytokine is 9.0 to 11.0 ng/ml.

7. The method of claim 1, wherein the second sample is prepared by: a mononuclear cell isolation step of isolating mononuclear cells contained in blood; a cytokine treatment step of treating the isolated mononuclear cells with a cytokine; and a phosphorylation staining step of performing phosphorylation staining.

8. The method of claim 7, wherein the cytokine is IL-6.

9. The method of claim 7, wherein the concentration of the cytokine is 19.0 to 21.0 ng/ml.

10. A method for providing information for monitoring a therapeutic response of colorectal cancer, the method comprising: measuring the level of STAT3 phosphorylation in Th cells contained in a first sample; and measuring the level of STAT3 phosphorylation in Tc cells contained in a second sample.

11. The method of claim 10, wherein the first sample and the second sample are obtained from a patient who is being treated for colorectal cancer.

12. The method of claim 10, wherein the first sample and the second sample include peripheral blood.

13. The method of claim 10, wherein the measuring of the level of STAT3 phosphorylation is performed using flow cytometry.

14. The method of claim 10, wherein the first sample is prepared by: a mononuclear cell isolation step of isolating mononuclear cells contained in blood; a cytokine treatment step of treating the isolated mononuclear cells with a cytokine; and a phosphorylation staining step of performing phosphorylation staining.

15. The method of claim 14, wherein the cytokine is IL-10.

16. The method of claim 14, wherein the concentration of the cytokine is 9.0 to 11.0 ng/ml.

17. The method of claim 10, wherein the second sample is prepared by: a mononuclear cell isolation step of isolating mononuclear cells contained in blood; a cytokine treatment step of treating the isolated mononuclear cells with a cytokine; and a phosphorylation staining step of performing phosphorylation staining.

18. The method of claim 17, wherein the cytokine is IL-6.

19. The method of claim 17, wherein the concentration of the cytokine is 19.0 to 21.0 ng/ml.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0051] FIG. 1 is a graph showing the results that there were differences in STAT1 phosphorylation by IL-6 stimulation in the blood immune cells of healthy persons and the blood immune cells and tumor immune cells of cancer patients according to an embodiment of the present disclosure.

[0052] FIG. 2 is a graph showing the results that there was a difference in STAT3 phosphorylation by IL-6 stimulation in the blood immune cells of healthy person and the blood immune cells and tumor immune cells of cancer patients.

[0053] FIG. 3 is a graph showing the results that there was a difference in STAT3 phosphorylation by IL-10 stimulation in the blood immune cells of healthy person and the blood immune cells and tumor immune cells of cancer patients.

[0054] FIG. 4 is a graph showing the results that there was a difference in STAT5 phosphorylation by IL-2 stimulation in the blood immune cells of healthy person and the blood immune cells and tumor immune cells of cancer patients.

[0055] FIG. 5 is a schematic diagram showing changes in values in the blood immune cells and tumor immune cells of cancer patients by using the values in the blood immune cells of healthy persons as base values, from the results in FIGS. 1 to 4 according to an embodiment of the present disclosure.

[0056] FIG. 6 shows the results of experimenting the change of phosphorylation of each STAT to each cytokine after co-culture of blood immune cells of healthy persons and a colorectal cell line at various ratios according to an embodiment of the present disclosure. On the whole, statistically significant decrease patterns were shown in the immune cells (B, C, and D) co-cultured with the colorectal cell line compared with the base values (A). (A: PBMC only, B: direct culture of PBMC+HCT116 (1:1), C: direct culture of PBMC+HCT116 (1:10), D: indirect culture of PBMC+HCT116 (1:10))

[0057] FIG. 7 shows that cluster analysis was performed with the levels of phosphorylation of each STAT to each cytokine according to an embodiment of the present disclosure, and resultantly, there were two groups wherein colorectal patients were mainly distributed in one group and healthy persons were mainly distributed in the other group.

[0058] FIG. 8 shows that principal component analysis (PCA) was performed with the phosphorylation levels of each STAT to each cytokine according to an embodiment of the present disclosure and that the colorectal cancer patients (red dots) and healthy persons (green dots) were discriminated from each other.

[0059] FIG. 9 is a schematic diagram of the distributions of colorectal cancer patients (red dots) and healthy persons (green dots) by using, as axes, respective items from cytokine and STAT combinations with largest differences (IL-6/pSTAT3 and IL-10/pSTAT3) found in the colorectal cancer patients and the healthy persons according to an embodiment of the present disclosure.

[0060] FIG. 10 is a schematic diagram showing a procedure wherein a statistical model was made by finding useful features for distinguishing between cancer patients and normal persons in training cohort and then validating the performance of the model through the use of validation cohort according to an embodiment of the present invention.

[0061] FIG. 11 shows the ROC analysis result depicting the performance of a statistical model using two features (IL-6/pSTAT3 and IL-10/pSTAT3) presented in this study in a training cohort according to an embodiment of the present invention.

[0062] FIG. 12 shows the ROC analysis result depicting the performance of a statistical model using two features (IL-6/pSTAT3 and IL-10/pSTAT3) presented in this study in a validation cohort according to an embodiment of the present invention.

[0063] FIG. 13 shows the ROC analysis result depicting the performance of a statistical model using the two features (IL-6/pSTAT3 and IL-10/pSTAT3) presented in this study in training and validation cohorts (black line) and the ROC analysis result depicting the performance of a statistical model simultaneously employing the two features (IL-6/pSTAT3 and IL-10/pSTAT3) presented in this study in training and validation cohorts (red line) and a colorectal cancer marker (CEA) according to an embodiment of the present disclosure.

BEST MODE FOR CARRYING OUT THE INVENTION

[0064] A method for providing information required for the diagnosis of colorectal cancer, the method including: measuring the level of STAT3 phosphorylation in Th cells contained in a first sample; and measuring the level of STAT3 phosphorylation in Tc cells contained in a second sample.

DETAILED DESCRIPTION

[0065] Hereinafter, the present disclosure will be described in more detail by the following examples. However, these examples are used only for illustration, and the scope of the present disclosure is not limited by these examples.

Experimental Example 1: Subject Collection

[0066] The subject group included a colorectal cancer group and a healthy group. The colorectal cancer group was composed of patients before surgery and anticancer treatment among patients diagnosed with colorectal cancer in a biopsy during colonoscopy. About 10 ml of fresh peripheral blood was collected prior to surgery, from each of the patients who verbally consented, into a test tube containing heparin as an anti-coagulant. The blood from healthy persons was obtained from an external tissue bank (Korea Gynecology Cancer Back). The blood was promptly delivered to a laboratory of our center on the day of collection.

Experimental Example 2: Cell Isolation, Stimulation, and Fixation

[0067] Mononuclear were isolated from fresh whole blood by using a specific gravity liquid (1.077) such as Ficoll. The isolation method followed a typical method. Briefly, whole blood was diluted with RPMI1640 medium at 1:1, and then Ficoll and the diluted whole blood were placed in a 50-ml test tube at a ratio of 1:1. After centrifugation at 1300 rpm (350 g) for 20 minutes, the mononuclear cell layer separated between Ficoll and plasma was carefully recovered. The isolated mononuclear cells were suspended in RPMI 1640 culture medium containing 10% fetal bovine serum (FBS), at a concentration of 0.5×106 to 1.0×106 cells/ml, and then 1.0 ml was dispensed in each of test tubes prepared under the conditions of test tubes 1 to 4 (test tube 1: no cytokine 1 stimulation (unstimulated, unstim), test tube 2: cytokine 1 stimulated (stimulated, stim), test tube 3: no cytokine 2 stimulation (unstimulated, unstim), and test tube 4: cytokine 2 stimulation (stimulated, stim), and the like) according to the number of cytokines to be identified, and corresponding cytokines were added thereto according to Table 1 below, followed by incubation in a 37° C. incubator for 15 minutes. When the phosphorylated STAT protein (pSTAT) targets to be measured are the same, even different cytokines may share the unstim test tubes. The optimal concentration for each cytokine is shown in Table 1 below. The optimal concentration and reaction time were established through prior experiments.

[0068] Then, the test tubes were taken out, and quickly treated with 1.5% paraformaldehyde, and then left at room temperature at 25° C. for 10 minutes, and the supernatant was removed by centrifugation at 1000 rpm (300 g) for 10 minutes. Then, the cells were well suspended as single cells by using a mixer (vortex), and 1.0 ml of a cold 100% methanol stock solution, which had been stored at −20° C. or lower, was added to fix the cells. Care is taken to ensure that the cells were sufficiently present as single cells by adding the cells while mixing cells on the mixer, even during addition. Then, the cells were fixed in a −70° C. refrigerator for 1 hour or longer.

TABLE-US-00001 TABLE 1 Cytokine IL-6 IL-10 IL-2 Concentration 20 ng/ml 10 ng/ml 20 ng/ml

Experimental Example 3: Phosphorylation Staining and Flow Cytometry

[0069] The upper methanol was removed by centrifugation at 1000 rpm (300 g) for 10 minutes, and then the cells were washed three times with phosphate buffered saline (PBS) containing 0.5% bovine serum albumin (BSA) to completely remove the residual liquid. A monoclonal antibody to pSTAT to be identified and a monoclonal antibody cocktail capable of identifying cell fraction were prepared, and then mixed and incubated with the cell suspension to make a final volume of 100 μl. The cells were incubated in a dark place for 30 minutes, washed once with PBS containing 0.5% BSA, and then re-suspended in 300 μl, and thereafter, subjected to acquisition and analysis by using a flow cytometer.

[0070] The composition of each test tube for cytokine stimulation is shown in Table 2, and the composition of the antibody reagent used for each test tube is shown in Table 3.

[0071] In addition, helper T cells and cytotoxic T cells were discriminated by a particular monoclonal marker, and then the median value (median MFI) of the pSTAT expression levels (mean fluorescence intensity, MFI) to each cytokine stimulation on histogram was derived under unstim and stim conditions. Finally, the ratio of stim MFI/unstim MFI was expressed and the results are shown in Table 4.

TABLE-US-00002 TABLE 2 Test tube 1 2 3 4 5 6 Stimulant None None IL-6 IL-6 IL-10 IL-2 Concen- — — 20 ng/ml 20 ng/ml 10 ng/ml 20 ng/ml tration

TABLE-US-00003 TABLE 3 Stain antibody/ Test tube 1 2 3 4 5 6 pSTAT1 (FITC) 5 — 5 — — — pSTAT3 (FITC) — 5 — 5 5 — pSTAT3 (FITC)5 — — — — — 5 CD25 (PE) 2 2 2 2 2 2 CD3 (PercpCY5.5) 10 10 10 10 10 10 CD4 (PE-CY7) 5 5 5 5 5 5 CD45(APC-CY7) 5 5 5 5 5 5

Example 1: Levels of STAT Phosphorylation to Cytokines in Immune Cells

[0072] The levels of phosphorylated STAT proteins (pSTAT) in response to IL-6, IL-10 and IL-2 in the immune cells of the peripheral blood and tumor tissue of the patients and the peripheral blood of the healthy control were observed, and the results are shown in FIGS. 1 to 5 and Tables 4 to 7 (peripheral blood) and Tables 8 to 11 (tumor site).

TABLE-US-00004 TABLE 4 IL- IL- IL- IL- IL- IL- ID\CIPS 2_pSTAT5_Th 6_pSTAT1_Th 6_pSTAT3_Th 10_pSTAT3_Th 2_pSTAT5_Treg 6_pSTAT1_Treg CRC_CIPS_01 NA 2.79 1.67 0.95 NA 2.24 CRC_CIPS_02 NA 1.96 3.35 1.92 NA 2.04 CRC_CIPS_03 NA 6.59 3.46 2.8 NA 3.94 CRC_CIPS_04 NA 16.9 3.53 3.3 NA 7.19 CRC_CIPS_05 NA 9.68 4.1 4.03 NA 5.48 CRC_CIPS_06 NA 15.7 3.53 3.14 NA 5.51 CRC_CIPS_07 NA 7.09 4.07 3.37 NA 2.85 CRC_CIPS_08 NA 6.75 4.66 5.46 NA 3.79 CRC_CIPS_09 NA 14.4 7.66 8.34 NA 7.99 CRC_CIPS_10 NA 14 7.81 9.04 NA 7.67 CRC_CIPS_11 NA 1.59 3.88 3.81 NA 1.68 CRC_CIPS_12 NA 3 4.4 3.41 NA 1.83 CRC_CIPS_13 NA 8.23 2.86 1.46 NA 3.1 CRC_CIPS_14 NA 8.15 6.83 2.55 NA 4.68 CRC_CIPS_15 NA 3.75 5.26 3 NA 2.04 IL- IL- IL- IL- IL- IL- ID\CIPS 6_pSTAT3_Treg 10_pSTAT3_Treg 2_pSTAT5_Tc 6_pSTAT1_Tc 6_pSTAT3_Tc 10_pSTAT3_Tc CRC_CIPS_01 1.57 1.22 NA 2.52 1.68 0.95 CRC_CIPS_02 3.53 2.34 NA 0.89 1.3 2.27 CRC_CIPS_03 3.56 3.43 NA 0.89 0.92 3.47 CRC_CIPS_04 4.05 4.38 NA 1 1.11 5.91 CRC_CIPS_05 4.79 5.55 NA 1.04 1.26 7.9 CRC_CIPS_06 3.28 3.85 NA 1.48 1.23 4.66 CRC_CIPS_07 4.11 4.03 NA 1.08 1.14 5.21 CRC_CIPS_08 4.43 5.14 NA 1.37 1.48 6.9 CRC_CIPS_09 6.59 7.47 NA 1.3 1.57 9.87 CRC_CIPS_10 6.94 7.91 NA 1.33 1.24 9.86 CRC_CIPS_11 3.24 3.6 NA 1.14 1.38 4.4 CRC_CIPS_12 4.26 4.34 NA 1.08 1.59 5.89 CRC_CIPS_13 3.93 1.95 NA 1.6 1.3 1.86 CRC_CIPS_14 6.71 3.84 NA 0.97 1.14 3.81 CRC_CIPS_15 4.57 3.98 NA 1.64 1.14 4

TABLE-US-00005 TABLE 5 IL- IL- IL- IL- IL- IL- ID\CIPS 2_pSTAT5_Th 6_pSTAT1_Th 6_pSTAT3_Th 10_pSTAT3_Th 2_pSTAT5_Treg 6_pSTAT1_Treg CRC_CIPS_16 NA 0.84 1.22 6.97 NA 2.75 CRC_CIPS_17 NA 2.13 4.11 3.27 NA 2.09 CRC_CIPS_18 NA 5 8.99 4.19 NA 2.49 CRC_CIPS_19 NA 5.13 5.04 3.55 NA 4.52 CRC_CIPS_20 NA 2.4 6.09 3.24 NA 2.92 CRC_CIPS_21 NA 9.71 4.11 2.71 NA 17.6 CRC_CIPS_22 NA 7.07 1.53 1.14 NA 4.64 CRC_CIPS_23 NA 4.61 3.73 1.57 NA 7.29 CRC_CIPS_24 NA 13.2 6.06 3.97 NA 9.5 CRC_CIPS_25 5.67 NA 5.57 4.3 12.6 NA CRC_CIPS_26 3.6 5.49 5.21 3.75 6.3 3.84 CRC_CIPS_27 3.08 7.34 3.36 1.75 6.53 6.11 CRC_CIPS_28 3.97 9.2 5.56 5.42 5.93 10 CRC_CIPS_29 NA NA 6.04 5.35 NA NA CRC_CIPS_30 3.18 2.19 4.39 3.61 5.44 2.38 IL- IL- IL- IL- IL- IL- ID\CIPS 6_pSTAT3_Treg 10_pSTAT3_Treg 2_pSTAT5_Tc 6_pSTAT1_Tc 6_pSTAT3_Tc 10_pSTAT3_Tc CRC_CIPS_16 8.7 6.59 NA 0.82 1.16 7.4 CRC_CIPS_17 4.42 3.81 NA 0.97 1.22 3.8 CRC_CIPS_18 11.7 7.03 NA 1.08 1.49 5.52 CRC_CIPS_19 6.08 5.01 NA 1.16 1.27 7.24 CRC_CIPS_20 7 4.09 NA 1.23 1.14 4.6 CRC_CIPS_21 8.53 6.33 NA 1.02 1.25 7.21 CRC_CIPS_22 1.02 1.29 NA 1.1 0.31 1.25 CRC_CIPS_23 4.46 2.04 NA 1.29 1.09 1.83 CRC_CIPS_24 9.11 6.95 NA 1.12 1.47 3.97 CRC_CIPS_25 10.4 9.59 7.16 NA 1.19 6.65 CRC_CIPS_26 10.5 10.8 4.64 1.33 1.22 5.07 CRC_CIPS_27 3.07 2.27 2.38 1.25 1.02 1.78 CRC_CIPS_28 5.49 6.47 3.79 1.05 1.15 5.38 CRC_CIPS_29 5.69 6.02 NA NA 1.42 6.02 CRC_CIPS_30 4.83 4.74 2.58 1.14 1.4 3.56

TABLE-US-00006 TABLE 6 IL- IL- IL- IL- IL- IL- ID\CIPS 2_pSTAT5_Th 6_pSTAT1_Th 6_pSTAT3_Th 10_pSTAT3_Th 2_pSTAT5_Treg 6_pSTAT1_Treg CRC_CIPS_31 3.67 NA 5.42 NA 7.14 NA CRC_CIPS_32 3.36 NA 5.57 NA 6.04 NA CRC_CIPS_33 3.27 NA 4.57 NA 5.06 NA CRC_CIPS_34 3.26 NA 3 NA 5.03 NA CRC_CIPS_35 3.73 7.46 6.41 1.5 7.96 2.04 CRC_CIPS_36 2.96 11.1 5.82 2.7 5.96 15.1 CRC_CIPS_37 5.63 NA 5.4 2.25 7.48 NA CRC_CIPS_38 6.19 NA 4.74 4.15 13.8 NA CRC_CIPS_39 5.09 NA 3.65 2.98 7.18 NA CRC_CIPS_40 3.96 NA 3.72 1.72 6.8 NA IL- IL- IL- IL- IL- IL- ID\CIPS 6_pSTAT3_Treg 10_pSTAT3_Treg 2_pSTAT5_Tc 6_pSTAT1_Tc 6_pSTAT3_Tc 10_pSTAT3_Tc CRC_CIPS_31 4.98 NA 3.32 NA 1.04 NA CRC_CIPS_32 7.2 NA 3.37 NA 1.25 NA CRC_CIPS_33 5.73 NA 3.19 NA 1.16 NA CRC_CIPS_34 4.03 NA 2.53 NA 1.12 NA CRC_CIPS_35 5.05 1.93 4.13 1.08 1.26 1.65 CRC_CIPS_36 5.94 3.91 4 1.12 1.17 2.83 CRC_CIPS_37 6.59 3.81 4.55 NA 1.09 2.24 CRC_CIPS_38 7.48 7.14 5.19 NA 1.28 4.38 CRC_CIPS_39 4.18 4.02 4.43 NA 1.18 3.27 CRC_CIPS_40 4.76 2.62 2.8 NA 0.95 1.53

TABLE-US-00007 TABLE 7 IL- IL- IL- IL- IL- IL- ID\CIPS 2_pSTAT5_Th 6_pSTAT1_Th 6_pSTAT3_Th 10_pSTAT3_Th 2_pSTAT5_Treg 6_pSTAT1_Treg CON_CIPS_01 3.7 9.48 4.93 2.27 6.67 6.75 CON_CIPS_02 3.13 7.39 4.54 2.15 8.86 7.39 CON_CIPS_03 4.76 15.4 4.67 2.38 12.1 13.4 CON_CIPS_04 5.22 16 2.71 1.54 12 19.4 CON_CIPS_05 3.57 15 3.41 1.68 6.85 12.9 CON_CIPS_06 2.73 13.3 4.63 2.06 5.56 6.72 CON_CIPS_07 2.77 7.91 4.13 2.06 5.79 4.61 CON_CIPS_08 2.31 9.55 3.55 2 4.63 7.9 CON_CIPS_09 8.92 5.95 5.35 2.91 23.8 4.88 CON_CIPS_10 9.88 3.46 6.47 2.49 22 3.97 CON_CIPS_11 7.47 3.16 4.93 2.76 19.6 4.55 CON_CIPS_12 3.42 8.27 3.05 1.63 4.99 6.89 CON_CIPS_13 2.77 10.5 3.13 1.83 4.21 9.75 CON_CIPS_14 2.3 10.3 4.09 2.17 4.65 9.03 CON_CIPS_15 3.91 9.11 4.92 1.49 10.9 5.66 CON_CIPS_16 4.86 15.4 4.06 1.49 10.4 8.41 IL- IL- IL- IL- IL- IL- ID\CIPS 6_pSTAT3_Treg 10_pSTAT3_Treg 2_pSTAT5_Tc 6_pSTAT1_Tc 6_pSTAT3_Tc 10_pSTAT3_Tc CON_CIPS_01 5.43 3.8 2.42 7.69 3.85 2.22 CON_CIPS_02 5.15 3.42 2.98 1.17 1.36 2.62 CON_CIPS_03 6 4.14 6.17 1.71 1.8 3.25 CON_CIPS_04 3.55 2.45 5.55 15.5 2.67 1.83 CON_CIPS_05 3.57 2.46 3.46 2.92 2.33 1.75 CON_CIPS_06 4.46 3.06 2.87 1.34 1.48 2.61 CON_CIPS_07 4.26 2.92 2.45 1.63 1.91 2.21 CON_CIPS_08 4.07 2.78 1.92 2.88 2.17 1.95 CON_CIPS_09 10.3 8.5 8.67 1.4 1.33 4.14 CON_CIPS_10 8.91 5.3 7.39 0.92 1.07 3.3 CON_CIPS_11 6.25 4.72 4.99 1.1 1.28 3.36 CON_CIPS_12 2.84 1.84 2.93 1.53 1.39 1.68 CON_CIPS_13 2.68 2.14 3.19 1.33 1.42 2.03 CON_CIPS_14 3.72 2.67 2.78 1.53 1.59 2.36 CON_CIPS_15 5.17 2.23 3.29 1.67 1.74 1.75 CON_CIPS_16 4.04 2.4 4.51 2.4 2.32 1.54

TABLE-US-00008 TABLE 8 IL- IL- IL- IL- IL- IL- ID/CIPS 2_pSTAT5_Th 6_pSTAT1_Th 6_pSTAT3_Th 10_pSTAT3_Th 2_pSTAT5_Treg 6_pSTAT1_Treg CRC_CIPS_01 NA 1 0.72 NA 1.25 CRC_CIPS_02 NA 2.05 1.77 1.39 NA 2.2 CRC_CIPS_03 NA 1.56 1.98 1.09 NA 1.48 CRC_CIPS_04 NA 1.34 1.16 1.51 NA 1.49 CRC_CIPS_05 NA 1.01 0.84 1.61 NA 1.11 CRC_CIPS_06 NA 1.35 0.91 2.28 NA 1.67 CRC_CIPS_07 NA 1.03 1.2 2.02 NA 1.15 CRC_CIPS_08 NA 1.6 1.46 3.37 NA 1.8 CRC_CIPS_09 NA 0.94 1.13 2.42 NA 0.84 CRC_CIPS_10 NA 0.94 1.3 2.58 NA 1 CRC_CIPS_11 NA 1.12 1.26 1.46 NA 1.1 CRC_CIPS_12 NA 1.04 1.14 2.01 NA 1.08 CRC_CIPS_13 NA 0.59 1.18 1.37 NA 0.59 CRC_CIPS_14 NA 1.13 1.92 2.01 NA 1.45 CRC_CIPS_15 NA 1.24 1.01 2 NA 1.17 IL- IL- IL- IL- IL- IL- ID/CIPS 6_pSTAT3_Treg 10_pSTAT3_Treg 2_pSTAT5_Tc 6_pSTAT1_Tc 6_pSTAT3_Tc 10_pSTAT3_Tc CRC_CIPS_01 0.65 NA 0.97 0.87 CRC_CIPS_02 1.7 1.48 NA 1.29 1.13 1.48 CRC_CIPS_03 2.06 1.14 NA 0.94 1.26 1.17 CRC_CIPS_04 1.47 1.61 NA 1.04 0.97 1.78 CRC_CIPS_05 0.96 2.04 NA 1.05 0.93 2.16 CRC_CIPS_06 1.44 3 NA 1.23 1.06 4.3 CRC_CIPS_07 1.27 2.37 NA 1.02 1.03 2.43 CRC_CIPS_08 1.7 3.5 NA 1.11 1.27 6.12 CRC_CIPS_09 0.96 2.22 NA 1.06 1.01 3.49 CRC_CIPS_10 1.38 2.75 NA 0.85 1.23 4.65 CRC_CIPS_11 1.46 0.55 NA 1.42 1.46 3.43 CRC_CIPS_12 1.14 2.13 NA 1.42 1.01 2.07 CRC_CIPS_13 1.46 1.55 NA 0.48 0.98 1.49 CRC_CIPS_14 2.91 3.1 NA 0.8 1.12 2.22 CRC_CIPS_15 1.34 2.56 NA 1.12 1.07 2.85

TABLE-US-00009 TABLE 9 IL- IL- IL- IL- IL- IL- ID/CIPS 2_pSTAT5_Th 6_pSTAT1_Th 6_pSTAT3_Th 10_pSTAT3_Th 2_pSTAT5_Treg 6_pSTAT1_Treg CRC_CIPS_16 NA 1.85 2.41 1.9 NA 2.45 CRC_CIPS_17 NA 0.89 1.12 1.52 NA 0.92 CRC_CIPS_18 NA 0.94 1.46 2.28 NA 0.82 CRC_CIPS_19 NA 0.99 1.26 2.33 NA 1.28 CRC_CIPS_20 NA 1.73 3.32 1.87 NA 3.22 CRC_CIPS_21 NA 1.39 1.81 2.2 NA 8.27 CRC_CIPS_22 NA 1.65 2.32 1.93 NA 2.24 CRC_CIPS_23 NA 0.94 1.06 3.72 NA 2 CRC_CIPS_24 NA 1.53 1.73 2.35 NA 1.68 CRC_CIPS_25 3.33 NA 1.86 1.68 12.7 NA CRC_CIPS_26 3.79 1.39 1.42 2.53 9.69 1.71 CRC_CIPS_27 3 1.05 1.26 1.4 5.93 1.04 CRC_CIPS_28 2.84 1.2 1.2 2.8 5.21 2.23 CRC_CIPS_29 4.43 1.17 1.15 1.95 6.08 1.96 CRC_CIPS_30 2.53 NA NA NA 4.52 NA IL- IL- IL- IL- IL- IL- ID/CIPS 6_pSTAT3_Treg 10_pSTAT3_Treg 2_pSTAT5_Tc 6_pSTAT1_Tc 6_pSTAT3_Tc 10_pSTAT3_Tc CRC_CIPS_16 3.05 2.6 NA 1.08 1.05 2.66 CRC_CIPS_17 1.37 2.04 NA 0.77 0.92 1.4 CRC_CIPS_18 1.49 2.92 NA 0.89 1.25 2.78 CRC_CIPS_19 2.12 4.12 NA 0.89 1.08 2.19 CRC_CIPS_20 4.96 2.6 NA 1.08 1.21 1.87 CRC_CIPS_21 8.36 7.86 NA 1.1 1.22 3.74 CRC_CIPS_22 3 3.22 NA 0.7 0.98 1.9 CRC_CIPS_23 0.93 7.33 NA 1 1.11 4.56 CRC_CIPS_24 2.58 3.96 NA 1.21 1.2 2.34 CRC_CIPS_25 4.61 5.56 4.69 NA 1.12 2.27 CRC_CIPS_26 4.89 10.6 4.08 1.07 1.06 3 CRC_CIPS_27 1.3 1.68 2.4  0.92 1.04 1.45 CRC_CIPS_28 2.56 4.44 3.04 1.04 1.05 2.98 CRC_CIPS_29 1.78 2.54 4.71 1.12 1.13 2.57 CRC_CIPS_30 NA NA 2.3  NA NA NA

TABLE-US-00010 TABLE 10 IL- IL- IL- IL- IL- IL- ID/CIPS 2_pSTAT5_Th 6_pSTAT1_Th 6_pSTAT3_Th 10_pSTAT3_Th 2_pSTAT5_Treg 6_pSTAT1_Treg CRC_CIPS_31 2.1 NA 1.06 NA 4.93 NA CRC_CIPS_32 2.89 NA 1.08 NA 6.79 NA CRC_CIPS_33 3.04 NA 1.06 NA 9.39 NA CRC_CIPS_34 3.1 NA NA NA 8.61 NA CRC_CIPS_35 1.28 NA NA NA 1.89 NA CRC_CIPS_36 2.35 NA 1.21 1.05 4.21 NA CRC_CIPS_37 3.57 NA 1.22 1.62 7.72 NA CRC_CIPS_38 1.85 NA 1.32 1.34 7.82 NA CRC_CIPS_39 1.86 NA 1.17 1.27 4.45 NA CRC_CIPS_40 2.97 0.99 1.15 1.31 6.14 1.41 IL- IL- IL- IL- IL- IL- ID/CIPS 6_pSTAT3_Treg 10_pSTAT3_Treg 2_pSTAT5_Tc 6_pSTAT1_Tc 6_pSTAT3_Tc 10_pSTAT3_Tc CRC_CIPS_31 2.1 NA 2.66 NA 0.92 NA CRC_CIPS_32 1.28 NA 3.07 NA 1.09 NA CRC_CIPS_33 1.1 NA 2.62 NA 1.09 NA CRC_CIPS_34 NA NA 2.59 NA NA NA CRC_CIPS_35 NA NA 1.34 NA NA NA CRC_CIPS_36 1.71 NA 2.04 NA 1.11 1.15 CRC_CIPS_37 1.68 2.53 3.02 NA 1.13 1.61 CRC_CIPS_38 2.11 2.32 1.84 NA 1.38 1.49 CRC_CIPS_39 1.2 1.65 2.08 NA 1.09 1.38 CRC_CIPS_40 1.67 1.49 3.14 1.01 1.08 1.26

TABLE-US-00011 TABLE 11 IL- IL- IL- IL- IL- IL- ID/CIPS 2_pSTAT5_Th 6_pSTAT1_Th 6_pSTAT3_Th 10_pSTAT3_Th 2_pSTAT5_Treg 6_pSTAT1_Treg CON_CIPS_01 NA NA NA NA NA NA CON_CIPS_02 NA NA NA NA NA NA CON_CIPS_03 NA NA NA NA NA NA CON_CIPS_04 NA NA NA NA NA NA CON_CIPS_05 NA NA NA NA NA NA CON_CIPS_06 NA NA NA NA NA NA CON_CIPS_07 NA NA NA NA NA NA CON_CIPS_08 NA NA NA NA NA NA CON_CIPS_09 NA NA NA NA NA NA CON_CIPS_10 NA NA NA NA NA NA CON_CIPS_11 NA NA NA NA NA NA CON_CIPS_12 NA NA NA NA NA NA CON_CIPS_13 NA NA NA NA NA NA CON_CIPS_14 NA NA NA NA NA NA CON_CIPS_15 NA NA NA NA NA NA CON_CIPS_16 NA NA NA NA NA NA IL- IL- IL- IL- IL- IL- ID/CIPS 6_pSTAT3_Treg 10_pSTAT3_Treg 2_pSTAT5_Tc 6_pSTAT1_Tc 6_pSTAT3_Tc 10_pSTAT3_Tc CON_CIPS_01 NA NA NA NA NA NA CON_CIPS_02 NA NA NA NA NA NA CON_CIPS_03 NA NA NA NA NA NA CON_CIPS_04 NA NA NA NA NA NA CON_CIPS_05 NA NA NA NA NA NA CON_CIPS_06 NA NA NA NA NA NA CON_CIPS_07 NA NA NA NA NA NA CON_CIPS_08 NA NA NA NA NA NA CON_CIPS_09 NA NA NA NA NA NA CON_CIPS_10 NA NA NA NA NA NA CON_CIPS_11 NA NA NA NA NA NA CON_CIPS_12 NA NA NA NA NA NA CON_CIPS_13 NA NA NA NA NA NA CON_CIPS_14 NA NA NA NA NA NA CON_CIPS_15 NA NA NA NA NA NA CON_CIPS_16 NA NA NA NA NA NA

[0073] As can be seen in FIGS. 1 to 5 and Tables 4 to 11, IL-6-induced pSTAT1 and pSTAT3 were significantly decreased in tumor infiltrating lymphocytes (TILs). It was also identified that the cytokine-induced phosphorylated STAT signature (CIPS signature) of the peripheral blood lymphocytes reflected the CIPS signature of TILs.

[0074] Such similar phenomenon was observed in IL-6-induced pSTAT1 of Helper T cells, regulatory T cells, and cytotoxic T cells, as well as in pSTAT3 of Tc cells. However, unusually, IL-10-induced pSTAT3 was similar in both TILs and healthy control cells, but significantly increased in the peripheral blood lymphocytes of the patients.

[0075] Overall, it was identified that the levels of intracellular STAT protein phosphorylation (pSTAT) by IL-6 and IL-10 were statistically very different between the immune cells derived from tumor tissue of colorectal cancer patients and the immune cells derived from the blood of normal persons and that there was phosphorylation at the medium levels therebetween in the immune cells derived from the blood of the colorectal cancer patients.

Example 2: In-Vitro Co-Culture Experiment Using Cancer Cell Lines

[0076] In order to investigate whether the findings observed in the patient-derived immune cells were caused by tumor cells, HCT116 (American Type Culture Collection, ATCC CCL-247), which is a colorectal cancer cell line, and mononuclear cells of the peripheral blood of normal persons were co-cultured in vitro. The cell mixing conditions and the number of cells in the in-vitro co-culture experiment are shown in Table 6. The levels of STAT protein phosphorylation for each cytokine were measured, the results are shown in FIG. 6 and Tables 13 to 15. (Table 13: Th, Table 14: Treg, and Table 15: Tc)

[0077] Co-culturing was performed under two conditions. That is, while the ratios of tumor cells and mononuclear cells of normal persons were 1:1 and 1:10, the first condition was that the two kinds of cells were directly mixed and co-cultured in one experimental well (direct), and the second condition was that, in an experimental well with a septum (transwell), the tumor cells were placed in the upper layer of the septum and the mononuclear cells of normal persons were placed in the lower layer and co-cultured (indirect).

TABLE-US-00012 TABLE 12 Number of mononuclear Ratio Number of tumor cells cells of normal persons 1:1 3 × 10.sup.6 3 × 10.sup.6 1:10 3 × 10.sup.5 3 × 10.sup.6

TABLE-US-00013 TABLE 13 ID/CIPS IL-2_pSTAT5_Th IL-6_pSTAT1_Th IL-6_pSTAT3_Th IL-10_pSTAT3_Th PBMC_01 11.72 5.98 PBMC_02 2.31 2.94 1.96 1.02 PBMC_03 3.86 1.97 1.62 1.08 PBMC_04 3.92 1.88 1.72 0.87 PBMC_05 5.51 5.62 3.07 1.55 PBMC_06 6.32 7.68 2.49 1.32 PBMC_07 6.88 2.03 2.76 1.41 PBMC_08 3.68 5.31 3.80 1.91 PBMC_09 8.03 3.10 2.34 1.67 PBMC_10 7.00 1.82 1.45 1.37 PBMC_11 8.11 1.05 1.58 1.38 PBMC_12 4.55 2.99 1.46 1.36 PBMC_13 4.04 5.49 2.29 1.57 PBMC_14 7.41 7.54 2.55 1.68 PBMC_HCT116_R1_Direct_01 3.50 0.09 0.69 1.15 PBMC_HCT116_R1_Direct_02 2.23 1.47 1.12 1.15 PBMC_HCT116_R1_Direct_03 2.69 1.17 1.20 0.95 PBMC_HCT116_R1_Direct_04 2.39 1.20 1.11 1.12 PBMC_HCT116_R1_Direct_05 2.71 1.28 1.18 1.41 PBMC_HCT116_R1_Direct_06 5.29 1.26 1.24 1.28 PBMC_HCT116_R1_Direct_07 3.07 1.58 1.34 1.22 PBMC_HCT116_R1_Direct_08 4.76 1.30 0.90 0.88 PBMC_HCT116_R10_Direct_01 2.80 0.27 0.68 0.91 PBMC_HCT116_R10_Direct_02 1.70 1.12 1.28 1.02 PBMC_HCT116_R10_Direct_03 2.47 1.68 1.43 1.09 PBMC_HCT116_R10_Direct_04 2.53 1.90 1.56 1.22 PBMC_HCT116_R10_Direct_05 1.71 1.70 1.21 1.39 PBMC_HCT116_R10_Direct_06 4.16 1.38 1.36 1.16 PBMC_HCT116_R10_Direct_07 2.49 1.55 1.16 1.30 PBMC_HCT116_R10_Direct_08 3.80 0.97 1.21 1.53 PBMC_HCT116_R10_Direct_09 5.46 1.08 1.22 1.14 PBMC_HCT116_R10_Direct_10 3.29 0.87 0.99 1.28 PBMC_HCT116_R10_Direct_11 2.71 0.95 1.05 1.12 PBMC_HCT116_R10_Direct_12 4.00 0.86 1.15 1.12 PBMC_HCT116_R10_Indirect_01 7.26 1.09 1.30 1.07 PBMC_HCT116_R10_Indirect_02 7.16 1.14 1.30 1.28 PBMC_HCT116_R10_Indirect_03 2.63 1.04 0.97 1.14 PBMC_HCT116_R10_Indirect_04 5.34 1.01 1.16 1.30

TABLE-US-00014 TABLE 14 ID/CIPS IL-2_pSTAT5_Treg IL-6_pSTAT1_Treg IL-6_pSTAT3_Treg IL-10_pSTAT3_Treg PBMC_01 30.51 6.61 PBMC_02 4.01 2.29 1.75 1.48 PBMC_03 3.25 1.98 5.70 2.10 PBMC_04 10.92 9.03 1.43 0.90 PBMC_05 13.47 3.28 3.02 1.80 PBMC_06 10.96 10.74 3.28 2.57 PBMC_07 11.54 3.29 2.44 1.79 PBMC_08 6.27 4.53 2.80 2.28 PBMC_09 7.68 4.75 3.22 2.10 PBMC_10 11.00 1.63 1.35 1.41 PBMC_11 8.19 0.97 1.52 1.63 PBMC_12 4.82 1.63 1.52 1.50 PBMC_13 1.74 6.84 2.98 2.56 PBMC_14 6.36 7.70 2.94 2.06 PBMC_HCT116_R1_Direct_01 4.98 −0.12 0.52 1.78 PBMC_HCT116_R1_Direct_02 2.72 1.15 1.69 1.77 PBMC_HCT116_R1_Direct_03 1.73 0.96 1.45 1.28 PBMC_HCT116_R1_Direct_04 12.00 1.15 1.17 1.38 PBMC_HCT116_R1_Direct_05 10.88 2.14 1.27 2.15 PBMC_HCT116_R1_Direct_06 7.77 1.72 0.98 1.15 PBMC_HCT116_R1_Direct_07 8.14 1.65 1.33 1.36 PBMC_HCT116_R1_Direct_08 14.60 1.31 0.94 1.02 PBMC_HCT116_R10_Direct_01 4.94 0.11 0.51 1.47 PBMC_HCT116_R10_Direct_02 1.61 1.15 1.45 1.24 PBMC_HCT116_R10_Direct_03 1.16 2.26 1.93 1.34 PBMC_HCT116_R10_Direct_04 8.56 3.58 1.62 1.26 PBMC_HCT116_R10_Direct_05 4.27 1.45 1.16 1.68 PBMC_HCT116_R10_Direct_06 6.02 3.75 1.37 1.29 PBMC_HCT116_R10_Direct_07 5.20 1.89 1.27 1.74 PBMC_HCT116_R10_Direct_08 7.94 0.87 1.24 1.54 PBMC_HCT116_R10_Direct_09 6.89 0.96 0.96 1.31 PBMC_HCT116_R10_Direct_10 6.72 0.80 1.21 1.37 PBMC_HCT116_R10_Direct_11 2.27 0.95 1.02 1.25 PBMC_HCT116_R10_Direct_12 3.92 1.01 1.15 1.26 PBMC_HCT116_R10_Indirect_01 8.50 0.93 1.24 1.04 PBMC_HCT116_R10_Indirect_02 3.20 1.36 1.42 1.59 PBMC_HCT116_R10_Indirect_03 1.26 1.05 0.94 1.24 PBMC_HCT116_R10_Indirect_04 2.68 1.27 1.27 1.46

TABLE-US-00015 TABLE 15 ID/CIPS IL-2_pSTAT5_Tc IL-6_pSTAT1_Tc IL-6_pSTAT3_Tc IL-10 pSTAT3_Tc PBMC_01 1.63 1.76 PBMC_02 3.32 0.36 0.12 1.25 PBMC_03 6.04 1.22 1.06 1.27 PBMC_04 0.83 1.14 1.09 1.13 PBMC_05 6.93 1.37 1.44 1.65 PBMC_06 6.63 1.66 1.98 1.61 PBMC_07 7.88 0.94 1.00 1.70 PBMC_08 3.51 1.48 1.78 1.92 PBMC_09 4.58 1.27 1.41 2.13 PBMC_10 6.48 1.21 1.00 1.76 PBMC_11 7.95 0.95 1.11 1.70 PBMC_12 4.86 1.12 1.05 2.39 PBMC_13 4.50 2.06 1.98 1.82 PBMC_14 5.40 1.53 1.44 2.00 PBMC_HCT116_R1_Direct_01 4.15 −0.18 0.06 1.81 PBMC_HCT116_R1_Direct_02 4.22 1.24 1.00 1.39 PBMC_HCT116_R1_Direct_03 0.55 0.98 1.05 1.42 PBMC_HCT116_R1_Direct_04 5.71 1.00 1.01 1.57 PBMC_HCT116_R1_Direct_05 5.53 1.00 1.00 1.92 PBMC_HCT116_R1_Direct_06 5.64 1.07 1.04 1.52 PBMC_HCT116_R1_Direct_07 3.64 1.25 1.11 1.38 PBMC_HCT116_R1_Direct_08 9.34 1.21 0.89 1.21 PBMC_HCT116_R10_Direct_01 4.06 −0.06 0.03 1.52 PBMC_HCT116_R10_Direct_02 3.92 0.99 1.09 1.28 PBMC_HCT116_R10_Direct_03 1.94 1.18 1.10 1.53 PBMC_HCT116_R10_Direct_04 5.05 1.19 1.29 1.54 PBMC_HCT116_R10_Direct_05 2.59 1.39 1.06 1.57 PBMC_HCT116_R10_Direct_06 4.36 1.14 0.90 1.57 PBMC_HCT116_R10_Direct_07 2.56 1.30 1.16 1.53 PBMC_HCT116_R10_Direct_08 3.64 0.90 1.09 1.88 PBMC_HCT116_R10_Direct_09 5.91 1.01 1.01 1.17 PBMC_HCT116_R10_Direct_10 7.27 0.79 0.96 1.35 PBMC_HCT116_R10_Direct_11 4.39 0.98 0.98 1.22 PBMC_HCT116_R10_Direct_12 4.22 1.00 1.03 1.32 PBMC_HCT116_R10_Indirect_01 7.69 1.11 1.21 1.17 PBMC_HCT116_R10_Indirect_02 7.38 1.00 1.13 1.68 PBMC_HCT116_R10_Indirect_03 3.39 1.04 0.98 1.35 PBMC_HCT116_R10_Indirect_04 5.23 0.93 1.05 1.56

[0078] As can be seen from FIG. 6 and Tables 13 to 15, it was observed that in both cases of direct contact culture or indirect culture with tumor cells, abnormality was induced in cytokine signaling in peripheral lymphocytes of normal persons similar to T cells of the tumor infiltrating environment. In addition, this was not affected by the ratio of normal cells and tumor cell lines in co-culture or the manner of direct or indirect culture (1:1 and 1:10). However, the IL-2-induced pSTAT5 signatures were not observed to show significant decreases in all of Th cells, Tc cells, and Treg cells. Especially, almost similar levels of phosphorylation in Treg cells, suggesting that no functional abnormality occurred in response to IL-2 in the STAT signaling system even in the tumor environment. Overall, similar to the results in actual patients, the levels of pSTAT by IL-6 and IL-10 were statistically significantly different, and mainly decreased in the immune T cells cultured with tumor cells.

Test Example: Cluster Analysis

[0079] CIPS signatures of 30 CRC patients and 15 healthy persons were subjected to cluster analysis. Specifically, the distances between sample results were analyzed by the hierarchical clustering method using R language, and in order to schematize the distances, a heatmap was drawn using the gplot R package. The results are shown in FIG. 7.

[0080] As can be seen in FIG. 7, between the two groups, there were distinct differences in the IL-10-induced pSTAT3 signatures on Th, Treg, and Tc cells.

Test Example: Principle Component Aanalysis

[0081] Analysis was performed using the principal component analysis package embedded in software through the R language, and the results are shown in FIGS. 8 and 9.

[0082] As can be seen from FIG. 8, there was different types of clustering between the colorectal cancer patient group and the normal person group. Especially, as confirmed in FIG. 9., the colorectal cancer patient group and the normal person group can be well distinguished by only the numerical values of IL-6-induced pSTAT3 on Tc cells and IL-10-induced pSTAT3 on Th cells.

Test Example: Statistical Method and Leave-One-Out Cross Validation (LOOCV)

[0083] Two CIPS patterns were identified through a statistical method and leave-one-out cross validation. Specifically, two features with the highest mean decrease Gini (MDG) value were selected among several CIPS features by using the random Forest package of R language, and a model was established using the logistic regression function embedded in R language. LOOCV was performed through R coding, and the ROCR package was utilized to plot an ROC curve. The results are shown in FIGS. 10 to 11.

[0084] As can be confirmed from FIGS. 10 and 11, the use of IL-6-induced pSTAT3 on Tc cells and IL-10-induced pSTAT3 on Th cells can discriminate the tumor group and the normal group, and the AUC was 0.88. This was reproduced in the validation cohort with 15 CRC patients and 17 healthy persons (AUC 0.941). When training cohort and validation cohort were synthetically analyzed, the AUC was 0.938.

[0085] The discrimination between groups was analyzed by applying the carcinoembryonic antigen (CEA) protein marker, known as an existing CRC tumor marker, to both the two CIPS patterns, that is, IL-6-induced pSTAT3 on Tc cells and IL-10-induced pSTAT3 on Th cells. Specifically, it was predicted whether each patient was a cancer patient with a probability of 50% or more by using the previously established model, and the results were compared with the actually labeled (cancer patient vs. healthy person) values. The tumor patients were essentially tested for CEA, and thus the previously obtained test value and two markers derived in this experiment were analyzed by the same manner and model, and the results are shown in FIG. 13 and Table 16.

TABLE-US-00016 TABLE 16 CRC patients Health controls Positive predicted 41 4 Negative predicted 4 29

[0086] As can be seen from FIG. 13 and Table 16, the AUC was identified to be excellent, 0.958, proving that the diagnostic use of the two markers in combination can maximize the utility thereof. The positive and negative predictive values were shown as 91% and 88%, respectively.

Review

[0087] Combining the above results, it was confirmed that the measurement values of STAT phosphorylation by interleukin in immune T cells derived from blood were different between normal persons and colorectal cancer patients, and the combination of these values enables a technique capable of diagnosing a colorectal patient through the blood. Even the use of two markers in combination showed excellent performance with sensitivity of 91% and specificity of 88%, and the use thereof in combination with existing known colorectal cancer markers can further improve the diagnostic sensitivity and specificity thereof.

INDUSTRIAL APPLICABILITY

[0088] The present disclosure relates to a marker for diagnosing colorectal cancer, a method for providing information required for diagnosis of colorectal cancer by using the same, and a method for providing information for monitoring a therapeutic response of colorectal cancer by using the same.