PROTEIN SIGNATURE FOR THE DIAGNOSIS OF COLORECTAL CANCER AND/OR PRE-CANCEROUS STAGE THEREOF

Abstract

The present invention refers to an in vitro method for the diagnosis of colorectal cancer and/or pre-cancerous stage thereof.

Claims

1-8. (canceled)

9. A method for detecting a protein biomarker in a biological sample from a subject at risk of developing colorectal cancer or a pre-cancerous stage of colorectal cancer, said method comprising: (a) contacting the biological sample with a reagent capable of specifically binding Flt3L and a reagent capable of specifically binding CYFRA21-1; and (b) measuring level of Flt3L and CYFRA21-1 in the biological sample.

10. The method of claim 9, further comprising measuring level of AREG.

11. The method of claim 10, further comprising measuring level of ErbB4 or CLEC2C.

12. The method of claim 9, wherein the reagent capable of specifically binding Flt3L and the reagent capable of specifically binding CYFRA21-1 are each an enzyme-linked immunosorbent assay (ELISA) reagent or a chemiluminescence immunoassay (CLIA) reagent.

13. The method of claim 9, wherein the pre-cancerous stage of colorectal cancer is advanced colorectal adenoma.

14. The method of claim 9, wherein said biological sample is a minimally invasive biological sample.

15. The method of claim 14, wherein said minimally invasive biological sample is a blood sample, a serum sample or a plasma sample.

16. The method of claim 9, further comprising performing colonoscopy on the subject.

17. A method for treating a subject having colorectal cancer or a pre-cancerous stage of colorectal cancer, the method comprising administering to the subject a therapy for colorectal cancer or pre-cancerous stage of colorectal cancer, wherein a biological sample from the subject has been determined to have a deviation or a variation in the level of Flt3L and CYFRA21-1 as compared to a control sample.

18. The method of claim 17, wherein the biological sample from the subject has been determined to have a decreased level of Flt3L as compared to a control sample and an increased level of CYFRA21-1 as compared to a control sample.

19. The method of claim 17, wherein the biological sample has been further determined to have a deviation or a variation in the level of AREG as compared to a control sample.

20. The method of claim 19, wherein the biological sample has been further determined to have an increased level of AREG as compared to a control sample.

21. The method of claim 17, wherein the biological sample has been further determined to have a deviation or a variation in the level of ErbB4 or CLEC2C as compared to a control sample.

22. The method of claim 21, wherein the biological sample has been further determined to have a decreased level of ErbB4 or an increased level of CLEC2C as compared to a control sample.

23. The method of claim 17, comprising, prior to therapy, performing colonoscopy on the subject.

24. The method of claim 17, wherein said therapy comprises removing colorectal cancer or a polyp.

25. The method of claim 17, wherein said biological sample is a minimally invasive biological sample.

26. The method of claim 25, wherein said biological sample is a blood sample, a serum sample or a plasma sample.

27. A kit comprising reagents for determining the level of protein biomarkers Flt3L and CYFRA21-1 and instructions for use.

Description

BRIEF DESCRIPTION OF THE FIGURES

[0042] FIG. 1. Receiver-operating-characteristic (ROC) curve for: A) [F1t3L and CYFRA21-1] in colorectal cancer. Area Under Curve (AUC)=0.865. B) [F1t3L and CYFRA21-1] in advanced colorectal adenoma. Area Under Curve (AUC)=0.606. X axis represents Specificity. Y axis represents Sensitivity.

[0043] FIG. 2. Receiver-operating-characteristic (ROC) curve for: A) [F1t3L and CYFRA21-1 and AREG] in colorectal cancer. Area Under Curve (AUC)=0.899. B) [F1t3L and CYFRA21-1 and AREG] in advanced colorectal adenoma. Area Under Curve (AUC)=0.720. X axis represents Specificity. Y axis represents Sensitivity.

[0044] FIG. 3. Receiver-operating-characteristic (ROC) curve for: A) [F1t3L and CYFRA21-1 and AREG and ErbB4] in colorectal cancer. Area Under Curve (AUC)=0.931. B) [F1t3L and CYFRA21-1 and AREG and ErbB4] in advanced colorectal adenoma. Area Under Curve (AUC)=0.707. X axis represents Specificity. Y axis represents Sensitivity.

[0045] FIG. 4. Receiver-operating-characteristic (ROC) curve for: A) [F1t3L and CYFRA21-1 and AREG and CLEC2C] in colorectal cancer. Area Under Curve (AUC)=0.915. B) [F1t3L and CYFRA21-1 and AREG and CLEC2C] in advanced colorectal adenoma. Area Under Curve (AUC)=0.727. X axis represents Specificity. Y axis represents Sensitivity.

[0046] FIG. 5. Receiver-operating-characteristic (ROC) curve for: A) [AREG and CYFRA21-1] in colorectal cancer. Area Under Curve (AUC)=0.878. B) [AREG and CYFRA21-1] in advanced colorectal adenoma. Area Under Curve (AUC)=0.722. X axis represents Specificity. Y axis represents Sensitivity.

[0047] FIG. 6. Receiver-operating-characteristic (ROC) curve for: A) [AREG and CYFRA21-1 and F1t3L and ErbB4] in colorectal cancer. Area Under Curve (AUC)=0.931. B) [AREG and CYFRA21-1 and F1t3L and ErbB4] in advanced colorectal adenoma. Area Under Curve (AUC)=0.707. X axis represents Specificity. Y axis represents Sensitivity.

[0048] FIG. 7. Receiver-operating-characteristic (ROC) curve for: A) [AREG and CYFRA21-1 and F1t3L and CLEC2C] in colorectal cancer. Area Under Curve (AUC)=0.915. B) [AREG and CYFRA21-1 and F1t3L and CLEC2C] in advanced colorectal adenoma. Area Under Curve (AUC)=0.727. X axis represents Specificity. Y axis represents Sensitivity.

[0049] FIG. 8. Receiver-operating-characteristic (ROC) curve for: A) [AREG and CYFRA21-1 and CD147 and HGFR] in colorectal cancer. Area Under Curve (AUC)=0.888. B) [AREG and CYFRA21-1 and CD147 and HGFR] in advanced colorectal adenoma. Area Under Curve (AUC)=0.769. X axis represents Specificity. Y axis represents Sensitivity.

DETAILED DESCRIPTION OF THE INVENTION

Example 1. Material and Methods

Example 1.1. Population of Study

[0050] A total of 96 subjects from eight Spanish hospitals (Hospital de Burgos, Hospital de Vigo, Hospital de Donosti, Hospital de Ourense, Hospital del Bierzo, Hospital de Beltvigte and Hospital de Zaragoza) were prospectively included in this study: 64 patients newly diagnosed with sporadic colorectal neoplasia (32 with CRC and 32 with AA) and 32 healthy individuals without personal history of any cancer and with a recent colonoscopy confirming the lack of colorectal neoplastic lesions. Patients with AA were those with adenomas having a size of at least 10 mm or histologically having high grade dysplasia or >20% villous component. The characteristics of participants are shown in Table 1. Blood samples were collected prior to endoscopy or surgery in all individuals.

TABLE-US-00002 TABLE 1 Cases Control (CTL) AA CRC TOTAL Mean age (SD) 64.3 (44-86) 65.1 (52-88) 71.6 (54-85) 67 (44-88) GENDER Male 13 18 18 49 (51%) Femal e 19 14 14 47 (49%) COLORECTAL FEATURES TNM stage I 4 II 9 III 10 IV 6 Unknown 3 Location Ascending colon and cecum 10 Descending colon and sigma 12 Transverse colon 3 Rectum 3 Unknown 4 ADVANCED COLORECTAL ADENOMA FEATURES Size = >10 mm 28 Small AA (<=15 mm) 19 Big AA (>15mm) 13 Mean size (mm) (SD) 18.8 No. AAs Mean (SD) 2.3 High-grade dysplasia Yes 9 No 21 Unknown 2 Villous component Yes 13 No 17 Unknown 2

Clinical-Pathological Characteristics of the Study Cohort

[0051] The study was approved by the Institutional Ethics Committee of each Hospital, and written informed consent was obtained from all participants in accordance with the Declaration of Helsinki.

Example 1.2. Sample Preparation

[0052] Ten mL of whole blood from each participant were collected in EDTA K2 containing tubes. Blood samples were placed at 4° C. until plasma separation. Samples were centrifuged at 1,600×g for 10 min at 4° C. to spin down blood cells, and plasma was transferred into new tubes, followed by further centrifugation at 16,000×g for 10 minutes at 4° C. to completely remove cellular components.

Example 1.3. Molecular Analysis

[0053] The concentration of the biomarkers in plasma samples was established using commercial ELISA (Enzyme-linked immunosorbent assay) and CLIA (Chemiluminescence immunoassay) test and following their corresponding instruction manual. HGFR and ErbB4 was analyzed with ELISA kit from Cloud clone Corp. Level of CD147, CLEC2C, Flt3L, and FasL was measured using ELISA Kit form Elabscience. In the case of the IFNgamma, ELISA kit from Abcam was used. Related to CLIA test, CYFRA21-1 and AREG were analyzed with CLIA test from Cloud Clone Corp.

Example 1.4. Data Quantification

[0054] For the protein quantification step the samples were processed with the corresponding kit (ELISA/CLIA) and distributed in experimental plates. Each plate contained also control data used to construct a standard curve. Fluorescence data obtained from each run (expressed as integer numbers) have been background corrected for each sample and quantified using a standard curve generated using a 2-degree polynomial regression model.

Example 1.5. Statistical Analysis

[0055] Three groups of individuals were considered in the analysis. CRC (Individuals diagnosed with colorectal cancer), AA (Individuals diagnosed with advanced adenoma) and CTL (Individuals with no disease).

[0056] Raw quantification data have been transformed by applying square root function, and then centering and scaling so that, after the transformation, each protein measure have mean 0 and standard deviation 1. Quantification values are summarized in Table 2 and Table 3, where each protein is described as median and interquartile range in the different groups considered.

[0057] Non-normality of the data was confirmed by Shapiro-Wilk test and, consequently, Wilcoxon rank-sum test was used to compare either CRC cases or AA cases against CTL individuals.

[0058] Diagnostic performance for the individual proteins and some of their combinations has been assessed by their receiver operating characteristic (ROC) curves, and the area under the ROC curves (AUC). Moreover, sensitivities, specificities, positive predictive and negative predictive values (PPV and NPV) for the different tests were calculated at the optimal cutoff point defined by the best Youden's Index (or equivalently, the point of the ROC that maximizes the sum of sensitivity and specificity).

[0059] Scores used for deriving the ROC-AUCs and the rest of performance values were obtained using univariate logistic regression model for the individual proteins and multivariate logistic regression models for the different combination of proteins considered. 95% CI for the AUCs was obtained with the DeLong methodology both in individual markers and combination of them.

Example 2. Results

Example 2.1. Individual Marker Results

[0060] Different metrics to evaluate the individual proteins were determined, also perming the following comparisons: CRC/AA vs CTL. It can be seen that AREG, CYFRA21-1 and Flt3L are significantly different between CRC and CTL groups and their AUC are significantly different from 0.5 (as their 95% confidence interval do not include 0.5). In the case of AA group, AREG also shows statistically differences compared to CTL group.

[0061] Table 2 and Table 3 shows metrics for individual proteins, including p-value from Wilcoxon test (p.Wilc), area under the ROC curve (AUC), and Sensitivity (Sens.), Specificity (Spec.), and positive (VPP) and negative (VPN) predictive values computed in the cut-off point of the ROC curve with the best Youden's index. The sign column indicates, for the biomarkers with p-value<0.25, whether high levels of the marker increase or decrease the risk of disease (+ and − respectively).

TABLE-US-00003 TABLE 2 CRC. vs. CTL p.Wilc. Sign AUC Sens. Spec. VPP VPN AREG 0.0008 + 0.744 (0.619, 0.868) 65.62 81.25 77.78 70.27 CD147 0.5280 0.546 (0.402, 0.691) 53.12 62.50 58.62 57.14 CLEC2C 0.2021 + 0.593 (0.452, 0.734) 93.75 28.12 56.60 81.82 CYFRA21-1 0.0000 + 0.795 (0.682, 0.909) 90.62 68.75 74.36 88.00 ErbB4 0.1177 − 0.614 (0.47, 0.758)  53.12 75.00 68.00 61.54 FasL 0.1859 + 0.598 (0.454, 0.741) 54.84 68.75 62.96 61.11 Flt3L 0.0191 −  0.67 (0.531, 0.809) 56.25 84.38 78.26 65.85 HGFR 0.1729 +  0.6 (0.452, 0.747) 65.62 68.75 67.74 66.67 IFNgamma 0.1537 + 0.604 (0.464, 0.745) 68.75 53.12 59.46 62.96

TABLE-US-00004 TABLE 3 AA. vs. CTL p.Wilc. Sign AUC Sens. Spec. VPP VPN AREG 0.0286 +  0.66 (0.525, 0.795) 87.50 40.62 59.57 76.47 CD147 0.1772 + 0.599 (0.458, 0.739) 87.50 31.25 56.00 71.43 CLEC2C 0.7831 0.521 (0.376, 0.665) 100.00 9.38 52.46 100.00 CYFRA21-1 0.1412 + 0.607 (0.467, 0.748) 90.62 37.50 59.18 80.00 ErbB4 0.3270 0.572 (0.427, 0.716) 50.00 71.88 64.00 58.97 FasL 0.5730 0.542 (0.394, 0.689) 74.19 46.88 57.50 65.22 Flt3L 0.8155 0.518 (0.372, 0.663) 43.75 75.00 63.64 57.14 HGFR 0.0678 + 0.633 (0.493, 0.773) 68.75 62.50 64.71 66.67 IFNgamma 0.8467 0.515 (0.37, 0.659)  81.25 31.25 54.17 62.50

Example 2.2. Best Combinations of Biomarkers

[0062] With the aim of improving individual diagnostic capability, combinations of proteins have been explored with the following procedure: Based on markers with p<0.25 either in CRC. vs. CTL (Table 3) or AA. vs. CTL (Table 4) comparisons, we used multivariate logistic regression to explore all possible combinations of two, three and four of these proteins taken at the same time.

[0063] Table 4, Table 5, Table 5 bis, Table 6 and Table 6 bis show the AUC achieved for the combinations of two, three and four biomarkers respectively, discriminating CRC vs CTL.

TABLE-US-00005 TABLE 4 Combinations of two biomarkers CRC vs CTL AUC AREG, CYFRA21-1 0.8779297 Flt3L, CYFRA21-1 0.8652344 CYFRA21-1, ErbB4 0.8359375 AREG, CLEC2C 0.8349609 CYFRA21-1, IFNgamma 0.8017578 CYFRA21-1, FasL 0.7993952 CLEC2C, CYFRA21-1 0.7988281 CYFRA21-1, HGFR 0.7919922 AREG, Flt3L 0.7832031 AREG, HGFR 0.7626953 AREG, IFNgamma 0.7431641 AREG, ErbB4 0.7324219 AREG, FasL 0.7247984 Flt3L, HGFR 0.6982422 CLEC2C, Flt3L 0.6953125 ErbB4, Flt3L 0.6914062 FasL, Flt3L 0.6814516 Flt3L, IFNgamma 0.6708984 ErbB4, IFNgamma 0.6318359 ErbB4, HGFR 0.6142578 CLEC2C, IFNgamma 0.6083984 CLEC2C, ErbB4 0.6064453 FasL, HGFR 0.6018145 HGFR, IFNgamma 0.5869141 CLEC2C, FasL 0.5866935 ErbB4, FasL 0.5856855 FasL, IFNgamma 0.5836694 CLEC2C, HGFR 0.5810547

TABLE-US-00006 TABLE 5 Combinations of three biomarkers for CRC vs CTL supporting the combination Flt3L + CYFRA21-1 AUC Flt3L, CYFRA21-1, AREG 0.8994141 AREG, CLEC2C, CYFRA21-1 0.8955078 AREG, CYFRA21-1, ErbB4 0.8955078 AREG, CYFRA21-1, FasL 0.8931452 Flt3L, CYFRA21-1 0.8847656 AREG, CYFRA21-1, IFNgamma 0.8837891 AREG, CYFRA21-1, HGFR 0.8759766 Flt3L, CYFRA21-1, CLEC2C 0.8681641 Flt3L, CYFRA21-1, FasL 0.8679435 Flt3L, CYFRA21-1, IFNgamma 0.8671875 Flt3L, CYFRA21-1, HGFR 0.8662109 AREG, CLEC2C, Flt3L 0.8427734 CYFRA21-1, ErbB4, HGFR 0.8388672 CYFRA21-1, ErbB4, IFNgamma 0.8359375 CLEC2C, CYFRA21-1, ErbB4 0.8349609 AREG, CLEC2C, HGFR 0.8330078 CYFRA21-1, ErbB4, FasL 0.8326613 AREG, CLEC2C, FasL 0.8316532 AREG, CLEC2C, ErbB4 0.8300781 AREG, CLEC2C, IFNgamma 0.8173828 AREG, Flt3L, HGFR 0.8066406 CLEC2C, CYFRA21-1, IFNgamma 0.8066406 CYFRA21-1, FasL, IFNgamma 0.8054435 CYFRA21-1, HGFR, IFNgamma 0.8037109 CYFRA21-1, FasL, HGFR 0.8014113 CLEC2C, CYFRA21-1, FasL 0.7973790 CLEC2C, CYFRA21-1, HGFR 0.7968750 AREG, ErbB4, Flt3L 0.7841797 AREG, Flt3L, IFNgamma 0.7832031 AREG, FasL, Flt3L 0.7782258 AREG, ErbB4, HGFR 0.7705078 AREG, HGFR, IFNgamma 0.7666016 AREG, FasL, HGFR 0.7641129 AREG, ErbB4, IFNgamma 0.7451172 AREG, FasL, IFNgamma 0.7358871 AREG, ErbB4, FasL 0.7197581 ErbB4, Flt3L, HGFR 0.7119141 CLEC2C, FasL, Flt3L 0.7076613 CLEC2C, ErbB4, Flt3L 0.7031250 ErbB4, FasL, Flt3L 0.7006048 CLEC2C, Flt3L, HGFR 0.6962891 FasL, Flt3L, HGFR 0.6935484 CLEC2C, Flt3L, IFNgamma 0.6933594 Flt3L, HGFR, IFNgamma 0.6894531 ErbB4, Flt3L, IFNgamma 0.6875000 FasL, Flt3L, IFNgamma 0.6814516 ErbB4, FasL, IFNgamma 0.6250000 ErbB4, HGFR, IFNgamma 0.6230469 CLEC2C, ErbB4, IFNgamma 0.6191406 ErbB4, FasL, HGFR 0.6139113 CLEC2C, ErbB4, HGFR 0.6123047 CLEC2C, ErbB4, FasL 0.6068548 CLEC2C, FasL, IFNgamma 0.6048387 FasL, HGFR, IFNgamma 0.5997984 CLEC2C, FasL, HGFR 0.5967742 CLEC2C, HGFR, IFNgamma 0.5966797

TABLE-US-00007 TABLE 5 bis Combinations of three biomarkers for CRC vs CTL supporting the combination AREG + CYFRA21-1 AUC AREG, CYFRA21-1, Flt3L 0.8994141 AREG, CYFRA21-1, CLEC2C 0.8955078 AREG, CYFRA21-1, ErbB4 0.8955078 AREG, CYFRA21-1, FasL 0.8931452 CYFRA21-1, ErbB4, Flt3L 0.8847656 AREG, CYFRA21-1, IFNgamma 0.8837891 AREG, CYFRA21-1, HGFR 0.8759766 CLEC2C, CYFRA21-1, Flt3L 0.8681641 CYFRA21-1, FasL, Flt3L 0.8679435 CYFRA21-1, Flt3L, IFNgamma 0.8671875 CYFRA21-1, Flt3L, HGFR 0.8662109 AREG, CLEC2C, Flt3L 0.8427734 CYFRA21-1, ErbB4, HGFR 0.8388672 CYFRA21-1, ErbB4, IFNgamma 0.8359375 CLEC2C, CYFRA21-1, ErbB4 0.8349609 AREG, CLEC2C, HGFR 0.8330078 CYFRA21-1, ErbB4, FasL 0.8326613 AREG, CLEC2C, FasL 0.8316532 AREG, CLEC2C, ErbB4 0.8300781 AREG, CLEC2C, IFNgamma 0.8173828 AREG, Flt3L, HGFR 0.8066406 CLEC2C, CYFRA21-1, IFNgamma 0.8066406 CYFRA21-1, FasL, IFNgamma 0.8054435 CYFRA21-1, HGFR, IFNgamma 0.8037109 CYFRA21-1, FasL, HGFR 0.8014113 CLEC2C, CYFRA21-1, FasL 0.7973790 CLEC2C, CYFRA21-1, HGFR 0.7968750 AREG, ErbB4, Flt3L 0.7841797 AREG, Flt3L, IFNgamma 0.7832031 AREG, FasL, Flt3L 0.7782258 AREG, ErbB4, HGFR 0.7705078 AREG, HGFR, IFNgamma 0.7666016 AREG, FasL, HGFR 0.7641129 AREG, ErbB4, IFNgamma 0.7451172 AREG, FasL, IFNgamma 0.7358871 AREG, ErbB4, FasL 0.7197581 ErbB4, Flt3L, HGFR 0.7119141 CLEC2C, FasL, Flt3L 0.7076613 CLEC2C, ErbB4, Flt3L 0.7031250 ErbB4, FasL, Flt3L 0.7006048 CLEC2C, Flt3L, HGFR 0.6962891 FasL, Flt3L, HGFR 0.6935484 CLEC2C, Flt3L, IFNgamma 0.6933594 Flt3L, HGFR, IFNgamma 0.6894531 ErbB4, Flt3L, IFNgamma 0.6875000 FasL, Flt3L, IFNgamma 0.6814516 ErbB4, FasL, IFNgamma 0.6250000 ErbB4, HGFR, IFNgamma 0.6230469 CLEC2C, ErbB4, IFNgamma 0.6191406 ErbB4, FasL, HGFR 0.6139113 CLEC2C, ErbB4, HGFR 0.6123047 CLEC2C, ErbB4, FasL 0.6068548 CLEC2C, FasL, IFNgamma 0.6048387 FasL, HGFR, IFNgamma 0.5997984 CLEC2C, FasL, HGFR 0.5967742 CLEC2C, HGFR, IFNgamma 0.5966797

TABLE-US-00008 TABLE 6 Combinations of four biomarkers for CRC vs CTL supporting the combination Flt3L + CYFRA21-1 AUC Flt3L, CYFRA21-1, ErbB4, AREG 0.9306641 Flt3L, CYFRA21-1, AREG, CLEC2C 0.9150391 AREG, CLEC2C, CYFRA21-1, ErbB4 0.9023438 AREG, CYFRA21-1, ErbB4, FasL 0.9022177 AREG, CLEC2C, CYFRA21-1, IFNgamma 0.9003906 Flt3L, CYFRA21-1, HGFR, AREG, 0.9003906 AREG, CLEC2C, CYFRA21-1, FasL 0.9002016 AREG, CYFRA21-1, ErbB4, IFNgamma 0.8994141 Flt3L, CYFRA21-1, IFNgamma, AREG 0.8984375 Flt3L, CYFRA21-1, FasL, AREG 0.8981855 AREG, CYFRA21-1, FasL, IFNgamma 0.8951613 AREG, CYFRA21-1, ErbB4, HGFR 0.8945312 AREG, CLEC2C, CYFRA21-1, HGFR 0.8935547 AREG, CYFRA21-1, FasL, HGFR 0.8901210 Flt3L, CYFRA21-1, ErbB4, HGFR 0.8867188 Flt3L, CYFRA21-1, ErbB4, IFNgamma 0.8867188 AREG, CYFRA21-1, HGFR, IFNgamma 0.8847656 Flt3L, CYFRA21-1, ErbB4, CLEC2C 0.8847656 Flt3L, CYFRA21-1, ErbB4, FasL 0.8830645 Flt3L, CYFRA21-1, FasL, IFNgamma 0.8689516 Flt3L, CYFRA21-1, HGFR, IFNgamma 0.8671875 Flt3L, CYFRA21-1, FasL, HGFR 0.8669355 Flt3L, CYFRA21-1, IFNgamma, CLEC2C 0.8662109 Flt3L, CYFRA21-1, FasL, CLEC2C 0.8649194 Flt3L, CYFRA21-1, HGFR, CLEC2C 0.8632812 AREG, CLEC2C, Flt3L, HGFR 0.8564453 AREG, CLEC2C, ErbB4, Flt3L 0.8457031 AREG, CLEC2C, FasL, Flt3L 0.8447581 AREG, CLEC2C, Flt3L, IFNgamma 0.8447266 CYFRA21-1, ErbB4, HGFR, IFNgamma 0.8417969 CLEC2C, CYFRA21-1, ErbB4, HGFR 0.8398438 AREG, CLEC2C, ErbB4, HGFR 0.8378906 CLEC2C, CYFRA21-1, ErbB4, IFNgamma 0.8359375 AREG, CLEC2C, ErbB4, FasL 0.8346774 AREG, CLEC2C, FasL, HGFR 0.8326613 CLEC2C, CYFRA21-1, ErbB4, FasL 0.8326613 CYFRA21-1, ErbB4, FasL, IFNgamma 0.8326613 CYFRA21-1, ErbB4, FasL, HGFR 0.8316532 AREG, CLEC2C, HGFR, IFNgamma 0.8271484 AREG, CLEC2C, ErbB4, IFNgamma 0.8251953 AREG, CLEC2C, FasL, IFNgamma 0.8245968 AREG, ErbB4, Flt3L, HGFR 0.8203125 CLEC2C, CYFRA21-1, FasL, IFNgamma 0.8074597 AREG, Flt3L, HGFR, IFNgamma 0.8066406 CYFRA21-1, FasL, HGFR, IFNgamma 0.8064516 CLEC2C, CYFRA21-1, HGFR, IFNgamma 0.8056641 AREG, FasL, Flt3L, HGFR 0.7993952 CLEC2C, CYFRA21-1, FasL, HGFR 0.7983871 AREG, ErbB4, Flt3L, IFNgamma 0.7861328 AREG, ErbB4, HGFR, IFNgamma 0.7802734 AREG, ErbB4, FasL, Flt3L 0.7802419 AREG, FasL, Flt3L, IFNgamma 0.7772177 AREG, ErbB4, FasL, HGFR 0.7721774 AREG, FasL, HGFR, IFNgamma 0.7681452 AREG, ErbB4, FasL, IFNgamma 0.7419355 ErbB4, FasL, Flt3L, HGFR 0.7358871 CLEC2C, ErbB4, FasL, Flt3L 0.7167339 CLEC2C, FasL, Flt3L, HGFR 0.7086694 CLEC2C, FasL, Flt3L, IFNgamma 0.7056452 CLEC2C, ErbB4, Flt3L, HGFR 0.7050781 ErbB4, Flt3L, HGFR, IFNgamma 0.7050781 CLEC2C, ErbB4, Flt3L, IFNgamma 0.7011719 ErbB4, FasL, Flt3L, IFNgamma 0.6985887 CLEC2C, Flt3L, HGFR, IFNgamma 0.6933594 FasL, Flt3L, HGFR, IFNgamma 0.6895161 CLEC2C, ErbB4, FasL, IFNgamma 0.6290323 CLEC2C, ErbB4, FasL, HGFR 0.6239919 CLEC2C, ErbB4, HGFR, IFNgamma 0.6220703 ErbB4, F asL, HGFR, IFNgamma 0.6118952 CLEC2C, FasL, HGFR, IFNgamma 0.6088710

TABLE-US-00009 TABLE 6 bis Combinations of four biomarkers for CRC vs CTL supporting the combination AREG + CYFRA21-1 AUC AREG, CYFRA21-1, Flt3L, ErbB4 0.9306641 AREG, CYFRA21-1, Flt3L CLEC2C 0.9150391 AREG, CYFRA21-1, ErbB4, CLEC2C 0.9023438 AREG, CYFRA21-1, ErbB4, FasL 0.9022177 AREG, CYFRA21-1, CLEC2C, IFNgamma 0.9003906 AREG, CYFRA21-1, Flt3L, HGFR 0.9003906 AREG, CYFRA21-1, CLEC2C, FasL 0.9002016 AREG, CYFRA21-1, ErbB4, IFNgamma 0.8994141 AREG, CYFRA21-1, Flt3L, IFNgamma 0.8984375 AREG, CYFRA21-1, Flt3L, FasL, 0.8981855 AREG, CYFRA21-1, FasL, IFNgamma 0.8951613 AREG, CYFRA21-1, ErbB4, HGFR 0.8945312 AREG, CYFRA21-1, HGFR, CLEC2C, 0.8935547 AREG, CYFRA21-1, FasL, HGFR 0.8901210 CYFRA21-1, ErbB4, Flt3L, HGFR 0.8867188 CYFRA21-1, ErbB4, Flt3L, IFNgamma 0.8867188 AREG, CYFRA21-1, HGFR, IFNgamma 0.8847656 CLEC2C, CYFRA21-1, ErbB4, Flt3L 0.8847656 CYFRA21-1, ErbB4, FasL, Flt3L 0.8830645 CYFRA21-1, FasL, Flt3L, IFNgamma 0.8689516 CYFRA21-1, Flt3L, HGFR, IFNgamma 0.8671875 CYFRA21-1, FasL, Flt3L, HGFR 0.8669355 CLEC2C, CYFRA21-1, Flt3L, IFNgamma 0.8662109 CLEC2C, CYFRA21-1, FasL, Flt3L 0.8649194 CLEC2C, CYFRA21-1, Flt3L, HGFR 0.8632812 AREG, CLEC2C, Flt3L, HGFR 0.8564453 AREG, CLEC2C, ErbB4, Flt3L 0.8457031 AREG, CLEC2C, FasL, Flt3L 0.8447581 AREG, CLEC2C, Flt3L, IFNgamma 0.8447266 CYFRA21-1, ErbB4, HGFR, IFNgamma 0.8417969 CLEC2C, CYFRA21-1, ErbB4, HGFR 0.8398438 AREG, CLEC2C, ErbB4, HGFR 0.8378906 CLEC2C, CYFRA21-1, ErbB4, IFNgamma 0.8359375 AREG, CLEC2C, ErbB4, FasL 0.8346774 AREG, CLEC2C, FasL, HGFR 0.8326613 CLEC2C, CYFRA21-1, ErbB4, FasL 0.8326613 CYFRA21-1, ErbB4, FasL, IFNgamma 0.8326613 CYFRA21-1, ErbB4, FasL, HGFR 0.8316532 AREG, CLEC2C, HGFR, IFNgamma 0.8271484 AREG, CLEC2C, ErbB4, IFNgamma 0.8251953 AREG, CLEC2C, FasL, IFNgamma 0.8245968 AREG, ErbB4, Flt3L, HGFR 0.8203125 CLEC2C, CYFRA21-1, FasL, IFNgamma 0.8074597 AREG, Flt3L, HGFR, IFNgamma 0.8066406 CYFRA21-1, FasL, HGFR, IFNgamma 0.8064516 CLEC2C, CYFRA21-1, HGFR, IFNgamma 0.8056641 AREG, FasL, Flt3L, HGFR 0.7993952 CLEC2C, CYFRA21-1, FasL, HGFR 0.7983871 AREG, ErbB4, Flt3L, IFNgamma 0.7861328 AREG, ErbB4, HGFR, IFNgamma 0.7802734 AREG, ErbB4, FasL, Flt3L 0.7802419 AREG, FasL, Flt3L, IFNgamma 0.7772177 AREG, ErbB4, FasL, HGFR 0.7721774 AREG, FasL, HGFR, IFNgamma 0.7681452 AREG, ErbB4, FasL, IFNgamma 0.7419355 ErbB4, FasL, Flt3L, HGFR 0.7358871 CLEC2C, ErbB4, FasL, Flt3L 0.7167339 CLEC2C, FasL, Flt3L, HGFR 0.7086694 CLEC2C, FasL, Flt3L, IFNgamma 0.7056452 CLEC2C, ErbB4, Flt3L, HGFR 0.7050781 ErbB4, Flt3L, HGFR, IFNgamma 0.7050781 CLEC2C, ErbB4, Flt3L, IFNgamma 0.7011719 ErbB4, FasL, Flt3L, IFNgamma 0.6985887 CLEC2C, Flt3L, HGFR, IFNgamma 0.6933594 FasL, Flt3L, HGFR, IFNgamma 0.6895161 CLEC2C, ErbB4, FasL, IFNgamma 0.6290323 CLEC2C, ErbB4, FasL, HGFR 0.6239919 CLEC2C, ErbB4, HGFR, IFNgamma 0.6220703 ErbB4, FasL, HGFR, IFNgamma 0.6118952 CLEC2C, FasL, HGFR, IFNgamma 0.6088710

[0064] Table 7, Table 8 and Table 9 show the AUC achieved for the combinations of two, three and four biomarkers respectively, discriminating AA vs CTL.

TABLE-US-00010 TABLE 7 Biomarker combination AA vs CTL AUC AREG, CD147 0.7548828 AREG, HGFR 0.7460938 AREG, CYFRA21-1 0.7221680 CYFRA21-1, HGFR 0.6250000 CD147, HGFR 0.6191406 CD147, CYFRA21-1 0.6152344

TABLE-US-00011 TABLE 8 Biomarker combination AA vs CTL AUC AREG, CD147, CYFRA21-1 0.7617188 AREG, CYFRA21-1, HGFR 0.7607422 AREG, CD147, HGFR 0.7539062 CD147, CYFRA21-1, HGFR 0.6337891

TABLE-US-00012 TABLE 9 Biomarker combination AA vs CTL AUC AREG, CYFRA21-1, HGFR, CD147 0.7685547

[0065] Based on their respective AUCs, the best models have been selected. Table 10 and Table 10bis show the best results for CRC. Table 11 and Table 11bis show the best results for AA. The metrics for the best combinations of proteins are included, comprising area under the ROC curve (AUC), Sensitivity (Sens.), Specificity (Spec.), and positive (PPV) and negative (NPV) predictive values computed in the cut-off point of the ROC curve with the best Youden's index.

TABLE-US-00013 TABLE 10 Biomarker combination CRC. vs. CTL supporting AUC Flt3L + CYFRA21-1 (95% CI) Sens Spec PPV NPV Flt3L, CYFRA21-1 0.865(0.779, 0.625 0.969 0.952 0.721 0.952) Flt3L, CYFRA21-1, 0.899(0.821, 0.781 0.938 0.926 0.811 AREG 0.978) Flt3L, CYFRA21-1, 0.931(0.861, 0.875 0.938 0.933 0.882 AREG, ErbB4 1) Flt3L, CYFRA21-1, 0.915(0.848, 0.844 0.844 0.844 0.844 AREG, CLEC2C 0.982)

TABLE-US-00014 TABLE 10bis Biomarker combination CRC. vs. CTL supporting AUC AREG + CYFRA21-1 (95% CI) Sens Spec PPV NPV AREG, CYFRA21-1 0.878(0.789, 0.875 0.844 0.848 0.871 0.966) AREG, CLEC2C 0.835(0.729, 0.906 0.812 0.829 0.897 0.941) AREG, HGFR 0.763(0.643, 0.656 0.812 0.778 0.703 0.883) AREG, CD147 0.842(0.734, 0.844 0.844 0.844 0.844 0.95) AREG, CYFRA21-1, Flt3L 0.899(0.821, 0.781 0.938 0.926 0.811 0.978) AREG, CYFRA21-1, 0.896(0.814, 0.875 0.844 0.848 0.871 CLEC2C 0.977) AREG, CYFRA21-1, ErbB4 0.896(0.812, 0.875 0.844 0.848 0.871 0.979) AREG, CYFRA21-1, FasL 0.893(0.81, 0.903 0.812 0.824 0.897 0.976) AREG, CYFRA21-1, CD147 0.886(0.797, 0.875 0.844 0.848 0.871 0.975) AREG, CYFRA21-1, HGFR 0.876(0.787, 0.875 0.844 0.848 0.871 0.965) AREG, CD147, HGFR 0.843(0.735, 0.844 0.844 0.844 0.844 0.951) AREG, CYFRA21-1, 0.931(0.861, 0.875 0.938 0.933 0.882 ErbB4, Flt3L 1) AREG, CYFRA21-1, 0.915(0.848, 0.844 0.844 0.844 0.844 Flt3L, CLEC2C 0.982) AREG, CYFRA21-1, 0.888(0.801, 0.875 0.844 0.848 0.871 CD147, HGFR 0.975)

TABLE-US-00015 TABLE 11 Biomarker combination supporting AUC AA. vs. CTL Flt3L + CYFRA21-1 (95% CI) Sens Spec PPV NPV Flt3L, CYFRA21-1 0.606(0.466, 0.906 0.312 0.569 0.769 0.747) Flt3L, CYFRA21-1, AREG 0.72(0.591, 0.812 0.625 0.684 0.769 0.848) Flt3L, CYFRA21-1, 0.707(0.578, 0.656 0.75 0.724 0.686 AREG, ErbB4 0.836) Flt3L, CYFRA21-1, 0.727(0.6, 0.812 0.625 0.684 0.769 AREG, CLEC2C 0.853)

TABLE-US-00016 TABLE 11bis Biomarker combination supporting AUC AA. vs. CTL AREG + CYFRA21-1 (95% CI) Sens Spec PPV NPV AREG, CYFRA21-1 0.722(0.594, 0.844 0.625 0.692 0.8 0.85) AREG, CLEC2C 0.738(0.613, 0.781 0.688 0.714 0.759 0.864) AREG, HGFR 0.746(0.621, 0.531 0.938 0.895 0.667 0.871) AREG, CD147 0.755(0.633, 0.656 0.844 0.808 0.711 0.877) AREG, CYFRA21-1, Flt3L 0.72(0.591, 0.812 0.625 0.684 0.769 0.848) AREG, CYFRA21-1, 0.728(0.601, 0.812 0.625 0.684 0.769 CLEC2C 0.854) AREG, CYFRA21-1, ErbB4 0.71(0.582, 0.656 0.75 0.724 0.686 0.838) AREG, CYFRA21-1, FasL 0.711(0.581, 0.774 0.625 0.667 0.741 0.84) AREG, CYFRA21-1, CD147 0.762(0.642, 0.844 0.656 0.711 0.808 0.882) AREG, CYFRA21-1, HGFR 0.761(0.634, 0.75 0.75 0.75 0.75 0.887) AREG, CD147, HGFR 0.754(0.632, 0.562 0.906 0.857 0.674 0.876) AREG, CYFRA21-1, 0.707(0.578, 0.656 0.75 0.724 0.686 Flt3L, ErbB4, 0.836) AREG, CYFRA21-1, 0.727(0.6, 0.812 0.625 0.684 0.769 Flt3L, CLEC2C 0.853) AREG, CYFRA21-1, 0.769(0.65, 0.781 0.719 0.735 0.767 CD147, HGFR 0.888)

[0066] Finally, Table 12 and Table 12bis have been designed to show the overlapping of the most important signatures claimed in the present invention. It is clearly shown that all the best signature signatures comprise [Flt3L and CYFRA21-1] and [AREG and CYFRA21-1].

TABLE-US-00017 TABLE 12 CRC vs AA vs AREG CLEC2C CYFRA21-1 Flt3L ErbB4 CTL CTL X X X X 0.931 0.707 X X X X 0.915 0.727 X X X 0.899 0.720 X X 0.865 0.606

TABLE-US-00018 TABLE 12 bis CD147 FasL CLEC2C AREG CYFRA21-1 Flt3L ErbB4 HGFR CRC AA X X X X 0.931 0.707 X X X X 0.915 0.727 X X X 0.899 0.720 X X X 0.896 0.728 X X X 0.896 0.710 X X X 0.893 0.711 X X X X 0.888 0.769 X X X 0.886 0.762 X X 0.878 0.722 X X X 0.876 0.761 X X X 0.843 0.754 X X 0.842 0.755 X X 0.835 0.738 X X 0.763 0.746