KR102018205B1 - Diagnosis composition of colorectal cancer and diagnosis method of colorectal cancer using the same - Google Patents

Abstract

The present invention relates to a composition for diagnosing colorectal cancer and a method for diagnosing colorectal cancer using the composition. Specifically, the composition for diagnosing colorectal cancer of the present invention may be useful for early treatment of colorectal cancer and to improve the survival rate of colorectal cancer patients by confirming the expression level of a specific protein in body fluids and thus easily diagnosing colorectal cancer. Can be.

Description

DIAGNOSIS COMPOSITION OF COLORECTAL CANCER AND DIAGNOSIS METHOD OF COLORECTAL CANCER USING THE SAME

The present invention relates to a composition for diagnosing colorectal cancer and a method for diagnosing colorectal cancer using the composition.

Colorectal cancer is a malignant tumor of the colon and rectum. In recent years, the incidence of eating habits is increasing rapidly and its age is gradually decreasing. Colorectal cancer is caused by several hereditary diseases such as high fat, low fiber diet and familial polyposis, and inflammatory bowel disease such as ulcerative colitis.

In general, most of the early stages of colorectal cancer, even if you do not have symptoms specific to the colon because it is difficult to say that the characteristic symptoms. Generally, however, symptoms such as changes in bowel habits, bloody or mucous stools (mucus mixed with mucus), thin stools, weight loss, abdominal discomfort (abdominal pain and bloating), fatigue, loss of appetite, vomiting, and nausea Seems.

The prognosis for colorectal cancer is more than 90% for five-year survival for early (stage 1) patients, but only 5% for patients with metastasized (stage 4) (Cancer Facts and Figures, 2004; American Cancer Society , 2004). Therefore, accurate early diagnosis and treatment of colorectal cancer will contribute to lower mortality from colorectal cancer and lower the cost of cancer treatment.

Colorectal cancer screening is important for reducing disease incidence and mortality because colorectal cancer develops slowly in removable precancerous lesions or in early stages that can be treated. Currently, screening tests for diagnosis of colorectal cancer include fecal occult blood test, tumor marker test, colonography, colonoscopy, computed tomography, abdominal ultrasonography, transrectal ultrasound, and S colonoscopy. However, colonoscopy, the most reliable colorectal cancer screening test at present, has low compliance and diffusion rate, and fecal occult blood test, an option of the most widely used noninvasive screening, has low sensitivity. Other screening tests have limitations in early diagnosis.

In order to overcome the above problems, it is necessary to develop a new method for early diagnosis of colorectal cancer. Recently, in order to find blood markers of colorectal cancer, standard methods such as ELISA and RIA, as well as chromatographic or mass spectrometry methods have been attempted, and various types of cytological markers, DNA markers or mRNA markers have been tried. Studies are ongoing (Sabrina H. et al. , Cancer Epidemiol. Biomarkers Prev., 16 (10): 1935-53, 2007). In addition, methods for diagnosing cancer by discovering biomarkers and comparing patterns of biomarker panels by protein profiling using Surface-Enhanced Laser Desorption / Ionization Time-of-Flight Mass Spectrometry (SELDI-TOF-MS) technology (Petricoin EF et al. , Lancet 359 (9306); 572-577, 2002) are also being studied. The development of agents for screening and diagnosing biomarkers, which enables accurate determination of colorectal cancer, is the biggest challenge to conquer colorectal cancer.

Thus, the present inventors are trying to screen biomarkers for the diagnosis of colorectal cancer, analyze the expression of protein from colorectal cancer patients and normal serum, and using statistical techniques as a biomarker of colorectal cancer TTR (transthyretin), Epidermal growth factor receptor (EGFR), D. Dimer, c-reactive protein (CRP) and apolipoprotein A4 (ApoA4) proteins were selected. In addition, when the combination of the above protein markers for colorectal cancer diagnosis and screening, the present invention was completed by confirming that it is possible to distinguish between colorectal cancer patients and normal people with high accuracy.

It is an object of the present invention to provide a composition and kit for diagnosing colorectal cancer comprising a detection reagent that specifically binds to a selected biomarker.

Another object of the present invention is to provide a method for providing information of colorectal cancer diagnosis using the composition for diagnosing colorectal cancer.

In order to achieve the above object, the present invention provides a composition for diagnosing colorectal cancer comprising a detection reagent that specifically binds to a biomarker consisting of TTR, EGFR, D. Dimer, CRP and ApoA4.

The present invention also provides a kit for diagnosing colorectal cancer comprising the composition for diagnosing colorectal cancer.

In addition, the present invention consists of primers, probes and anti-sense nucleotides that specifically bind to nucleic acid sequences of genes encoding biomarkers consisting of TTR, EGFR, D. Dimer, CRP, and ApoA4. It provides a kit for diagnosing colorectal cancer comprising at least one selected from the group.

In addition, the present invention 1) measuring the amount of protein expression consisting of TTR, EGFR, D. Dimer, CRP and ApoA4 from the sample; And 2) comparing the protein expression level of step 1) with the protein expression level of the normal individual.

In addition, the present invention comprises the steps of 1) measuring the expression level of a gene encoding any one or more proteins selected from the group consisting of TTR, EGFR, D. Dimer, CRP and ApoA4 from the sample; And 2) comparing the gene expression amount of step 1) with the gene expression amount of a normal individual.

The composition for diagnosing colorectal cancer of the present invention may be useful for early treatment of colorectal cancer and to improve the survival rate of colorectal cancer patients by confirming the amount of expression of a specific protein in the body fluid, thereby making early diagnosis of colorectal cancer.

1 is a graph confirming the AUC values according to various numbers of colorectal cancer biomarker combinations.

Hereinafter, the present invention will be described in detail.

The present invention provides a composition for diagnosing colon cancer comprising a detection reagent that specifically binds to a biomarker consisting of TTR, EGFR, D. Dimer, CRP, and ApoA4.

The TTR, EGFR, D. Dimer, CRP and ApoA4 proteins may be polypeptides composed of any sequence known in the art. The polypeptide may be a variant or fragment of an amino acid having a different sequence by deletion, insertion, substitution, or a combination of amino acid residues within a range that does not affect the function of the protein. Amino acid exchange in proteins or peptides that do not alter the activity of the molecule as a whole is known in the art. In some cases, it may be modified by phosphorylation, sulfation, acrylation, glycosylation, methylation, farnesylation, or the like.

The detection reagent may be any one or more selected from the group consisting of antibodies, antibody fragments, aptamers and D-peptides. The antibody may be a monoclonal antibody, polyclonal antibody or recombinant antibody. Antibodies can be readily prepared using techniques well known in the art. The antibody fragment may comprise a functional fragment of an antibody molecule. A functional fragment of an antibody molecule refers to a fragment having at least antigen binding function and may be Fab, F (ab '), F (ab') ₂ , Fv, and the like. The aptamer is an oligonucleotide molecule having binding activity to a predetermined target molecule, and may be RNA, DNA, modified oligonucleotide, or a mixture thereof, and may be in linear or cyclic form.

Such monoclonal antibodies can be prepared using hybridoma methods, or phage antibody library techniques, which are well known in the art. In general, hybridoma cells secreting monoclonal antibodies can be made by fusing cancer cells with immune cells isolated from immunologically suitable host animals, such as mice injected with antigenic proteins. These two populations of cell fusions are performed using methods known in the art, such as polyethylene glycol, and cells producing antibodies can be propagated by standard culture methods. Specifically, subcloning may be performed using a limiting dilution method to obtain a uniform cell population, and then hybridoma cells capable of producing an antibody specific for the antigen may be prepared by culturing in large quantities in vitro or in vivo. Antibodies prepared by the above method can be isolated and purified using methods such as gel electrophoresis, dialysis, salt precipitation, ion exchange chromatography, affinity chromatography and the like.

The polyclonal antibody can be prepared by injecting an immunogen biomarker protein or fragment thereof into an external host according to methods well known in the art. The external host can be a mammal such as a mouse, rat, sheep, rabbit. When the immunogen is injected by intramuscular, intraperitoneal or subcutaneous injection methods, it can be administered with an adjuvant to increase antigenicity. Thereafter, blood may be collected periodically from an external host to obtain serum showing improved titer and specificity for the antigen, from which the antibody may be isolated and purified.

The detection reagent may be a conjugate labeled with a detector such as a chromophore, a fluorescent substance, a radioisotope or a colloid. The chromophore can be peroxidase, alkaline phosphatase or acidic phosphatase, and the fluorescent material can be fluorescein carboxylic acid (FCA), fluorescein isothiocyanate (FITC), fluorescein thiourea (FTH), 7-acetase. Toxycoumarin-3-yl, Fluorescein-5-yl, Fluorescein-6-yl, 2 ', 7'-dichlorofluorescein-5-yl, 2', 7'-dichlorofluorescein-6 -Yl, dihydro tetramethyllosamine-4-yl, tetramethyldamin-5-yl, tetramethyldamin-6-yl, 4,4-difluoro-5,7-dimethyl-4-bora- 3a, 4a-diaza-s-indacene-3-ethyl or 4,4-difluoro-5,7-diphenyl-4-bora-3a, 4a-diaza-s-indacene-3-ethyl , Cy3, Cy5, poly L-lysine-fluorescein isothiocyanate (FITC), rhodamine-B-isothiocyanate (RITC), PE (Phycoerythrin) or rhodamine.

The detection reagent may further include a ligand that can specifically bind to the detection reagent. The ligand may be a conjugate labeled with a detector such as a chromophore, a fluorescent substance, a radioisotope or a colloid, and a ligand treated with streptavidin or avidin.

In addition to the detection reagents described above, the diagnostic composition of the present invention may include distilled water or a buffer to stably maintain their structure.

In a specific embodiment of the present invention, the present inventors analyze the expression of protein from colorectal cancer patients and normal serum, and select TTR, EGFR, D.Dimer, CRP and ApoA4 proteins, which are biomarkers of colorectal cancer, using statistical techniques It was. In addition, a classification model was created using the combination of the biomarkers, and it was confirmed that the classification model can distinguish colon cancer patients from normal people with high accuracy (FIGS. 1 and 3 to 6).

The present invention also provides a kit for diagnosing colorectal cancer, comprising the composition for diagnosing colorectal cancer of the present invention.

The composition and the diagnostic reagent for diagnosing colorectal cancer may have the characteristics as described above. For example, the composition for diagnosing colorectal cancer may include a detection reagent that specifically binds to a biomarker consisting of TTR, EGFR, D. Dimer, CRP, and ApoA4.

On the other hand, the detection reagent may be any one selected from the group consisting of antibodies, antibody fragments, aptamers and D-peptide. The detection reagent may be bound to a solid substrate to facilitate subsequent steps such as washing or separation of the complex. As the solid substrate, synthetic resin, nitrocellulose, glass substrate, metal substrate, glass fiber, microspheres or microbeads may be used. In addition, as the synthetic resin, polyester, polyvinyl chloride, polystyrene, polypropylene, PVDF or nylon may be used.

The kit distinguishes whether the subject is a colorectal cancer risk group and enables a medical practitioner such as a doctor to diagnose colorectal cancer as well as monitor the patient's response to the treatment and change the treatment accordingly. It can also be used to identify compounds that modulate the expression of one or more markers in vivo or ex vivo in a colorectal cancer model such as mouse and rat.

The colorectal cancer diagnostic kit may be prepared by a conventional manufacturing method known to those skilled in the art, and may further include a buffer, a stabilizer, an inactive protein, and the like.

The kit can be used for ultra-fast screening by fluorescence method performed by detecting fluorescence of a fluorescent substance attached as a detector to detect the amount of detection reagent or by radiation method performed by detecting radiation of a radioisotope attached as a detector. Throughput screening (HTS) system, surface plasmon resonance (SPR) method for measuring the plasmon resonance change of the surface in real time without labeling of the detector, or surface plasmon resonance imaging (SPRI) method for imaging and confirming the SPR system can be used.

In a specific embodiment of the present invention, the present inventors analyze the expression of protein from colorectal cancer patients and normal serum, and select TTR, EGFR, D.Dimer, CRP and ApoA4 proteins, which are biomarkers of colorectal cancer, using statistical techniques It was. In addition, a classification model was created using the combination of the biomarkers, and it was confirmed that the classification model can distinguish colon cancer patients from normal people with high accuracy (see FIG. 1 and Tables 3 to 6).

The invention also includes any one or more selected from the group consisting of primers, probes and antisense nucleotides that specifically bind to nucleic acid sequences of genes encoding biomarkers consisting of TTR, EGFR, D. Dimer, CRP and ApoA4. It provides a diagnostic kit for colorectal cancer.

The TTR, EGFR, D. Dimer, CRP and ApoA4 proteins may have the characteristics as described above. The primer is complementary to the gene encoding the biomarker found in the present invention, any primer designed to amplify it can be used.

The probe is a nucleic acid fragment corresponding to a few to several hundred bases, which can make specific binding with DNA or RNA, and can be used to confirm the presence or absence of specific DNA or RNA. The probe may be prepared in the form of oligonucleotide probe, single-stranded DNA probe, double-stranded DNA probe, RNA probe, etc., and may be labeled with biotin, FITC, rhodamine, digoxigenin, or the like, or labeled with radioisotopes. have.

The antisense nucleotides can be those having double or single stranded DNA, double or single stranded RNA, DNA / RNA hybrids, DNA and RNA analogues and base, sugar or backbone modifications.

The colorectal cancer diagnostic kit may have the characteristics as described above.

In a specific embodiment of the present invention, the present inventors analyze the expression of protein from colorectal cancer patients and normal serum, and select TTR, EGFR, D.Dimer, CRP and ApoA4 proteins, which are biomarkers of colorectal cancer, using statistical techniques It was. In addition, a classification model was created using the combination of the biomarkers, and it was confirmed that the classification model can distinguish colon cancer patients from normal people with high accuracy (FIGS. 1 and 3 to 6).

In addition, the present invention 1) measuring the amount of protein expression consisting of TTR, EGFR, D. Dimer, CRP and ApoA4 from the sample; And 2) comparing the protein expression level of step 1) with the protein expression level of the normal individual.

The sample of step 1) may include a biological sample capable of identifying a disease-specific polypeptide that can be distinguished from a normal state such as urine, blood, serum or plasma. Specifically, it may be blood, serum or plasma which is a biological liquid sample. In one embodiment of the invention, the sample may be serum.

Samples may be pretreated using methods such as anion exchange chromatography, affinity chromatography, size exclusion chromatography, liquid chromatography, continuous extraction, centrifugation or gel electrophoresis. In one embodiment of the present invention, the sample may be pretreated by centrifugation.

The expression level of step 1) may be measured by any one or more methods selected from the group consisting of Western blot, enzyme-immunochemical detection (ELISA), immunohistochemical staining, immunoprecipitation and immunofluorescence. At this time, the expression amount of the gene encoding the TTR, EGFR and ApoA4 protein is reduced compared to the control, the expression amount of the gene encoding the CRP and D. Dimer protein may be increased compared to the control.

In a specific embodiment of the present invention, the present inventors analyze the expression of protein from colorectal cancer patients and normal serum, and select TTR, EGFR, D.Dimer, CRP and ApoA4 proteins, which are biomarkers of colorectal cancer, using statistical techniques It was. In addition, a classification model was created using the combination of the biomarkers, and it was confirmed that the classification model can distinguish colon cancer patients from normal people with high accuracy (FIGS. 1 and 3 to 6).

In addition, the present invention comprises the steps of 1) measuring the expression level of a gene encoding a protein consisting of TTR, EGFR, D. Dimer, CRP and ApoA4 from the sample; And 2) comparing the gene expression amount of step 1) with the gene expression amount of a normal individual.

The sample of step 1) may include a biological sample capable of identifying a disease-specific nucleotide that can be distinguished from a normal state such as urine, blood, serum or plasma. Specifically, it may be blood, serum or plasma which is a biological liquid sample. In one embodiment of the invention, the sample may be serum.

The expression level of step 1) can be measured by reverse transcription polymerase chain reaction or real time polymerase chain reaction. At this time, the expression amount of the gene encoding the TTR, EGFR and ApoA4 protein is reduced compared to the control, the expression amount of the gene encoding the CRP and D. Dimer protein may be increased compared to the control.

In a specific embodiment of the present invention, the present inventors analyze the expression of protein from colorectal cancer patients and normal serum, and select TTR, EGFR, D.Dimer, CRP and ApoA4 proteins, which are biomarkers of colorectal cancer, using statistical techniques It was. In addition, a classification model was created using the combination of the biomarkers, and it was confirmed that the classification model can distinguish colon cancer patients from normal people with high accuracy (FIGS. 1 and 3 to 6).

Hereinafter, the present invention will be described in detail by the following examples.

However, the following Examples are only for illustrating the present invention, and the contents of the present invention are not limited thereto.

Serum obtained

First, serum was obtained from 290 healthy people (176 males and 114 females) at Seoul National University Hospital, and 75 and 25 colorectal cancer patients from Keimyung University Biobank and Pusan National University Human Resource Bank, respectively. 46 patients, 54 women) were obtained serum. Peripheral blood (5 ml) was collected from the normal or colon cancer patient and placed in a Vacutainer SST II tube (Becton Dickinson), which was left at room temperature. After 1 hour, the tube was centrifuged at 3000 g for 5 minutes and the supernatant was taken to obtain serum and the obtained serum was stored at -80 ° C until use.

Quantification of Protein

In order to select a candidate for colorectal cancer biomarker, 120 protein marker candidate groups were first selected from tens of thousands of proteins present in the human body, and clinical significance, ease of analysis, and algorithms were determined through two-dimensional electrophoresis and SELDI-TOF MS analysis. In consideration of accuracy, cost, and clinical conditions, about 50 markers were selected from the 120 protein marker candidate groups. Afterwards, 150 patients with colorectal cancer and 400 normal subjects were validated through statistical analysis of the results. Finally, ApoA1, ApoA2, AFP, CEA, CA125, CA19-9, B2M, and CRP were identified as candidates for colorectal cancer biomarkers. , 17 proteins, such as CYFRA21-1, VDBP, PAI-1, sVCAM-1, RANTES, EGFR, ApoA4, TTR and D.Dimer, were selected. Serum samples were used to quantify the 17 proteins.

<2-1> Antibodies, Kits, and Standard Proteins

The proteins of ApoA1, ApoA2, AFP, CEA, CA125, CA19-9, B2M, CRP, CYFRA21-1, VDBP, PAI-1, sVCAM-1, RANTES, EGFR, ApoA4, TTR and D.Dimer are shown in Table 1 and Quantification was carried out using the kit or antibody described in Section 2. For the standard protein, ApoA4 protein was self-made, EGFR and sVCAM-1 proteins were purchased from R & D Systems, PAI-1 protein from Calbiochem, RNATES protein from PeproTect, and VDBP protein from Biodesign. . For test and calibrator, Siemens for TTR and CRP proteins, Roche for D.Dimer, CEA, CYFRA21-1, B2M, CA125, CA19-9 and AFP proteins, ApoA1 And ApoA2 protein was purchased from Sekisui.

Where to Buy Antibodies, Kits, and Standard Proteins Biomarker Manufacturer of Standards Corresponding Antibody Manufacturer 1 Corresponding Antibody Manufacturer 2 ApoA4 self-production Abcam self-production EGFR R & D Systems R & D Systems R & D Systems PAI-1 Calbiochem Innovative Research US Biological Life Sciences RANTES PeproTech R & D Systems R & D Systems sVCAM-1 R & D Systems R & D Systems R & D Systems VDBP Biodesign Thermofire Thermofire

Where to Buy Antibodies, Kits, and Standard Proteins Biomarker Medicine Calibrator manufacturer TTR N Antiserum to human PreAlbumin N Protein standard SL Siemens D.Dimer D-DI2 D-Dimer Gen. 2 Calibrator set Roche ApoA1 Apo A-1 AutoN "Daiichi" Apo auto N Daiichi Sekisui ApoA2 Apo A-2 AutoN "Daiichi" Apo auto N Daiichi Sekisui CEA Elecsys CEA CEA CalSet Roche CYFRA21-1 Elecsys CYFRA 21-1 CYFRA 21-1 CalSet Roche B2M Tina-quant β2-microglobulin β2-Microglobulin Calibrator Roche CA125 Elecsys CA 125 Ⅱ CA 125 Ⅱ CalSet Roche CA19-9 Elecsys CA 19-9 CA 19-9 CalSet Roche CRP CardioPhase hsCRP N Rheumatology standard SL Siemens AFP Elecsys AFP AFP CalSetⅡ Roche

<2-2> EGFR  Quantification of Protein

The serum concentration of EGFR protein is measured by enzyme-linked immunosorbent assay (ELISA), a method in which an antibody labels an enzyme and measures the activity of the enzyme to quantitatively measure the strength and amount of the antigen-antibody reaction. Was measured using the method. The detection antibody of EGFR protein was labeled with biotin and used for ELISA.

Specifically, first, 400 μg of anti-human-EGFR antibody (R & D systems, US) was added to 800 μl of PBS solution to biotinylate the EGFR detection antibody, and then 10 mM so that the molar ratio of the solution was 20 times that of the antibody. EZ-Link Sulfo-NHS-LC-Biotin (sulfosuccinimidyl-6- [biotin-amido] hexanoate, ThermoFisher Scientific, US) was added thereto and reacted at room temperature for 30 minutes. When biotin labeling was completed, dialysis was repeated three times by adding 1 L of PBS solution, which was stored at -80 ° C.

Quantification of EGFR protein was carried out overnight at 4 ° C by adding 100 μl of capture antibody (R & D systems, US) to human EGFR at a concentration of 0.8 μg / ml in each well of a 96-well microplate (Nalgene Nunc Inc., US). It was. The next day, the wells were washed three times with PBS containing 0.05% Tween 20, and then the PBS solution containing 5% skim milk was placed in the wells and stirred at room temperature for 1 hour to block nonspecific binding. After washing the wells three times with PBS containing 0.05% Tween 20, 100 μl of EGFR standard protein, the serum of normal and colorectal cancer patients obtained in Example 1, was added to each well and allowed to react at room temperature for 2 hours. Wash three times. The biotin-labeled detection antibody prepared by the above method was treated in each well at a concentration of 0.2 μg / ml and reacted for another 2 hours at room temperature. After the reaction was washed three times, the reaction was added for 20 minutes at room temperature by the addition of 1X straptavidin-horseradish-peroxidase (R & D systems, US) and washed five times at the end of the reaction. In order to induce the color reaction, 50 μl of TMB (tetramethylbenzidine, R & D systems, US) was added to each well, and after 20 minutes, 50 μl of 2 N sulfuric acid was added to each well to stop the reaction. The absorbance was then measured at 450 nm using a microplate reader (Emax, Molecular Devices LLC., US). The measured values were analyzed by 5-parametric-curve fitting using SoftMax Pro software (Molecular Device).

<2-3> Quantification of RANTES, sVCAM-1, ApoA4, PAI-1 and VDBP Proteins

Serum concentrations of RANTES, sVCAM-1, ApoA4, PAI-1 and VDBP proteins were determined by multiplex immunoassay using the xMAP technology platform (Luminex Corp. US). The microspheres were used in the immunoassay after binding the capture antibody by carbodiimide method and minimize the exposure of the microspheres to light in the whole process.

Specifically, the microsphere suspension of MagPlex (Luminex Corp.) was mixed by vortex and then suspended in a sonic vessel (Sonicor Instrument Corporation, US) for 20 seconds. 1 × 10 ⁶ microspheres were transferred to a microtube, separated using a magnet, the solution was removed, washed with 100 μl of distilled water, and then resuspended in 80 μl of 0.1 M sodium phosphate buffer (pH 6.2). It was. Thereafter, 50 mg / ml of N-hydroxy-sulfosuccinimide (ThermoFisher Scientific, US) and 1-ethyl-3- (3-dimethylaminopropyl) -carbodiimide hydrochloride (1 10 μl each of -ethyl-3- (3-dimethylaminopropyl) -carbodiimide hydrochloride, ThermoFisher Scientific, US) was added thereto, followed by reaction at room temperature for 20 minutes. At this time, the reactants were mixed at 10 minute intervals. The microspheres were washed twice with 250 μl 50 mM MES pH 5.0 and then resuspended in 100 μl 50 mM MES pH 5.0. The final volume was added to the carboxyl-activated microspheres by adding 10 μg of anti-RANTES, anti-sVCAM-1, anti-ApoA4, anti-PAI-1 or anti-VDBP antibody, and 50 mM MES solution. After 500 μl, it was mixed for 2 hours at room temperature. After completion of the antibody binding reaction, the microspheres were washed twice with 500 μl of PBS-TBN (PBS containing 1% BSA, 0.02% Tween 20 and 0.05% sodium azide) and counted by a hemocytometer. Antibody-bound microspheres were suspended in 500 μl PBS-TBN solution at a concentration of 1 × 10 ⁶ and stored at 2-8 ° C. in the dark.

The RANTES and sVCAM-1 proteins were quantified in multiple assays, simultaneously measured in one well, while the ApoA4, PAI-1 and VDBP proteins were quantified in a single assay, measuring only one protein in one well. Specifically, 20 μl of the serum of normal and colorectal cancer patients obtained in Example 1 and 20 μl of the mixed microspheres conjugated with a capture antibody against RANTES, sVCAM-1, ApoA4, PAI-1 or VDBP protein prepared according to the above method were prepared. After mixing, add 20 microliters of RANTES, sVCAM-1, ApoA4, PAI-1 or VDBP standard protein, or the serum-containing microsphere mixture to each well of a 96-well microplate, and react at room temperature for 1 hour. I was. Thereafter, 20 μl of biotin-labeled detection antibody and 20 μl of Streptavidin-R-Phycoerythrin (Jackson ImmunoResearch) were sequentially added and reacted for 1 hour and 30 minutes, respectively. The reaction plate was washed twice with 200 μl of PBST (PBS containing 0.05% Tween 20) solution and microplate cleaner (HydroFlex ™, TECAN, Switzerland) per well and 100 μl of PBST (0.05) The intensity of fluorescence was measured by Luminex TM200 by resuspending in PBS) solution containing% Tween 20. RANTES, sVCAM-1, ApoA4, PAI-1 and VDBP protein concentrations in serum samples were analyzed by five parameter curve fitting using Beadview Software (Upstate, US).

<2-4> Quantification of ApoA1, ApoA2, TTR, CEA, CYFRA21-1, B2M, CA125, CA19-9, CRP, D.Dimer and AFP Proteins

ApoA1, ApoA2 and B2M proteins were measured by immunoadjuvant method using Hitachi 7080 (Hitachi Medical Corp., Japan) equipment according to the manufacturer's protocol. TTR and CRP proteins were measured by immunoadjuvant method according to the manufacturer's protocol using the BN2 System (Siemens AG., Germany) equipment. CEA, CYFRA21-1, CA125, CA19-9 proteins were cobas e601 (Hoffmann-La Roche AG., Switzerland) equipment, and D. Dimer proteins were prepared using the Roche c501 (Hoffmann-La Roche AG., Switzerland) equipment. It was measured by electrochemical emission immunoassay according to the protocol.

Colorectal cancer Biomarker  Statistical analysis

On the 17 markers (ApoA1, ApoA2, AFP, CEA, CA125, CA19-9, B2M, CRP, CYFRA21-1, VDBP, PAI-1, sVCAM-1, RANTES, EGFR, ApoA4, TTR and D.Dimer) The significance of the difference in expression level between the colorectal cancer patients and normal people was confirmed by t-test. A log ₁₀ transformation was performed on the experimental value obtained in Example 2, and the value (measurement data) was used for statistical analysis. As a result of t-test, if the p-value was 0.1 or less, it was determined as a significant marker.

Significance of the Marker t df P-value ApoA1 -11.026 137.718 0.000 ApoA2 -8.910 112.951 0.000 AFP -3.081 163.526 0.002 CEA 5.514 115.217 0.000 CA125 2.299 122.779 0.023 CA19-9 2.339 124.014 0.021 TTR -15.595 115.429 0.000 B2M 1.969 147.882 0.051 CRP 13.036 159.103 0.000 CYFRA21-1 3.144 130.071 0.002 VDBP -3.117 138.126 0.002 PAI-1 -3.362 134.633 0.001 sVCAM-1 3.648 138.161 0.000 RANTES -4.036 118.763 0.000 EGFR -14.944 132.346 0.000 D.Dimer 12.631 130.984 0.000 ApoA4 -9.172 134.678 0.000

As a result, as shown in Table 3, ApoA1, ApoA2, AFP, CEA, CA125, CA19-9, B2M, CRP, CYFRA21-1, VDBP, PAI-1, sVCAM-1, RANTES, EGFR, ApoA4, TTR and D Dimer markers were significant for the difference in expression levels between colorectal cancer patients and normal subjects (Table 3).

Biomarker  Attribution

ApoA1, ApoA2, AFP, CEA, CA125, CA19-9, B2M, CRP, CYFRA21-1, VDBP, PAI-1, sVCAM-1, RANTES, EGFR, ApoA4, TTR determined as significant markers in Example 3 Or we constructed a classification model using D.Dimer markers and measured the contribution of biomarkers in each classification model.

Specifically, the classification model was constructed using a logistic regression model, which is represented by Equation 1 below.

[Equation 1]

In Equation 1, X ₁ to X _p are values obtained by standardizing the measured data of each biomarker determined as a significant marker in Example 3 with an average of 0 and a variance of 1, and β ₀ to β _p are unknown variables. Unknown variables are identified using the R statistical package (R Development Core Team (2007) .R: A language and environment for statistical computing.R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07- 0, URL http://www.R-project.org. The greater the absolute value of the ridge estimate, the greater the contribution from the logistic regression model of the biomarker.

As a result, TTR> EGFR> D.Dimer> CRP> ApoA4> ApoA1> CEA> ApoA2> RANTES> B2M> PAI-1> AFP> sVCAM-1> CA125> CYFRA21-1> CA19-9> VDBP Attribution decreased.

variety Biomarker  Measure performance of combinations

The contributions measured in Example 4 were used to remove markers with low contributions, and the performance of various biomarker combinations determined as significant markers in Example 3 was measured.

Specifically, samples of the normal and colorectal cancer patients obtained in Example 1 were randomly divided, and 80% were the training data and 20% were the evaluation data. On the other hand, one combination was made of 17 markers determined as significant markers in Example 3. Then, using the training group, a colon cancer and normal classification model was made in the same manner as in Example 4 for the combination, and the training group was predicted to the model. The above steps were repeated 1000 times to obtain 1000 AUC values, and the average of the values was calculated to determine how well the model predicted the training population and to measure the performance of various biomarker combinations.

Performance of various biomarker combinations Marker combination Number of markers Average (AUC) TTR, EGFR, D.Dimer, CRP, ApoA4, ApoA1, CEA, ApoA2, RANTES, B2M, PAI-1, AFP, sVCAM-1, CA125, CYFRA21-1, CA19-9, VDBP 17 0.9807 TTR, EGFR, D.Dimer, CRP, ApoA4, ApoA1, CEA, ApoA2, RANTES, B2M, PAI-1, AFP, sVCAM-1, CA125, CYFRA21-1, CA19-9 16 0.9811 TTR, EGFR, D.Dimer, CRP, ApoA4, ApoA1, CEA, ApoA2, RANTES, B2M, PAI-1, AFP, sVCAM-1, CA125, CYFRA21-1 15 0.9812 TTR, EGFR, D.Dimer, CRP, ApoA4, ApoA1, CEA, ApoA2, RANTES, B2M, PAI-1, AFP, sVCAM-1, CA125 14 0.9816 TTR, EGFR, D.Dimer, CRP, ApoA4, ApoA1, CEA, ApoA2, RANTES, B2M, PAI-1, AFP, sVCAM-1 13 0.9816 TTR, EGFR, D.Dimer, CRP, ApoA4, ApoA1, CEA, ApoA2, RANTES, B2M, PAI-1, AFP 12 0.9823 TTR, EGFR, D.Dimer, CRP, ApoA4, ApoA1, CEA, ApoA2, RANTES, B2M, PAI-1 11 0.9823 TTR, EGFR, D.Dimer, CRP, ApoA4, ApoA1, CEA, ApoA2, RANTES, B2M 10 0.9824 TTR, EGFR, D.Dimer, CRP, ApoA4, ApoA1, CEA, ApoA2, RANTES 9 0.9819 TTR, EGFR, D.Dimer, CRP, ApoA4, ApoA1, CEA, ApoA2 8 0.9809 TTR, EGFR, D.Dimer, CRP, ApoA4, ApoA1, CEA 7 0.9820 TTR, EGFR, D.Dimer, CRP, ApoA4, ApoA1 6 0.9817 TTR, EGFR, D.Dimer, CRP, ApoA4 5 0.9817 TTR, EGFR, D.Dimer, CRP 4 0.9786 TTR, EGFR, D.Dimer 3 0.9805 TTR, EGFR 2 0.9741 TTR One 0.9577

As a result, as shown in FIG. 1 and Table 4, although the AUC value increased exponentially to the number of three markers, similar AUC values were shown from five or more. In the case of having similar AUC values, the smaller the number of markers, the lower the cost. Finally, TTR, EGFR, D. Dimer, CRP and ApoA4 were selected as biomarkers of colorectal cancer (FIG. 1 and Table 4).

Performance Measurement of TTR, EGFR, D.Dimer, CRP, and ApoA4 Biomarker Combinations

In Example 5, the performance of the biomarker was confirmed by measuring the specificity, sensitivity, and accuracy of the TTR, EGFR, D. Dimer, CRP, and ApoA4 biomarker combinations with the highest AUC values. Specificity is a ratio of a normal person determined to be normal, calculated as shown in Equation 2 below, and sensitivity is a ratio determined to cancer patients as a cancer, calculated as shown in Equation 3 below. (accuracy) was calculated as the average of sensitivity and specificity at the ratio of normal to cancer.

[Equation 2]

[Equation 3]

Performance of TTR, EGFR, D.Dimer, CRP, and ApoA4 Biomarker Combinations Specificity Sensitivity Accuracy Threshold 91.38% 93.91% 92.03% 0.227656

As a result, as shown in Table 5, the classification model made with the combination of TTR, EGFR, D.Dimer, CRP, and ApoA4 biomarkers showed 91.38% specificity, 93.91% sensitivity, 92.03% accuracy, and a threshold value of 0.227656. Is shown (Table 5). Through this, it was confirmed that if the threshold value is greater than 0.227656, it may be diagnosed as colorectal cancer patient and less than 0.227656 as a normal person.

Validation of classification models made with TTR, EGFR, D.Dimer, CRP, and ApoA4 biomarker combinations

The classification model made from the combination of TTR, EGFR, D. Dimer, CRP and ApoA4 biomarker generated in Example 5 was verified by the following method.

First, the same method as in <Example 1> was performed except that 95 healthy subjects were studied in Seoul National University Hospital, Department of Family Medicine, and 25 and 70 colon cancer patients, respectively, at Keimyung University Biobank and Pusan National University Human Resource Bank. Serum was obtained. TTR, EGFR, D.Dimer, CRP, and ApoA4 proteins were quantified in the same manner as in <Example 2>, and then the specificity, sensitivity, accuracy, and threshold were measured in the same manner as in <Example 6>. Specificity, sensitivity and accuracy were confirmed at 0.227656.

Performance of Classification Models Made from TTR, EGFR, D.Dimer, CRP, and ApoA4 Biomarker Combinations Threshold Specificity Sensitivity Accuracy 0.2276564 91.58% 92.63% 92.11%

As a result, as shown in Table 6, the classification model made with the combination of TTR, EGFR, D.Dimer, CRP, and ApoA4 biomarkers showed 91.58% specificity, 92.63% sensitivity, and 92.11% accuracy when the threshold value was 0.2276564. It was confirmed that it is shown (Table 6). Through this, the classification model made with the combination of TTR, EGFR, D. Dimer, CRP and ApoA4 biomarker can distinguish colon cancer patients from normal people with high accuracy.

Claims (10)

A composition for diagnosing colon cancer comprising a detection reagent that specifically binds to TTR (transthyretin), EGFR (epidermal growth factor receptor), D. Dimer, c-reactive protein (CRP) and ApoA4 (apolipoprotein A4) protein.
The composition for diagnosing colorectal cancer according to claim 1, wherein the detection reagent is any one or more selected from the group consisting of an antibody, an antibody fragment, an aptamer, and a D-peptide.
The composition for diagnosing colorectal cancer according to claim 2, wherein the antibody is a monoclonal antibody or a polyclonal antibody.
Claim 1 colorectal cancer diagnostic kit comprising a composition for diagnosing colorectal cancer.
Any one or more selected from the group consisting of primers, probes and anti-sense nucleotides that specifically bind to nucleic acid sequences of genes encoding TTR, EGFR, D. Dimer, CRP and ApoA4 proteins Kits for diagnosing colorectal cancer.
1) measuring the expression level of TTR, EGFR, D. Dimer, CRP and ApoA4 protein from the sample; And
2) comparing the protein expression level of step 1) with the protein expression level of a normal individual.
The method of claim 6, wherein the sample of step 1) is urine, blood, serum or plasma.
The method of claim 6, wherein the expression levels of the TTR, EGFR and ApoA4 proteins are reduced compared to normal individuals.
The method of claim 6, wherein the expression levels of the CRP and D. Dimer proteins are increased compared to normal individuals.
1) measuring the expression level of the gene encoding the TTR, EGFR, D. Dimer, CRP and ApoA4 protein from the sample; And
2) comparing the gene expression amount of step 1) with the gene expression amount of a normal individual.

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