Biomarker panel for detecting colorectal cancer and uses thereof

Abstract

The application provides a biomarker group for detecting colorectal cancer, comprising AREG gene and ZKSCAN3 gene. The application also provides application of a reagent for detecting expression levels of AREG gene and ZKSCAN3 gene in preparation of a product for detecting colorectal cancer. The application further provides a product for detecting colorectal cancer, comprising a reagent for detecting expression levels of AREG gene and ZKSCAN3 gene. The biomarker group of the application has the advantages of high sensitivity, high specificity and high accuracy, and is especially suitable for detecting early colorectal cancer.

Description

Technical Field

[0001] This invention relates to the field of molecular diagnostics, specifically to a biomarker set for detecting colorectal cancer and its applications. Background Technology

[0002] Colorectal cancer (CRC) is one of the most common and deadliest cancers worldwide. [1,2] Its incidence rate is rising rapidly in many Asian countries. [3] The survival rate of CRC patients largely depends on the stage of cancer at diagnosis. The 5-year survival rate is generally high for CRC patients diagnosed with stage I and II cancers, at 91% and 82% respectively, but the 5-year survival rate typically drops sharply to only 12% for patients diagnosed with stage IV cancers. [4,5] Most cases of CRC develop slowly and gradually, therefore, CRC is potentially curable if precancerous polyps and early-stage tumors can be detected and removed early. [6] Unfortunately, most CRCs are discovered at a late stage, causing nearly one million deaths each year. [7] Therefore, early detection of CRC is crucial for reducing the high mortality rate of CRC.

[0003] Currently, endoscopic examination combined with biopsy and pathological examination remains the gold standard for clinical diagnosis of CRC. [6,8] Colonoscopy is an effective method for detecting CRC. [9] However, due to its invasiveness, complex bowel preparation, and the need for repeated testing in early screening, it is difficult to achieve the desired results.

[10] Patient compliance is poor. Other non-invasive screening methods include fecal immunochemical testing (FIT), fecal occult blood testing (FOBT), and serum biomarkers (such as carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9)). However, these tests either have low specificity or cannot reliably detect early CRC in a timely manner. [11-13] In addition, fecal DNA testing based on specific mutation and methylation characteristics is mainly offered as a home test, but it has not yet been widely used in clinical practice due to its relatively high cost and complex procedures. [14,15] .

[0004] Therefore, there is an urgent clinical need for a new method that is accurate, simple, safe, and low-cost to detect early CRC. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by providing a biomarker set for detecting colorectal cancer and its applications.

[0006] On the one hand, the present invention provides a set of biomarkers for detecting colorectal cancer, including the AREG gene and the ZKSCAN3 gene.

[0007] On the other hand, the present invention provides the application of reagents for detecting the expression levels of the AREG gene and ZKSCAN3 gene in the preparation of products for detecting colorectal cancer.

[0008] Optionally, the colorectal cancer is stage I, stage II, stage III, or stage IV colorectal cancer; preferably, the colorectal cancer is stage I or stage II colorectal cancer; more preferably, the colorectal cancer is stage I colorectal cancer.

[0009] Optionally, the reagents include those for detecting the expression levels of the AREG and ZKSCAN3 genes using RT-qPCR technology.

[0010] Optionally, the reagent includes specific primers for the AREG gene and the ZKSCAN3 gene; optionally, it also includes specific primers for the HPRT1 gene.

[0011] Optionally, the specific primers for the AREG gene include the sequences of SEQ ID NO:1 and SEQ ID NO:2; the specific primers for the ZKSCAN3 gene include the sequences of SEQ ID NO:3 and SEQ ID NO:4; and the specific primers for the HPRT1 gene include the sequences of SEQ ID NO:5 and SEQ ID NO:6.

[0012] Optionally, methods for detecting colorectal cancer include:

[0013] Obtain the subject's white blood cells;

[0014] Normalized transcript expression of AREG and ZKSCAN3 genes in blood leukocytes was measured. HIR-CRC scores were calculated using the formula HIR-CRC = 1 / (1+e^(-(-3.216+0.721×AREG-0.826×ZKSCAN3))), where AREG represents the normalized expression level of AREG gene relative to HPRT1 gene, and ZKSCAN3 represents the normalized expression level of ZKSCAN3 gene relative to HPRT1 gene.

[0015] The HIR-CRC score is compared with a cutoff value to determine whether the subject has colorectal cancer; wherein the cutoff value is 0.5; when the HIR-CRC score is greater than 0.5, the subject is determined to have colorectal cancer.

[0016] On the other hand, the present invention provides a product for detecting colorectal cancer, including reagents for detecting the expression levels of the AREG gene and the ZKSCAN3 gene.

[0017] Optionally, the product is a reagent kit, a drug, a gene chip, or a test strip.

[0018] Optionally, the product is a reagent kit.

[0019] Optionally, the reagents include those for detecting the expression levels of the AREG and ZKSCAN3 genes using RT-qPCR technology.

[0020] Optionally, the reagent includes specific primers for the AREG gene and the ZKSCAN3 gene; optionally, it also includes specific primers for the HPRT1 gene.

[0021] Optionally, the specific primers for the AREG gene include the sequences of SEQ ID NO:1 and SEQ ID NO:2; the specific primers for the ZKSCAN3 gene include the sequences of SEQ ID NO:3 and SEQ ID NO:4; and the specific primers for the HPRT1 gene include the sequences of SEQ ID NO:5 and SEQ ID NO:6.

[0022] As can be seen from the above technical solutions, the biomarker group for detecting colorectal cancer of the present invention and its application have at least the following advantages:

[0023] The detection performance of the biomarker set of the present invention does not depend on the subject's disease state, nor on the subject's CEA or CA19-9 levels, and has the advantages of high sensitivity, high specificity and high accuracy.

[0024] The detection method of this invention improves upon the shortcomings of current colorectal cancer screening methods that mainly rely on imaging examinations and CEA or CA19-9 testing, reducing the false negative rate of colorectal cancer and making it particularly suitable for the detection of early colorectal cancer.

[0025] The detection of subjects using the biomarker set of the present invention is a non-invasive method that is simple to operate, low in cost, and does not cause any harm to the subjects. Attached Figure Description

[0026] Figure 1This is a flowchart of the research workflow for Example 1. The study in Example 1 recruited 514 participants. RNA-seq was performed to compare the entire transcriptome of leukocytes among 10 CRC and 12 HC samples to identify leukocyte genes associated with CRC. A minimal two-gene signature was identified in the initial cohort of 95 samples to strongly distinguish between CRC and HC. An RT-qPCR assay based on the two-gene signature was developed. Clinical sensitivity and specificity were first evaluated in an expanded training cohort of 314 samples, including 95 samples from the initial identification cohort. Validation was subsequently performed in an independent cohort containing 178 samples.

[0027] Figure 2 The genetic characteristics and comparisons associated with CRC in leukocytes are shown. (A) Volcano plots show differentially expressed genes between 10 CRC and 12 HC samples, examined using RNA-seq. 141 differentially expressed genes are shown in both upper quadrants, with absolute fold change >2 and FDR p-value <0.05. (B) Heatmaps of different CRC clusters are shown using unsupervised Pearson hierarchical clustering based on the ten most expressed genes among CRC-related genes. (C) to (G) dot plots show that, compared to HC individuals, transcript expression of AREG (C), CXCL1 (D), CXCL8 (E), and IFITM10 (F) was significantly increased and transcript expression of ZKSCAN3 (G) was significantly decreased in leukocytes of CRC patients when measured using RT-qPCR and normalized for HPRT1 in an identification cohort of 95 samples. ***p<0.001.

[0028] Figure 3 The identification, training, and testing of two-gene signatures for detecting CRC in HC are shown. (A) ROC curves, measured using RT-qPCR and normalized relative to HPRT1 using ΔCt quantification, show five candidate biomarkers and two-gene signatures (AREG and ZKSCAN3 combination) for distinguishing CRC and HC in an identification cohort of 95 samples consisting of 47 CRCs and 48 HCs. (C) Bootstrapping validation of the stability of the two-gene signatures, as shown in the calibration curves. An ideal line represents perfect calibration. A clear line represents the data of the present invention, with error correction representing the bootstrapping calibration of the two-gene signatures, showing a very small mean absolute error of 0.01. (D) ROC curves show the differentiation of CRC and HC in an independent validation cohort of 178 samples using AREG, ZKSCAN3, and AREG & ZKSCAN3 combination assays using RT-qPCR. Area under the curve (AUC), 95% confidence interval (CI), and p-value are provided for each analysis.

[0029] Figure 4The stability of the three RNA signatures in detecting early-stage, CEA-negative, and CA19-9-negative CRC is shown. (A) and (B) are dot plots showing AREG (A) and ZKSCAN3 (B) expression in a cohort of 492 samples comprising 206 CRCs and 286 HCs, measured using RT-qPCR. (C) shows a dot plot of HIR-CRC scores, calculated using logistic regression equations derived from AREG and ZKSCAN3 expression in the same cohort. (D) through (F) are dot plots showing HIR-CRC scores in HCs and CRCs classified according to different tumor stages (D), CEA status (E), and CA19-9 status (F). Detailed Implementation

[0030] To fully understand the purpose, features, and effects of this invention, the invention will be described in detail below through specific embodiments. Except as described below, the methods of this invention employ conventional methods or apparatus in the art.

[0031] Unless otherwise stated, the technical and scientific terms used in this invention have the meanings commonly understood by those skilled in the art. The following references will provide those skilled in the art with general definitions of many of the terms used in this invention: Wu Naihu, Huang Meijuan. Principles of Molecular Genetics. Chemical Industry Press, 2015; Zhu Shenggeng, Xu Changfa. Biochemistry (4th Edition). Higher Education Press, 2016; Ding Mingxiao et al. Cell Biology (5th Edition). Higher Education Press, 2020; J.E. Krebs, translated by Jiang Songmin. Lewin Gene XII. Science Press, 2021; Robert F. Weaver, translated by Zheng Yonglian et al. Molecular Biology (5th Edition). Science Press, 2021; B. Alberts et al., translated by Ding Xiaoyan et al. Essentials of Cell Biology (3rd Edition). Science Press, 2021. Those skilled in the art will recognize that many methods and materials similar to or equivalent to those described herein can be used in the practice of this invention. In fact, this invention is by no means limited to the methods and materials described herein.

[0032] In this invention, "colorectal cancer" (CRC) is a common malignant tumor of the gastrointestinal tract. It can occur in any part of the colon or rectum, most commonly in the rectum and sigmoid colon, followed by the cecum, ascending colon, descending colon, and transverse colon. Most tumors are adenocarcinomas, with a minority being squamous cell carcinomas and mucinous carcinomas. CRC can spread to other tissues and organs via lymphatic, hematogenous, and direct routes. Based on the depth of tumor invasion of the intestinal wall, the presence of lymphatic metastasis, and the presence of distant metastasis, CRC can be divided into four stages: Stage I, Stage II, Stage III, and Stage IV. Stages I and II are early stages with better treatment outcomes, while Stages III and IV are late stages with poor treatment outcomes.

[0033] biomarker group

[0034] Early-stage CRC is potentially curable, therefore CRC monitoring is crucial for improving the prognosis and survival of CRC patients. CRC screening methods generally fall into two main categories. One strategy is through imaging examinations, with colonoscopy being the gold standard for CRC diagnosis. However, colonoscopy is not an effective, highly invasive screening method. Other routine imaging methods, such as CT, MRI, and PET-CT, are also being evaluated, but have not yet been clinically recommended due to their high cost and radiation risks. Another strategy is through screening for CRC-related symptoms or tumor-derived biomarkers. FIT and FOBT screen for the presence of blood in stool, but these methods have poor sensitivity for CRC (25-38%) and advanced adenomas (16-31%). CEA and CA19-9 are representative examples of blood biomarkers used for CRC screening. However, according to the inventors' research, the sensitivities of CEA and CA19-9 for detecting CRC are 39% and 21%, respectively. CEA and CA19-9 are particularly poor in detecting early-stage CRC, with sensitivities of 33% and 9%, respectively (as shown in Table 3). This aligns with previous reports that the CEA positivity rate for stage I and II CRC is 6.3%–33%, and the CA19-9 positivity rate is 7.4%–11%. Other novel biomarkers, such as DNA mutations, DNA methylation, non-coding RNA, and exosomal proteins in feces and blood, require large-scale evaluation in clinical settings. A major problem with tumor-derived biomarker-based screening methods is the low abundance of these biomarkers in early CRC, leading to low sensitivity for routine tests such as CEA and CA19-9, or the high cost of complex testing procedures such as fecal sample preparation and sequencing. Therefore, it is worthwhile to explore new screening strategies to achieve safe, simple, and robust CRC detection at an early stage of potential treatment options.

[0035] Human immune cells perform immune recognition and surveillance functions, representing novel potential biomarkers for monitoring human health. Recent studies have shown that specific expression changes within immune cells such as peripheral blood monocytes or tissue macrophages are associated with diseases such as cancer and infectious diseases. In this invention, the inventors performed whole-transcriptome RNA-seq to identify differentially expressed genes associated with CRC in blood leukocytes. Through this study, the inventors ultimately identified a minimal two-gene signature to distinguish CRC from healthy controls.

[0036] In a first aspect, the present invention provides a set of biomarkers for detecting colorectal cancer, including the AREG gene and the ZKSCAN3 gene.

[0037] In this invention, the AREG gene is a member of the epidermal growth factor (EGF) family, an important autocrine growth factor and a mitogen for astrocytes, Schwann cells, and fibroblasts. It is a ligand for EGF and is associated with transforming growth factor α (TGF-α). This protein interacts with the epidermal growth factor receptor (EGFR) to promote the growth of normal epithelial cells. The human AREG gene code is 314, the mRNA encoding is NM_001657.4, and the sequence is SEQ ID NO:7, as follows:

[0038] >NM_001657.4 Homo sapiens amphiregulin(AREG),mRNA

[0039]

[0040] It should be noted that in this invention, "AREG gene" includes the AREG gene and any polynucleotides of the AREG gene with functional equivalents, for example, including: (1) the nucleotide sequence shown in SEQ ID NO:7, (2) a nucleotide sequence that hybridizes to the nucleotide sequence shown in SEQ ID NO:7 under stringent conditions and encodes a protein with the same function, and (3) a nucleotide sequence that has at least 70%, preferably at least 80%, more preferably at least 90%, and most preferably at least 95% homology to the nucleotide sequence defined in (1) or (2) and encodes a protein with the same function.

[0041] In this invention, the ZKSCAN3 gene is a zinc finger 3 gene with KRAB and SCAN domains, possessing DNA-binding transcriptional repression activation activity, RNA polymerase II specificity, RNA polymerase II cis-regulatory region sequence-specific DNA-binding activity, and chromatin-binding activity. It participates in multiple processes, including negative regulation of autophagy, negative regulation of cellular senescence, and transcriptional regulation, using DNA as a template. It is located in the cytoplasm and nucleoplasm. The gene code for human ZKSCAN3 is 80317, the mRNA encoding is NM_001242894.2, and the sequence is SEQ ID NO:8, as follows:

[0042] >NM_001242894.2 Homo sapiens zinc finger with KRAB and SCAN domains 3(ZKSCAN3),transcript variant 1,mRNA

[0043]

[0044] It should be noted that, in this invention, “ZKSCAN3 gene” includes the ZKSCAN3 gene and any functional equivalent of the ZKSCAN3 gene, such as: (1) the nucleotide sequence shown in SEQ ID NO:8, (2) a nucleotide sequence that hybridizes to the nucleotide sequence shown in SEQ ID NO:8 under stringent conditions and encodes a protein with the same function, and (3) a nucleotide sequence that has at least 70%, preferably at least 80%, more preferably at least 90%, and most preferably at least 95% homology to the nucleotide sequence defined in (1) or (2) and encodes a protein with the same function.

[0045] The biomarker set of the present invention can be used to detect colorectal cancer at various stages, including stage I, stage II, stage III, and stage IV colorectal cancer. Because the biomarker set of the present invention has high sensitivity, high specificity, and high accuracy, it is preferably suitable for screening stage I and stage II colorectal cancer, and particularly preferably suitable for screening stage I colorectal cancer.

[0046] In this invention, the inventors did not seek biomarkers directly derived from tumors, but instead focused on circulating blood leukocytes, an important cellular component of the human immune system. Previous research has shown that specific changes in gene expression within various immune cells can provide new diagnostic potential for diseases. In this invention, the inventors hypothesized that the occurrence of CRC triggers changes in the expression of specific genes within blood leukocytes, and that these gene signatures could be used to detect CRC. To this end, the inventors compared the transcriptomes of blood leukocytes in CRC and HC samples and definitively identified the gene expression signatures within blood cells associated with CRC (such as...). Figure 2 (As shown). Through in-depth research, the inventors finally determined that the alterations in the genetic characteristics of the AREG and ZKSCAN3 genes in blood leukocytes occur in the early stages of tumor development and persist throughout tumor progression.

[0047] Furthermore, after research, the inventors hypothesized that a small number of CRC cells from early-stage malignant tumor masses could trigger sustained immune recognition and amplify through blood circulation. This hypothesis is consistent with observations that AREG and ZKSCAN3 are both immune-related genes that play important roles in blood cells. AREG overexpression is frequently found in the serum and tissues of human cancers, while tissue ZKSCAN3 functions as a major transcriptional repressor of autophagy. In this invention, the inventors found that differential expression of the AREG and ZKSCAN3 genes in blood leukocytes is associated with the occurrence of CRC (e.g., Figure 4(As shown in (A) and (B)). The inventors’ research provides early evidence that changes in the expression of the AREG and ZKSCAN3 genes in blood leukocytes are a useful strategy for detecting CRC, especially early CRC.

[0048] Application of biomarkers

[0049] Secondly, this invention provides the application of reagents for detecting the expression levels of the AREG gene and ZKSCAN3 gene in the preparation of products for detecting colorectal cancer.

[0050] Preferably, the reagents for detecting the expression levels of the AREG gene and ZKSCAN3 gene include reagents for detecting the expression levels of the AREG gene and ZKSCAN3 gene using RT-qPCR technology.

[0051] More preferably, the reagents for detecting the above-mentioned biomarker group by RT-qPCR technology include specific primers for amplifying the AREG gene and the ZKSCAN3 gene. More preferably, the reagents for detecting the above-mentioned biomarker group by RT-qPCR technology also include specific primers for amplifying the HPRT1 gene.

[0052] More preferably, the reagents for detecting the biomarker group are specific primers SEQ ID NO:1 to SEQ ID NO:6 for the AREG gene, ZKSCAN3 gene, and internal reference gene HPRT1. Specifically:

[0053]

[0054] Based on the application of the AREG and ZKSCAN3 genes, the inventors further developed a simple and reliable RT-qPCR detection method for detecting the expression levels of AREG and ZKSCAN3 genes in blood leukocytes. Furthermore, the expression levels of AREG and ZKSCAN3 genes in blood leukocytes can also be used to detect colorectal cancer.

[0055] Thirdly, the present invention provides a method for detecting the expression levels of the AREG gene and the ZKSCAN3 gene, comprising:

[0056] Step S101: Obtain the subject's blood leukocytes.

[0057] Specifically, a whole blood sample, such as a venous peripheral blood whole blood sample, is obtained from the subject. The whole blood sample is processed to obtain white blood cells. The specific method for processing the whole blood sample can be implemented with reference to existing technology. For example, a commercially available sample preparation kit can be used to lyse, centrifuge, precipitate, etc., the whole blood sample to obtain blood white blood cells.

[0058] Step S102: Measure the normalized transcript expression of the AREG and ZKSCAN3 genes in blood leukocytes and calculate the HIR-CRC score.

[0059] Specifically, total RNA is extracted from blood leukocytes, and cDNA is synthesized from the total RNA. Both the extraction of total RNA and the synthesis of cDNA can be carried out with reference to existing technical protocols, for example, commercially available kits can be used.

[0060] After synthesizing cDNA, PCR was performed using the cDNA as a template to obtain the normalized expression levels of the AREG and ZKSCAN3 genes relative to the HPRT1 gene. Specifically, the comparison cycle threshold (Ct) method was used to normalize the AREG and ZKSCAN3 genes against the intracellular reference gene HPRT1. The normalized expression of the candidate gene - dCt = Ct value of HPRT1 gene - Ct value of candidate gene.

[0061] The HIR-CRC score was calculated using the normalized expression levels of the AREG and ZKSCAN3 genes relative to the HPRT1 gene. The formula used was: HIR-CRC = 1 / (1 + e^(-(-3.216 + 0.721 × AREG - 0.826 × ZKSCAN3))), where AREG represents the normalized expression level of the AREG gene relative to the HPRT1 gene, and ZKSCAN3 represents the normalized expression level of the ZKSCAN3 gene relative to the HPRT1 gene. The expression after the "^" is located at the square of e; for example, "e^A" means "e...". A ", which is e raised to the power of A.

[0062] HIR-CRC scores can be used to show the expression levels of the AREG and ZKSCAN3 genes.

[0063] Fourthly, the present invention provides a method for detecting colorectal cancer, comprising:

[0064] Step S201: Obtain the subject's blood leukocytes.

[0065] Specifically, a whole blood sample, such as a venous peripheral blood whole blood sample, is obtained from the subject. The whole blood sample is processed to obtain white blood cells. The specific method for processing the whole blood sample can be implemented with reference to existing technology. For example, a commercially available sample preparation kit can be used to lyse, centrifuge, precipitate, etc., the whole blood sample to obtain blood white blood cells.

[0066] Step S202: Measure the normalized transcript expression of the AREG and ZKSCAN3 genes in blood leukocytes and calculate the HIR-CRC score.

[0067] Specifically, total RNA is extracted from blood leukocytes, and cDNA is synthesized from the total RNA. Both the extraction of total RNA and the synthesis of cDNA can be carried out with reference to existing technical protocols, for example, commercially available kits can be used.

[0068] After synthesizing cDNA, PCR was performed using the cDNA as a template to obtain the normalized expression levels of the AREG and ZKSCAN3 genes relative to the HPRT1 gene. Specifically, the comparison cycle threshold (Ct) method was used to normalize the AREG and ZKSCAN3 genes against the intracellular reference gene HPRT1. The normalized expression of the candidate gene - dCt = Ct value of HPRT1 gene - Ct value of candidate gene.

[0069] The HIR-CRC score was calculated using the normalized expression levels of the AREG and ZKSCAN3 genes relative to the HPRT1 gene. The formula used was: HIR-CRC = 1 / (1 + e^(-(-3.216 + 0.721 × AREG - 0.826 × ZKSCAN3))), where AREG represents the normalized expression level of the AREG gene relative to the HPRT1 gene, and ZKSCAN3 represents the normalized expression level of the ZKSCAN3 gene relative to the HPRT1 gene. The expression after the "^" is located at the square of e; for example, "e^A" means "e...". A ", which is e raised to the power of A.

[0070] Step 203: Compare the HIR-CRC score with the cutoff value to determine whether the subject has colorectal cancer.

[0071] Specifically, the cutoff value is 0.5. A score greater than 0.5 indicates that the subject has colorectal cancer; otherwise, it indicates that the subject does not have colorectal cancer.

[0072] Following the recommendations of the Youden index method, a cutoff value of 0.5 was chosen to maximize the clinical performance of sensitivity and specificity.

[0073] Products for detecting colorectal cancer

[0074] Fifthly, this invention provides a product for detecting colorectal cancer, including reagents for detecting the expression levels of the AREG and ZKSCAN3 genes. The product for detecting colorectal cancer can be a kit, a drug, a gene chip, or a test strip.

[0075] The kit is a gene detection kit, which includes reagents for detecting the expression levels of the AREG and ZKSCAN3 genes using RT-qPCR technology.

[0076] The drug may be a formulation with the following characteristics: the formulation includes reagents for detecting the expression levels of the AREG gene and ZKSCAN3 gene using RT-qPCR technology, and the formulation can be used to detect the expression levels of the AREG gene and ZKSCAN3 gene.

[0077] The gene chip includes: i) a solid-phase carrier, and ii) a probe, which is immobilized on the solid-phase carrier and can hybridize with the nucleic acid sequences of the AREG gene and the ZKSCAN3 gene.

[0078] The test strip includes: i) a test strip carrier, and ii) nucleic acid immobilized on the test strip carrier, which can detect the expression levels of the AREG gene and the ZKSCAN3 gene.

[0079] In a preferred embodiment, the product for detecting colorectal cancer is a kit that includes reagents for detecting the expression levels of the AREG and ZKSCAN3 genes using RT-qPCR technology.

[0080] Preferably, the reagents for detecting the expression levels of the AREG and ZKSCAN3 genes using RT-qPCR technology include specific primers for amplifying the AREG and ZKSCAN3 genes. More preferably, the reagents for detecting the expression levels of the AREG and ZKSCAN3 genes using RT-qPCR technology further include specific primers for amplifying the HPRT1 gene.

[0081] More preferably, the reagents for detecting the AREG gene and ZKSCAN3 gene are specific primers SEQ ID NO:1 to SEQ ID NO:6 for the AREG gene, ZKSCAN3 gene, and the internal reference gene HPRT1. Specifically:

[0082]

[0083] Optionally, the kit of the present invention may further include a negative control and a positive control. The negative control may be nuclease-free water, and the positive control may be an artificially prepared sample with a cutoff value greater than 0.5.

[0084] It should be noted that the kit of the present invention may also include other suitable components, such as measuring instruments, diluents, buffers, enzymes, pharmaceutically acceptable carriers, syringes, or other suitable accessories that will be readily recognized by those skilled in the art, who can rationally select and formulate them according to the intended purpose. Optionally, the kit of the present invention also includes instructions for use. The instructions for use typically include a clear description of the techniques used to achieve the desired results when using the components of the kit, such as detecting the expression levels of the AREG and ZKSCAN3 genes.

[0085] Example

[0086] The present invention is further illustrated below by way of embodiments, but the invention is not limited to the scope of the embodiments described herein. Experimental methods in the following embodiments that do not specify specific conditions were performed according to conventional methods and conditions, or as selected according to the product instructions.

[0087] Example 1: Screening of biomarkers for the detection of colorectal cancer

[0088] 1. Sample Source

[0089] The study subjects were divided into a healthy control (HC) group and a primary colorectal cancer (CRC) patient group. Nucleated white blood cells were obtained from the whole blood samples of these subjects using the red blood cell lysis method.

[0090] Whole blood samples from the healthy control group were collected from volunteers undergoing routine annual physical examinations at the Shangyu People's Hospital Physical Examination Center in Shaoxing City. The test results showed no serious diseases and no history of intestinal diseases.

[0091] Blood samples from patients with primary colorectal cancer (before treatment) were collected from the Affiliated Hospital of Qingdao University, the Affiliated Hospital of Hangzhou Normal University, and Hunan Cancer Hospital. All CRC cases were confirmed by pathological examination of postoperative or biopsy tissue samples.

[0092] All samples were collected in accordance with the protocol approved by the relevant review committee, and informed consent was obtained from all subjects before sample collection.

[0093] 2. Methods

[0094] according to Figure 1 The process shown involves the following steps:

[0095] 2.1 In the initial discovery phase, 22 samples (10 CRC and 12 HC) were used to screen for biomarkers that differentiate between HC and CRC patients.

[0096] Blood sample collection and purification of circulating immune cells

[0097] At the hospital, a professional nurse draws 2ml of venous blood and places it in an EDTA-K2 blood collection tube (Sanli EDTAK2, Hunan Medical Device Registration Certificate 20152220045). The tube is immediately inverted and mixed thoroughly, then stored at 4℃. Whole blood collection must be pretreated within 4 hours using a sample pretreatment kit (Jizhun Biotechnology, Zhejiang Shaoxing Medical Device Registration Certificate 20210096). Take 1ml of EDTA-K2-treated whole blood and mix thoroughly with 10ml of reagent A, allowing it to stand at room temperature for 10 minutes. Centrifuge at 300g for 5 minutes at room temperature to precipitate circulating immune cells. Add 10ml of refrigerated reagent B, and pipette repeatedly 5 times to thoroughly mix the precipitate. Centrifuge again at 300g for 5 minutes at room temperature to precipitate circulating immune cells. Discard the supernatant, dissolve the circulating immune cell precipitate thoroughly in 700µL of reagent C, and store at -80℃ until RNA extraction.

[0098] RNA extraction, library preparation, and RNA-seq next-generation sequencing

[0099] Total RNA from circulating immune cells via RNA was extracted using a colorectal cancer early screening kit. The extracted RNA was quantified using an ND1000 nanodrop spectrophotometer (Thermo Scientific, USA), and RNA integrity (RIN) was assessed using an Agilent Bioanalyzer 2100 (Agilent, USA). RNA samples with a concentration greater than 100 ng / µL and an RIN greater than 8 were... Transcriptome libraries were prepared using the Single Cell / Low Input RNA Library Prep Kit for Illumina, and transcriptome sequencing (RNA-Seq) data greater than 12 Gb per sample were obtained on an Illumina Novaseq sequencer. The raw FastQ data were analyzed using the STAR analysis pipeline of Partek Flow (Partek, USA) to obtain quantitative data on gene RNA expression throughout the entire transcriptome. ANOVA analysis of leukocyte RNA expression in peripheral blood of CRC and HC samples was used to obtain biomarkers of CRC-specific RNA levels. Candidate genes (i.e., candidate biomarkers) had to meet the following criteria: in comparison between CRC and HC samples, the fold change of upregulated genes should be greater than 2, the fold change of downregulated genes should be less than -2, and the p-value should be less than 0.01. Ultimately, 10 genes were selected for RT-qPCR validation.

[0100] 2.2 Identification of 2-gene signatures in 95 samples (47 CRC, 48 HC)

[0101] To evaluate the diagnostic value of these five genes, the inventors performed RT-qPCR on a cohort of 95 samples (47 CRC and 48 HC) and calculated the normalized expression value of -dCt using HPRT1 as an internal reference. Univariate ROC analysis and multivariate binary logistic regression analysis were also conducted.

[0102] 2.3 In the training group of 314 samples (134 CRC and 180 HC), a detection method based on RT-qPCR technology was established to establish a HIR-colorectal cancer diagnostic method (HIR stands for Human Immune Response).

[0103] Candidate biomarkers identified by RNA-Seq were validated using RT-qPCR.

[0104] The primer sequences used for RT-qPCR validation are as follows:

[0105]

[0106] 200 nanograms of total RNA through The colorectal cancer early screening kit reverse transcribed cDNA, and 1 / 50 of the reverse transcribed cDNA product was detected. The comparison cycle threshold (Ct) method was used to normalize the expression of candidate genes against an intracellular reference gene (HPRT1). In subsequent analyses, -dCt was used as the normalized expression level of the candidate gene. The normalized expression level of the candidate gene was calculated as: -dCt = Ct value of HPRT1 gene - Ct value of candidate gene.

[0107] RT-qPCR data of normalized expression levels of each candidate gene relative to the internal control HPRT1, obtained from 134 CRC and 180 HC samples, were compared with those of the reference gene. Receiver operating characteristic (ROC) curves were generated using SPSS software. The area under the ROC curve (AUC) was used as a biomarker to evaluate individual candidate genes as distinct CRC markers. A model was constructed using a stepwise logistic regression method to calculate the joint ROC curves of multiple candidate genes differentiating CRC, thus obtaining a minimal set of HIR-colorectal cancer diagnosis probability values ​​(0-1). The model included the AREG and ZKSCAN3 genes. The probability algorithm for HIR-colorectal cancer diagnosis was 1 / (1+e^(-(-3.216+0.721×AREG-0.826×ZKSCAN3))), where AREG and ZKSCAN3 represent the -dCt values ​​of normalized HPRT1 expression, respectively.

[0108] Based on the Youden index method, a cutoff value of 0.5 was chosen to optimize the sensitivity and specificity for clinical application. A HIR-probability of colorectal cancer diagnosis greater than 0.5 indicates that the sample can be considered CRC.

[0109] 2.4 Retrospective testing was performed using this RT-qPCR method in an independent validation cohort of 178 samples (72 CRC and 106 HC).

[0110] The standardized expression levels of the AREG and ZKSCAN3 genes in circulating immune cells were obtained using the method described in section 2.3, and the probability value for HIR-mediated colorectal cancer detection was calculated using 1 / (1+e^(-(-3.216+0.721×AREG-0.826×ZKSCAN3))). Sensitivity and specificity were calculated with a cutoff value of 0.5.

[0111] 2.5 CEA and CA19-9 Detection

[0112] For comparison, CEA and CA19-9 levels were measured in CRC patients in both the training and validation groups. The concentrations of CEA and CA19-9 in the tested serum were measured using a carcinoembryonic antigen (CEA) quantitative assay kit and a carbohydrate antigen 19-9 (CA19-9) quantitative assay kit (Shanghai TransGen Biotech Co., Ltd.). A serum CEA concentration greater than 5 ng / ml was defined as a CEA-positive sample, and a serum CEA concentration less than 5 ng / ml was defined as a CEA-negative sample. A serum CA19-9 concentration greater than 35 U / ml was defined as a CA19-9-positive sample, and a serum CA19-9 concentration less than 35 U / ml was defined as a CA19-9-negative sample.

[0113] 3. Statistical Analysis

[0114] The significance of the difference in sample means between the HC group and the CRC group was analyzed using post-hoc paired Bonferroni corrected t-test.

[0115] Univariate binary logistic regression analysis was used to determine the predictive accuracy of individual biomarkers. The p-values ​​for each independent biomarker were determined by the Wald chi-square test, with a cutoff value of p < 0.05. ROC analysis also demonstrated the discriminative power of each biomarker. A stepwise forward multivariate binary logistic regression approach was used to determine the predictive accuracy when biomarkers were used in combination.

[0116] Table 1. Specific information about the samples used in Example 1.

[0117] Discovery Group Identification Group training group Verification group Health comparison n 12 48 180 106 Age, median (range) 50(40-69) 59(42-69) 58(40-79) 59(40-71) Gender, n (%) female 6(50％) 20(42％) 73(41％) 44(42％) male 6(50％) 28(58％) 107(59％) 62(58％) colorectal cancer patients n 10 47 134 72 Age, median (range) 63(56-70) 63(54-79) 64(48-80) 63(52-76) Gender, n (%) female 2(20％) 19(40％) 48(36％) 28(39％) male 8(80％) 28(60％) 86(64％) 44(61％) Tumor stage, n (%) I 3(30％) 7(15％) 40(30％) 24(33％) II 5(50％) 21(45％) 46(34％) 25(45％) III 2(20％) 17(36％) 41(31％) 20(28％) IV 0(0％) 2(4％) 7(5％) 3(4％) Lymph node metastasis, n (%) yes 5(50％) 27(57％) 69(51％) 32(44％) no 5(50％) 20(43％) 65(49％) 40(56％) Remote transfer, n (%) yes 1(10％) 8(17％) 19(14％) 11(15％) no 9(90％) 39(83％) 115(86％) 61(85％) CEA,n(%) <5ng / ml 6(60％) 24(51％) 82(61％) 43(60％) ≥5ng / ml 4(40％) 23(49％) 52(39％) 29(40％) CA19-9,n(%) <35U / ml 7(70％) 38(81％) 106(79％) 57(79％) ≥35U / ml 3(30％) 9(19％) 28(21％) 15(21％)

[0118] Fisher's exact test was used, and p < 0.05, indicating no statistically significant difference in sample distribution between CRC and HC, or between different groups.

[0119] 4. Results

[0120] 4.1 Identification of HIR-based molecular markers for colorectal cancer diagnosis by circulating immune cells

[0121] In order to screen for biomarkers derived from circulating immune cells, the inventors performed whole transcriptome RNA sequencing (RNA-Seq) on circulating immune cell samples from 22 individuals (including 10 CRC patients and 12 HC patients) and compared their transcriptome differences in order to identify RNA biomarkers that could distinguish between HC and CRC.

[0122] Figure 2 Principal component analysis showed that circulating immune cells expressed specific RNAs that recognize colorectal cancer. Figure 2 Principal component analysis showed significant differences in transcripts between the HC and CRC circulating immune cell samples. Quantitative reverse transcription PCR (RT-qPCR) was used to quantify these transcripts, and five transcripts—AREG, CXCL1, CXCL8, IFITM10, and ZKSCAN3—were shown to be differentially expressed between the CRC and HC circulating immune cell samples (p<0.05).

[0123] 4.2 HIR-based molecular markers for colorectal cancer diagnosis accurately identified CRC samples in the identification group.

[0124] To assess the diagnostic value of these five genes, the inventors performed RT-qPCR on a group of 95 identification samples (47 CRC and 48 HC) and used HPRT1 as an internal reference to calculate the normalized expression value of -dCt.

[0125] like Figure 3 As shown in (A), the univariate ROC analysis revealed that the AUCs in the ROC curves for each individual biomarker were: AREG gene (AUC = 0.79), CXCL1 gene (AUC = 0.84), CXCL8 gene (AUC = 0.89), IFITM10 gene (AUC = 0.87), and ZKSCAN3 gene (AUC = 0.22).

[0126] Then, multivariate binary logistic regression analysis was performed on the above-mentioned test samples to analyze the diagnostic accuracy of these five gene random combinations in distinguishing between HC and CRC. Figure 3(A) The results showed that in this group of 95 people, the HIR-colorectal cancer diagnostic marker composed of the AREG gene and the ZKSCAN3 gene had a higher AUC of 0.93 (CI: 0.89-0.98), which was significantly better than any one of the five genes alone.

[0127] Based on this, the inventors established a quantitative RT-qPCR detection method for HIR-related colorectal cancer in a training group of 314 samples (134 CRC and 180 HC). The probability algorithm for HIR-related colorectal cancer diagnosis is 1 / (1+e^(-(-3.216+0.721×AREG-0.826×ZKSCAN3))), where AREG and ZKSCAN3 represent the -dCt value of HPRT1 gene expression normalization, respectively. Following the Youden index method, 0.5 was selected as the cutoff value to optimize the sensitivity and specificity for clinical application. A CRC probability greater than 0.5 indicates that the sample can be considered to have colorectal cancer.

[0128] like Figure 3 As shown in (B), at the cutoff point of 0.5, the sensitivity and specificity of the HIR-based liver cancer detection method in distinguishing CRC in this training group were 80% and 81%, respectively.

[0129] The effectiveness of the HIR-based colorectal cancer detection method and logic equation was validated in an independent validation cohort of 178 cases, including 106 cases of HC and 72 cases of CRC. Figure 3 As shown in (D), the AUC obtained based on HIR-colorectal cancer detection was 0.93 (CI: 0.89-0.97). As shown in Table 2, with 0.5 as the cutoff value, the sensitivity and specificity of the HIR-colorectal cancer diagnostic method in this group were 82% and 78%, respectively.

[0130] Table 2 Diagnostic performance of single or combined biomarkers for CRC detection

[0131]

[0132]

[0133] CRC, colorectal cancer; HC, healthy controls; HIR-CRC is a risk score calculated based on 2-gene characteristics including AREG and ZKSCAN3; early CRC, stage I and II CRC; late CRC, stage III and IV CRC; CEA negative, serum carcinoembryonic antigen <5 ng / ml; CEA positive, serum CEA >5 ng / ml; CA19-9 negative, serum carbohydrate antigen 19-9 <35 U / ml; CA19-9 positive, CA19-9 >35 U / ml; SE, sensitivity; SP, specificity NPV, negative predictive value; PPV, positive predictive value.

[0134] 4.3 Evaluation of the detection performance of HIR-colorectal cancer diagnostic markers in different subgroups of CRC patients

[0135] Subsequently, 492 samples from the training and validation groups were pooled into case groups consisting of 206 CRC and 286 HC. The detection performance of the HIR-colorectal cancer diagnostic marker in different subgroups of CRC patients was evaluated using the colorectal cancer probability obtained by HIR-colorectal cancer diagnosis 1 / (1+e^(-(-3.216+0.721×AREG-0.826×ZKSCAN3))). The results are as follows. Figure 4 As shown in Table 3.

[0136] As shown in Table 3, the sensitivity of HIR-colorectal cancer diagnostic markers in this combination group was 80%, CEA's sensitivity was 39%, and CA19-9's sensitivity was 21%. In early CRC, the sensitivity of HIR-colorectal cancer was 82%, CEA's sensitivity was 33%, and CA19-9's sensitivity was 9%. In CEA-negative samples, the sensitivity of HIR-colorectal cancer was 76%, and CA19-9's sensitivity was 15%. In CA19-9-negative samples, the sensitivity of HIR-colorectal cancer was 80%, and CEA's sensitivity was 31%.

[0137] Table 3: Clinical sensitivity of CEA, CA19-9, and HIR-CRC in identifying different CRC subgroups

[0138]

[0139] Example 2: Kit for detecting colorectal cancer

[0140] Early screening kits for colorectal cancer detection include the following premixed solutions.

[0141] serial number Element 22 tests / kits 1 BAN extraction reagent 110 microliters 2 Reverse transcription buffer premix 132 microliters 3 reverse transcriptase 22 microliters 4 Real-time PCR premix 110 microliters 5 AREG primers 11 microliters 6 ZKSCAN3 primers 11 microliters 7 HPRT1 primers 11 microliters 8 Enzyme-free water 1200 microliters 9 Positive control 10 microliters

[0142] The positive control samples mentioned above were artificial samples with an HIR-colorectal cancer detection threshold greater than 0.5. They were prepared by cloning the amplicon of the detection gene PCR into a T-easy vector, and then, based on the 90th percentile copy number of the detection gene distribution in colorectal cancer patient samples, preparing the corresponding copy number in the positive control samples using the amplicon clone. The HIR-colorectal cancer detection threshold obtained from the positive control samples was determined using the RT-qPCR method described in this paper.

[0143] The components of the quantitative PCR premix for the target gene / 22 tests kit are as follows:

[0144] 2x Quantitative PCR Master Premix 110ul 10 μM forward primer for the gene to be tested 11ul 10µM reverse primer for the gene to be tested 11ul Nuclease-free water 880ul Total 220ul

[0145] The primers were synthesized by IDT (Integrated DNA Technologies, Inc.), and the PCR master premix was purchased from KAPA Biosystems.

[0146] Example 3: Detection of colorectal cancer

[0147] 1. Blood sample collection and purification of circulating immune cells

[0148] At the hospital, a professional nurse draws 2ml of venous blood and places it in an EDTA-K2 blood collection tube (Sanli EDTAK2, Hunan Medical Device Registration Certificate 20152220045). The tube is immediately inverted and mixed thoroughly, then stored at 4℃. Whole blood collection must be pretreated within 4 hours using a sample pretreatment kit (Jizhun Biotechnology, Zhejiang Shaoxing Medical Device Registration Certificate 20210096). Take 1ml of EDTA-K2-treated whole blood and mix thoroughly with 10ml of reagent A, allowing it to stand at room temperature for 10 minutes. Centrifuge at 300g for 5 minutes at room temperature to precipitate circulating immune cells. Add 10ml of refrigerated reagent B, and pipette repeatedly 5 times to thoroughly mix the precipitate. Centrifuge again at 300g for 5 minutes at room temperature to precipitate circulating immune cells. Discard the supernatant, dissolve the circulating immune cell precipitate thoroughly in 700µL of reagent C, and store at -80℃ until RNA extraction.

[0149] 2. RNA extraction

[0150] Total RNA from circulating immune cells via RNA was extracted using a colorectal cancer early screening kit. The extracted RNA was quantified using an ND1000 nanodrop spectrophotometer (Thermo Scientific, USA).

[0151] 3. Reverse transcription

[0152] 200 ng of total RNA was reverse transcribed into cDNA using the early screening kit described in Example 2.

[0153] Reverse transcription reaction system:

[0154] Components volume 200ng total RNA 2.0ul Reverse transcription premix 5.0μL <![CDATA[MultiScribe TM Reverse transcriptase 1.0μL Nuclease-free water 12.0μL Total reaction volume 20.0μL

[0155] Reverse transcription reaction conditions:

[0156] set up Step 1 Step 2 Step 3 Step 4 temperature 25℃ 37℃ 85℃ 4℃ time 10 minutes 120 minutes 5 minutes ∞

[0157] 4. Testing

[0158] The colorectal cancer early screening kit of Example 2 was used for detection, and the reverse transcription reaction product diluted 5 times was used as the input sample to be tested in the kit.

[0159] The quantitative PCR reaction settings for each gene are as follows:

[0160] Gene-specific quantitative PCR premix 8ul 5x dilution of reverse transcription product 2ul

[0161] The quantitative PCR reaction conditions for each gene are:

[0162]

[0163] The Ct value was determined when the fluorescence intensity reached 0.05 using an ABI Q6 real-time quantitative PCR instrument. Normalized expression of each gene was obtained using the -dCt method. The probability value of colorectal cancer risk was calculated using 1 / (1+e^(-(-3.216+0.721×AREG-0.826×ZKSCAN3))). Sensitivity and specificity were calculated with a cutoff value of 0.5. The results were consistent with those in Example 1.

[0164] The above embodiments are preferred embodiments of the present invention, but the embodiments in this aspect are not limited to the above embodiments. Any substitutions, modifications, combinations, changes, simplifications, etc., made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

[0165] References:

[0166] 1. Jemal, A. et al., Cancer Statistics, CA Cancer J Clin, 2009. 59(4): p.225-49.

[0167] 2. Torre, LA et al., Global Cancer Statistics, 2012. CA Cancer J Clin, 2015. 65(2): p.87-108.

[0168] 3. Sung, JJ et al., Increased incidence of colorectal cancer in Asia: the significance of screening. Lancet Oncol, 2005.6(11):p.871-6.

[0169] 4. Miller, KD et al., Cancer treatment and survival statistics, CA Cancer J Clin, 2019. 69(5): p. 363-385.

[0170] 5. Siegel, RL, KD Miller and A. Jemal, Cancer Statistics, CA Cancer J Clin, 2016. 66(1): p. 7-30.

[0171] 6. ASoP et al. Committee, The role of endoscopy in the staging and management of colorectal cancer. GastrointestEndosc, 2013, 78(1):p.8-12.

[0172] 7. Sung, H. et al., Global Cancer Statistics 2020: Global Incidence and Mortality Estimates for 36 Cancers in 185 Countries. CA Cancer J Clin, 2021.71(3):p.209-249.

[0173] 8. Loeve, F. et al., Endoscopic colorectal cancer screening: a cost-saving analysis. J Natl Cancer Inst, 2000. 92(7):p.557-63.

[0174] 9. Knudsen, AB et al., Estimation of benefits, burdens, and harms of colorectal cancer screening strategies: a modeling study by the U.S. Preventive Services Task Force. JAMA, 2016, 315(23):p.2595-609.

[0175] 10. Carroll, MR, HE Seaman, and SP Halloran, Testing and investigation of colorectal cancer screening. Clinical Biochemistry, 2014, 47(10-11):p.921-39.

[0176] 11. Garborg, K. et al., Current status of colorectal cancer screening. Ann Oncol, 2013, 24(8): p. 1963-72.

[0177] 12. Duffy, MJ et al., Clinical application of biochemical markers in colorectal cancer: European Organisation for Cancer Markers (EGTM) guidelines. Eur J Cancer, 2003, 39(6): p.718-27.

[0178] 13. Gao, Y. et al. Evaluation of serum CEA, CA19-9, CA72-4, CA125 and ferritin as diagnostic biomarkers and clinical parameters for colorectal cancer. Scientific Representative, 2018. 8(1): p. 2732.

[0179] 14. Imperiale, TF, DF Ransohoff and SH Itzkowitz, multi-target fecal DNA detection for colorectal cancer screening. N Engl J Med, 2014, 371(2):p.187-8.

[0180] 15. Han, YD, et al., Early detection of colorectal cancer based on the presence of methylated syndecan-2 (SDC2) in fecal DNA. Clinical Epigenetics, 2019.11(1):p.51.

Claims

1. A set of biomarkers for detecting gene expression in the blood leukocytes of a subject to diagnose colorectal cancer, characterized in that, Composed of the AREG gene and the ZKSCAN3 gene; The colorectal cancer mentioned herein is either stage I or stage II colorectal cancer.

2. Application of reagents for detecting the expression levels of AREG and ZKSCAN3 genes in the blood leukocytes of subjects in the preparation of products for detecting stage I or stage II colorectal cancer.

3. The application according to claim 2, characterized in that, The reagents include those used to detect the expression levels of the AREG and ZKSCAN3 genes using RT-qPCR technology.

4. The application according to claim 2, characterized in that, The reagents include specific primers for the AREG gene and the ZKSCAN3 gene.

5. The application according to claim 4, characterized in that, The reagent also includes specific primers for the HPRT1 gene.

6. The application according to claim 4, characterized in that, The specific primers for the AREG gene include the sequences of SEQ ID NO:1 and SEQ ID NO:2; the specific primers for the ZKSCAN3 gene include the sequences of SEQ ID NO:3 and SEQ ID NO:4; and the specific primers for the HPRT1 gene include the sequences of SEQ ID NO:5 and SEQ ID NO:

6.

7. The application according to any one of claims 2 to 6, characterized in that, The applications include: Obtain the subject's white blood cells; Normalized transcript expression of AREG and ZKSCAN3 genes in blood leukocytes was measured. HIR-CRC scores were calculated using the formula HIR-CRC = 1 / (1+e^(-(-3.216+0.721×AREG-0.826×ZKSCAN3))), where AREG represents the normalized expression level of AREG gene relative to HPRT1 gene, and ZKSCAN3 represents the normalized expression level of ZKSCAN3 gene relative to HPRT1 gene. The HIR-CRC score is compared with a cutoff value to determine whether the subject has colorectal cancer; wherein the cutoff value is 0.5; when the HIR-CRC score is greater than 0.5, the subject is determined to have colorectal cancer.

8. A product for detecting stage I or stage II colorectal cancer, characterized in that, This includes reagents for detecting the expression levels of the AREG and ZKSCAN3 genes in the white blood cells of the subjects.

9. The product according to claim 8, characterized in that, The products mentioned are reagent kits, drugs, gene chips, or test strips.

10. The product according to claim 9, characterized in that, The product in question is a reagent kit.

11. The product according to claim 8, characterized in that, The reagents include those used to detect the expression levels of the AREG and ZKSCAN3 genes using RT-qPCR technology.

12. The product according to claim 11, characterized in that, The reagents include specific primers for the AREG gene and the ZKSCAN3 gene.

13. The product according to claim 12, characterized in that, The reagent also includes specific primers for the HPRT1 gene.

14. The product according to claim 12, characterized in that, The specific primers for the AREG gene include the sequences of SEQ ID NO:1 and SEQ ID NO:2; the specific primers for the ZKSCAN3 gene include the sequences of SEQ ID NO:3 and SEQ ID NO:4; and the specific primers for the HPRT1 gene include the sequences of SEQ ID NO:5 and SEQ ID NO:6.

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