Detection kit and method for identifying colorectal cancer status through exosomal miRNA markers

Abstract

Provided herein is a detection kit for diagnosing colorectal cancer status in a subject, comprising a detection reagent for detecting the level of a miRNA biomarker in a biological sample from the subject, wherein the miRNA biomarker is selected from hsa-miR-320a-3p, hsa-miR-19a-3p, hsa-miR-19b-3p, hsa-miR-31-5p, hsa-miR-92a-3p, hsa-miR-196a-5p, hsa-miR-409-5p, hsa-miR-520d-5p and hsa-miR-33b-3p and any combination thereof. Also provided herein is a method for diagnosing colorectal cancer status in a subject. The detection kit and method provided herein provide a new, efficient, non-invasive and accurate approach for screening, diagnosis and prognostic analysis of early colorectal cancer.

Description

Technical Field

[0001] The present invention belongs to the field of genetic engineering and oncology, and specifically relates to exosomal miRNA markers related to auxiliary diagnosis of colorectal cancer and their applications. Background Art

[0002] Colorectal cancer is one of the major cancers threatening the lives and health of people in my country and around the world, posing a serious social burden. The development and progression of colorectal cancer generally follows an "adenoma-carcinoma" sequence, with the progression from precancerous lesions to cancer typically taking 5 to 10 years, providing a critical window for early diagnosis and clinical intervention. Furthermore, the prognosis of colorectal cancer is closely related to the stage at diagnosis. The 5-year relative survival rate for stage I colorectal cancer is 90%, while the 5-year relative survival rate for stage IV colorectal cancer with distant metastasis is only 14%. Extensive research and practice have demonstrated that colorectal cancer screening, early diagnosis, and early treatment can effectively reduce colorectal cancer mortality.

[0003] Colonoscopy holds a unique and irreplaceable position in colorectal cancer screening and is a core component of the entire screening process. Pathological examination of colonoscopic biopsy specimens is the gold standard for colorectal cancer diagnosis. Endoscopic resection of precancerous lesions can reduce colorectal cancer morbidity and mortality. Colonoscopy allows direct visualization of the colorectal lining and is the most sensitive method for detecting intestinal tumors. However, colonoscopy still has a certain rate of missed diagnoses, primarily in the proximal colon, with serrated polyps and flat adenomas being the most common. Proper bowel preparation, standardized colonoscopy techniques, and meticulous and patient endoscopic observation are crucial measures to reduce this rate of missed lesions. Therefore, colonoscopy places high demands on both the examinee and the endoscopist. Because of the dietary restrictions and rigorous bowel cleansing required before colonoscopy, some examinees who undergo colonoscopy without sedation or anesthesia experience significant pain, leading to poor compliance. Furthermore, the direct and indirect costs of colonoscopy can also influence screening participation. Furthermore, colonoscopy is an invasive procedure with a significant incidence of complications, which often leads to fear and refusal among the target population. Domestic and international research data show that even with a positive fecal occult blood test, only 30% to 40% of cases undergo subsequent colonoscopy. CT, PET-CT, MRI, and ultrasound are all conventional imaging methods for colorectal cancer. Compared to colonoscopy, these imaging tests offer advantages such as non-invasiveness, convenience, and rapidity, leading to higher patient compliance. However, these methods require rigorous patient preparation and physician skill, and are associated with issues such as false positives and radiation hazards. Due to the inherent limitations of imaging tests, they are difficult to meet the urgent need for large-scale screening. With the advancement of molecular biology research, attention has shifted to molecular markers for the early diagnosis of colorectal cancer. Plasma Septin 9 gene methylation testing and fecal pyruvate kinase (M2-PK) testing are currently the most widely used molecular screening methods for colorectal cancer. A recent large-scale clinical trial in my country found that plasma Septin 9 gene methylation testing had a sensitivity and specificity of 74.8% and 87.4%, respectively, for diagnosing colorectal cancer, both exceeding those of FIT testing. However, mSEPT9 has insufficient diagnostic sensitivity and specificity for precancerous lesions (colorectal adenomas and polyps, advanced adenomas) and is not recommended for population screening. It can be used as an option and supplement for individualized diagnosis.

[0004] Exosomes are small vesicles approximately 30-150 nm in diameter secreted by living cells and widely distributed in various human body fluids. Exosomes derived from different tissues contain not only their specific proteins but also key molecules that carry out their functions. Exosomes are secreted and released by cells, disseminate throughout body fluids such as the blood, and can then be ingested by other cells, acting as crucial mediators of intercellular communication. Research has shown that exosomes play a crucial role in tumorigenesis, invasion, and metastasis.

[0005] miRNAs (miRNAs) are a class of endogenous noncoding RNAs found in eukaryotes that have post-transcriptional regulatory functions. They are typically 19-25 nucleotides in length. As small, single-stranded noncoding RNAs, they can silence target mRNAs by binding to their corresponding 3'-untranslated regions (3'-UTRs) or open reading frames. Numerous studies have demonstrated that miRNAs are involved in regulating diverse physiological processes, including immune defense, immune surveillance, immune homeostasis, and tumorigenesis and progression. Consequently, many circulating miRNAs have been used in tumor diagnosis, prognosis, and treatment. In 2008, American researchers first reported that circulating miRNAs have the potential to become novel biomarkers for solid tumors. Subsequent studies evaluated the feasibility of miR-21 and miR-92a in stool samples for distinguishing colorectal cancer from colorectal polyps, finding that miR-21 and miR-92a had good diagnostic potential for both. However, the poor stability of circulating free miRNAs under physiological conditions limits their use as reliable biomarkers. As the research deepened, researchers found that the miRNA in extracellular vesicles is not only highly consistent with the pre-secretory matrix, but also thanks to the lipid bilayer membrane structure of the vesicles (exosomes), its contents have extremely strong stability, greatly improving the application of miRNA in various application fields.

[0006] Faced with the increasingly severe occurrence and development of colorectal cancer, how to effectively reduce the disease burden of colorectal cancer in my country has become a major public health issue that needs to be addressed urgently. Summary of the Invention

[0007] In one aspect, provided herein is a detection kit for diagnosing colorectal cancer status in a subject, comprising a detection reagent for detecting the level of a miRNA biomarker in a biological sample from the subject, wherein the miRNA biomarker is selected from hsa-miR-320a-3p, hsa-miR-19a-3p, hsa-miR-19b-3p, hsa-miR-31-5p, hsa-miR-92a-3p, hsa-miR-196a-5p, hsa-miR-409-5p, hsa-miR-520d-5p and hsa-miR-33b-3p and any combination thereof.

[0008] In some embodiments, the miRNA biomarkers include hsa-miR-320a-3p, hsa-miR-19b-3p, or hsa-miR-196a-5p; include hsa-miR-320a-3p, hsa-miR-31-5p, and hsa-miR-409-5p; or include hsa-miR-19b-3p, hsa-miR-196a-5p, and hsa-miR-33b-3p.

[0009] In some embodiments, the miRNA biomarker is hsa-miR-320a-3p, hsa-miR-19a-3p, hsa-miR-19b-3p, hsa-miR-31-5p, hsa-miR-92a-3p, hsa-miR-196a-5p, hsa-miR-409-5p, hsa-miR-520d-5p, and hsa-miR-33b-3p.

[0010] In some embodiments, the colorectal cancer status includes colorectal cancer susceptibility or the presence, progression, subtype, stage, and / or differentiation status of colorectal cancer.

[0011] In some embodiments, the colorectal cancer status is colorectal cancer stage I or stage II, and the miRNA biomarker is hsa-miR-320a-3p, hsa-miR-19b-3p and / or hsa-miR-196a-5p.

[0012] In some embodiments, the colorectal cancer state is adenocarcinoma and the miRNA biomarker is hsa-miR-320a-3p, hsa-miR-19a-3p, hsa-miR-31-5p, hsa-miR-92a-3p, hsa-miR-196a-5p, hsa-miR-409-5p and / or hsa-miR-33b-3p.

[0013] In some embodiments, the colorectal cancer state is mucinous adenocarcinoma and the miRNA biomarker is hsa-miR-320a-3p, hsa-miR-31-5p, hsa-miR-196a-5p and / or hsa-miR-19b-3p.

[0014] In some embodiments, the colorectal cancer state is signet ring cell carcinoma and the miRNA biomarker is hsa-miR-320a-3p, hsa-miR-92a-3p, hsa-miR-196a-5p and / or hsa-miR-33b-3p.

[0015] In some embodiments, the colorectal cancer state is other types of colorectal cancer, and the miRNA biomarker is hsa-miR-320a-3p, hsa-miR-19a-3p, hsa-miR-19b-3p, hsa-miR-31-5p, hsa-miR-196a-5p, hsa-miR-409-5p, hsa-miR-520d-5p and / or hsa-miR-33b-3p.

[0016] In some embodiments, the detection reagents for detecting the level of miRNA biomarkers include reverse transcription primers, PCR amplification primer pairs and / or Taqman probes.

[0017] In some embodiments, the detection reagents for detecting the level of hsa-miR-320a-3p include: a reverse transcription primer including the sequence shown in SEQ ID NO: 10; a PCR amplification primer pair including the sequences shown in SEQ ID NOs: 19 and 28; and / or a Taqman probe including the sequence shown in SEQ ID NO: 29; the detection reagents for detecting the level of hsa-miR-19a-3p include: a reverse transcription primer including the sequence shown in SEQ ID NO: 11; a PCR amplification primer pair including the sequences shown in SEQ ID NOs: 20 and 28; and / or a Taqman probe including the sequence shown in SEQ ID NO: 30; the detection reagents for detecting the level of hsa-miR-19b-3p include: a reverse transcription primer including the sequence shown in SEQ ID NO: 12; a PCR amplification primer pair including the sequences shown in SEQ ID NOs: 21 and 28; and / or a Taqman probe including the sequence shown in SEQ ID NO: 31; the detection reagents for detecting the level of hsa-miR-31-5p include: a reverse transcription primer including the sequence shown in SEQ ID NO: 13; a PCR amplification primer pair including the sequences shown in SEQ ID NOs: 21 and 28; and / or a Taqman probe including the sequence shown in SEQ ID NO: 32 NO: 13; a PCR amplification primer pair comprising the sequences shown in SEQ ID NOs: 22 and 28; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 32; a detection reagent for detecting the level of hsa-miR-92a-3p comprises: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 14; a PCR amplification primer pair comprising the sequences shown in SEQ ID NOs: 23 and 28; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 33; a detection reagent for detecting the level of hsa-miR-196a-5p comprises: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 15; a PCR amplification primer pair comprising the sequences shown in SEQ ID NOs: 24 and 28; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 34; a detection reagent for detecting the level of hsa-miR-409-5p comprises: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 16; a PCR amplification primer pair comprising the sequences shown in SEQ ID NOs: 25 and 28; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 34 and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 35; a detection reagent for detecting the level of hsa-miR-520d-5p comprises: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 17; a PCR amplification primer pair comprising the sequences shown in SEQ ID NOs: 26 and 28; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 36;The detection reagents for detecting the level of hsa-miR-33b-3p include: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 18; a PCR amplification primer pair comprising the sequences shown in SEQ ID NO: 27 and 28; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 37.

[0018] In some embodiments, the detection kit further includes a detection reagent for detecting the level of hsa-miR-let-7d as an internal reference gene; the detection reagent includes: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 38; a PCR amplification primer pair comprising the sequences shown in SEQ ID NOs: 39 and 28; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 40.

[0019] In some embodiments, the detection kit further comprises a reagent for isolating exosomes from the biological sample; optionally, further comprises a reagent for extracting miRNA from the exosomes.

[0020] In some embodiments, the detection kit further comprises instructions for determining the colorectal cancer status of the subject based on logistic regression according to the level of the miRNA biomarker.

[0021] In some embodiments, the biological sample is selected from the group consisting of blood, serum, plasma, feces, milk, ascites, urine, and tissue biopsy; preferably plasma, serum, or feces.

[0022] In another aspect, provided herein is a method for identifying colorectal cancer status in a subject, comprising: 1) isolating exosomes from a biological sample from the subject; 2) detecting the level of a miRNA biomarker in the exosomes, wherein the miRNA biomarker is selected from the group consisting of hsa-miR-320a-3p, hsa-miR-19a-3p, hsa-miR-19b-3p, hsa-miR-31-5p, hsa-miR-92a-3p, hsa-miR-196a-5p, hsa-miR-409-5p, hsa-miR-520d-5p and hsa-miR-33b-3p, and any combination thereof; and 3) comparing the level of the miRNA biomarker detected in step 2) with the level of the corresponding miRNA in a population to determine the colorectal cancer status in the subject.

[0023] In some embodiments, the miRNA biomarkers include hsa-miR-320a-3p, hsa-miR-19b-3p, or hsa-miR-196a-5p; include hsa-miR-320a-3p, hsa-miR-31-5p, and hsa-miR-409-5p; or include hsa-miR-19b-3p, hsa-miR-196a-5p, and hsa-miR-33b-3p.

[0024] In some embodiments, the miRNA biomarker is hsa-miR-320a-3p, hsa-miR-19a-3p, hsa-miR-19b-3p, hsa-miR-31-5p, hsa-miR-92a-3p, hsa-miR-196a-5p, hsa-miR-409-5p, hsa-miR-520d-5p, and hsa-miR-33b-3p.

[0025] In some embodiments, the colorectal cancer status includes colorectal cancer susceptibility or the presence, progression, subtype, stage, and / or differentiation status of colorectal cancer.

[0026] In some embodiments, the colorectal cancer status is colorectal cancer stage I or stage II, and the miRNA biomarker is hsa-miR-320a-3p, hsa-miR-19b-3p and / or hsa-miR-196a-5p.

[0027] In some embodiments, the colorectal cancer state is adenocarcinoma and the miRNA biomarker is hsa-miR-320a-3p, hsa-miR-19a-3p, hsa-miR-31-5p, hsa-miR-92a-3p, hsa-miR-196a-5p, hsa-miR-409-5p and / or hsa-miR-33b-3p.

[0028] In some embodiments, the colorectal cancer state is mucinous adenocarcinoma and the miRNA biomarker is hsa-miR-320a-3p, hsa-miR-31-5p, hsa-miR-196a-5p and / or hsa-miR-19b-3p.

[0029] In some embodiments, the colorectal cancer state is signet ring cell carcinoma and the miRNA biomarker is hsa-miR-320a-3p, hsa-miR-92a-3p, hsa-miR-196a-5p and / or hsa-miR-33b-3p.

[0030] In some embodiments, the colorectal cancer state is other types of colorectal cancer, and the miRNA biomarker is hsa-miR-320a-3p, hsa-miR-19a-3p, hsa-miR-19b-3p, hsa-miR-31-5p, hsa-miR-196a-5p, hsa-miR-409-5p, hsa-miR-520d-5p and / or hsa-miR-33b-3p.

[0031] In some embodiments, the detection of the miRNA biomarker level in step 2) comprises using a miRNA biomarker-specific detection reagent, wherein the detection reagent comprises a reverse transcription primer, a PCR amplification primer pair, and / or a Taqman probe.

[0032] In some embodiments, the detection reagents for detecting the level of hsa-miR-320a-3p include: a reverse transcription primer including the sequence shown in SEQ ID NO: 10; a PCR amplification primer pair including the sequences shown in SEQ ID NOs: 19 and 28; and / or a Taqman probe including the sequence shown in SEQ ID NO: 29; the detection reagents for detecting the level of hsa-miR-19a-3p include: a reverse transcription primer including the sequence shown in SEQ ID NO: 11; a PCR amplification primer pair including the sequences shown in SEQ ID NOs: 20 and 28; and / or a Taqman probe including the sequence shown in SEQ ID NO: 30; the detection reagents for detecting the level of hsa-miR-19b-3p include: a reverse transcription primer including the sequence shown in SEQ ID NO: 12; a PCR amplification primer pair including the sequences shown in SEQ ID NOs: 21 and 28; and / or a Taqman probe including the sequence shown in SEQ ID NO: 31; the detection reagents for detecting the level of hsa-miR-31-5p include: a reverse transcription primer including the sequence shown in SEQ ID NO: 13; a PCR amplification primer pair including the sequences shown in SEQ ID NOs: 21 and 28; and / or a Taqman probe including the sequence shown in SEQ ID NO: 32 NO: 13; a PCR amplification primer pair comprising the sequences shown in SEQ ID NOs: 22 and 28; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 32; a detection reagent for detecting the level of hsa-miR-92a-3p comprises: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 14; a PCR amplification primer pair comprising the sequences shown in SEQ ID NOs: 23 and 28; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 33; a detection reagent for detecting the level of hsa-miR-196a-5p comprises: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 15; a PCR amplification primer pair comprising the sequences shown in SEQ ID NOs: 24 and 28; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 34; a detection reagent for detecting the level of hsa-miR-409-5p comprises: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 16; a PCR amplification primer pair comprising the sequences shown in SEQ ID NOs: 25 and 28; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 34 and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 35; a detection reagent for detecting the level of hsa-miR-520d-5p comprises: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 17; a PCR amplification primer pair comprising the sequences shown in SEQ ID NOs: 26 and 28; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 36;The detection reagents for detecting the level of hsa-miR-33b-3p include: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 18; a PCR amplification primer pair comprising the sequences shown in SEQ ID NO: 27 and 28; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 37.;

[0033] In some embodiments, step 2) further includes detecting the level of hsa-miR-let-7d as an internal reference gene; the detection reagents for detecting the level of hsa-miR-let-7d include: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 38; a PCR amplification primer pair comprising the sequences shown in SEQ ID NO: 39 and 28; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 40.

[0034] In some embodiments, step 3) includes determining the colorectal cancer status in the subject based on logistic regression according to the miRNA biomarker level.

[0035] In some embodiments, the biological sample is selected from blood, serum, plasma, feces, milk, ascites, urine, and tissue biopsy; preferably plasma, serum, or feces.

[0036] The detection kits and methods provided herein can provide an efficient, non-invasive, and accurate new approach for the screening, diagnosis, and prognostic analysis of early colorectal cancer. Brief Description of the Drawings

[0037] Figure 1 Shows the level distribution (relative expression) of 9 exosomal miRNA biomarkers in different stages of colorectal cancer. ***: P value ≤ 0.001; **: 0.001 < P ≤ 0.01; *: 0.01 < P value ≤ 0.05; ns: P value > 0.05.

[0038] Figure 2 Shows the level distribution (relative expression) of 9 exosomal miRNA biomarkers in different subtypes of colorectal cancer. ***: P value ≤ 0.001; **: 0.001 < P ≤ 0.01; *: 0.01 < P value ≤ 0.05; ns: P value > 0.05. <了

[0039] Figure 3Receiver operating characteristic (ROC) curves for single miRNA markers and different combinations of miRNA markers for colorectal cancer diagnosis are shown. (A) hsa-miR-320a-3p alone; (B) hsa-miR-19b-3p alone; (C) hsa-miR-196a-5p alone; (D) hsa-miR-320a-3p + hsa-miR-31-5p + hsa-miR-409-5p combination; (E) hsa-miR-19b-3p + hsa-miR-196a-5p + hsa-miR-33b-3p combination; (F) nine biomarker combinations. The horizontal axis represents 100 minus specificity; the vertical axis represents sensitivity. DETAILED DESCRIPTION

[0040] Unless otherwise specified, the technical terms used in this application have the meanings commonly understood by those skilled in the art to which the present invention belongs.

[0041] The present application relates to a method for early diagnosis of colorectal cancer, comprising the following steps: 1) collecting a biological sample; 2) determining the expression level of exosomal miRNA biomarkers in the biological sample, wherein the markers are one or more of hsa-miR-320a-3p, hsa-miR-19a-3p, hsa-miR-19b-3p, hsa-miR-31-5p, hsa-miR-92a-3p, hsa-miR-196a-5p, hsa-miR-409-5p, hsa-miR-520d-5p, and hsa-miR-33b-3p; and 3) comparing the expression level of the exosomal miRNA detected in step 2) with the expression level of the corresponding biomarker in a population to determine whether the subject has colorectal cancer. The sequences of the above-mentioned miRNA biomarkers and the internal reference (hsa-miR-let-7d) are as follows.

[0042]

[0043] As used herein, the term "subject" refers to an individual who has or is suspected of having a disease. In predicting susceptibility, "subject" may also include healthy individuals. This term is often used interchangeably with "patient," "test subject," "treatment subject," and the like.

[0044] The term "population" as used here generally refers to healthy people. When analyzing a specific disease, a "population" can also refer to people who do not have that disease but have other conditions. For example, for colorectal cancer, the population can include healthy people or non-colorectal cancer patients, including those with adenomas, enteritis, polyps, and some other types of cancer. Additionally, individuals can be designated as "populations" based on characteristics such as age, smoking status, alcoholism, and personal health status. Exosomal miRNA levels within a population can be determined by measuring a sufficient number of individuals.

[0045] In addition, the method can also be used to predict the colorectal cancer stage of the subject, and recommendations can be made for the subject's treatment based on this, such as further colorectal examination, surgical operation, medication guidance, or no further action.

[0046] Detection of exosomal miRNA in step 2) involves precipitating exosomes from a biological sample, extracting exosomal miRNA, and measuring expression levels using marker-specific RT-PCR primers and fluorescence quantitative primers. The inventors designed primer pairs specific to the gene sequence of each biomarker, including primers for hsa-miR-let-7d, which serves as an internal control.

[0047] In some embodiments, the primers and probes corresponding to the biomarkers used in the method can be purchased commercially. For example, the exosomal miRNA marker primers used in the Examples herein include specific miRNA stem-loop RT-PCR primers synthesized and produced by Sangon Biotech (Shanghai) Co., Ltd.

[0048] In an embodiment of the method of the present invention, the reporter fluorescent group at the 5' end of the fluorescent probe can be FAM, JOE, TET, HEX, Cy3, Texas Red, Rox or Cy5; the quencher group at the 3' end can be BHQ1, BHQ2, BHQ3, TAMRA, DABCYL or MGB.

[0049] The biological sample is mainly derived from the subject's body fluids, including blood, serum, plasma, feces, milk, ascites, urine and tissue biopsy, etc., preferably plasma, serum and feces.

[0050] In the method of the present invention, the subject's age, smoking and drinking status, whether he or she suffers from diabetes, and family history of colorectal cancer can be used as reference indicators to provide a more accurate graded risk prediction for the diagnosis of colorectal cancer.

[0051] In some embodiments, a diagnostic model based on the expression level of exosomal miRNA is constructed using a statistical method selected from the following methods: rank sum test, multiple linear regression, principal component analysis, decision tree, random forest, Probit regression, logistic regression, cluster analysis, neural network, Bayesian and non-Bayesian methods, etc. 2 The differences in miRNA expression levels among different study groups were compared using t-test, paired t-test, and nonparametric rank sum test. The diagnostic value of miRNA biomarkers (or their combination) was confirmed by calculating ROC curve analysis.

[0052] This method can provide clinicians with reference information beyond existing colorectal cancer monitoring methods, and can assist physicians in assessing and grading patients' risk of colorectal cancer and planning subsequent actions.

[0053] The methods of the present invention can be used for the prognosis of colorectal cancer. For example, biological samples can be obtained from subjects before and after treatment, or during treatment, and the expression levels of exosomal miRNAs can be measured using the methods described above. By dynamically monitoring miRNA expression levels, the efficacy of the current treatment regimen can be determined.

[0054] The combination of these biomarker miRNAs provides a novel method for determining the pathological classification and staging of colorectal cancer lesions. Furthermore, the expression levels of exosomal miRNAs in biological samples correlate with the presence of premalignant or preclinical conditions in patients. Therefore, this method can also be used to predict the presence of colorectal cancer, its benign or malignant nature, and the likelihood of colorectal cancer metastasis.

[0055] The method for measuring the biomarker exosomal miRNA is selected from one or more of the following methods: real-time fluorescence quantitative PCR, Northern blotting, digital PCR, microarray chip method, high-throughput sequencing, nanogold labeling method, high-resolution melting curve technology and time-of-flight mass spectrometry.

[0056] As used herein, "and / or" refers to any one or any combination of the preceding and following objects. For example, "A, B and / or C" may include A, B, C, "A and B", "A and C", "B and C", and "A, B and C".

[0057] This article discloses exosomal miRNA markers relevant to the auxiliary diagnosis of colorectal cancer and their applications. The markers are one or more of hsa-miR-320a-3p, hsa-miR-19a-3p, hsa-miR-19b-3p, hsa-miR-31-5p, hsa-miR-92a-3p, hsa-miR-196a-5p, hsa-miR-409-5p, hsa-miR-520d-5p, and hsa-miR-33b-3p. Exosomal miRNAs play an important role in tumorigenesis, invasion, and metastasis. Studies have shown that the contents of exosomes are directly derived from parent cells and have excellent stability and integrity. Therefore, as novel markers, exosomal miRNAs offer inherent advantages such as strong diagnostic capabilities, high stability, and easy access. The development of such markers will provide new diagnostic and therapeutic approaches for a variety of diseases, including cancer. This article discloses a preferred combination of exosomal miRNA markers for diagnosing colorectal cancer. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve analysis of this combination can reach 0.964, with an accuracy of 94.19% and a specificity of 96.26%.

[0058] The present invention is further described below by way of examples.

[0059] Example 1: Extraction of plasma exosomes

[0060] The brief process of extracting exosomes from plasma is as follows:

[0061] 1. Take out the plasma to be tested and centrifuge it at 3000×g for 15 minutes to remove some debris and insoluble components.

[0062] 2. The exosome extraction kit was ExoQuick kit (EXOQ5TM-1, SBI). The supernatant was transferred to a new 1.5 mL EP tube and an appropriate amount of ExoQuick-TC was added. The two were thoroughly mixed using a vortex shaker.

[0063] 3. Incubate the plasma thoroughly mixed with ExoQuick-TC at 4°C for more than 12 hours.

[0064] 4. Centrifuge the incubated ExoQuick-TC / plasma mixture at 1500×g for 30 minutes. Exosomes will precipitate as beige solids at the bottom of the EP tube.

[0065] 5. Discard the supernatant and resuspend the exosomes in 1× PBS solution for later use.

[0066] Example 2: Extraction of exosomal miRNA

[0067] ABI plasma RNA extraction kit (AM1556) was used. According to the kit instructions, 200 μl of exosome resuspension was aspirated from each sample to extract RNA, and finally dissolved with 100 μl DEPC water.

[0068] Example 3: Preparation of cDNA

[0069] miRNA reverse transcription reaction system

[0070] Reagents used to prepare the reverse transcription reaction system were purchased from Sangon Biotech (Shanghai) Co., Ltd., including M-MuLV reverse transcriptase (Cat: B600005), RNase inhibitor (Cat: B600008), and dNTP Mix 10 mM (Cat: B500056). The reverse transcription reaction system is as follows:

[0071] Table 1 Reverse transcription reaction system

[0072]

[0073]

[0074] Reverse transcription procedure:

[0075] 16℃ for 30min, 42℃ for 30min, 85℃ for 5min, cooling down by 4℃.

[0076] Example 4: Real-time fluorescence PCR detection of miRNA expression levels

[0077] This example uses real-time fluorescence quantitative PCR as an example to detect miRNA expression levels. The miRNA markers detected are hsa-miR-320a-3p, hsa-miR-19a-3p, hsa-miR-19b-3p, hsa-miR-31-5p, hsa-miR-92a-3p, hsa-miR-196a-5p, hsa-miR-409-5p, hsa-miR-520d-5p, and hsa-miR-33b-3p, with hsa-let-7d as the internal reference. Primers and probes for these ten miRNAs were designed as follows:

[0078] hsa-miR-320a-3p primer set

[0079] Reverse transcription primers:

[0080] 5'-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACTCGCCC-3' (SEQ ID NO: 10)

[0081] Forward primer: 5'-GCGAAAAGCTGGGTTGAGA-3' (SEQ ID NO: 19)

[0082] Probe: NO 7: 5'-Cy5-GGATACGACTCGCCC-BHQ3-3' (SEQ ID NO: 29)

[0083] hsa-miR-19a-3p primer set

[0084] Reverse transcription primers:

[0085] 5'-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACTCAGTT-3' (SEQ ID NO: 11)

[0086] Forward primer: 5'-GCGTGTGCAAATCTATGCAA-3' (SEQ ID NO: 20)

[0087] Probe: 5'-Texas Red-CTGAGTCGTATCCAGTGCG-BHQ2-3' (SEQ ID NO: 30)

[0088] hsa-miR-19b-3p primer set

[0089] Reverse transcription primers:

[0090] 5'-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACTCAGTT-3' (SEQ ID NO: 12)

[0091] Forward primer: 5'-CGTGTGCAAATCCATGCAA-3' (SEQ ID NO: 21)

[0092] Probe: 5'-HEX-ACTGAGTCGTATCCAGTGCG-BHQ1-3' (SEQ ID NO: 31)

[0093] hsa-miR-31-5p primer set

[0094] Reverse transcription primers:

[0095] 5'-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACAGCTAT-3' (SEQ ID NO: 13)

[0096] Forward primer: 5'-GCGAGGCAAGATGCTGGC-3' (SEQ ID NO: 22)

[0097] Probe: 5'-FAM-GCTGTCGTATCCAGTGCG-BHQ2-3' (SEQ ID NO: 32)

[0098] hsa-miR-92a-3p primer set

[0099] Reverse transcription primers:

[0100] 5'-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACACAGGC-3' (SEQ ID NO: 14)

[0101] Forward primer: 5'-GCGTATTGCACTTGTCCCG-3' (SEQ ID NO: 23)

[0102] Probe: 5'-Texas Red-GATACGACACAGGCCG-BHQ2-3' (SEQ ID NO: 33)

[0103] hsa-miR-196a-5p primer set

[0104] Reverse transcription primers:

[0105] 5'-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACCCCAAC-3' (SEQ ID NO: 15)

[0106] Forward primer: 5'-CGCGCGTAGGTAGTTTCATGTT-3' (SEQ ID NO: 24)

[0107] Probe: 5'-CY5-TGGGGTCGTATCCAGTGC-BHQ1-3' (SEQ ID NO: 34)

[0108] hsa-miR-409-5p primer set

[0109] Reverse transcription primers:

[0110] 5'-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACATGCAA-3' (SEQ ID NO: 16)

[0111] Forward primer: 5'-GCGAGGTTACCCGAGCAACT-3' (SEQ ID NO: 25)

[0112] Probe: 5'-FAM-TGCATGTCGTATCCAGTGC-BHQ2-3' (SEQ ID NO: 35)

[0113] hsa-miR-520d-5p primer set

[0114] Reverse transcription primers:

[0115] 5'-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACGGGGCT-3' (SEQ ID NO: 17)

[0116] Forward primer: 5'-CGCGCGCACAAAGGGA-3' (SEQ ID NO: 26)

[0117] Probe: 5'-HEX-CCCGTCGTATCCAGTGC-BHQ2-3' (SEQ ID NO: 36)

[0118] hsa-miR-33b-3p primer set

[0119] Reverse transcription primers:

[0120] 5'-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACGGGCTG-3' (SEQ ID NO: 18)

[0121] Forward primer: 5'-GCAGTGCCTCGGCAGTG-3' (SEQ ID NO: 27)

[0122] Probe: 5'-Texas Red-GCCCGTCGTATCCAGTG-BHQ2-3' (SEQ ID NO: 37)

[0123] Primer set for miRNA detection internal reference gene let-7

[0124] Reverse transcription primers:

[0125] 5'-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACAACTAT-3' (SEQ ID NO: 38)

[0126] Forward primer: 5'-GCCCGCAGAGGTAGTAGGTTGC-3' (SEQ ID NO: 39)

[0127] Probe: 5'-FAM-CTGGATACGACAACTAT-BHQ1-3' (SEQ ID NO: 40)

[0128] According to the miRNA stem-loop primer design principle, the above miRNAs share the same set of reverse primers:

[0129] 5'-AGTGCAGGGTCCGAGGTATT-3' (SEQ ID NO: 28)

[0130] To detect miRNA expression levels, PCR reactions were performed three times for each sample. The total volume of each reaction system was 20 μl, including 10 μl PCR reaction solution, 5 μl primer mixture, and 5 μl PCR template (see Table 2 below).

[0131] Table 2 Reaction procedures for detecting miRNA expression levels

[0132]

[0133] Example 5: Determination of sensitivity and specificity of plasma in patients with colorectal cancer and non-colorectal cancer populations (including patients with benign conditions, other types of cancer interference, and healthy people)

[0134] 845 samples from patients with pathologically confirmed colorectal cancer ("case group") and 728 samples from patients with confirmed non-colorectal cancer ("control group") were used. The control group included 224 patients with enteritis, 232 patients with pathologically confirmed non-cancerous colorectal polyps, 198 patients with pathologically confirmed non-cancerous colorectal adenomas, and 74 other types of samples (specifically, 27 colorectal healthy samples and 47 other cancers: 22 gastric cancers, 10 esophageal cancers, and 15 liver cancers) (see Table 3). All samples were collected from Beijing Aipuyi Medical Testing Center. The colorectal cancer samples in the case group included all stages and common types of the disease. Colorectal cancer patients were diagnosed by colonoscopy, imaging, and pathology. The sample staging was based on the international TNM staging standard, and the sample typing was determined by tissue biopsy and immunohistochemistry. The control group samples included common types of benign conditions seen in the entire study population, some other types of cancer interference samples, and some colorectal healthy normal samples. Complete clinical pathology reports were obtained after surgery, including patient age, smoking history, race, stage, type, and collection location coded for each sample.

[0135] Table 3 Colorectal cancer stage and other characteristics of the subjects

[0136]

[0137]

[0138] As shown in Table 3, a total of 1573 samples were studied. The case group included 845 patients with pathologically confirmed colorectal cancer, encompassing patients of all common colorectal cancer types and stages. The control group consisted of 728 samples from patients diagnosed with non-colorectal cancer, including 224 patients with enteritis, 232 patients with pathologically confirmed non-cancerous colorectal polyps, 198 patients with pathologically confirmed non-cancerous colorectal adenomas, and 74 samples of other types (specifically, 27 samples with normal colorectal function and 47 samples with other cancers: 22 gastric cancer, 10 esophageal cancer, and 15 liver cancer). Plasma was used for the study, and real-time PCR was used to measure the expression levels of exosomal miRNAs in these 1573 samples. To help determine the ability of these biomarker genes to distinguish between cancers and benign colorectal diseases with similar symptoms, all samples were obtained from the same clinical cohort (patients undergoing surgery for colorectal polyps). All samples were collected before any intervention and before disease status was known. The disease status was then determined by pathological examination of the ex vivo tissue. A single sample collection scheme was used to collect plasma and monitor compliance. This ensured sample quality and eliminated the possibility of any collection, processing and biological bias in the sample set. These samples showed that the average patient age (58.43 years) in individuals with colorectal cancer was higher than that in those with benign conditions or healthy individuals (55.68 years), and there was a trend of increasing with the progression of the disease stage (Table 3). Overall, the distribution of colorectal cancer types was similar to that seen in all colorectal cancer cases in the population, with the proportion of adenocarcinoma (70%) being higher than that of other types of colorectal cancer. The non-colorectal cancer controls in the study represented common benign colorectal diseases, including enteritis, intestinal polyps, adenomas, etc., as well as interference samples of some other types of cancer and some healthy samples.

[0139] To determine the diagnostic ability of the selected biomarkers for different stages of colorectal cancer (especially early stage), the detection levels of 9 miRNA markers in benign samples and colorectal cancer samples of different stages were compared ( Figure 1 For early colorectal cancer samples, hsa-miR-320a-3p, hsa-miR-19b-3p, and hsa-miR-196a-5p had a high degree of discrimination (P value < 0.001); hsa-miR-31-5p, hsa-miR-19a-3p, and hsa-miR-33b-3p also showed a certain degree of significant difference between early colorectal cancer and benign diseases (P value < 0.05), but the effect was slightly weaker.

[0140] In addition, we compared the levels of the above 9 miRNAs between samples of benign conditions and various subtypes of colorectal cancer to see if there were statistically significant differences ( Figure 2 For adenocarcinoma, hsa-miR-320a-3p, hsa-miR-19a-3p, hsa-miR-31-5p, hsa-miR-92a-3p, hsa-miR-196a-5p, hsa-miR-409-5p, and hsa-miR-33b-3p all had high discriminatory power (P < 0.001), whereas hsa-miR-19b-3p and hsa-miR-520d-5p had slightly poorer discriminatory power (P < 0.01). For mucinous adenocarcinoma, hsa-miR-320a-3p, hsa-miR-31-5p, hsa-miR-196a-5p, and hsa-miR-19b-3p had high discriminatory power (P < 0.001). For signet ring cell carcinoma, hsa-miR-320a-3p, hsa-miR-92a-3p, hsa-miR-196a-5p, and hsa-miR-33b-3p showed high discriminatory power (P < 0.001), while hsa-miR-19b-3p and hsa-miR-409-5p showed slightly lower discriminatory power (P < 0.05). For other types of colorectal cancer, except for hsa-miR-92a-3p, other miRNA markers showed good discriminatory power (P < 0.01).

[0141] In terms of simplicity and cost reduction, measuring single miRNA levels is superior to measuring multiple miRNA markers. However, single miRNA levels may not provide the inherent diversity of complex diseases, so the construction of multiple marker diagnostic models is often necessary. Multiple marker diagnostic models require the use of statistical analysis methods. The following uses a logistic regression model as an example to construct a multiple miRNA marker diagnostic model.

[0142] The logistic regression model was constructed by dividing the samples into case and control groups and then optimizing the regression coefficients using commercially available software packages (IBM SPSS Statistics 24 and MedCalc 11.4.2.0, purchased from IBM and MedCalc, respectively). There was a regression coefficient for each marker, plus a bias parameter, to maximize the likelihood of the logistic regression model for the training data. After training, the set of regression coefficients defined the logistic regression model. By substituting the expression levels of the miRNA markers into the logistic regression equation, one skilled in the art can easily use this diagnostic model to predict the likelihood of any new sample being a case or a control.

[0143] The inventors compared the effectiveness of single markers and multi-marker combinations in diagnosing colorectal cancer, and obtained a more optimal combination by constructing a logistic regression model and analyzing the results. Among them, hsa-miR-320a-3p, hsa-miR-19b-3p, and hsa-miR-196a-5p were excellent in diagnosing colorectal cancer when used alone (see Figure 3 A, 3B, 3C). When analyzing the diagnostic efficacy of multi-marker combinations, it was found that hsa-miR-320a-3p+hsa-miR-31-5p+hsa-miR-409-5p and hsa-miR-19b-3p+ hsa-miR-196a-5p+hsa-miR-33b-3p could provide better diagnostic performance for colorectal cancer (see Figure 3 To achieve better diagnosis of colorectal cancer, we conducted a comprehensive analysis of the expression levels of 9 miRNAs. The results showed that the combined analysis of 9 miRNA markers can achieve better diagnostic efficacy, with an AUC value of 0.964 (see Figure 3 F). The area under the curve (AUC) information of the receiver operating characteristic (ROC) curve analysis obtained for each marker and combination is summarized in Table 4 below.

[0144] Table 4 Area under the curve (AUC) of receiver operating characteristic (ROC) curve analysis of selected markers and combinations

[0145]

[0146] To determine the sensitivity of the selected markers and combinations for identifying different stages of colorectal cancer, particularly early stages (I or II), the diagnostic sensitivity of colorectal cancer samples at each stage, particularly early stages (the most critical period for marker detection), was measured and compared. The results showed that the diagnostic sensitivity of single markers for early colorectal cancer was slightly lower than that of marker combinations. However, the diagnostic sensitivity of each marker combination increased with increasing colorectal cancer stage. The combination of "hsa-miR-320a-3p+hsa-miR-31-5p+hsa-miR-409-5p" and the nine markers achieved a sensitivity of over 90% for both stages I and II, demonstrating strong diagnostic capabilities for early colorectal cancer (see Table 5).

[0147] Table 5 Sensitivity of each marker and combination in different colorectal cancer stages

[0148]

[0149] To evaluate the sensitivity of the selected markers and combinations for identifying different types of colorectal cancer (particularly adenocarcinoma, which accounts for a relatively high proportion), the diagnostic sensitivity of the markers and combinations was compared across common colorectal cancer subtypes. The results showed that hsa-miR-320a-3p, hsa-miR-320a-3p + hsa-miR-31-5p + hsa-miR-409-5p demonstrated diagnostic sensitivities exceeding 95% for each subtype of colorectal cancer. Combined analysis of hsa-miR-196a-5p and nine other markers demonstrated a diagnostic sensitivity of ≥90% for each subtype of colorectal cancer, demonstrating excellent diagnostic efficacy (Table 6).

[0150] Table 6 Sensitivity of each marker and combination in different colorectal cancer types

[0151]

[0152] To evaluate the specificity of the two marker combinations in a control group of non-colorectal cancer patients, the study included samples from common colorectal diseases such as enteritis, polyps, and adenomas, as well as other control samples (interfering samples from other cancer types and healthy individuals). The specificity of the two combinations was compared in non-colorectal cancer samples, particularly those from diseases or other cancers that are easily confused with colorectal cancer. The results showed that the selected miRNA markers, when used alone, demonstrated good discrimination against common colorectal cancer interfering samples. The combinations of "hsa-miR-320a-3p + hsa-miR-31-5p + hsa-miR-409-5p" and "hsa-miR-19b-3p + hsa-miR-196a-5p + hsa-miR-33b-3p" achieved diagnostic specificity exceeding 96% for colorectal polyps and adenomas, and combined analysis of all nine markers further increased the discrimination ability to 97.8% (see Table 7).

[0153] Table 7 Specificity of each marker and combination in control samples

[0154]

[0155] To evaluate the sensitivity of the selected markers and combinations for identifying different grades of colorectal cancer differentiation (see the UICC / AJCC TNM staging system for details), the sensitivity of the two combinations was compared across different differentiation grades, particularly low-grade and undifferentiated samples. The results showed that single miRNA markers were less effective in diagnosing colorectal cancer of varying differentiation grades. The combinations of "hsa-miR-320a-3p + hsa-miR-31-5p + hsa-miR-409-5p" and "hsa-miR-19b-3p + hsa-miR-196a-5p + hsa-miR-33b-3p" achieved diagnostic specificity exceeding 92% for poorly differentiated colorectal cancer. The combined use of all nine markers increased the overall diagnostic specificity for poorly differentiated colorectal cancer to 96%. The sensitivity also increased with increasing differentiation (see Table 8).

[0156] Table 8 Sensitivity of each marker and combination in different grades of colorectal cancer differentiation

[0157]

[0158]

[0159] The technical solution provided in this article improves the sensitivity and specificity of colorectal cancer detection by jointly detecting multiple exosomal miRNAs, thereby ensuring the accuracy and reliability of the test results.

[0160] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them. Those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may be modified, or some or all of the technical features therein may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments herein, and they should all be included in the scope of the specification herein. SEQUENCE LISTING <110> Beijing Aikelun Medical Technology Co., Ltd. <120> Detection kit and method for identifying colorectal cancer status through exosomal miRNA markers <130> 21800CI <160> 41 <170> PatentIn version 3.3 <210> 1 <211> twenty two <212> RNA <213> Homo sapiens <400> 1 cagugguuuu acccuauggu ag 22 <210> 2 <211> 23 <212> RNA <213> Homo sapiens <400> 2 ugugcaaauc uaugcaaaac uga 23 <210> 3 <211> 23 <212> RNA <213> Homo sapiens <400> 3 ugugcaaauc caugcaaaac uga 23 <210> 4 <211> 21 <212> RNA <213> Homo sapiens <400> 4 aggcaagaug cuggcauagc u 21 <210> 5 <211> 22 <212> RNA <213> Homo sapiens <400> 5 ucguaccgug aguaauaaug cg 22 <210> 6 <211> 22 <212> RNA <213> Homo sapiens <400> 6 uagguaguuu cauguuguug gg 22 <210> 7 <211> 23 <212> RNA <213> Homo sapiens <400> 7 agguuacccg agcaacuuug cau 23 <210> 8 <211> 20 <212> RNA <213> Homo sapiens <400> 8 cuacaaaggg aagcccuuuc 20 <210> 9 <211> twenty two <212> RNA <213> Homo sapiens <400> 9 cagugccucg gcagugcagc cc 22 <210> 10 <211> 50 <212> DNA <213> Artificial <220> <223> Reverse transcription primers <400> 10 gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgactcgccc 50 <210> 11 <211> 50 <212> DNA <213> Artificial <220> <223> Reverse transcription primers <400> 11 gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgactcagtt 50 <210> 12 <211> 50 <212> DNA <213> Artificial <220> <223> Reverse transcription primers <400> 12 gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgactcagtt 50 <210> 13 <211> 50 <212> DNA <213> Artificial <220> <223> Reverse transcription primers <400> 13 gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgacagctat 50 <210> 14 <211> 50 <212> DNA <213> Artificial <220> <223> Reverse transcription primers <400> 14 gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgacacaggc 50 <210> 15 <211> 50 <212> DNA <213> Artificial <220> <223> Reverse transcription primers <400> 15 gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgaccccaac 50 <210> 16 <211> 50 <212> DNA <213> Artificial <220> <223> Reverse transcription primers <400> 16 gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgacatgcaa 50 <210> 17 <211> 50 <212> DNA <213> Artificial <220> <223> Reverse transcription primers <400> 17 gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgacggggct 50 <210> 18 <211> 50 <212> DNA <213> Artificial <220> <223> Reverse transcription primers <400> 18 gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgacgggctg 50 <210> 19 <211> 19 <212> DNA <213> Artificial <220> <223> Forward primer <400> 19 gcgaaaagct gggttgaga 19 <210> 20 <211> 20 <212> DNA <213> Artificial <220> <223> Forward primer <400> 20 gcgtgtgcaa atctatgcaa 20 <210> twenty one <211> 19 <212> DNA <213> Artificial <220> <223> Forward primer <400> twenty one cgtgtgcaaa tccatgcaa 19 <210> twenty two <211> 18 <212> DNA <213> Artificial <220> <223> Forward primer <400> twenty two gcgaggcaag atgctggc 18 <210> twenty three <211> 19 <212> DNA <213> Artificial <220> <223> Forward primer <400> twenty three gcgtattgca cttgtcccg 19 <210> twenty four <211> twenty two <212> DNA <213> Artificial <220> <223> Forward primer <400> twenty four cgcgcgtagg tagtttcatg tt 22 <210> 25 <211> 20 <212> DNA <213> Artificial <220> <223> Forward primer <400> 25 gcgaggttac ccgagcaact 20 <210> 26 <211> 16 <212> DNA <213> Artificial <220> <223> Forward primer <400> 26 cgcgcgcaca aaggga 16 <210> 27 <211> 17 <212> DNA <213> Artificial <220> <223> Forward primer <400> 27 gcagtgcctc ggcagtg 17 <210> 28 <211> 20 <212> DNA <213> Artificial <220> <223> Reverse primer <400> 28 agtgcagggt ccgaggtatt 20 <210> 29 <211> 15 <212> DNA <213> Artificial <220> <223> probe <400> 29 ggatacgact cgccc 15 <210> 30 <211> 19 <212> DNA <213> Artificial <220> <223> probe <400> 30 ctgagtcgta tccagtgcg 19 <210> 31 <211> 20 <212> DNA <213> Artificial <220> <223> 32 <400> 31 actgagtcgt atccagtgcg 20 <210> 32 <211> 18 <212> DNA <213> Artificial <220> <223> probe <400> 32 gctgtcgtat ccagtgcg 18 <210> 33 <211> 16 <212> DNA <213> Artificial <220> <223> probe <400> 33 gatacgacac aggccg 16 <210> 34 <211> 18 <212> DNA <213> Artificial <220> <223> probe <400> 34 tggggtcgta tccagtgc 18 <210> 35 <211> 19 <212> DNA <213> Artificial <220> <223> probe <400> 35 tgcatgtcgt atccagtgc 19 <210> 36 <211> 17 <212> DNA <213> Artificial <220> <223> probe <400> 36 cccgtcgtat ccagtgc 17 <210> 37 <211> 17 <212> DNA <213> Artificial <220> <223> probe <400> 37 gcccgtcgta tccagtg 17 <210> 38 <211> 50 <212> DNA <213> Artificial <220> <223> Reverse transcription primers <400> 38 gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgacaactat 50 <210> 39 <211> twenty two <212> DNA <213> Artificial <220> <223> Forward primer <400> 39 gcccgcagag gtagtaggtt gc 22 <210> 40 <211> 17 <212> DNA <213> Artificial <220> <223> probe <400> 40 ctggatacga caactat 17 <210> 41 <211> twenty two <212> RNA <213> Homo sapiens <400> 41 agagguagua gguugcauag uu 22

Claims

1. Use of a detection kit in the preparation of a diagnostic kit for diagnosing colorectal cancer in a subject, wherein the detection kit comprises a detection reagent for detecting the level of exosomal miRNA biomarkers in a biological sample from the subject, wherein the miRNA biomarkers are hsa-miR-320a-3p, hsa-miR-31-5p and hsa-miR-409-5p, and the biological sample is selected from blood, serum and plasma.

2. The use of claim 1, wherein the miRNA biomarker further comprises one or more of the following biomarkers: hsa-miR-19a-3p, hsa-miR-19b-3p, hsa-miR-92a-3p, hsa-miR-196a-5p, hsa-hsa-miR-520d-5p, and hsa-miR-33b-3p.

3. The method according to claim 1 or 2, wherein the detection reagent for detecting the level of miRNA biomarkers comprises a reverse transcription primer, a PCR amplification primer pair and / or a Taqman probe.

4. The use according to claim 1, wherein: Detection reagents for detecting the level of hsa-miR-320a-3p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 10; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 19 and 28; and / or a Taqman probe with the sequence shown in SEQ ID NO: 29; The detection reagents for detecting the level of hsa-miR-31-5p include: a reverse transcription primer of the sequence shown in SEQ ID NO: 13; a PCR amplification primer pair of the sequences shown in SEQ ID NO: 22 and 28; and / or a Taqman probe of the sequence shown in SEQ ID NO: 32; and The detection reagents for detecting the level of hsa-miR-409-5p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 16; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 25 and 28; and / or a Taqman probe with the sequence shown in SEQ ID NO:

35.

5. The use according to claim 2, wherein: Detection reagents for detecting the level of hsa-miR-320a-3p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 10; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 19 and 28; and / or a Taqman probe with the sequence shown in SEQ ID NO: 29; Detection reagents for detecting the level of hsa-miR-19a-3p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 11; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 20 and 28; and / or a Taqman probe with the sequence shown in SEQ ID NO: 30; Detection reagents for detecting the level of hsa-miR-19b-3p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 12; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 21 and 28; and / or a Taqman probe with the sequence shown in SEQ ID NO: 31; Detection reagents for detecting the level of hsa-miR-31-5p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 13; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 22 and 28; and / or a Taqman probe with the sequence shown in SEQ ID NO: 32; Detection reagents for detecting the level of hsa-miR-92a-3p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 14; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 23 and 28; and / or a Taqman probe with the sequence shown in SEQ ID NO: 33; Detection reagents for detecting the level of hsa-miR-196a-5p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 15; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 24 and 28; and / or a Taqman probe with the sequence shown in SEQ ID NO: 34; Detection reagents for detecting the level of hsa-miR-409-5p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 16; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 25 and 28; and / or a Taqman probe with the sequence shown in SEQ ID NO: 35; Detection reagents for detecting the level of hsa-miR-520d-5p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 17; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 26 and 28; and / or a Taqman probe with the sequence shown in SEQ ID NO: 36; and The detection reagents for detecting the level of hsa-miR-33b-3p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 18; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 27 and 28; and / or a Taqman probe with the sequence shown in SEQ ID NO:

37.

6. The use according to claim 1 or 2, wherein the detection kit further comprises a detection reagent for detecting the level of hsa-miR-let-7d as an internal reference gene; the detection reagent comprises: a reverse transcription primer having a sequence as shown in SEQ ID NO: 38; and a PCR amplification primer pair having sequences as shown in SEQ ID NO: 39 and 28; and / or a Taqman probe having the sequence shown in SEQ ID NO:

40.

7. The use according to claim 1 or 2, wherein the detection kit further comprises a reagent for isolating exosomes from the biological sample; optionally, further comprises a reagent for extracting miRNA from the exosomes.

8. The use according to claim 1 or 2, wherein the diagnostic kit comprises instructions for determining the colorectal cancer status in the subject based on logistic regression according to the level of the miRNA biomarker.

Images