Use of cfRNA in preparation of a marker product for early diagnosis of colorectal cancer

Abstract

The application provides application of cfRNA in preparation of a marker product for early diagnosis of colorectal cancer, the cfRNA being selected from one or more of 21 RNAs, and the product being a chip or a kit. Compared with the prior art, the application has the following advantages: the application of the cfRNA in preparation of the marker product for early diagnosis of colorectal cancer can be used for early screening of colorectal cancer, judgment of benign and malignant, differential diagnosis, monitoring of disease complications and recurrence, evaluation of curative effect, drug efficacy and guidance of precise medication and the like, and has the advantages of wide detection spectrum, high sensitivity, good specificity, low detection cost, convenient sampling, easy storage of samples and the like.

Description

Technical Field

[0001] This application relates to the field of biomedical technology, specifically to the application of cfRNA in the preparation of biomarker products for the early diagnosis of colorectal cancer. Background Technology

[0002] Colorectal cancer (CRC) is one of the most common malignant tumors worldwide. Environmental factors, dietary habits, and genetics all contribute to its development. Based on the source of mutations, CRC can be classified as sporadic (70%), hereditary (5%), and familial (20%), with genetic and environmental factors playing significant roles in its etiology. Epidemiological surveys show that over 1.9 million people worldwide develop CRC each year, ranking third in incidence and second in mortality among all cancers. National cancer statistics released by the China Cancer Center in 2022 show that China had 550,000 new CRC cases and 290,000 new deaths, ranking second and fifth in incidence and mortality among malignant tumors nationwide, respectively. Data shows that approximately 60% of CRC patients are diagnosed in developed countries, and over 70% of CRC patients are over 60 years old at the time of diagnosis.

[0003] Studies have shown that the 5-year survival rate for stage I CRC is 90%, while the 5-year survival rate for stage IV is only 10%. Despite the high morbidity and mortality rates of CRC, its early cure rate is high; if lesions are detected and surgically removed in the precancerous stage, the 5-year survival rate can reach 100%. Therefore, early screening, diagnosis, and treatment of CRC are of great significance in improving the survival rate of CRC patients. However, colonoscopy, pathological sections, fecal occult blood tests, and cancer-related antigen (CEA, CA199, CA50, CA724) screening are still the main methods for clinical diagnosis of CRC, which are insufficient to meet the needs of non-invasive, early, sensitive, and specific precision diagnosis and treatment of CRC in the new era. At the same time, limited by factors such as detection methods and costs, the early detection rate of CRC and other digestive system malignancies in my country is less than 10%. Therefore, developing new CRC detection biomarkers and methods, and promoting the widespread adoption of early screening and diagnosis of CRC and other malignancies, is of great practical significance in meeting the needs of precision medicine for CRC patients.

[0004] Circulating tumor RNA (cfRNA) is a novel direction in liquid biopsy for tumors, encompassing microRNA, tsRNA, rsRNA, and others. cfRNA detection offers advantages such as being non-invasive, providing dynamic monitoring, and overcoming tumor heterogeneity. The focus of tumor diagnosis, including CRC, is gradually shifting from traditional detection methods to liquid biopsy. Circulating tumor cells (CTCs) are an independent prognostic marker in stage IV CRC, but their capture is relatively difficult, limiting their clinical application. Circulating tumor genes (circulating tumor DNA), or ctDNA technology, is a novel liquid biopsy technique developed alongside targeted therapy. It primarily guides medication by detecting changes in driver genes, but faces inherent limitations in early tumor screening; therefore, no ctDNA product has yet been approved for use in this area. Blood contains a rich variety and quantity of cfRNAs, including microRNA, tsRNA, rsRNA, lncRNA, snoRNA, and other non-coding small RNAs. Furthermore, the abundance of cfRNAs in blood is higher than that of CTCs and ctDNA, but lower than that of proteins, making it more suitable as a target for screening and monitoring diseases such as tumors. Multiple studies have found that blood cfRNA has high sensitivity and specificity for the diagnosis of tumor-related diseases, with diagnostic efficacy superior to other types of biomarkers such as DNA. More importantly, compared to ctDNA, cfRNA can accurately reflect the origin and occurrence of tumors, and its content variations and sequence characteristics provide richer information for detection. Given the excellent properties and disease relevance of cfRNA, developing novel cfRNA-based biomarkers and detection technologies for early detection of CRC has significant clinical implications and broad market prospects. Summary of the Invention

[0005] To address the aforementioned technical limitations, this application proposes the application of cfRNA in the preparation of biomarker products for the early diagnosis of colorectal cancer; it overcomes the deficiencies and defects mentioned in the background art.

[0006] To achieve the above objectives, this application adopts the following technical solution:

[0007] The inventive point of this application is to provide the use of cfRNA in the preparation of biomarker products for the early diagnosis of colorectal cancer, wherein the cfRNA is selected from one or more of miR-26a, 16S-rRNA, tRNA-Asp-GTC, tRNA-Gly-CCC, miR-21, miR-451a, miR-92a-3p, 5.8S-rRNA, tRNA-His-GTG, miR-320a-3p, let-7g-5p, miR-223, miR-1274b, miR-16, let-7f, miR-98, 28S-rRNA, 45S-rRNA, miR-34b, tRNA-Val-CAC, and tRNA-Glu-CTC.

[0008] In actual use, the above-mentioned cfRNAs are specifically: hsa-miR-26a, 16S-rRNA, mature-tRNA-Asp-GTC_5_end, mature-tRNA-Gly-CCC_5_end, miR-21, hsa-miR-451a, hsa-miR-92a-3p, 5.8S-rRNA, mature-tRNA-His-GTG, hsa-miR-320a-3p, hsa-let-7g-5p, hsa-miR-223, miR-1274b, hsa-miR-16, hsa-let-7f, hsa-miR-98, 28S-rRNA, 45S-rRNA, hsa-miR-34b, mature-tRNA-Val-CAC_5_end, and mature-tRNA-Glu-CTC.

[0009] Optionally, in the application, the sequences of the above-mentioned cfRNA are shown as SEQ ID No. 1-SEQ ID No. 21 (Table 1).

[0010] Optionally, in the application, the above-mentioned cfRNA may preferably be tRNA-Asp-GTC, miR-223, let-7f, and 28S-rRNA.

[0011] Optionally, in the aforementioned application, the cfRNA may also be preferably selected as:

[0012] tRNA-Asp-GTC, miR-223, let-7f, 28S-rRNA, and tRNA-Glu-CTC; or

[0013] tRNA-Asp-GTC, miR-223, let-7f, 28S-rRNA, and 5.8S-rRNA; or

[0014] tRNA-Asp-GTC, miR-223, let-7f, 28S-rRNA, tRNA-Glu-CTC and 5.8S-rRNA.

[0015] Optionally, in the application, the aforementioned marker product includes a chip or a reagent kit.

[0016] Optionally, in the application, the above-mentioned biomarker product includes a reagent for detecting the expression level of cfRNA in sample plasma, wherein the cfRNA is selected from one or more of miR-26a, 16S-rRNA, tRNA-Asp-GTC, tRNA-Gly-CCC, miR-21, miR-451a, miR-92a-3p, 5.8S-rRNA, tRNA-His-GTG, miR-320a-3p, let-7g-5p, miR-223, miR-1274b, miR-16, let-7f, miR-98, 28S-rRNA, 45S-rRNA, miR-34b, tRNA-Val-CAC, and tRNA-Glu-CTC.

[0017] Optionally, in the application, the reagents are selected from: probes that specifically recognize the cfRNA; or primers that specifically amplify the cfRNA.

[0018] Optionally, in the above-mentioned primer sequences for specifically amplifying the cfRNA, the reverse transcription primer sequences are shown in SEQ ID No. 22-SEQ ID No. 42, the upstream primers are shown in SEQ ID No. 43-SEQ ID No. 63, and the downstream primers are shown in SEQ ID No. 64-SEQ ID No. 84; the probe sequences for specifically recognizing the cfRNA are shown in SEQ ID No. 85-SEQ ID No. 105 (Table 2).

[0019] The second inventive point of this application is to provide a biomarker product for the early diagnosis of colorectal cancer, wherein the biomarker product diagnoses colorectal cancer at an early stage by detecting the expression level of the cfRNA in a sample.

[0020] Optionally, the above-mentioned product is used to detect the expression level of the cfRNA using real-time quantitative PCR, gene chip, or high-throughput sequencing platform methods.

[0021] The biomarker product of this application not only provides the best combination for clinical colorectal cancer screening and postoperative monitoring, but also provides a treatment method for optimal clinical classification of colorectal cancer patients.

[0022] This application combines multiple combined detection results with routine pathological results for comprehensive judgment, which greatly increases the detection accuracy, with a precision of >95%. Furthermore, existing detection methods are not the most sensitive and lack comprehensive consideration of individualized clinical characteristics, which may lead to the product's detection results not truly reflecting the patient's actual condition.

[0023] Based on the screening of a group of cfRNAs abnormally highly expressed in colorectal cancer patients, this application further uses them as candidate biomarkers for early detection of colorectal cancer. During the detection process, considering cost and ease of operation, this application employs a one-step reverse transcription-quantitative real-time PCR technique, which significantly simplifies the operation compared to the traditional two-step method and avoids contamination from opening the container. Furthermore, this application utilizes the widely used TaqMan probe method for real-time quantitative PCR. Compared to the SYBR Green I dye method, the TaqMan probe method offers advantages in specificity and sensitivity. Given the low concentration of small cfRNA fragments (<45nt) in human serum / plasma, improving detection specificity is a major challenge. To improve detection specificity and avoid false positive results, the inventors independently designed specific probes and primers for the target small cfRNA fragments (<45nt) based on the principles of TaqMan probe technology. Currently, there is no mature reagent system on the market for detecting microRNA, tsRNA, and rsRNA in serum using multiplex Taqman probes. The applicant optimized the existing RNA extraction, reverse transcription-fluorescent PCR one-step reagent system on the market and repeatedly tested it with different sample types, and finally established a stable standard detection system (SOP).

[0024] Compared with the prior art, this application has the following advantages:

[0025] The application of cfRNA provided in this application in the preparation of biomarker products for the early diagnosis of colorectal cancer can be used for early screening, benign / malignant determination, differential diagnosis, monitoring of disease complications and recurrence, efficacy evaluation, drug efficacy, and guidance of precision medicine for colorectal cancer. It has advantages such as broad detection spectrum, high sensitivity, good specificity, low detection cost, convenient sample collection, and easy sample storage. The method using this biomarker product can be widely used in early screening and prognosis of colorectal cancer, improving upon single-type biomarkers or currently widely used clinical biomarkers that suffer from inherent instability leading to insurmountable individual variability, as well as low specificity and low sensitivity. It significantly improves the clinical detection rate of early colorectal cancer and reduces the misdiagnosis and missed diagnosis rates, becoming an effective means of colorectal cancer screening and diagnosis. Attached Figure Description

[0026] Figure 1This is a heatmap of high-expression biomarkers obtained after high-throughput sequencing of small RNAs in normal individuals and CRC patients.

[0027] Figure 2 This is a comparison of the four serum RNA extraction methods in Example 2 of this application.

[0028] Figure 3 This is a comparison of the correlation between serum volume and RNA extraction type in Example 2 of this application.

[0029] Figure 4 This is the amplification curve of the four markers amplified simultaneously in Example 2 of this application.

[0030] Figure 5 The ROC curve of the biomarker obtained after quantitative PCR detection of the case sample in Example 2 of this application.

[0031] Figure 6 This is a flowchart illustrating the entire process of early CRC diagnosis using cfRNA markers in Embodiment 2 of this application.

[0032] Figure 7 This document compares the detection results of cfRNA markers 16S-rRNA, tRNA-Gly-CCC, miR-34b, and miR-26a in a non-colorectal cancer patient group (control group, a mixed group of healthy and colorectal polyp patients) and a rectal cancer patient group (colorectal cancer stage I-IV patients, CRC) as described in an embodiment of this application.

[0033] Figure 8 This document compares the detection results of cfRNA markers miR-21, tRNA-Asp-GTC, miR-320a-3p, miR-92a-3p, and tRNA-Val-CAC in a non-colorectal cancer patient group (control group, a mixed group of healthy and colorectal polyp patients) and a rectal cancer patient group (colorectal cancer stage I-IV patients, CRC) as described in an embodiment of this application.

[0034] Figure 9 This document compares the detection results of cfRNA markers tRNA-His-GTG, let-7f, let-7g-5p, and tRNA-Glu-CTC in a non-colorectal cancer patient group (control group, a mixed group of healthy and colorectal polyp patients) and a rectal cancer patient group (colorectal cancer stage I-IV patients, CRC) as described in an embodiment of this application.

[0035] Figure 10This document compares the detection results of cfRNA markers 28S-rRNA, miR-223, miR-92a-3p, and miR-1274b in a non-colorectal cancer patient group (control group, a mixed group of healthy and colorectal polyp patients) and a rectal cancer patient group (colorectal cancer stage I-IV patients, CRC) as described in an embodiment of this application.

[0036] Figure 11 This document compares the detection results of cfRNA markers miR-451a, 5.8S-rRNA, and miR-16 in a non-colorectal cancer patient group (control group, a mixed group of healthy and colorectal polyp patients) and a rectal cancer patient group (colorectal cancer stage I-IV patients, CRC) as described in an embodiment of this application.

[0037] Figure 12 This is a comparison of the detection results of the cfRNA marker miR-98 in a non-colorectal cancer patient group (control group, a mixed group of healthy and colorectal polyp patients) and a rectal cancer patient group (colorectal cancer stage I-IV patients, CRC) as described in an embodiment of this application.

[0038] Figure 13 This is a comparison of the detection results of the cfRNA marker 45S-rRNA in a non-colorectal cancer patient group (control group, mixed group of healthy and colorectal polyp patients) and a rectal cancer patient group (colorectal cancer stage I-IV patients, CRC) as described in an embodiment of this application.

[0039] Figure 14 A flowchart for the biomarker screening strategy.

[0040] Figure 15 Sample information table for monitoring 401 colorectal cancer samples collected clinically.

[0041] Figure 16 The ROC curve of the miR-223 biomarker was obtained after quantitative PCR detection of case samples in one embodiment of this application.

[0042] Figure 17 The ROC curve of the 28S-rRNA marker obtained after quantitative PCR detection of case samples in one embodiment of this application is shown.

[0043] Figure 18 The ROC curve of the tRNA-ASP-GTC biomarker obtained after quantitative PCR detection of case samples in one embodiment of this application is shown.

[0044] Figure 19 The ROC curve of the Let-7f biomarker obtained after quantitative PCR detection of case samples in one embodiment of this application is shown.

[0045] Figure 20 This document presents the results of a combined analysis of 141 positive colorectal cancer samples and 260 negative samples using four biomarkers: miR-223, 28S-rRNA, tRNA-ASP-GTC, and Let-7f, as well as the detection results of some samples with clear pathological stages, in one embodiment of this application. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this application clearer, a more detailed description is provided below. However, it should be understood that the description herein is merely for explaining this application and is not intended to limit its scope.

[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. All reagents and instruments used herein are commercially available, and the characterization methods involved can be found in relevant descriptions in the prior art, and will not be repeated here.

[0048] To further understand this application, the following detailed description is provided in conjunction with the preferred embodiments.

[0049] Example 1

[0050] The application of cfRNA in the preparation of biomarker products for early diagnosis of colorectal cancer. The cfRNAs selected are hsa-miR-26a, 16S-rRNA, mature-tRNA-Asp-GTC_5_end (tRNA-Asp-GTC), mature-tRNA-Gly-CCC_5_end, miR-21, hsa-miR-451a, hsa-miR-92a-3p, 5.8S-rRNA, and mature-tRNA-His-GTG(tRNA). One or more of the following: NA-His-GTG, hsa-miR-320a-3p, hsa-let-7g-5p (let-7g-5p), hsa-miR-223, miR-1274b, hsa-miR-16, hsa-let-7f, hsa-miR-98, 28S-rRNA, 45S-rRNA, hsa-miR-34b, mature-tRNA-Val-CAC_5_end, and mature-tRNA-Glu-CTC.

[0051] cfRNA can be preferentially selected as tRNA-Asp-GTC, miR-223, let-7f and 28S-rRNA.

[0052] cfRNA can also be preferentially selected as:

[0053] tRNA-Asp-GTC, miR-223, let-7f, 28S-rRNA, and tRNA-Glu-CTC; or

[0054] tRNA-Asp-GTC, miR-223, let-7f, 28S-rRNA, and 5.8S-rRNA; or

[0055] tRNA-Asp-GTC, miR-223, let-7f, 28S-rRNA, tRNA-Glu-CTC and 5.8S-rRNA.

[0056] The sequences of cfRNA are shown in Table 1 as SEQ ID No. 1-SEQ ID No. 21.

[0057] Table 1

[0058]

[0059]

[0060] Biomarker products include chips or reagent kits.

[0061] The biomarker products include reagents for detecting the expression level of cfRNA in sample plasma. The cfRNA is selected from one or more of the following: hsa-miR-26a, 16S-rRNA, mature-tRNA-Asp-GTC_5_end, mature-tRNA-Gly-CCC_5_end, miR-21, hsa-miR-451a, hsa-miR-92a-3p, 5.8S-rRNA, mature-tRNA-His-GTG, hsa-miR-320a-3p, hsa-let-7g-5p, hsa-miR-223, miR-1274b, hsa-miR-16, hsa-let-7f, hsa-miR-98, 28S-rRNA, 45S-rRNA, hsa-miR-34b, mature-tRNA-Val-CAC_5_end, and mature-tRNA-Glu-CTC.

[0062] The reagents are selected from: probes that specifically recognize cfRNA; or primers that specifically amplify cfRNA.

[0063] The primer sequences for specifically amplifying cfRNA are as follows: reverse transcription primer sequences are shown in SEQ ID No. 22-SEQ ID No. 42; upstream primer sequences are shown in SEQ ID No. 43-SEQ ID No. 63; and downstream primer sequences are shown in SEQ ID No. 64-SEQ ID No. 84. The probe sequences for specifically recognizing cfRNA are shown in SEQ ID No. 85-SEQ ID No. 105. The specific sequences are shown in Table 2.

[0064] Table 2

[0065]

[0066]

[0067]

[0068]

[0069] The second inventive point of this application is to provide a biomarker product for the early diagnosis of colorectal cancer. The biomarker product detects the expression level of cfRNA in a sample to make an early diagnosis of colorectal cancer.

[0070] The product detects cfRNA expression levels using real-time quantitative PCR, gene chip methods, or high-throughput sequencing platforms.

[0071] Example 2

[0072] 1. Obtain a set of cfRNA biomarkers for early diagnosis and prognostic assessment of CRC:

[0073] (1) High-throughput sequencing:

[0074] Small RNA sequencing was performed on healthy individuals and CRC patients, and heatmaps of high-expression biomarkers were created based on the sequencing data, such as... Figure 1 As shown.

[0075] (2) Screening using a small sample size and multiple biomarkers with dyes:

[0076] Twenty-one biomarkers with high expression and upregulation were selected from the sequencing results, and primers and probes were designed and validated.

[0077] The names and sequences of the high-expression biomarkers are shown in Table 1.

[0078] Marker primer and probe combination:

[0079] The specific sequences of the reverse transcription primer (RP), the upstream amplification primer (qFP), the downstream amplification primer (qRP), and the probe (TM) are shown in Table 2.

[0080] 2. Extraction method determination and optimization:

[0081] (1) Determine the extraction reagents and extraction methods. Based on the total RNA and cfRNA quality extracted from the test samples using the separation kit, select the best extraction method.

[0082] The optimal extraction method was ultimately determined to be the silica-matrix centrifugal column method. The results of the extraction method are compared below. Figure 3 As shown. Figure 3 Among them, the three methods, TianGen, Ambion, and Qiagen, are all silicon matrix centrifugal column methods, and all of them are 2-6 Ct earlier than the Trizol extraction method.

[0083] In the preliminary research of this technology, the inventors selected several representative small RNAs for detection and evaluation. Among them, miR-16 and U6 are commonly used internal reference genes for short-fragment cfRNA detection, 28S-rRNA is a representative small RNA derived from ribosomal RNA (rRNA), tRNA-val-CAC-5 is a representative small RNA derived from transfer RNA (tRNA), and miR-21 and miR-483a-5p are representative RNAs that bind to serum exosomes or AGO proteins. The comprehensive detection of these six RNAs can represent the overall detection level of small RNAs in serum.

[0084] (2) Continue to optimize the influencing factors in the extraction process. The TianGen total RNA extraction kit and small RNA extraction kit were used to optimize the sample extraction volume: comparisons were set for serum volume of 100 μL, 300 μL, total RNA and small RNA, respectively.

[0085] The comparison results are as follows Figure 4 As shown.

[0086] Figure 4 In the study, the 300μL group was about 1-2 Ct earlier than the 100μL group; the total RNA extraction group was 0.45-1.3 Ct earlier than the small RNA extraction group. Therefore, the 300μL serum volume was ultimately selected for total RNA extraction.

[0087] 3. Establishment and optimization of the reaction procedure and reaction system for multiplex RT-qPCR:

[0088] The final reaction system is shown in Table 3.

[0089] Table 3

[0090] DNA polymerase 0.3 M-MuLV reverse transcriptase 0.3 nuclease inhibitors 0.2 UDG enzyme 0.3 PCR buffer 6 dNTP Mix (10mM) 1 Reverse transcription primers (2 pmol / μL) 0.5 Upstream primer (10 pmol / μL) 0.3 Downstream primer (10 pmol / μL) 0.3 Probe (10 pmol / μL) 0.3 template 3 DEPC water Supplement to 30 Total volume 30

[0091] Based on the above amplification system, four biomarkers can be amplified simultaneously without problems.

[0092] The reagents in this system, including reverse transcription primers, upstream primers, downstream primers, and probes, were synthesized by Invitrogen (Shanghai) Trading Co., Ltd., while the remaining reagents were purchased from Takara Bio (Dalian) Co., Ltd.

[0093] 4. Biomarker Selection Strategy

[0094] according to Figure 14 The process involves screening and confirming markers.

[0095] 1) Library construction and sequencing: RNA libraries were constructed from 3 mixed colorectal cancer-positive samples and 3 mixed healthy physical examination samples, and high-throughput small RNA sequencing was performed. The results are shown in […]. Figure 1 Twenty-one highly expressed miRNAs were screened, and suitable primers and probes were designed.

[0096] 2) Biomarker Screening: RT-qPCR was used for biomarker screening. The positive group consisted of 30 colorectal cancer samples, and the negative group consisted of 15 colorectal polyp samples and 15 healthy controls. A t-test was performed between the positive and negative groups; a p-value ≤ 0.05 was considered statistically significant. p-value > 0.05 was considered ns, 0.05 < p-value < 0.01 was considered *, 0.01 < p-value < 0.001 was considered **, and 0.001 < p-value < 0.0001 was considered ***. Figures 7-13 ).

[0097] The p-values ​​were sorted from smallest to largest: the distinguishing effect of single markers was 28S-rRNA > miR-223 > tRNA-Asp-GTC > let-7f > tRNA-Glu-CTC > 5.8S-rRNA.

[0098] Table 4 shows the sample information for inclusion marker screening. The control group consisted of 30 negative samples (Con) and 30 positive samples (CRC). There were no significant differences in age or sex between the two groups. Of the 30 positive samples, 3 were stage I and II (10%), and 27 were stage III and IV (90%).

[0099] Table 4

[0100]

[0101] 3) Determination of multi-channel biomarker combination: Based on the first 4 biomarkers screened in the previous step, multi-channel probes were designed and validated. The diagnostic combination is: tRNA-Asp-GTC, let-7f, 28S-rRNA, miR-223.

[0102] Monitoring was conducted on 401 colorectal cancer samples collected clinically. Sample information is as follows: Figure 15 As shown.

[0103] ROC curves and sensitivity / specificity values ​​for detecting a single marker.

[0104] like Figure 16-19 As shown:

[0105] The miR-223 marker has an ROC of 0.884, a sensitivity of 70.51%, and a specificity of 91.02%.

[0106] The 28S-rRNA marker had a ROC of 0.893, a sensitivity of 73.08%, and a specificity of 88.57%.

[0107] The tRNA-ASP-GTC biomarker had an ROC of 0.896, a sensitivity of 75.64%, and a specificity of 89.39%.

[0108] The Let-7f marker had an ROC of 0.913, a sensitivity of 80.77%, and a specificity of 92.24%.

[0109] The results of the comprehensive analysis of the four markers were used to make early diagnosis of CRC using the markers provided in this application, based on the clinical pathological diagnosis results and calculated according to the formula shown in Table 5.

[0110] Table 5

[0111]

[0112] In Table 5 above, sensitivity = A / (A+C) and specificity = D / (B+D).

[0113] The test data of colorectal cancer positive samples and non-colorectal cancer samples were entered into SPSS software to calculate the area under the ROC curve.

[0114] The results are as follows Figure 5 As shown, the sensitivity is 84.62%, the specificity is 96.33%, and the area under the ROC curve is 0.963.

[0115] Figure 20The results show that after jointly interpreting four biomarkers—miR-223, 28S-rRNA, tRNA-ASP-GTC, and Let-7f—on 141 positive and 260 negative colorectal cancer samples, the specificity was 96.33% and the sensitivity was 84.62%. The results also show that among the 141 positive colorectal cancer samples, 133 samples had a clear pathological stage (AJCC staging, 8th edition). Specifically, 19 out of 22 cases were stage I, 45 out of 52 cases were stage II, 49 out of 56 cases were stage III, and all 3 cases were stage IV. Figure 20 The results show that joint interpretation of the four markers, compared to... Figures 16-19 The four markers shown can be interpreted individually, which can effectively improve specificity and sensitivity, and yield more accurate interpretation results.

[0116] Example 3

[0117] Detection process for 4 core biomarkers:

[0118] 1. Extract total RNA from serum samples:

[0119] Collect 2-5 mL of venous blood using a non-anticoagulating vacuum collection tube, let stand for 30 min, centrifuge at 3000 RPM for 10 min, collect the supernatant, and extract total RNA from the serum.

[0120] Serum total RNA was extracted using the Tiangen Total RNA Extraction Kit (DP419).

[0121] 2. RT-qPCR detection:

[0122] The reaction system was prepared according to Table 3. Using the extracted total RNA as a template, a quadruple qPCR reaction system was adopted. Primer and probe combinations of four markers were added to the same system for four-channel real-time PCR detection, and fluorescence signals were collected.

[0123] 3. Calculate miRNA concentration:

[0124] After the reaction was completed, the concentration of each miRNA in the sample was calculated based on the fluorescence Ct value of the sample and the standard curve.

[0125] The quadruple qPCR reaction conditions were: 16℃ for 5 min; 50℃ for 15 min; 95℃ for 10 min; 95℃ for 15 s; 60℃ for 40 s; 50 cycles. Fluorescence signals were detected and collected at 60℃.

[0126] Other markers can also be detected using a similar procedure.

[0127] The testing process is as follows Figure 6 As shown, the detection comparison results of each marker are as follows: Figures 7-13As shown.

[0128] Figures 7-13 In this study, the Control group consisted of 15 healthy controls and 15 patients with colorectal polyps. The CRC group comprised 30 patients with stage I-IV colorectal cancer. The ultimate goal was to identify, in the biomarker screening stage, biomarkers that significantly differentiated colorectal cancer patients from non-colorectal cancer patients. The figures indicate that a t-test was performed on the two groups, with p > 0.05 as ns, 0.05 < p < 0.01 as *, 0.01 < p < 0.001 as **, and 0.001 < p < 0.0001 as ***.

[0129] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. The application of cfRNA in the preparation of biomarker products for early diagnosis of colorectal cancer, characterized in that, The cfRNA was selected as tRNA-Asp-GTC, miR-223, let-7f, and 28S-rRNA; or tRNA-Asp-GTC, miR-223, let-7f, 28S-rRNA, and tRNA-Glu-CTC; or tRNA-Asp-GTC, miR-223, let-7f, 28S-rRNA, and 5.8S-rRNA; or tRNA-Asp-GTC, miR-223, let-7f, 28S-rRNA, tRNA-Glu-CTC and 5.8S-rRNA.

2. The application according to claim 1, characterized in that, In the cfRNA, The sequence of tRNA-Asp-GTC is shown in SEQ ID No. 3; The sequence of miR-223 is shown in SEQ ID No. 12; The sequence of let-7f is shown in SEQ ID No. 15; The sequence of 28S-rRNA is shown in SEQ ID No. 17; The sequence of tRNA-Glu-CTC is shown in SEQ ID No. 21; The sequence of 5.8S-rRNA is shown in SEQ ID No.

8.

3. The application according to claim 1 or 2, characterized in that, The marker products include chips or reagent kits.

4. The application according to claim 3, characterized in that, The biomarker product includes a reagent for detecting the expression level of cfRNA in sample plasma, wherein the cfRNA is selected from tRNA-Asp-GTC, 5.8S-rRNA, miR-223, let-7f, 28S-rRNA and tRNA-Glu-CTC.

5. The application according to claim 4, characterized in that, The reagents are selected from: probes that specifically recognize the cfRNA; or primers that specifically amplify the cfRNA.

6. A biomarker product for the early diagnosis of colorectal cancer, characterized in that, The biomarker product enables early diagnosis of colorectal cancer by detecting the expression level of cfRNA in samples using real-time quantitative PCR, gene chip methods, or high-throughput sequencing platforms; the cfRNA is selected as... tRNA-Asp-GTC, miR-223, let-7f, and 28S-rRNA; or tRNA-Asp-GTC, miR-223, let-7f, 28S-rRNA, and tRNA-Glu-CTC; or tRNA-Asp-GTC, miR-223, let-7f, 28S-rRNA, and 5.8S-rRNA; or tRNA-Asp-GTC, miR-223, let-7f, 28S-rRNA, tRNA-Glu-CTC and 5.8S-rRNA.

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