Systems and kits for early adjuvant diagnosis of breast cancer and detection of minimal residual disease at various stages

Abstract

The application discloses a system and a kit for early auxiliary diagnosis of breast cancer and detection of micro residual lesions at various stages, and relates to the technical field of medical diagnosis.The system provided by the application uses the read value ratio of miRNA mature bodies and isomers to perform early auxiliary diagnosis of breast cancer and detection of micro residual lesions at various stages, and has high diagnostic sensitivity and specificity; and the system provides more accurate diagnostic basis for early adoption of treatment or intervention means by breast cancer patients.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical diagnosis, in particular, to a system and kit for early auxiliary diagnosis of breast cancer and detection of micro residual lesions at each stage. BACKGROUND

[0002] At present, breast cancer is the most common and highest incidence malignant tumor in women worldwide, which seriously threatens the life and health of women. Early detection, accurate diagnosis and real-time dynamic monitoring are the key to improve the cure rate of breast cancer and improve the prognosis of patients. At present, the clinical management of breast cancer mainly relies on the following traditional technologies: imaging examination: such as mammography (molybdenum target), ultrasound and magnetic resonance imaging (MRI). These methods are important means of early screening, but still have limitations such as high false positive rate (leading to unnecessary puncture biopsy), low sensitivity to dense breast tissue and inability to provide molecular biological information of tumor. Tissue biopsy: as the "gold standard" for diagnosing breast cancer, tumor tissue is obtained by puncture or surgery for pathological and molecular typing (such as ER, PR, HER2, Ki-67). More importantly, tumors have spatial heterogeneity (different characteristics of different regions of the same tumor) and temporal heterogeneity (tumor genome evolves during treatment), and single tissue biopsy cannot comprehensively and dynamically reflect the overall picture and evolution of the tumor. Traditional tumor marker detection: such as CA15-3, CEA, etc. The concentration detection of these protein markers in blood is often used for efficacy monitoring, but their sensitivity and specificity are relatively low, especially in early breast cancer, the positive rate is extremely low, which cannot be used for early diagnosis. With the rapid development of gene detection technology, liquid biopsy plays an increasingly important role in precision medicine, providing a new direction for the whole process management of breast cancer. Liquid biopsy detects extremely small amounts of tumor-derived circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), circulating cell-free DNA (cfDNA) and small extracellular vesicle (sEV) contents in body fluids such as blood and urine, thereby more accurately managing breast cancer patients, providing molecular level information, and the most widely used is the ctDNA detection technology.

[0003] Despite the promising prospect, there are still many challenges in the clinical practice of ctDNA detection in the whole process management of breast cancer. The first is the sensitivity challenge (especially in early breast cancer and follow-up micro residual disease (MRD) stage). The tumor volume of early breast cancer or MRD patients is small, and the ctDNA content released into the blood by cancer cell apoptosis or necrosis is extremely low, and the abundance may be as low as 0.01% or less. Even the background noise of the current most sensitive NGS detection technology may still mask these extremely weak true signals, resulting in false negative results, that is, there are actually cancer cells in the patient's body, but the detection is not possible. The specificity challenge is false positive, and benign mutations produced by hematopoietic stem cells with age will appear in white blood cells and plasma, which is easy to be misjudged as tumor source. Thus leading to false positive, which may cause unnecessary anxiety and excessive medical intervention of patients. For metastatic lesions that do not release ctDNA or release less, NGS detection may lead to incomplete judgment of tumor gene map, affecting the accuracy of treatment decision. SUMMARY

[0004] The purpose of the present application is to provide a system and kit for early auxiliary diagnosis of breast cancer and detection of micro residual disease at each stage. The system provided by the present application can be used for early auxiliary diagnosis of breast cancer and detection of micro residual disease, and has high diagnostic sensitivity and specificity; and can provide more accurate diagnostic basis for early treatment or intervention of breast cancer patients.

[0005] The present application is implemented as follows:

[0006] A system for early auxiliary diagnosis of breast cancer and / or detection of micro residual disease, the system comprising an information acquisition module, a calculation module and a diagnosis module;

[0007] The information acquisition module is configured to perform the step of acquiring sequencing information of a plurality of miRNA mature bodies and isomers thereof of a subject; the sequencing information comprises sequencing reads values;

[0008] The calculation module is configured to perform the step of substituting the sequencing reads values into a calculation model to calculate a threshold value; the threshold value is calculated and determined by the ratio of the reads values of the miRNA mature bodies and their corresponding isomers;

[0009] The diagnosis module is configured to perform the operation of judging the health status of the subject according to the threshold value.

[0010] The present application finds that, by creatively using the sequencing reads ratio of a plurality of miRNA mature bodies and their isomers, early auxiliary diagnosis of breast cancer and / or detection of micro residual disease at each stage can be performed, and the diagnostic sensitivity and specificity are high.

[0011] Optionally, in some embodiments of the present application, the isomer comprises: miRNA-1nt isomer and miRNA-2nt isomer.

[0012] The miRNA-2nt isomer refers to a sequence in which 2 nucleotides are deleted from the 3' end of the target miRNA mature body sequence.

[0013] The miRNA-1nt isomer refers to a sequence in which 1 nucleotide is deleted from the 3' end of the target miRNA mature body sequence.

[0014] Optionally, in some embodiments of the present application, the calculation model comprises a breast cancer early auxiliary diagnosis model.

[0015] The mathematical formula of the breast cancer early auxiliary diagnosis model comprises: S1=ratio1.

[0016] S1 represents the risk threshold of the subject suffering from breast cancer; ratio1 represents the sum of the ratio of the sequencing reads value of 30 miRNA mature bodies to the sequencing reads value of the respective miRNA-1nt isomer corresponding thereto.

[0017] The calculation formula of ratio1 is as follows:

[0018] ratio1=a1+a2+a3+a4+a5+a6+a7+a8+a9+a10+a11+a12+a13+a14+a15+a16+a17+a18+a19+a20+a21+a22+a23+a24+a25+a26+a27+a28+a29+a30;

[0019] Wherein, a1-a30 respectively represent the ratio of the reads value of 30 miRNA mature bodies to the sequencing reads value of the respective miRNA-1nt isomer;

[0020] Wherein, for different molecular typing breast cancers, 30 miRNA mature bodies used are different; specifically as follows:

[0021] When diagnosed for Luminal A breast cancer, the 30 said miRNA mature bodies consist of the following 30 miRNAs: hsa-miR-100-5p, hsa-miR-106-3p, hsa-miR-10a-5p, hsa-miR-122-5p, hsa-miR-142-3p, hsa-miR-143-3p, hsa-miR-146b-5p, hsa-miR-148a-3p, hsa-miR-15a-5p, hsa-miR-182-5p, hsa-miR-185-5p, hsa-miR-186-5p, hsa-miR-193a-5p, hsa-miR-199a-3p, hsa-miR-199b-3p, hsa-miR-223-3p, hsa-miR-26a-3p, hsa-miR-26b-5p, hsa-miR-30b-5p, hsa-miR-30c-5p, hsa-miR-320a-3p, hsa-miR-328-3p, hsa-miR-409-3p, hsa-miR-483-5p, hsa-miR-486-5p, hsa-miR-584-5p, hsa-miR-7-5p, hsa-miR-96-5p, hsa-miR-98-5p, and hsa-miR-99b-5p;

[0022] When diagnosed for Luminal B type breast cancer, 30 of the miRNA mature bodies consist of the following 30 miRNAs: hsa-let-7f-5p, hsa-miR-100-5p, hsa-miR-10a-5p, hsa-miR-126-3p, hsa-miR-139-3p, hsa-miR-142-3p, hsa-miR-143-3p, hsa-miR-146b-5p, hsa-miR-15a-5p, hsa-miR-183-5p, hsa-miR-185-5p, hsa-miR-186-5p, hsa-miR-193a-5p, hsa-miR-199a-5p, hsa-miR-199b-3p, hsa-miR-223-3p, hsa-miR-25-3p, hsa-miR-26a-3p, hsa-miR-29a-3p, hsa-miR-30b-5p, hsa-miR-30c-5p, hsa-miR-30e-5p, hsa-miR-320a-3p, hsa-miR-409-3p, hsa-miR-483-3p, hsa-miR-483-5p, hsa-miR-532-3p, hsa-miR-96-5p, hsa-miR-98-5p, and hsa-miR-99b-5p;

[0023] When diagnosed for HER2 positive type breast cancer, 30 of the miRNA mature bodies consist of the following 30 miRNAs:

[0024] hsa-let-7a-5p, hsa-let-7d-3p, hsa-miR-100-5p, hsa-miR-10a-5p, hsa-miR- 127-3p, hsa-miR-129-5p, hsa-miR-1307-3p, hsa-miR-142-3p, hsa-miR-143-3p, hsa-miR-145-5p, hsa-miR-146b-5p, hsa-miR-150-5p, hsa-miR-15a-5p, hsa-miR-16-5p, hsa-miR-185-5p, hsa-miR-186-5p, hsa-miR-193a-5p, hsa-miR-199b-3p, hsa-miR-223-3p, hsa-miR-26a-3p, hsa-miR-26a-5p, hsa-miR-30b-5p, hsa-miR-30c-5p, hsa-miR-320a-3p, hsa-miR-375-3p, hsa-miR-409-3p, hsa-miR-483-5p, hsa-miR-96-5p, hsa-miR-98-5p, and hsa-miR-99b-5p;

[0025] When diagnosed for a basal-like breast cancer type breast cancer, the 30 miRNA mature bodies consist of the following 30 miRNAs: hsa-miR-100-5p, hsa-miR-10a-5p, hsa-miR-1287-5p, hsa-miR-142-3p, hsa-miR-143-3p, hsa-miR-146b-5p, hsa-miR-155-5p, hsa-miR-15a-5p, hsa-miR-185-5p, hsa-miR-186-5p, hsa-miR-193a-5p, hsa-miR-199b-3p, hsa-miR-19a-3p, hsa-miR-210-5p, hsa-miR-211-5p, hsa-miR-218-5p, hsa-miR-223-3p, hsa-miR-26a-3p, hsa-miR-30b-5p, hsa-miR-30c-5p, hsa-miR-3130-3p, hsa-miR-320a-3p, hsa-miR-338-3p, hsa-miR-34a-5p, hsa-miR-409-3p, hsa-miR-4485-3p, hsa-miR-483-5p, hsa-miR-96-5p, hsa-miR-98-5p, and hsa-miR-99b-5p.

[0026] Optionally, in some embodiments of the present application, the diagnostic module determines according to the risk threshold S1 of the early auxiliary diagnosis model of breast cancer, in the following manner:

[0027] If S1 of the subject is ≤ 16.2, it is determined that the subject has breast cancer and the molecular subtype is Luminal A; if S1 > 16.2, it is determined that the subject does not have breast cancer or has a benign lesion of the breast;

[0028] If S1 of the subject is ≤ 15.6, it is determined that the subject has breast cancer and the molecular subtype is Luminal B; if S1 > 15.6, it is determined that the subject does not have breast cancer or has a benign lesion of the breast;

[0029] If S1 of the subject is ≤ 14.8, it is determined that the subject has breast cancer and the molecular subtype is HER2 positive; if S1 > 14.8, it is determined that the subject does not have breast cancer or has a benign lesion of the breast;

[0030] If S1 of the subject is ≤ 15.5, it is determined that the subject has breast cancer and the molecular subtype is triple negative breast cancer (TNBC); if S1 > 15.5, it is determined that the subject does not have breast cancer or has a benign lesion of the breast.

[0031] Breast cancer has multiple molecular subtypes, and different subtypes have different treatment plans. The difference in treatment plans will lead to changes in gene mutations of ctDNA in breast cancer MRD detection. Using positive mutations in the baseline detection plan to dynamically monitor breast cancer will cause a certain degree of false negative.

[0032] The system provided by the present application can independently assist in diagnosing different molecular subtypes, and various subtypes have high specificity and sensitivity.

[0033] Optionally, in some embodiments of the present application, the calculation model comprises a micro-lesion residual evaluation model;

[0034] S2 = ratio2 + ratio3;

[0035] S2 represents a risk threshold of the subject having a breast cancer micro-lesion residue;

[0036] ratio2 represents the sum of the ratio of the sequencing reads value of 50 target miRNA mature bodies to the sequencing reads value of the miRNA-1nt isomer corresponding to each of the 50 target miRNA mature bodies, wherein the 50 target miRNA mature bodies are composed of miRNA mature bodies in the top 50 positions in descending order of the sequencing reads value of the miRNA-1nt isomer;

[0037] ratio3 represents the sum of the ratio of the sequencing reads value of 50 target miRNA mature bodies to the sequencing reads value of their respective miRNA-2nt isomer, wherein the 50 target miRNA mature bodies are composed of the top 50 miRNA mature bodies in terms of the sequencing reads value of their miRNA-2nt isomer from large to small.

[0038] The calculation formula of ratio2 is as follows:

[0039] ratio2 = b1+b2+b3+b4+b5+b6+b7+b8+b9+b10+b11+b12+b13+b14+b15+b16+b17+b18+b19+b20+b21+b22+b23+b24+b25+b26+b27+b28+b29+b30+b31+b32+b33+b34+b35+b36+b37+b38+b39+b40+b41+b42+b43+b44+b45+b46+b47+b48+b49+b50;

[0040] wherein b1-b50 respectively represent the ratio of the sequencing reads value of 50 miRNA mature bodies to the sequencing reads value of their respective miRNA-1nt isomer; the 50 miRNA mature bodies are composed of the top 50 miRNA mature bodies in terms of the sequencing reads value of their miRNA-1nt isomer from large to small.

[0041] The calculation formula of ratio3 is as follows:

[0042] ratio3 = c1+c2+c3+c4+c5+c6+c7+c8+c9+c10+c11+c12+c13+c14+c15+c16+c17+c18+c19+c20+c21+c22+c23+c24+c25+c26+c27+c28+c29+c30+c31+c32+c33+c34+c35+c36+c37+c38+c39+c40+c41+c42+c43+c44+c45+c46+c47+c48+c49+c50;

[0043] wherein c1-c50 respectively represent the ratio of the sequencing reads value of 50 miRNA mature bodies to the sequencing reads value of their respective miRNA-2nt isomer; the 50 miRNA mature bodies are composed of the top 50 miRNA mature bodies in terms of the sequencing reads value of their miRNA-2nt isomer from large to small.

[0044] It should be noted that when the system of the present application is used for diagnosis of different subjects, the miRNA mature body sequences of the top 50 sequencing reads values between different subjects may be completely identical or partially identical.

[0045] Optionally, in some embodiments of the present application, the diagnosis module judges according to the micro-lesion residual evaluation model risk threshold S2, and the judgment method is as follows:

[0046] If S2<20.6, it is judged that there is a breast cancer residual lesion in the subject patient, and the MRD result is positive;

[0047] If S2>48.9, it is judged that there is no breast cancer residual lesion in the subject, and the MRD result is negative;

[0048] If 20.6≤S2≤48.9, it is recommended that the subject be retested or intensively clinically followed up within 3 months.

[0049] Breast cancer has various molecular subtypes, and the treatment schemes of different subtypes are different. The difference in treatment schemes will lead to changes in gene mutations of ctDNA in breast cancer MRD detection. Using positive mutations in the baseline detection scheme to dynamically monitor breast cancer will cause a certain degree of false negative.

[0050] The system provided by the present application monitors or predicts the micro residual lesions of patients after surgical treatment, and in the short and long term after surgery. And its prediction window can be greatly advanced for months, providing a basis for earlier treatment of potential risks of tumor recurrence or metastasis in postoperative patients.

[0051] Optionally, in some embodiments of the present application, the miRNA is derived from the plasma small extracellular vesicles of the subject.

[0052] Small extracellular vesicles are secreted by cells, with a diameter of 40-150 nm, and can circulate in body fluids such as blood and urine. Such vesicles carry signal molecules derived from parent cells, and tumor cell-secreted vesicles can transport important signal molecules within the microenvironment of tumor occurrence, promoting tumor progression and metastasis. Optionally, in some embodiments of the present application, the foregoing micro residual lesion detection at each stage includes the following stages: before neoadjuvant therapy of breast cancer, after neoadjuvant therapy, before surgery, short-term and long-term micro residual lesion detection after surgery, etc.

[0053] Optionally, in some embodiments of the present application, the system further comprises a result display module for displaying the diagnosis conclusion obtained by the diagnosis module.

[0054] Optionally, in some embodiments of the present application, the result display module displays the diagnostic result through screen display, voice broadcast or printing.

[0055] It should be noted that the sequencing reads of miRNA and its isomers can be measured by common sequencing techniques in the art, such as PE150 or SE50 sequencing techniques based on iSeq100, MiniSeq, MiSeq, NextSeq550, NextSeq2000, NovaSeq6000 sequencers of Illumina Company; SE100, PE100 and PE150 sequencing techniques based on MGI sequencing platform of Huada Gene Company, etc.

[0056] It should be noted that the methods for extracting and separating plasma small extracellular vesicles and enriching miRNA and its isomers applied in the present application can all be carried out by using conventional techniques and kits in the art.

[0057] On the other hand, the present application provides a kit for early auxiliary diagnosis of breast cancer and / or detection of each stage of micro residual lesions, which contains reagents for detecting miRNA mature bodies and its isomers, and the detection result of the kit provides sequencing information for the information acquisition module in the system as described above.

[0058] Based on the content provided by the present application, any reagent in the art for detecting miRNA mature bodies and its isomers, as long as its result is to provide the reads value information of miRNA and its isomers for the acquisition of the above-mentioned system, belongs to the protection scope of the present application. The specific reagents for detecting miRNA and its isomers can be easily obtained by those skilled in the art. BRIEF DESCRIPTION OF DRAWINGS

[0059] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly introduced below, and it should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation on the scope, and for those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0060] Figure 1 The method flow diagram for acquiring miRNA mature bodies and its isomers of the subject in Example 1 is shown in the figure;

[0061] Figure 2 The ROC curve diagram for predicting by using the early auxiliary diagnosis model of breast cancer in Example 1 is shown in the figure;

[0062] Figure 3The statistical chart of positive predictive value of the model of the present application for each metastatic lesion in the patients in which the final organ metastatic lesions appeared in the patients who were continuously followed up after the operation of breast cancer using the model of each stage of micro residual lesion detection of breast cancer in Example 2;

[0063] Figure 4 The statistical chart of early time period of the appearance of MRD signal positive to the final confirmation of pathological recurrence of breast cancer of different molecular subtypes in clinical follow-up suggested by the model of each stage of micro residual lesion detection in Example 2. DETAILED DESCRIPTION

[0064] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below. The specific conditions not mentioned in the embodiments are carried out according to the conventional conditions or the conditions suggested by the manufacturers. The reagents or instruments not mentioned by the manufacturers are all conventional products which can be purchased in the market.

[0065] The features and performances of the present application will be further described in detail below in combination with the embodiments.

[0066] Example 1

[0067] This example provides an early auxiliary diagnosis model of breast cancer and verification of the diagnosis performance thereof

[0068] 1 The threshold formula of the early auxiliary diagnosis model of breast cancer in this example is as follows:

[0069] S1=ratio1;

[0070] S1 represents the risk threshold of the subject suffering from breast cancer; and ratio1 represents the sum of the ratio of the sequencing reads value of each of the 30 target miRNA mature bodies to the sequencing reads value of the corresponding miRNA-1nt isomer thereof.

[0071] The calculation formula of ratio1 is as follows:

[0072] ratio1=a1+a2+a3+a4+a5+a6+a7+a8+a9+a10+a11+a12+a13+a14+a15+a16+a17+a18+a19+a20+a21+a22+a23+a24+a25+a26+a27+a28+a29+a30;

[0073] Wherein, a1-a30 respectively represent the ratio of the reads value of each of the 30 miRNA mature bodies to the sequencing reads value of the corresponding miRNA-1nt isomer thereof.

[0074] For different molecular subtypes of breast cancer diagnosis, 30 miRNA mature bodies used are different, see Table 1.

[0075] Table 1

[0076]

[0077] The diagnosis mode using the above threshold value is as follows:

[0078] When diagnosing Luminal A type breast cancer, if S1≤16.2 is detected in the subject, it is judged as breast cancer positive and the molecular subtype is Luminal A type, and when S1>16.2, it is judged as negative or benign breast lesion;

[0079] When diagnosing Luminal B type breast cancer, if S1≤15.6 is detected in the subject, it is judged as breast cancer positive and the molecular subtype is Luminal B type, and when S1>15.6, it is judged as negative or benign breast lesion;

[0080] When diagnosing HER2 positive type breast cancer, if S1≤14.8 is detected in the subject, it is judged as breast cancer positive and the molecular subtype is HER2 positive type, and when S1>14.8, it is judged as negative or benign breast lesion;

[0081] When diagnosing triple negative breast cancer type breast cancer, if S1≤15.5 is detected in the subject, it is judged as breast cancer positive and the molecular subtype is triple negative breast cancer (TNBC), and when S1>15.5, it is judged as negative or benign breast lesion.

[0082] 2. Use the above model to verify its diagnostic performance:

[0083] 300 subjects with breast imaging reporting and data system (BI-RADS) classification of 4 and 5 and without tissue biopsy; using prior art and referring to Figure 1 The process obtains the reads value of miRNA and its isomer miRNA-1nt of the subject; through sorting the reads value, the ratio1 value is obtained; for example, after analyzing the microRNA sequencing data of a subject, the reads of the following miRNA mature body and miRNA-1nt are obtained, as shown in the following Table 2:

[0084] Table 2

[0085]

[0086] In the table, the value of a = mature miRNA reads value / miRNA-1nt isomer reads value.

[0087] Referring to Table 1, the a values of 30 miRNAs required for the calculation of the Luminal A type are extracted from Table 2 above, and summed up, and the obtained S1 value is 85.01;

[0088] The S1 value of 30 microRNAs of the Luminal B type is 66.63;

[0089] The S1 value of 30 microRNAs of the HER2-positive type is 11.82;

[0090] The S1 value of 30 microRNAs of the TNBC type is 36.32.

[0091] According to the threshold judgment basis of each subtype in the early auxiliary diagnosis model of breast cancer, it is judged that the subject is breast cancer positive and the molecular typing is HER2-positive type.

[0092] And according to the above diagnosis method, the benign and malignant and molecular typing are predicted, and compared with the final clinical pathological diagnosis conclusion of the subject, the value of early auxiliary diagnosis of breast cancer is evaluated. The related results are shown in Figure 2 , Tables 3-7.

[0093] For all molecular typing of breast cancer, the sensitivity of the auxiliary diagnosis model provided in the embodiment for early auxiliary diagnosis is 100%, the specificity is 96%, and the AUC is as high as 0.982, see Figure 2 .

[0094] After excluding 12 cases without pathological diagnosis information, the positive predictive value of the molecular typing of breast cancer as Luminal A type is 93.9%, and the negative predictive value is 100%;

[0095] The positive predictive value of the molecular typing of breast cancer as Luminal B type is 94.7%, and the negative predictive value is 98.7%;

[0096] The positive predictive value of the molecular typing of breast cancer as HER2-positive type is 93.3%, and the negative predictive value is 99.4%;

[0097] The positive predictive value of the molecular typing of breast cancer as triple negative (TNBC) type is 84.6%, and the negative predictive value is 98.7%.

[0098] Table 3

[0099]

[0100] Table 4

[0101]

[0102] Table 5

[0103]

[0104] Table 6

[0105]

[0106] Table 7

[0107]

[0108] Example 2

[0109] This example provides a breast cancer micro-lesion residual evaluation model and verification of its diagnostic performance

[0110] 1 The threshold formula of the breast cancer micro-lesion residual of this example is as follows:

[0111] S2= ratio2+ ratio3;

[0112] S2 represents the risk threshold of the subject suffering from breast cancer; ratio2 represents the sum of the ratio of the sequencing reads value of 50 target miRNA mature bodies to the sequencing reads value of their respective miRNA-1nt isomer; wherein the 50 target miRNA mature bodies are composed of the top 50 miRNA mature bodies with the largest sequencing reads value of their miRNA-1nt isomer.

[0113] The calculation formula of ratio2 is as follows:

[0114] ratio2 = b1 + b2 + b3 + b4 + b5 + b6 + b7 + b8 + b9 + b10 + b11 + b12 + b13 + b14 + b15 + b16 + b17 + b18 + b19 + b20 + b21 + b22 + b23 + b24 + b25 + b26 + b27 + b28 + b29 + b30 + b31 + b32 + b33 + b34 + b35 + b36 + b37 + b38 + b39 + b40 + b41 + b42 + b43 + b44 + b45 + b46 + b47 + b48 + b49 + b50;

[0115] Wherein, b1-b50 respectively represent the ratio of the sequencing reads value of 50 miRNA mature bodies to the sequencing reads value of their respective miRNA-1nt isomer; the 50 miRNA mature bodies are composed of the top 50 miRNA mature bodies with the largest sequencing reads value of their miRNA-1nt isomer.

[0116] ratio3 represents the sum of the ratio of the sequencing reads value of 50 target miRNA mature bodies to the sequencing reads value of their respective miRNA-2nt isomer, wherein the 50 target miRNA mature bodies are composed of the top 50 miRNA mature bodies in terms of the sequencing reads value of their miRNA-2nt isomer from large to small.

[0117] The calculation formula of ratio3 is as follows:

[0118] ratio3 = c1 + c2 + c3 + c4 + c5 + c6 + c7 + c8 + c9 + c10 + c11 + c12 + c13 + c14 + c15 + c16 + c17 + c18 + c19 + c20 + c21 + c22 + c23 + c24 + c25 + c26 + c27 + c28 + c29 + c30 + c31 + c32 + c33 + c34 + c35 + c36 + c37 + c38 + c39 + c40 + c41 + c42 + c43 + c44 + c45 + c46 + c47 + c48 + c49 + c50;

[0119] Wherein, c1-c50 respectively represent the ratio of the sequencing reads value of 50 miRNA mature bodies to the sequencing reads value of their respective miRNA-2nt isomer; the 50 miRNA mature bodies are composed of the top 50 miRNA mature bodies in terms of the sequencing reads value of their miRNA-2nt isomer from large to small.

[0120] The diagnosis method using the above threshold value is as follows:

[0121] If S2 < 20.6, it is judged that there is a breast cancer residual lesion in the body of the test patient, and the MRD result is positive;

[0122] If S2 > 48.9, it is judged that there is no breast cancer residual lesion in the body of the test patient, and the MRD result is negative;

[0123] If 20.6≤S2≤48.9, it is recommended that the test patient be retested within 3 months or clinical follow-up be strengthened.

[0124] 2. The model is used for performance verification:

[0125] 150 breast cancer patients diagnosed by postoperative pathology were enrolled, and plasma small extracellular vesicle miRNA sequencing was performed within one month after surgery (same as Example 1), and S2 value was obtained.

[0126] The reads of all miRNAs and their different isomers measured by a certain patient are shown in Table 8 below.

[0127] Table 8

[0128]

[0129] In the table, b value = mature miRNA reads value / miRNA-1 nt isomer reads value, c value = mature miRNA reads value / miRNA-2 nt isomer reads value;

[0130] The top 50 miRNA-1 nt isomer reads (from large to small) are sorted from the above table, respectively, the b value of the 50 mature / miRNA-1 nt isomers is extracted, and the sum is obtained, and the value ratio2 is 6.09;

[0131] The top 50 miRNA-2 nt isomer reads (from large to small) are sorted, respectively, the c value of the 50 mature / miRNA-2 nt isomers is extracted, and the sum is obtained, and the value ratio3 is 13.62.

[0132] Therefore, the sum of ratio2+ ratio3 is 19.71, that is, S2 of the patient is 19.71. According to the breast cancer microlesion residual evaluation model judgment mode, S2 is less than 20.60, so it is judged that the subject has breast cancer residual lesion, and the MRD result is positive, and the breast cancer appears recurrence at the molecular level. The S2 calculation method of other patients is calculated according to the method.

[0133] If S2<20.60, the patient is excluded from follow-up, which indicates that the current neoadjuvant therapy or surgery has not achieved effective control of breast cancer lesions. Then the above-mentioned patients are repeatedly detected every 3-6 months, and the S2 data of all patients are obtained, until the S2 value of any patient appears <20.60 for the first time, the patient stops detection, which indicates that the patient has experienced the process from clinical lesion complete remission to molecular recurrence at the molecular detection level. Then the patient is only followed up until the image or pathological recurrence and metastasis lesions appear.

[0134] According to the follow-up situation, the detection rate of different organ metastatic lesions of the patients and the window period from MRD positive to clinical follow-up confirmed recurrence metastasis are counted in the presence of different organ metastatic lesions.

[0135] At 1 month after surgery, the S2 value of 7 of the 150 breast cancer patients is still less than 20.60. After excluding the 7 cases, in the follow-up of the 143 cases, 61 patients finally appeared bone metastasis, 22 patients finally appeared lung metastasis, 19 patients finally appeared liver metastasis, 14 patients finally appeared brain metastasis, and 27 patients appeared multiple organ metastasis (simultaneous lung+brain metastasis, or simultaneous bone+lung+liver metastasis, etc.).

[0136] Using S² < 20.60 as the criterion for determining the presence of MRD, the detection rate of bone metastasis in this embodiment is 93.44%, and the detection rate of lung metastasis is 90.91%.

[0137] The detection rate of liver metastasis was 94.74%, the detection rate of brain metastasis was 85.71%, and the detection rate of multiple organ metastasis was 100%.

[0138] The MRD detection rate in patients with brain metastases from breast cancer exceeded 85%, significantly higher than the 17% achieved by the current ctDNA testing protocol.

[0139] These 134 breast cancer patients (S2 value < 20.60, and 9 other patients with S2 value ≤ 48.90 were not included in the statistics) were grouped according to the molecular subtype of pathological diagnosis. The interval between the detection of MRD positivity before clinical recurrence and metastasis of Luminal A, Luminal B, HER2 positive and TNBC types was statistically analyzed.

[0140] The early onset time for Luminal A type 2 encephalopathy ranged from 17 to 42 months, with a median of 31.5 months.

[0141] The early intervention time for Luminal B is between 22 and 40 months, with a median of 32.5 months.

[0142] The early detection time for HER2 positivity ranges from 18 to 31 months, with a median of 20.5 months.

[0143] The lead time for TNBC is between 12 and 22 months, with a median of 15.5 months.

[0144] Compared to the currently common technical approach of determining MRD positivity based on ctDNA sequencing, the model in this embodiment detects MRD positivity approximately 7 months earlier for TNBC, approximately 5.5 months earlier for HER2 positivity, and approximately 6-6.5 months earlier for Luminal A and B.

[0145] This embodiment demonstrates that the model significantly prolongs the observation and clinical intervention period for long-term postoperative monitoring of breast cancer patients, which will significantly benefit the patient's prognosis.

[0146] In summary, the present application has the following advantages: 1. In the field of early auxiliary diagnosis of breast cancer, by using 1ml of whole blood, a plurality of miRNA isomers in the plasma small extracellular vesicles are detected by using high-throughput sequencing technology, as low as 0.5Gb of raw sequencing data, and data analysis is completed within 3 days, accurate identification of breast benign disease and each molecular subtype of breast cancer is realized, and the diagnostic AUC is more than 0.95. 2. The present application solves the problem that the specificity is not ideal due to the use of similar miRNAs for detection in the diagnosis of a plurality of tumors with high incidence by introducing the breast cancer expression spectrum of dozens of plasma small extracellular vesicle miRNAs. 3. By adjusting the detection of the target of the plasma small extracellular vesicle miRNA isomer in the model and the ratio of the mature body and the isomer, the detection of the new adjuvant therapy, the postoperative short-term and long-term micro residual lesions of breast cancer of different molecular subtypes before surgery is realized.

[0147] The present application provides a reliable prediction means for early auxiliary diagnosis of breast cancer and monitoring of postoperative micro residual lesions, and provides a more accurate diagnostic basis for early treatment of breast cancer patients.

[0148] The above only describes the preferred embodiments of the present application and is not used to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A system for early auxiliary diagnosis of breast cancer and / or detection of minimal residual disease at various stages, characterized in that, The system includes an information acquisition module, a calculation module, and a diagnostic module; The information acquisition module is used to perform the step of acquiring sequencing information of multiple mature miRNAs and their isoforms from the subject; the sequencing information includes sequencing reads; the isoforms are miRNA-1nt isoforms and miRNA-2nt isoforms; the multiple miRNAs are derived from plasma microcellular extracellular vesicles of the subject; The calculation module is used to perform the step of substituting the sequencing reads value into the calculation model to calculate the threshold; the threshold is determined by the ratio of the reads value of the mature miRNA to its corresponding isoform; the calculation model includes an early auxiliary diagnosis model for breast cancer and / or a small residual disease assessment model; The mathematical formula for the early auxiliary diagnostic model for breast cancer includes: S1=ratio1; Wherein, S1 represents the risk threshold for the subject to develop breast cancer; ratio1 represents the sum of the ratios of the sequencing reads values ​​of multiple mature miRNAs to the sequencing reads values ​​of their respective miRNA-1nt isoforms; When used for the diagnosis of Luminal A breast cancer, the multiple mature miRNAs consist of the following 30 miRNAs: hsa-miR-100-5p, hsa-miR-106-3p, hsa-miR-10a-5p, hsa-miR-122-5p, hsa-miR-142-3p, hsa-miR-143-3p, hsa-miR-146b-5p, hsa-miR-148a-3p, hsa-miR-15a-5p, hsa-miR-182-5p, hsa-miR-185-5p, hsa-miR-186-5p, hsa-miR-193a-5p, hsa-miR-199... a-3p, hsa-miR-199b-3p, hsa-miR-223-3p, hsa-miR-26a-3p, hsa-miR-26b-5p, hsa-miR-30b-5p, hsa-miR-30c-5p, hsa-miR-320a-3p, hsa-miR-32 8-3p, hsa-miR-409-3p, hsa-miR-483-5p, hsa-miR-486-5p, hsa-miR-584-5p, hsa-miR-7-5p, hsa-miR-96-5p, hsa-miR-98-5p, and hsa-miR-99b-5p; When used for the diagnosis of Luminal B breast cancer, the multiple mature miRNAs consist of the following 30 miRNAs: hsa-let-7f-5p, hsa-miR-100-5p, hsa-miR-10a-5p, hsa-miR-126-3p, hsa-miR-139-3p, hsa-miR-142-3p, hsa-miR-143-3p, hsa-miR-146b-5p, hsa-miR-15a-5p, hsa-miR-183-5p, hsa-miR-185-5p, hsa-miR-186-5p, hsa-miR-193a-5p, hsa-miR-199a -5p, hsa-miR-199b-3p, hsa-miR-223-3p, hsa-miR-25-3p, hsa-miR-26a-3p, hsa-miR-29a-3p, hsa-miR-30b-5p, hsa-miR-30c-5p, hsa-miR-30e-5 p, hsa-miR-320a-3p, hsa-miR-409-3p, hsa-miR-483-3p, hsa-miR-483-5p, hsa-miR-532-3p, hsa-miR-96-5p, hsa-miR-98-5p, and hsa-miR-99b-5p; When diagnosing HER2-positive breast cancer, the multiple mature miRNAs consist of the following 30 miRNAs: hsa-let-7a-5p, hsa-let-7d-3p, hsa-miR-100-5p, hsa-miR-10a-5p, hsa-miR-127-3p, hsa-miR-129-5p, hsa-miR-1307-3p, hsa-miR- 142-3p, hsa-miR-143-3p, hsa-miR-145-5p, hsa-miR-146b-5p, hsa-miR-150-5p, hsa-miR-15a-5p, hsa-miR-16-5p, hsa-miR-185-5p, h sa-miR-186-5p, hsa-miR-193a-5p, hsa-miR-199b-3p, hsa-miR-223-3p, hsa-miR-26a-3p, hsa-miR-26a-5p, hsa-miR-30b-5p, hsa-miR -30c-5p, hsa-miR-320a-3p, hsa-miR-375-3p, hsa-miR-409-3p, hsa-miR-483-5p, hsa-miR-96-5p, hsa-miR-98-5p, and hsa-miR-99b-5p; When diagnosing triple-negative breast cancer, the multiple mature miRNAs consist of the following 30 miRNAs: hsa-miR-100-5p, hsa-miR-10a-5p, hsa-miR-1287-5p, hsa-miR-142-3p, hsa-miR-143-3p, hsa-miR-146b-5p, hsa-miR-155-5p, hsa-miR-15a-5p, hsa-miR-185-5p, hsa-miR-186-5p, hsa-miR-193a-5p, hsa-miR-199b-3p, hsa-miR-19a-3p, hsa-miR... -210-5p, hsa-miR-211-5p, hsa-miR-218-5p, hsa-miR-223-3p, hsa-miR-26a-3p, hsa-miR-30b-5p, hsa-miR-30c-5p, hsa-miR-3130-3p, hsa-miR-320 a-3p, hsa-miR-338-3p, hsa-miR-34a-5p, hsa-miR-409-3p, hsa-miR-4485-3p, hsa-miR-483-5p, hsa-miR-96-5p, hsa-miR-98-5p, and hsa-miR-99b-5p; The mathematical formula for the breast cancer minimal residual disease assessment model includes: S2 = ratio2 + ratio3; S2 represents the risk threshold for the subject having minimal residual disease in breast cancer; ratio2 represents the sum of the ratios of the sequencing reads of 50 target miRNA matures to the sequencing reads of their respective miRNA-1nt isoforms, wherein the 50 target miRNA matures are composed of the top 50 miRNA matures whose sequencing reads of their miRNA-1nt isoforms are arranged from largest to smallest. ratio3 represents the sum of the ratios of the sequencing reads of 50 target miRNA matures to the sequencing reads of their respective miRNA-2nt isoforms, wherein the 50 target miRNA matures are composed of the top 50 miRNA matures whose sequencing reads of their miRNA-2nt isoforms are arranged from largest to smallest. The diagnostic module is used to perform the operation of judging the health status of the subject based on a threshold. The diagnostic module makes a judgment based on the risk threshold S1 of the early auxiliary diagnostic model for breast cancer, and the judgment method is as follows: When diagnosing Luminal A type breast cancer, if the subject's S1 score is ≤16.2, the patient is judged to be positive for breast cancer and the molecular subtype is Luminal A. If S1 is >16.2, the patient is judged to be negative or to have benign breast lesions. When diagnosing Luminal B type breast cancer, if the subject's S1 score is ≤15.6, the patient is judged to be positive for breast cancer and the molecular subtype is Luminal B. If S1 is >15.6, the patient is judged to be negative or to have benign breast lesions. When diagnosing HER2-positive breast cancer, if the subject's S1 is ≤14.8, the subject is judged to be breast cancer positive and the molecular subtype is HER2 positive; if S1 is >14.8, the subject is judged to be negative or benign breast lesions. When diagnosing triple-negative breast cancer, if the subject's S1 score is ≤15.5, the subject is judged to be positive for breast cancer and the molecular subtype is triple-negative breast cancer; if S1 is >15.5, the subject is judged to be negative or benign breast lesions. Alternatively, the diagnostic module makes a judgment based on the risk threshold S2 of the residual microlesion assessment model, and the judgment method is as follows: If S2 < 20.6, then the patient is diagnosed with minimal residual disease of breast cancer, and the MRD result is positive. If S2 > 48.9, it is determined that there are no microresidual lesions of breast cancer in the subject, and the MRD result is negative; If 20.6≤S2≤48.9, it is recommended that the subject be retested within 3 months or undergo enhanced clinical follow-up.

2. The system according to claim 1, characterized in that, The system also includes a result display module, which is used to display the diagnostic conclusions obtained by the diagnostic module.

3. The system according to claim 2, characterized in that, The result display module displays the diagnostic results through screen display, sound broadcast, or printing.

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