CN117802243A

CN117802243A - miRNA marker, reagent, kit and diagnosis system for liver cancer diagnosis

Info

Publication number: CN117802243A
Application number: CN202410130975.XA
Authority: CN
Inventors: 曾超; 李伟娟; 董瑞华; 李玉; 郭静; 魏亮
Original assignee: Wuhan Youzhiyou Medical Technology Co ltd
Current assignee: Wuhan Youzhiyou Medical Technology Co ltd
Priority date: 2024-01-30
Filing date: 2024-01-30
Publication date: 2024-04-02

Abstract

The invention discloses a miRNA marker, a reagent, a kit and a diagnosis system for diagnosing liver cancer, wherein the miRNA marker at least comprises the following 8 plasma exosome miRNAs: hsa-miR-100-5p, hsa-miR-224-5p, hsa-miR-218-5p, hsa-miR-452-5p, hsa-miR-21-5p, hsa-miR-27a-3p, hsa-miR-192-5p and hsa-miR-122-5p. According to the invention, through high-throughput screening and low-throughput re-screening verification, 8 miRNAs are screened from more than 1000 plasma exosome miRNAs, and when the 8 miRNAs are combined to serve as markers for diagnosing liver cancer, the sensitivity and specificity are higher, the accuracy of diagnosis results is improved, and a new thought and tool are provided for diagnosing liver cancer.

Description

miRNA marker, reagent, kit and diagnosis system for liver cancer diagnosis

Technical Field

The invention belongs to the technical field of biomedicine, and particularly relates to a miRNA marker, a reagent, a kit and a diagnosis system for diagnosing liver cancer, which are developed based on plasma exosome miRNA.

Background

Hepatocellular carcinoma (Hepatocellular carcinoma, HCC) is one of the most common solid malignant tumors worldwide, belonging to the main category of primary liver cancer, accounting for about 90% of all primary liver cancer cases. Since 1980, the incidence of liver cancer has increased more than three times and the mortality has increased more than two times. Liver cancer is also very high in morbidity and mortality worldwide, especially in saharan africa and southeast asia countries. Over 800,000 people are diagnosed with liver cancer each year worldwide, which is also one of the main causes of cancer death worldwide, resulting in over 700,000 deaths each year. Chronic viral hepatitis and liver cirrhosis are common causes of liver cancer, wherein hepatitis b virus and hepatitis c virus infection are major risk factors, and liver cancer caused by the combination of the two is more than 80% of the incidence of all liver cancer. The rapid spread of viral hepatitis has attracted considerable attention in the population, as this not only leads to an increase in liver disease, but also leaves great room for early lesions of liver cancer. Liver cancer is difficult to find in early stages, mainly because early symptoms are not obvious or easily ignored. This results in many patients already in mid-late stages at diagnosis, missing the best treatment opportunity. It is counted that among the Chinese liver cancer patients, the early liver cancer patients only account for 23.2%, while the middle and late liver cancer patients account for 76.8%. Because liver cell cancer is insensitive to radiotherapy and chemotherapy, the prognosis is generally poor. It is counted that the 5-year survival rate of liver cell liver cancer patients is about 7%, and the 5-year survival rate of patients with tumor size smaller than 2cm and subjected to surgical excision can reach 86%. Therefore, under the condition that the current treatment means are limited, the method is particularly important for the regular liver health monitoring and early screening of high-risk groups, such as chronic hepatitis patients and individuals with family history of liver cancer, and early diagnosis can obviously improve the cure rate of liver cancer and the life quality of patients.

Because liver cancer contains abundant blood vessels, pathology or puncture biopsy is not required in many cases. alpha-Alpha Fetoprotein (AFP) is used as a main plasma marker for diagnosing liver cancer clinically at present, and has certain limitation in application. Although AFP levels are often elevated in liver cancer patients, about 30% to 40% of positively diagnosed liver cancer patients do not have significantly elevated AFP levels, such that AFP diagnostic sensitivity is no higher than 65%, even as low as 20% in some studies. Meanwhile, about 20% to 50% of patients with chronic hepatitis or cirrhosis exhibit an increase in AFP, i.e., the diagnostic specificity thereof remains to be improved.

Liquid biopsy is a representative diagnostic technique of "precision medical" for obtaining tumor information and assisting in cancer treatment by non-invasive sampling. Mainly comprises CTC, ctDNA and exosomes. Exosomes are small vesicles that are released by cells into the extracellular environment, typically between 30-150 nanometers in diameter. They are produced by cells through the processes of internalization and multi-foam formation and secreted into body fluids, including blood, urine, saliva, milk, etc., by fusion with cell membranes. Exosomes contain a variety of biomolecules including proteins, lipids, DNA and RNA. Their composition reflects the physiological state of the source cells. Among them, RNA in exosomes is of particular interest to researchers, in particular microRNAs (miRNAs). mirnas are a small, non-coding class of RNAs that are widely found in eukaryotes, and are typically about 22 bases in length. These RNA molecules do not encode proteins, but rather play an important regulatory role in cells. The miRNA is combined with the complementary sequence of the target mRNA to regulate the stability and translation efficiency of the target mRNA, so that the gene expression level is finely regulated. These micrornas are widely involved in the regulation of various life processes, such as cell proliferation, differentiation, apoptosis, and control of cell cycle. Research in the field of tumor biology shows that miRNAs are closely related to the occurrence of various cancers in human bodies. They can be used as novel oncogenes (oncogenes) or oncogenes (tumor suppressor genes) involved in the occurrence, development, invasion and metastasis of cancer. Some mirnas are abnormally expressed in cancer cells, either up-regulated (e.g., some oncogenic mirnas), or down-regulated (e.g., some cancer suppressing mirnas). This change in expression level affects the growth and differentiation of cells and can even drive the progression of tumors. For example, some mirnas promote proliferation and survival of cancer cells by inhibiting expression of tumor suppressor genes, while other mirnas may exert a cancer suppressing effect by targeting and down-regulating expression of oncogenes. In addition, mirnas are also involved in regulating processes such as metabolism, angiogenesis, cell migration, and invasion of cancer cells.

miRNA (Exosomal miRNA) in exosomes is a research hotspot in the biomedical field in recent years. Exosomes can be taken up by multiple types of cells and their contents released into the recipient cells, which means that mirnas in exosomes can transmit information in the body over long distances and affect the behavior of other cells. For example, mirnas contained in exosomes released by tumor cells may be involved in the establishment of tumor microenvironments, promoting tumor growth and metastasis. Furthermore, researchers have found that mirnas in exosomes differ from mirnas in cells in composition and relative abundance. This suggests that cells may regulate intracellular miRNA levels, or transmit specific signals to other cells, by selectively vesicular specific mirnas into exosomes. For example, under certain pathological conditions, the exogenesis of a particular miRNA increases, whereas under normal conditions it does not. This diversity in specific secretion and function suggests that exosome mirnas may have specific regulatory roles in intercellular communication, and also suggests that mirnas in exosomes have potential as biomarkers for early diagnosis of cancer and other diseases. In summary, the study of exosome mirnas provides a new perspective for understanding the intercellular communication mechanisms, and provides a new approach for early diagnosis, prognosis evaluation, and treatment of diseases.

The advantages of exosome mirnas in early tumor screening are mainly seen in the following aspects: the noninvasive-exosome miRNA detection is usually carried out through a blood sample, so that the damage to a patient is small, and the risk brought by the traditional invasive detection can be overcome; stability-in clinical samples such as serum, plasma, etc., exosome mirnas exist stably in a form of being encapsulated in vesicles; early detection-exosome miRNA shows abnormal expression in early stages of tumors (such as a precancerous state or extremely low tumor load), so that the method can be used for early warning and screening of high-risk groups; simplicity-compared to the study of protein-type diagnostic markers (the latter require the preparation of antibodies), the study of exosome mirnas is relatively simple, with relatively shorter cycles from discovery to validation to application.

Since 2011, several groups have discovered hsa-miR-122 as a potential marker for liver cancer diagnosis. In fact, hsa-miR-122 is one of miRNAs specifically expressed by livers, the proportion of the hsa-miR-122 in the liver miRNAs of adult human is 75%, and the expression level of the hsa-miR-122 is obviously changed in hepatic cell injury and liver cancer. For example, hsa-miR-122 is expressed in liver cancer patients in a generally lower amount than healthy controls, which makes it a powerful candidate for diagnosing liver cancer. Furthermore, hsa-miR-21 was also shown by several studies to be able to distinguish liver cancer patients from healthy controls. In one study, a small miRNA combination consisting of hsa-miR-21, hsa-miR-122 and hsa-miR-223 showed good liver cancer diagnosis performance. The combined use of these miRNAs improves the accuracy and specificity of diagnosis. However, most of the research is based on tissue or blood free miRNAs so far, and no systematic research has been seen to exploit the potential of exosome miRNAs as early diagnostic tools for liver cancer.

Disclosure of Invention

In view of the above, the present invention aims to mine exosome miRNA related to liver cancer, and by monitoring the expression level of specific exosome miRNA, the accuracy and sensitivity of early diagnosis of liver cancer are improved, so that an earlier treatment opportunity is provided for patients, and the treatment effect is improved.

In order to achieve the above purpose, the technical scheme of the invention is as follows:

the first aspect of the present invention provides a plasma exosome miRNA marker for liver cancer diagnosis, which at least comprises the following 8 miRNAs derived from plasma exosomes: the sequence of the hsa-miR-100-5p is shown as SEQ ID NO.1, the sequence of the hsa-miR-224-5p is shown as SEQ ID NO.2, the sequence of the hsa-miR-218-5p is shown as SEQ ID NO.3, the sequence of the hsa-miR-452-5p is shown as SEQ ID NO.4, the sequence of the hsa-miR-21-5p is shown as SEQ ID NO.5, the sequence of the hsa-miR-27a-3p is shown as SEQ ID NO.6, the sequence of the hsa-miR-192-5p is shown as SEQ ID NO.7, and the sequence of the hsa-miR-122-5p is shown as SEQ ID NO. 8.

The plasma exosome miRNA used in the invention has more advantages in miRNA enrichment and stability, and targets are easier to detect and reliable results are obtained. The inventor knows through small RNA-Seq and data analysis flow that some miRNAs have expression difference between liver cancer patients and non-liver cancer patients, and then carries out RT-qPCR detection and data analysis on miRNAs showing significant expression difference, finally screens and discovers from 1000 plasma exosome miRNAs after a large number of high-throughput screening, low-throughput rescreening verification and other works, and the 8 miRNAs are combined to serve as markers for diagnosing liver cancer, so that liver cancer patients and non-liver cancer patients can be better distinguished, the sensitivity and the specificity are higher, and the accuracy of diagnosis results is improved; therefore, the invention provides a new idea for diagnosing liver cancer.

Based on the plasma exosome miRNA marker provided by the invention, the second aspect of the invention provides application of the plasma exosome miRNA marker in preparing liver cancer diagnosis products, wherein the liver cancer diagnosis products comprise but are not limited to reagents, kits, diagnosis systems, gene chips and the like.

The third aspect of the invention provides a reagent or a kit for diagnosing liver cancer, which comprises a reagent for detecting the expression level of a plasma exosome miRNA marker, wherein the plasma exosome miRNA marker consists of hsa-miR-100-5p, hsa-miR-224-5p, hsa-miR-218-5p, hsa-miR-452-5p, hsa-miR-21-5p, hsa-miR-27a-3p, hsa-miR-192-5p and hsa-miR-122-5 p. The reagent or the kit can realize diagnosis of liver cancer by detecting the expression level of the miRNA, and the diagnosis result is accurate and reliable.

In some embodiments of the invention, the expression level is specifically a CT value obtained by fluorescent quantitative PCR detection of the corresponding miRNA.

Further, the invention obtains the reagent with good detection effect for detecting the CT value of the corresponding miRNA by optimizing and improving the sequence of the reverse transcription primer, the specific amplification primer and the probe used for the fluorescent quantitative PCR detection, and specifically comprises the following nucleic acid combinations:

Nucleic acid combination 1 for detecting hsa-miR-100-5p, comprising the nucleic acid molecules shown in SEQ ID NO.9, SEQ ID NO.17, SEQ ID NO.18 and SEQ ID NO. 19;

nucleic acid combination 2 for detecting hsa-miR-224-5p, comprising the nucleic acid molecules shown in SEQ ID NO.10, SEQ ID NO.17, SEQ ID NO.20 and SEQ ID NO. 21;

nucleic acid combination 3 for detecting hsa-miR-218-5p, comprising the nucleic acid molecules shown in SEQ ID NO.11, SEQ ID NO.17, SEQ ID NO.22 and SEQ ID NO. 23;

nucleic acid combination 4 for detecting hsa-miR-452-5p, comprising the nucleic acid molecules shown in SEQ ID NO.12, SEQ ID NO.17, SEQ ID NO.24 and SEQ ID NO. 25;

nucleic acid combination 5 for detecting hsa-miR-21-5p, comprising the nucleic acid molecules shown in SEQ ID NO.13, SEQ ID NO.17, SEQ ID NO.26 and SEQ ID NO. 27;

nucleic acid combination 6 for detecting hsa-miR-27a-3p, comprising the nucleic acid molecules shown in SEQ ID NO.14, SEQ ID NO.17, SEQ ID NO.28 and SEQ ID NO. 29;

nucleic acid combination 7 for detecting hsa-miR-192-5p, comprising the nucleic acid molecules shown in SEQ ID NO.15, SEQ ID NO.17, SEQ ID NO.30 and SEQ ID NO. 31;

nucleic acid combination 8 for detecting hsa-miR-122-5p, comprising the nucleic acid molecules shown in SEQ ID NO.16, SEQ ID NO.17, SEQ ID NO.32 and SEQ ID NO. 33.

Based on the nucleic acid combination provided by the invention, an 8-in-1 reverse transcription reaction system and a multiple fluorescence quantitative PCR reaction system are successfully constructed, namely the invention realizes that the reverse transcription reaction of 8 plasma exosome miRNA markers is carried out simultaneously by using a single reaction solution, and the fluorescence quantitative PCR detection of 8 plasma exosome miRNAs is carried out by using 3 multiple PCR reaction solutions. The construction of multiple systems greatly simplifies the detection flow and workload.

Specifically, the 8-in-1 reverse transcription reaction system contains nucleic acid molecules shown in SEQ ID NO. 9-16; the nucleic acid molecules shown in SEQ ID NO.9-16 are respectively reverse transcription primers of the 8 plasma exosome mRNA, and the proportion and the concentration of the primers in the 8-in-1 reverse transcription reaction system have an influence on the reaction result; preferably, in the 8-in-1 reverse transcription reaction system, the respective concentrations of SEQ ID NOS.9 to 16 are: 0.7. Mu.M, 0.3. Mu.M, 0.5. Mu.M, 0.4. Mu.M, 0.3. Mu.M, 0.4. Mu.M, 0.7. Mu.M, and 0.7. Mu.M.

Specifically, the fluorescent quantitative PCR reaction system consists of the following 3 reaction systems:

triple PCR reaction system 1, containing nucleic acid molecules shown as SEQ ID NO.17, SEQ ID NO.18, SEQ ID NO.19, SEQ ID NO.26, SEQ ID NO.27, SEQ ID NO.32 and SEQ ID NO.33, is used for detecting hsa-miR-100-5p, hsa-miR-21-5p and hsa-miR-122-5p;

Triple PCR reaction system 2, which contains nucleic acid molecules shown as SEQ ID NO.17, SEQ ID NO.20, SEQ ID NO.21, SEQ ID NO.24, SEQ ID NO.25, SEQ ID NO.28 and SEQ ID NO.29, detects hsa-miR-224-5p, hsa-miR-452-5p and hsa-miR-27a-3p;

the double PCR reaction system contains nucleic acids shown as SEQ ID NO.17, SEQ ID NO.22, SEQ ID NO.23, SEQ ID NO.30 and SEQ ID NO.31 and is used for detecting hsa-miR-218-5p and hsa-miR-192-5p.

In the fluorescent quantitative PCR reaction system, the interference among different primers needs to be considered in combining fluorescent quantitative PCR primers of different miRNAs into different PCR reaction system reactions, so that the degradation of amplification performance and non-specific amplification are avoided. The inventor creatively discovers that when the PCR is carried out according to the 3 PCR reaction systems, on one hand, the flow is shortened, the workload is saved, on the other hand, the interference among primers can be avoided, the degradation of the amplification performance and the non-specific amplification are avoided, and the detection efficiency is greatly improved.

In a fourth aspect, the present invention provides a method for detecting the expression level of a miRNA in a plasma exosome, comprising the steps of:

s1, obtaining exosomes of a plasma sample to be tested;

s2, extracting miRNA of the exosomes obtained in the step S1;

S3, carrying out reverse transcription reaction on the miRNA obtained in the step S2 by using the reagent or the kit to obtain a reverse transcription reaction product; and performing fluorescent quantitative PCR on the reverse transcription reaction product serving as a template to obtain the expression level of the miRNA.

Further, in the above method, step S3 specifically includes: carrying out reverse transcription reaction on the miRNA obtained in the step S2 by using an 8-1 reverse transcription reaction system to obtain a reverse transcription reaction product; and then the CT values of the corresponding miRNAs are detected by using the triple PCR reaction systems 1 and 2 and the double PCR reaction system respectively.

In a fifth aspect, the invention provides a diagnostic system for diagnosing liver cancer, which uses the expression level of plasma exosome miRNA as input value to analyze, wherein the plasma exosome miRNA is composed of hsa-miR-100-5p, hsa-miR-224-5p, hsa-miR-218-5p, hsa-miR-452-5p, hsa-miR-21-5p, hsa-miR-27a-3p, hsa-miR-192-5p and hsa-miR-122-5 p.

Further, the diagnosis system comprises an information acquisition module, a calculation module and a diagnosis module which are connected in sequence in a signal mode; wherein,

the information acquisition module is used for acquiring CT values of plasma exosome miRNA of the subject;

The calculation module is used for substituting the CT value into a diagnosis model to calculate a comprehensive judgment value, and the calculation formula of the diagnosis model is as follows: discrimination score

＝-0.1354507*CT _{hsa-miR-100-5p} -0.1545306*CT _{hsa-miR-224-5p} +0.6718041*CT _{hsa-miR-218-5p} -0.1343422*CT _{hsa-miR-452-5p} -0.2457968*CT _{hsa-miR-21-5p} +0.1629244*CT _{hsa-miR-27a-3p} -0.3057168*CT _{hsa-miR-192-5p} -0.3124913*CT _{hsa-miR-122-5p} +31.37566; in CT _{hsa-miR-100-5p} 、CT _{hsa-miR-224-5p} 、CT _{hsa-miR-218-5p} 、CT _{hsa-miR-452-5p} 、CT _{hsa-miR-21-5p} 、CT _{hsa-miR-27a-3p} 、CT _{hsa-miR-192-5p} And CT _{hsa-miR-122-5p} Respectively represent the CT values of the corresponding miRNAs.

The diagnosis module is used for judging the health condition of the subject according to the comprehensive judgment value; and if the comprehensive judgment value is smaller than the threshold value, judging that the subject is a non-liver cancer patient, and if the comprehensive judgment value is larger than or equal to the threshold value, judging that the subject is a liver cancer patient.

Further, in the above diagnostic system, the threshold value is 0; based on a calculation formula of the diagnosis model, the threshold is combined to diagnose the health condition of the subject, such as whether the liver cancer is suffered or not, so that the sensitivity and the specificity are higher, and a more accurate judgment result can be obtained.

Further, in the above diagnostic system, the diagnostic system further comprises a detection module in signal connection with the information acquisition module; the detection module is used for detecting CT value information of the plasma exosome miRNA of the subject.

Further, in the above diagnostic system, the diagnostic system further includes a result display module; the result display module is used for displaying the diagnosis result obtained by the diagnosis module. For example, the result display module may display the diagnosis result by means of screen display, voice broadcast or printing.

Compared with the prior art, the invention has the beneficial effects that:

aiming at plasma exosome miRNA, the invention adopts high-flux screening and low-flux re-screening verification of complete independent intellectual property rights, 8 miRNAs shown in SEQ ID NO.1-8 are screened from more than 1000 miRNAs, and when the 8 miRNAs are used as a marker group for diagnosing liver cancer, the 8 miRNAs have higher sensitivity and specificity, the accuracy of diagnosis results is improved, and a new thought and tool are provided for diagnosing liver cancer. In addition, the reverse transcription system, the fluorescent quantitative PCR system and the diagnosis model are established and optimized based on the marker group, and guidance is provided for the practical application of the miRNA marker group in liver cancer diagnosis.

Drawings

FIG. 1 is a schematic diagram of a small RNA-Seq library preparation procedure in example 1 of the present invention;

FIG. 2 is a graph showing the overall distribution of ncRNA in the control group and the liver cancer group according to example 1 of the present invention;

fig. 3 is a graph showing the results of an edgeR analysis of differentially expressed mirnas in example 1 of the present invention.

FIG. 4 is a statistical plot of the amounts of significant differentially expressed miRNAs shared or unique by DESeq2 and edge results in example 1 of the present invention.

Fig. 5 shows ROC curves and AUC between the liver cancer test group and the control test group in example 4 of the present invention.

FIG. 6 shows the ROC curve and AUC between the liver cancer test group and the control test group for the diagnosis model in example 4 of the present invention.

Detailed Description

The following detailed description of the technical solution of the present invention will be given with reference to the accompanying drawings and examples, which are only used to more clearly illustrate the technical solution of the present invention, and thus are only examples and should not be used to limit the scope of the present invention.

Unless defined otherwise, 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 invention belongs; the term "comprising" and any variations thereof in the description of the invention and in the claims is intended to cover a non-exclusive inclusion.

The following examples are not to be construed as limiting the specific techniques or conditions described in the literature in this field or as per the product specifications; the reagents or apparatus used were conventional products commercially available without the manufacturer's attention.

Example 1

The example provides a plasma exosome miRNA marker combination for liver cancer diagnosis, which specifically comprises hsa-miR-100-5p, hsa-miR-224-5p, hsa-miR-218-5p, hsa-miR-452-5p, hsa-miR-21-5p, hsa-miR-27a-3p, hsa-miR-192-5p and hsa-miR-122-5 p. The invention specifically discovers the combination through the following processes:

(1) Sample plasma exosome miRNA preparation flow.

Sample plasma (EDTA anticoagulation, non-hemolysis) collection method: collecting a fresh whole blood sample with a blood collection tube containing an anticoagulant; centrifuging the whole blood sample at 1000-2000g for 10-15 minutes; gently transfer the upper plasma to a new sterile tube, avoiding disturbing the lower cells.

The method for collecting the plasma exosomes comprises the following steps: the plasma was centrifuged at 3000g for 30 minutes to remove cell debris; filtering the supernatant after centrifugation through a 0.22 μm filter membrane to further remove cell debris; centrifuging the filtered plasma at 100,000g for at least 1 hour to precipitate exosomes; gently remove supernatant, avoid disturbing sediment; the pellet was resuspended with pre-chilled PBS and centrifuged again at 100,000g for 1 hour; all centrifugation steps were 4 ℃ to ensure exosomes stability; removing supernatant, slightly suspending the final precipitate in PBS, collecting exosomes, and storing at-80deg.C.

The preparation method of exosome miRNA comprises the following steps: treating the exosome sample with a QIAGEN QIAzol reagent to release total RNA therein; extracting miRNA according to the instruction manual of the manufacturer by using a QIAGEN miRNeasyMicro kit and performing a washing step; finally, the miRNA is resuspended with RNase-free water or provided buffer.

All operations in the step should be performed under aseptic conditions to avoid sample contamination; all used appliances are disposable consumables which are special for RNA and have no RNase and DNase; and moreover, the frozen samples are transported in a frozen and sealed way.

(2) Subjects entered group criteria.

According to the collection flow of the step (1), collecting and obtaining a blood sample of a subject, wherein the group entering standards of the liver cancer group subject and the control group subject are as follows:

liver cancer group subjects: the clinical initial diagnosis is liver cancer, especially early liver cancer BCLC stage 0 and stage A.

Control group subjects: chronic hepatitis b patient; patients with cirrhosis; patients with non-liver cancer malignancy; healthy people.

(3) High throughput screening of plasma exosome miRNAs for liver cancer diagnosis.

(1) small RNA-Seq high throughput sequencing.

In this example, plasma exosome miRNA was extracted from blood samples of 9 liver cancer subjects and 8 control subjects, and then Illumina HiSeq was used ^TM 2500 were subjected to small RNA-Seq high throughput screening. Because the miRNA fragment is shorter, the library construction flow mainly comprisesThe method comprises the following steps: extracting total RNA of plasma exosomes, sequentially connecting a 3 'end and a 5' joint, reversely transcribing into cDNA, and performing PCR amplification; and cutting the gel to recover a target fragment library, and sequencing the library with qualified quality inspection on a machine. The specific experimental procedure for library preparation is shown in FIG. 1. Raw data (raw reads) from Illumina HiSeqTM 2500 sequencing were first filtered: removing the joints at the two ends of reads, and removing the fragment length <17nt reads and low quality reads, etc., to complete the preliminary filtering of the data and obtain high quality data (clean reads).

(2) Sequencing data analysis.

In this example, clear reads in sequencing data were aligned to a reference genome using bowtie software, and the alignment results are shown in table 1:

TABLE 1 clear reads and reference genome alignment statistics

Clean_Reads in Table 1 represents the total amount of Clean Data in the sequencing Data, mapping_Reads represents the number of Clean Reads aligned to the genome in the sequencing Data.

The filtered reads were aligned with the database of authoritative miRNA/rRNA/tRNA/snRNA/snoRNA and injected with known non-coding RNAs (ncRNAs), including miRNA, rRNA, tRNA, snRNA, snoRNA. The databases specifically used are: the miRNA database was from miRBase version 22 (www.mirbase.org), the tRNA, rRNA, snRNA, snoRNA database was from Rfam14.6 (rfam. Xfam. Org), and the pirRNA database was from pirnabank (pirnabank. Ibab. Ac. In).

All sequenced clean reads were aligned and annotated to various RNA databases and the results were summarized and counted for liver cancer group (HCC) and control group (Normal), as shown in FIG. 2. The results show that the ratio difference of the ncRNA of the miRNA between the control group and the liver cancer group is obvious.

And comparing the clear reads obtained by sequencing with all human miRNA mature body sequences in a miRBase.v22 database through the miradeep 2 to obtain the information such as the structure, the length, the expression quantity and the like of the miRNA. The mirdieep 2 is software developed based on perl and can be used for miRNA identification and expression quantity calculation; the method has better performance on miRNA identification quantity, miRNA false negative and false positive control. miRNA calculated by RPM (Reads Per Million) values, rpm= (number of reads mapped to miRNA/number of reads in Clean Data) ×10 ⁶ ). miRNA counts in each sample were used for subsequent differential expression analysis, miRNA expression statistics are shown in table 2:

TABLE 2 statistics of miRNA comparison results

Sample of	miRNA.NO
		Sample_1	940
Sample_2	905
		Sample_3	956
Sample_4	889
		Sample_5	1008
Sample_6	932
		Sample_7	977
Sample_8	1036
		Sample_9	1124
Sample_10	1093
		Sample_11	1041
Sample_12	960
		Sample_13	1077
Sample_14	906
		Sample_15	993
Sample_16	1022
		Sample_17	1054

(3) Differential miRNA expression analysis.

The miRNA expression difference analysis has a plurality of different software, and because the algorithms of the software are based on different statistical algorithms and statistical assumptions, the obtained miRNA results of the difference expression are quite different, and the p values obtained by specific miRNAs in the comparison process between different samples can also have quite large differences. The inventor selects from a plurality of widely applied miRNA expression difference analysis programs, and finally selects DESeq2 and edge for expression difference analysis. DESeq2 is a commonly used R software package for differential gene expression analysis, using a negative binomial distribution model to estimate variance and verify statistical significance, particularly suitable for processing high throughput sequencing data; edge is a R-language package used for comparison of classical RNA sequencing, and differentially expressed mirnas were identified based on negative binomial distribution, similar to DESeq, using statistical methods such as the empirical bayesian method (empirical Bayes methods).

The specific operations of miRNA expression differential analysis in this example are as follows:

each sample miRNA count data obtained from the data analysis above was first analyzed using DESeq 2. Filtering out mirnas that occur in fewer samples before analyzing the differences in expression, i.e., retaining only mirnas that are expressed in at least 50% of the samples; after differential expression analysis using the DESeq function, mirnas with significant differential expression between samples were selected by significant levels Padj < 0.05.

Analysis was then performed using edder, again retaining only mirnas expressed in at least 50% of the samples, fitting a generalized linear model using glmQLFit function, and finally screening for significantly differentially expressed mirnas by significant levels Padj < 0.05.

Statistics of the number of significantly differentially expressed mirnas between samples finally obtained by the two analysis methods are shown in table 3.

TABLE 3 statistical results of significantly differentially expressed miRNAs

Analysis method	Sig	Up	Down
				DESeq2	402	269	133
edgeR	286	207	79

In table 3, sig is the number of mirnas significantly differentially expressed, up is the number of significantly Up-regulated mirnas, and Down is the number of significantly Down-regulated mirnas.

The volcanic plot is used for representing the edgeR analysis result of the differential expression miRNA, as shown in FIG. 3, and the abscissa represents the expression fold change of the miRNA in different samples; the ordinate represents the statistical significance of variation in miRNA expression levels, square dots represent candidate mirnas with significant upregulation, and circular dots represent candidate mirnas with significant downregulation.

And (4) utilizing RStudio to analyze DESeq2 and edge results, and finding out the common or specific obvious differential expression miRNA between the two analysis method results, wherein the statistical quantity of the differential expression miRNA is shown in figure 4. The differential expression data of the 255 mirnas in total were then combined with their RPM table in each sample sequencing result using the R platform dplyr package, mirnas were selected with RPM > 400, edgeR fold difference |log2 (FoldChange) | >1.5, edgR significant level Padj <0.005 in at least 50% of the samples, and finally a small RNA-seq prescreening result was obtained for 52 candidate mirnas in total, as shown in table 4.

TABLE 4 small RNA-SeqmiRNA Primary screening results

(4) The fluorescent quantitative PCR detection of the high-flux screening result is confirmed in the first round.

And (3) acquiring 34 subject blood samples according to the group entering standard in the step (2), wherein the subject queue is different from the subject queue in the high-throughput screening in 20 liver cancer groups and 14 control groups.

Firstly, extracting plasma exosome miRNA according to the step (1), and then, carrying out miRNA reverse transcription reaction through Takara PrimeScript RT Reagent Kit by utilizing a specific stem-loop primer designed for the candidate miRNA to obtain cDNA of each candidate miRNA. The reverse transcription reaction system is shown in Table 5, and the reaction process is as follows: 15min at 37 ℃;85 ℃ for 5min; holding at 4 ℃.

TABLE 5 reverse transcription reaction system

Component (A)	Volume (mu L)
		Extraction product of miRNA of plasma exosome	10
PrimeScript RT Enzyme Mix	1
		Specific stem-loop primer (10. Mu.M)	4
5×PrimeScript Buffer	4
		Rnase-free H ₂ O	1
Total	20

The fluorescent quantitative PCR is carried out by adopting a Taqman probe method, and the detection and confirmation of the candidate miRNA are carried out on an ABI 7500 fluorescent quantitative PCR instrument according to a PCR reaction system shown in the table 6 by utilizing a universal downstream primer SEQ ID NO.17, a specific upstream primer and a probe designed for the candidate miRNA.

TABLE 6 PCR reaction System

Taking an ABI 7500 fluorescent quantitative PCR instrument as an example, the operation flow of a PCR reaction system is as follows: 95 ℃ for 5min; (95 ℃ C. 15s,60 ℃ C. 40s, fluorescence was collected) for 45 cycles. As a result, 7500software is taken as an example, autoBaseline is set, threshold is set as Auto, and the CT value of the candidate miRNA in each sample is obtained.

Judging the obtained original CT values, only preserving miRNAs with CT values less than 35 in at least 20% samples (namely 7 samples), wherein the result shows that 36 miRNAs are excluded, and the 16 reserved candidate miRNAs comprise: has-miR-100-5p, has-miR-224-5p, has-miR-218-5p, has-miR-452-5p, has-miR-21-5p, has-miR-196a-5p, has-miR-27a-3p, has-miR-192-5p, has-miR-128-3p, has-miR-423-5p, has-miR-486-5p, has-miR-148a-3p, has-let-7d-3p, has-miR-26a-5p, has-miR-122-5p and has-miR-92a-3p.

(5) The final combined fluorescence quantitative PCR detection of the plasma exosome miRNA for diagnosing liver cancer is found.

The blood samples of 105 subjects were included according to the inclusion criteria in step (2), including 60 liver cancer groups and 45 control groups, and the subject cohort was different from the subject cohort in the high throughput screen. The inventors performed final confirmation of candidate mirnas by a fluorescent quantitative PCR method.

Firstly, extracting plasma exosome miRNA according to the step (1), wherein In the QIAGEN miRNeasyMicro kit extraction step, RNASpike-In, namely cel-miR-39, is added according to the specification requirement, and then, the Takara PrimeScript RT Reagent Kit is used for carrying out miRNA reverse transcription reaction, so that the 16 candidate miRNAs obtained In the step (4) and cDNA of the RNASpike-In are obtained (a reverse transcription reaction system and a process are the same as those In the step (4)).

Then, according to the PCR reaction system shown In Table 6, 16 candidate miRNAs and RNASpike-In were detected on an ABI 7500 fluorescent quantitative PCR apparatus (the operation flow is the same as that of step (4)). As a result, taking 7500software as an example, autopaseline is set, threshold is set as Auto, and CT values of 16 candidate mirnas and RNA Spike-In each sample are obtained, wherein the CT value exceeds 40.

And (3) calibrating CT values of each candidate miRNA by adopting RNA Spike-In and global normalization to eliminate experimental deviation and ensure the accuracy and comparability of qPCR data analysis. For each sample i (where i=1, 2, …, 105) and each candidate miRNA j (where j=1, 2, …, 16), the CT values after RNA Spike-In calibration were first calculated

Then calculating the final CT value after global normalization

In the above-mentioned formula(s),is the original CT value of miRNA j in the sample i;Is the CT value of RNA Spike-excel-miR-39 in sample i;I.e. a global normalization factor.

And then, analyzing the operation characteristic curve (receiver operating characteristic curve, abbreviated as ROC curve) of the acceptors between the liver cancer test group and the control test group by using the R platform pROC package, calculating the area under the curve (Area under the Curve, abbreviated as AUC), fitting a logistic regression model by using a glm function, and calculating the P value of each miRNA for distinguishing the liver cancer from the control, wherein the result is shown in the table 7.

TABLE 7 diagnostic Performance analysis results of 16 miRNAs

Candidate miRNAs	AUC	Lower 95% confidence interval limit	Upper 95% confidence interval limit	P value
					has-miR-100-5p	0.925926	0.868355	0.970284	1.11E-06
has-miR-224-5p	0.904444	0.840111	0.957221	4.41E-07
					has-miR-218-5p	0.902593	0.829634	0.959431	3.79E-07
has-miR-452-5p	0.872593	0.797319	0.939185	1.97E-07
					has-miR-21-5p	0.842222	0.758182	0.917451	1.67E-06
has-miR-27a-3p	0.831111	0.751729	0.901257	1.69E-06
					has-miR-192-5p	0.734074	0.626578	0.833451	0.000382
has-miR-122-5p	0.680556	0.572962	0.781208	0.001405
					has-miR-148a-3p	0.666852	0.542299	0.777592	0.004479
has-miR-196a-5p	0.641111	0.469243	0.747857	0.006499
					has-miR-128-3p	0.635926	0.485646	0.741935	0.105538
has-miR-486-5p	0.624259	0.393849	0.73359	0.029896
					has-miR-423-5p	0.541805	0.450046	0.667021	0.577323
has-miR-92a-3p	0.5299	0.463965	0.66374	0.795534
					has-let-7d-3p	0.517222	0.464651	0.640366	0.771896
has-miR-26a-5p	0.515926	0.465628	0.631103	0.930485

As can be seen from Table 7, the diagnostic properties of has-miR-100-5P, has-miR-224-5P, has-miR-218-5P, has-miR-452-5P, has-miR-21-5P, has-miR-27a-3P, has-miR-192-5P and has-miR-122-5P are optimal, and the significant flat P value is less than 0.005. In view of the fact that the composition form of the diagnostic kit is not too complex, the 8 plasma exosome miRNAs are selected to be used for constructing the liver cancer diagnostic kit, and the sequences of the 8 miRNAs are specifically shown in table 8.

TABLE 8 plasma exosome miRNAs for liver cancer diagnosis

Example 2

Based on the plasma exosome miRNA marker combination for liver cancer diagnosis provided by the invention, an 8-in-1 reverse transcription system and a fluorescent quantitative PCR system of the combination are constructed, and the method is as follows:

(1) Construction of 8-in-1 reverse transcription system of 8 plasma exosome miRNA markers.

The reverse transcription primer sequences of the 8 plasma exosomes mirnas are shown in table 9.

Table 9 reverse transcription primers for each miRNA

The experimental results of example 1 show that the reaction systems of has-miR-100-5p, has-miR-224-5p and has-miR-218-5p are stable and have the highest diagnosis performance, so that the inventor sets the using amount of 20 mu L of corresponding three reverse transcription primers (namely SEQ ID NO. 9-11) to be 1.5 mu L multiplied by 10 mu M, adopts an L16 (4^5) orthogonal table to carry out orthogonal experimental design, carries out 16 batches of experiments to explore the proportion of different reverse transcription primers, detects 8 miRNAs through fluorescence quantitative PCR for evaluation, and detects 3 multiple holes of each miRNA. And judging to be qualified (1) when the variation coefficient CV% between the compound holes of the 8 miRNAs is less than or equal to 1.5%, otherwise, judging to be unqualified (0). The evaluation results are shown in Table 10.

Table 10 results of comparative experiments with reverse transcription System

From the results in table 10, the agreement of each miRNA multiplex was better for system 10 and system 15. After repeated verification of system 10 and system 15 (10 times), the results showed 2 CT's in system 10 _{hsa-miR-224-5p} The coefficient of variation CV% > 1.5% is assumed to be caused by a higher total primer concentration in the reverse transcription reaction system. And then, carrying out optimized fine tuning on the system 15, and finally determining a reverse transcription system shown in the table 11, so that the high reverse transcription repeatability of each miRNA can be ensured.

Table 11 8-1 reverse transcription System

Component (A)	Volume (mu L)
		5×Buffer	4
SEQ ID NO.9(10μM)	1.5
		SEQ ID NO.10(10μM)	1.5
SEQ ID NO.11(10μM)	1.5
		SEQ ID NO.12(10μM)	0.6
SEQ ID NO.13(10μM)	0.6
		SEQ ID NO.14(10μM)	0.75
SEQ ID NO.15(10μM)	0.75
		SEQ ID NO.16(10μM)	0.8
RT Enzyme Mix	1
		RNA extraction products	7
Totalizing	20

(2) Construction and evaluation of a multiplex fluorescence quantitative PCR reaction system of 8 plasma exosome miRNA markers.

(1) Primer probe screening and multiple combination testing.

In order to make the fluorescence quantitative PCR detection process more convenient and efficient, the detection form of 8 miRNAs is considered to be optimized from a single PCR to a double or triple PCR form. In view of the structural specificity of the miRNA specific stem-loop primer, partial primer probes in single PCR detection cannot show good amplification performance in a double or triple PCR system, so the construction of the multiplex PCR reaction system is divided into 3 stages:

stage one: in order to ensure that the amplification systems of hsa-miR-100-5p, hsa-miR-224-5p and hsa-miR-218-5p with optimal diagnosis performance are efficient and stable, a multi-batch melting curve method experiment is carried out, and specific upstream primers corresponding to 3 miRNAs are screened and determined so that a melting curve presents a single peak; and then screening and determining FAM channel probes corresponding to 3 miRNAs, so that a monomer system amplification curve of the Taqman probe method presents obvious S type, a CT value is front, and fluorescence is high.

Stage two: the dual PCR marker combinations were tested by permutation and combination, with primer probes for hsa-miR-452-5p, hsa-miR-21-5p, hsa-miR-27a-3p, hsa-miR-192-5p, hsa-miR-122-5p, each combination being subjected to a screening test, and the combination results being shown in Table 12.

Table 12 double PCR marker combination test

In Table 12, 1 represents a double PCR amplification curve, CT values and fluorescence heights are normal, and Kong Quxian is gathered; 0 represents the double PCR amplification curve, the abnormal CT value or fluorescence height, or the dispersion of the compound pore curve. Table 12 the results show that: the monomer system primer probe of hsa-miR-218-5p is easily influenced by other primer probes of a double system, and the amplification performance is good when the monomer system primer probe and hsa-miR-192-5p form the double system; in the rest miRNA, hsa-miR-100-5p and hsa-miR-21-5p, hsa-miR-27a-3p or hsa-miR-122-5p can form a dual system meeting requirements, and hsa-miR-224-5p and hsa-miR-452-5p, hsa-miR-27a-3p or hsa-miR-122-5p can also form a dual system meeting requirements.

Stage three: triple PCR marker combinations other than hsa-miR-218-5p and hsa-miR-192-5p were tested, and 3-multiplex well assays were performed for each combination, and the combination results are shown in Table 13.

Table 13 triple PCR marker combination test

In Table 13, result 1 represents a double PCR amplification curve, CT values and fluorescence height were normal, and Kong Quxian was gathered; 0: representing the occurrence of abnormalities in the duplex PCR amplification curve, CT value or fluorescence height, or the dispersion of the duplex curve. The results in table 13 show: when hsa-miR-100-5p, hsa-miR-21-5p and hsa-miR-27a-3p are combined into a triple system, the amplification curve of hsa-miR-27a-3p is abnormal no matter how VIC and CY5 channels are distributed; in a triple system consisting of hsa-miR-100-5p, hsa-miR-21-5p and hsa-miR-122-5p, a VIC probe of hsa-miR-122-5p cannot tolerate the triple system and shows high abnormality of fluorescence. The probes were set to the common VIC channel, given the higher diagnostic properties of hsa-miR-452-5 p.

Combining the above results, this example uses the following triple or duplex PCR system: combination 1 is hsa-miR-100-5p (FAM), hsa-miR-21-5p (VIC) and hsa-miR-122-5p (CY 5); combination 2 is hsa-miR-224-5p (FAM), hsa-miR-452-5p (VIC) and hsa-miR-27a-3p (CY 5); combination 3 is hsa-miR-218-5p (FAM) and hsa-miR-192-5p (VIC).

(2) Multiplex PCR system optimization validation.

Through further system component concentration optimization, the fluorescence quantitative PCR detection of 8 plasma exosome miRNA markers in a three-tube reaction system shown in table 14 is finally realized, and the sequences of the primers and probes used are shown in table 15. And each reaction well collects fluorescent signals of a corresponding channel when fluorescent quantitative PCR amplification is carried out. Taking an ABI 7500 fluorescent quantitative PCR instrument as an example, the operation flow of the 3 reaction systems is as follows: 95℃for 5min, (15 s at 95℃and 40s at 60℃to collect fluorescence) 45 cycles.

Table 14 3 multiplex PCR reaction systems for detecting 8 plasma exosomes mirnas

TABLE 15 primer and probe information for 8 plasma exosome miRNAs

(3) And (5) evaluating the analysis performance of the reaction system.

The mixture of 8 kinds of miRNA fragments synthesized by artificial synthesis is firstly diluted to 6×10 ⁶ The copies/. Mu.L is used as a positive reference for accuracy detection; diluting the mixture of miR-1228 and miR-141 fragments outside the detection range to 6X 10 ⁶ cobies/. Mu.L as a specific reference for specific detection; diluting the mixture of 8 artificially synthesized miRNA fragments to 200 copies/. Mu.L, and taking the mixture as a detection limit reference for detection limit; the mixture of 8 kinds of miRNA fragments synthesized artificially was diluted to 2000 copies/. Mu.L as a repetitive reference for repetitive detection.

Detecting positive reference substances by using 3 reaction systems in the step (2), wherein the CT values of all corresponding fluorescent channels are less than 30; detecting a specific reference, wherein as a result, all fluorescent channels have no obvious amplification curve or CT values are more than or equal to 40; detecting a detection limit reference, wherein the CT values of all corresponding fluorescent channels are smaller than 38; the repetitive reference is detected 10 times each, and as a result, the CT values of all corresponding fluorescent channels are less than 35, and the variation coefficient CV% of the CT values of the corresponding reaction channels is less than 5.0%.

The results show that the detection performance of the 3 sets of multiple reaction systems constructed in the example meets the requirements.

Example 3

The example provides a kit for diagnosing liver cancer, which comprises the following reaction systems: 8-1 reverse transcription reaction system, triple PCR reaction system and double PCR reaction system. The preparation and assembly methods of the kit are shown in Table 16.

TABLE 16 preparation and assembly of 8-1 reverse transcription reaction system and multiplex PCR reaction system

The kit provided by the embodiment can carry out the specific stem-loop reverse transcription of 8 plasma exosome miRNAs by using 1-tube reverse transcription mixed solution, and carry out simultaneous detection of 8 miRNAs by using 3-tube PCR mixed solution, and is simple, convenient and efficient.

Example 4

Based on the kit provided by the invention, a diagnosis model for diagnosing liver cancer is established and verified in the embodiment, and the specific process is as follows:

(1) And (6) establishing a diagnosis model.

According to the standard of the group entry in example 1, 139 blood samples of subjects were collected, of which 71 liver cancer groups and 68 control groups, were subjected to miRNA extraction according to the plasma exosome RNA extraction method in example 1, and reverse transcription and PCR detection were performed using the kit of example 3.

Specifically, an 8-in-1 reverse transcription system was formulated according to table 17, and the reverse transcription reaction conditions were as follows: 15min at 37 ℃;85 ℃ for 5min; holding at 4 ℃.

Table 17 8-1 reverse transcription System

Reagent(s)	Usage amount (mu L)
		8-in-1 reverse transcription mixed solution	13
RNA	7
		Totalizing	20

Subjecting each cDNA obtained by reverse transcription to ddH ₂ O is diluted 5 times, 2 mu L of the mixture is added into 23 mu LPCR mixed solution 1 after the mixture is uniformly mixed, 2 mu L of the mixture is added into 23 mu LPCR mixed solution 2, 2 mu L of the mixture is added into 23 mu L of PCR mixed solution 3, fluorescent quantitative PCR amplification is carried out after the mixture is uniformly mixed, an ABI 7500 fluorescent quantitative PCR instrument is taken as an example for an amplification program, and the operation flow of the 3 PCR reaction systems is as follows: 95℃for 5min, (95℃for 15s,60℃for 40s, fluorescence collected) 45 cycles. Wherein, PCR mixture 1 and 2 collect FAM, VIC and CY5 fluorescence signals, and PCR mixture 3 collects FAM and VIC fluorescence signals. The results show that the CT of each miRNA in all samples is less than 35, and the amplification performance is good.

In this embodiment, a Linear Discriminant Analysis (LDA) model is built using LDA functions in the R-platform MASS package, and ROC curve analysis is performed using the pROC package. Linear discriminant analysis is a commonly used classification technique, particularly suited for classifying samples based on a number of variables. And performing LDA diagnosis model training by using CT values of all markers in the fluorescent quantitative PCR result, obtaining discriminant coefficients (comprising intercept items), and performing model verification by using a training set. The obtained LDA model discriminant is as follows:

Discrimination score

＝-0.1354507*CT _{hsa-miR-100-5p} -0.1545306*CT _{hsa-miR-224-5p} +0.6718041*CT _{hsa-miR-218-5p} -0.1343422*CT _{hsa-miR-452-5p} -0.2457968*CT _{hsa-miR-21-5p} +0.1629244*CT _{hsa-miR-27a-3p} -0.3057168*CT _{hsa-miR-192-5p} -0.3124913*CT _{hsa-miR-122-5p} +31.37566。

The positive judgment value of liver cancer is set to 0, namely: when the discrimination score (Y) >0, it is estimated that liver cancer; and when Y is less than or equal to 0, estimating that the liver cancer is non-liver cancer. The accuracy of the LDA model in the training set, 139 samples, was 87.76978%. The discrimination result matrix is shown in table 18. Auc=0.9405405, p <0.0001, sensitivity 93%, specificity 86% on training set of LDA model, ROC curve is shown in fig. 5.

Discrimination result matrix of table 18 LDA model on training set

(2) And (5) verifying a diagnosis model.

182 subjects blood samples different from the training set were collected according to the standard of the group entry in example 1, wherein 99 liver cancer groups and 83 control groups were obtained, and then miRNA extraction was performed according to the method for extracting plasma exosome RNA in example 1, and reverse transcription and PCR detection were performed using the kit of example 3.

The reverse transcription and PCR detection method were identical to the above, and then CT values of 8 mirnas were substituted into the discriminant in step (1) of this embodiment to obtain a discriminant score. When the discrimination score is greater than 0, it is estimated to be liver cancer; and when Y is less than or equal to 0, estimating that the liver cancer is non-liver cancer. ROC curve analysis was performed using the R-platform pROC package. The results showed that 182 samples were 86.26374% accurate. The discrimination result matrix is shown in table 19. Auc=0.9267373, p <0.0001, sensitivity 90%, specificity 92% and ROC curve of the LDA model on the validation set are shown in fig. 6, which shows that the LDA model of the present example is excellent in diagnostic performance when liver cancer is distinguished from the control.

Table 19 LDA model discrimination result matrix on verification set

In summary, the present invention provides a high reliability of plasma exosome miRNA combination for diagnosing liver cancer, which is at least characterized in the following aspects: firstly, in a step of high-throughput sequencing miRNA expression difference analysis, two different modes of DESeq2 and edge are adopted to carry out parallel analysis and intersection is taken, and then primary screening results are obtained through comprehensive judgment of RPM, log2 (FoldChange) and Padj < 0.005; secondly, in the re-screening step, RNA Spike-In and a global normalization factor are adopted to double calibrate the detection result so as to eliminate deviation, ensure accurate and reliable data, and obtain 8 miRNAs to construct a diagnosis system, wherein the AUC of the three miRNAs In the re-screening is more than 0.9. The invention builds and optimizes a multiple reverse transcription system and a multiple fluorescence quantitative PCR reaction system based on the 8 plasma exosome miRNA markers through a large number of experimental exploration, and further builds a diagnosis model for diagnosing liver cancer based on the reverse transcription system and the PCR reaction system, wherein the classification performance of the diagnosis model is excellent, and the AUC in 182 samples is proved to be more than 92%, and the total coincidence rate is more than 86%. Therefore, the invention provides a new way and a reliable tool for diagnosing liver cancer.

The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. Plasma exosome miRNA markers for liver cancer diagnosis are characterized by at least comprising the following 8 miRNAs derived from plasma exosomes: the sequence of the hsa-miR-100-5p is shown as SEQ ID NO.1, the sequence of the hsa-miR-224-5p is shown as SEQ ID NO.2, the sequence of the hsa-miR-218-5p is shown as SEQ ID NO.3, the sequence of the hsa-miR-452-5p is shown as SEQ ID NO.4, the sequence of the hsa-miR-21-5p is shown as SEQ ID NO.5, the sequence of the hsa-miR-27a-3p is shown as SEQ ID NO.6, the sequence of the hsa-miR-192-5p is shown as SEQ ID NO.7, and the sequence of the hsa-miR-122-5p is shown as SEQ ID NO. 8.

2. The use of the plasma exosome miRNA marker according to claim 1 for the preparation of a diagnostic product for liver cancer.

3. A reagent or kit for diagnosing liver cancer, comprising a reagent for detecting the expression level of a miRNA, wherein the miRNA is composed of hsa-miR-100-5p, hsa-miR-224-5p, hsa-miR-218-5p, hsa-miR-452-5p, hsa-miR-21-5p, hsa-miR-27a-3p, hsa-miR-192-5p, and hsa-miR-122-5p according to claim 1.

4. A reagent or kit according to claim 3, wherein the reagent for detecting the expression level of miRNA is specifically a reagent for detecting the CT value of the miRNA, comprising the following nucleic acid combination:

5. The reagent or the kit according to claim 4, comprising an 8-in-1 reverse transcription reaction system and a fluorescent quantitative PCR reaction system, wherein the 8-in-1 reverse transcription reaction system contains the nucleic acid molecules shown by SEQ ID NO.9-16, and the fluorescent quantitative PCR reaction system consists of the following three reaction systems:

triple PCR reaction system 1 comprising the nucleic acid molecules shown as SEQ ID NO.17, SEQ ID NO.18, SEQ ID NO.19, SEQ ID NO.26, SEQ ID NO.27, SEQ ID NO.32 and SEQ ID NO. 33;

triple PCR reaction system 2 comprising the nucleic acid molecules shown as SEQ ID NO.17, SEQ ID NO.20, SEQ ID NO.21, SEQ ID NO.24, SEQ ID NO.25, SEQ ID NO.28 and SEQ ID NO. 29;

a double PCR reaction system comprises nucleic acids shown as SEQ ID NO.17, SEQ ID NO.22, SEQ ID NO.23, SEQ ID NO.30 and SEQ ID NO. 31.

6. A method for detecting the expression level of a plasma exosome miRNA, comprising the steps of:

s1, obtaining exosomes of a plasma sample to be tested;

s2, extracting miRNA of the exosomes obtained in the step S1;

S3, carrying out reverse transcription reaction on the miRNA obtained in the step S2 by using the reagent or the kit according to the claim 4 or 5, and carrying out fluorescence quantitative PCR detection on the obtained reverse transcription reaction product to obtain the CT value of the miRNA.

7. A diagnostic system for diagnosing liver cancer, characterized in that the expression level of plasma exosome mirnas consisting of hsa-miR-100-5p, hsa-miR-224-5p, hsa-miR-218-5p, hsa-miR-452-5p, hsa-miR-21-5p, hsa-miR-27a-3p, hsa-miR-192-5p and hsa-miR-122-5p according to claim 1 is analyzed as an input value.

8. The diagnostic system of claim 7, comprising an information acquisition module, a calculation module, and a diagnostic module that are sequentially signally connected;

the calculation module is used for substituting the CT value into a diagnosis model to calculate a comprehensive judgment value, and the calculation formula of the diagnosis model is as follows: discrimination score = -0.1354507 ct _{hsa-miR-100-5p} -0.1545306*CT _{hsa-miR-224-5p} +0.6718041*CT _{hsa-miR-218-5p} -0.1343422*CT _{hsa-miR-452-5p} -0.2457968*CT _{hsa-miR-21-5p} +0.1629244*CT _{hsa-miR-27a-3p} -0.3057168*CT _{hsa-miR-192-5p} -0.3124913*CT _{hsa-miR-122-5p} +31.37566；

9. The diagnostic system of claim 8, wherein the threshold is 0.

10. The diagnostic system of claim 8, further comprising a detection module and/or a result display module; the detection module is in signal connection with the information acquisition module, the detection module is used for detecting CT value information of the plasma exosome miRNA of the subject, and the result display module is used for displaying a diagnosis result obtained by the diagnosis module.