A diagnostic marker for liver fibrosis in hepatitis b patients, methods and uses thereof

Abstract

The application discloses a diagnostic marker for liver fibrosis of hepatitis B patients, a method and application thereof. Based on bioinformatics analysis, the application finds a key liver fibrosis diagnostic marker RRM2. By detecting the expression level of RRM2 in serum of a to-be-detected person, the fibrosis staging diagnosis of hepatitis B patients can be realized. By comparing with other liver fibrosis indexes APRI, FIB-4 and M2BPGi, it is found that the diagnostic efficiency of RRM2 is high, and the fibrosis staging diagnosis of hepatitis B patients with / without normal ALT can be realized. The detection technology established by the application can be used for judging the liver fibrosis course of hepatitis B patients. In addition, the diagnostic marker disclosed by the application can be used for preparing reagents or kits for diagnosing liver fibrosis of hepatitis B patients or monitoring the progress of liver fibrosis of hepatitis B patients, and can be used for preparing antiviral drugs.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of biotechnology and medicine, in particular to a diagnostic marker for liver fibrosis in hepatitis B patients and uses thereof. BACKGROUND

[0002] It is well known that hepatitis B virus (HBV)-induced liver disease is one of the main sources of immune liver disease. In addition, chronic hepatitis B contributes to the development of immune-mediated liver injury, leading to progressive liver fibrosis or cirrhosis. Apparently, hepatitis B patients have a relatively high risk of developing hepatocellular carcinoma. HBV is a partially double-stranded DNA virus that infects hepatocytes and replicates in the nucleus. In hepatitis B patients, HBV clearance and liver damage are mainly induced by adaptive immune response. ALT activity is an important reference index for treatment selection and prognosis evaluation of hepatitis B patients. However, the level of serum ALT is not always consistent with the state of liver damage. 37% of hepatitis B patients with normal ALT have significant fibrosis and inflammation. At present, many hepatitis B patients with normal ALT often miss the best opportunity for antiviral treatment in routine examination. Therefore, it is urgent to find new and promising biomarkers.

[0003] Traditional liver fibrosis staging tests mainly rely on pathological histology, serum markers and imaging methods for detection, but the gold standard is still liver histopathology by liver biopsy. Although the traditional pathological examination has a certain accuracy, it is an invasive method, which brings many inconveniences to patients, and even causes complications and sequelae such as bleeding and infection. Compared with pathological examination, the development of serum markers brings convenience to the staging diagnosis of liver fibrosis, and the results are more stable. The wide application of liver damage markers ALT and AST shows the potential of serological markers in liver fibrosis staging. Therefore, it is urgent to explore more effective non-invasive clinical serological markers for monitoring the progress of liver fibrosis.

[0004] Ribonucleotide reductase (RR) is a kind of multi-subunit enzyme, which is a key enzyme for DNA synthesis and repair, and plays a key role in regulating the total rate of DNA synthesis. The active RR complex is composed of multimeric R1 and R2 subunits, which are RRM1 and RRM2, respectively. Studies have found that the increase of RRM2 activity is related to malignant transformation, cancer cell growth, tumor occurrence and HBV DNA replication.

[0005] RRM2 is often expressed in a disease-specific manner, thus having the potential as a biomarker. At present, the correlation of RRM2 in liver fibrosis of hepatitis B patients still needs further research, and exploring the role of RRM2 in the occurrence and development of liver fibrosis in hepatitis B patients helps to excavate new biomarkers for the diagnosis of liver fibrosis in hepatitis B patients or markers for monitoring treatment response, which plays an important role in the diagnosis, treatment and prevention of liver fibrosis in hepatitis B patients. SUMMARY

[0006] The present application aims to provide a diagnostic marker for liver fibrosis in hepatitis B patients and its use. The present application proposes that RRM2 can be used as a diagnostic marker for staging liver fibrosis in hepatitis B patients, and early diagnosis of hepatitis B patients can be achieved by detecting the expression level of RRM2 in the serum of the testee. The diagnostic marker provided by the present application has good specificity and can accurately identify the fibrosis stage of chronic hepatitis B patients with / without normal ALT. The present application has the advantages of reliability and security, and can realize rapid screening of liver fibrosis in chronic hepatitis B patients.

[0007] To solve the above technical problems, the technical scheme provided by the present application is as follows: a diagnostic marker for liver fibrosis in hepatitis B patients, wherein the diagnostic marker is RRM2.

[0008] The diagnostic method of the above-mentioned diagnostic marker for liver fibrosis in hepatitis B patients can realize the staging of liver fibrosis in hepatitis B patients by detecting the expression level of RRM2 in the serum of hepatitis B patients.

[0009] The above-mentioned diagnostic marker for liver fibrosis in hepatitis B patients is used in the preparation of a reagent or kit for diagnosing the staging of liver fibrosis in hepatitis B patients.

[0010] The reagent or kit in the above-mentioned use comprises RRM2.

[0011] The above-mentioned diagnostic marker for liver fibrosis in hepatitis B patients is used in the preparation of a drug for preventing or treating liver fibrosis in chronic hepatitis B patients.

[0012] The above-mentioned use comprises RRM2 in the drug.

[0013] Compared with the prior art, the present application proposes that RRM2 can be used as a diagnostic marker for staging liver fibrosis in hepatitis B patients, and early diagnosis of liver fibrosis in hepatitis B patients can be achieved by detecting the expression level of RRM2 in the serum of the testee. The diagnostic marker provided by the present application has good specificity and can accurately identify the fibrosis stage of chronic hepatitis B patients with / without normal ALT. The diagnostic marker of the present application has high sensitivity, and the standard of detection level is easy to establish. The detection method is simple, the diagnostic efficiency is high, the reliability is guaranteed, and rapid screening of liver fibrosis in chronic hepatitis B patients can be realized. Attached Figure Description

[0014] Figure 1 This is a cluster analysis diagram of immune-related subtypes of hepatitis B patients in Embodiment 1 of the present invention.

[0015] Figure 2 This is a diagram showing the construction results of key modules in the PPI network in Embodiment 2 of the present invention.

[0016] Figure 3 This is the association analysis of the module core gene RRM2 with fibrosis grading and staging in Embodiment 3 of the present invention.

[0017] Figure 4 This is the correlation analysis between serum RRM2 levels and liver fibrosis stages in Example 4 of the present invention.

[0018] Figure 5 This is the correlation analysis result of PD-L1, CTLA4 and LAG3 between the low expression group and the high expression group of RRM2 in Example 6 of the present invention. Detailed Implementation

[0019] The present invention will be further described below with reference to the accompanying drawings and embodiments, but this should not be construed as limiting the present invention.

[0020] Example 1: Cluster analysis of immune-related subtypes in hepatitis B patients.

[0021] The inventors of this application downloaded and analyzed transcriptomic profiles and clinically relevant data of 124 hepatitis B patients (GSE84044) from the GEO database (https: / / www.ncbi.nlm.nih.gov / ). The ssGSEA immune score for each patient was calculated using the "ssGSEA" package and then subjected to hierarchical clustering. Furthermore, the distribution of 29 immune components in immune-related subtypes was analyzed.

[0022] Experimental results are as follows Figure 1 As shown, Figure 1 The results showed that the 124 hepatitis B patients had three different immune states (Immunity_H, Immunity_M and Immunity_L) when assessing immune components, and the levels of 29 immune components in the Immunity_H group were higher than those in the Immunity_L group.

[0023] Example 2: Construction and functional enrichment analysis of key modules in PPI networks.

[0024] The inventors of the present application performed differential expression analysis between immune subtypes using |log fold change (FC)| > 1 and P < 0.05 as criteria. To investigate the interaction between differentially expressed genes, PPI network was generated by STRING database (https: / / string-db.org / ) with the minimum interaction score of 0.900. In Cytoscape software, MCODE plug-in was used to identify key modules.

[0025] The experimental results are shown in Table 2. Figure 2 Figure 2 The results showed that 391 differentially expressed genes were detected, a PPI network containing 181 nodes and 1206 edges was generated, and two key modules were identified.

[0026] Example 3: Correlation analysis of module key gene RRM2 and fibrosis classification and staging.

[0027] According to the staging and classification, the expression level of serum RRM2 in patients of different stages and classifications in GSE84044 was analyzed.

[0028] The experimental results are shown in Table 2. Figure 3 Figure 3 The results showed that RRM2 was positively correlated with fibrosis classification and staging.

[0029] Example 4: Correlation analysis of serum RRM2 and liver fibrosis staging.

[0030] The inventors of the present application collected blood samples from 317, 146 and 179 hepatitis B patients in the First Affiliated Hospital of Wenzhou Medical University (FAHWMU), the Second Affiliated Hospital of Wenzhou Medical University (SAHWMU) and the First Hospital of Zunyi (FPHZ), respectively. All patients underwent liver biopsy and obtained at least 2.0 cm long liver tissue specimens. The research of the present application was approved by the ethics committee of all centers, and all patients signed a written informed consent, all experiments conformed to the principles of the "Helsinki Declaration".

[0031] Among them, the liver specimens obtained by liver biopsy were evaluated for fibrosis staging according to Ishak fibrosis score (F0 represents no fibrosis, F≥3 represents significant fibrosis, and F≥5 represents cirrhosis). The blood samples were centrifuged at 1000g for 20 min in a 4℃ centrifuge, then the upper serum was extracted and stored at -80℃. At the same time, the relevant clinical indicators of hepatitis B patients such as age, gender, BMI, ALT, AST, ALP, PLT and HBV DNA were collected. The relevant clinical characteristics of hepatitis B patients are shown in Table 1:

[0032] ​​

[0033]

[0034] Table 1

[0035] The level of RRM2 in the serum of all hepatitis B patients was quantitatively determined using an enzyme-linked immunosorbent assay (ELISA) kit. The specific experimental steps are as follows:

[0036] (a): Set standard wells and sample wells, and add 50 μL of standard of different concentrations to each standard well;

[0037] (b): Add 50 μL of the sample to be tested to the sample well; no addition to the blank well;

[0038] (c): Add 100 μL of horseradish peroxidase (HRP)-labeled detection antibody to each well of the standard well and the sample well except the blank well, seal the reaction well with a sealing film, and incubate in a 37°C water bath or incubator for 60 min;

[0039] (d): Discard the liquid and pat dry on a blotting paper, fill each well with washing solution (350 μL), stand for 1 min, shake off the washing solution, and pat dry on a blotting paper. Repeat the plate washing for 5 times (or use a plate washer to wash the plate);

[0040] (e): Add 50 μL of substrate A and B to each well, and incubate at 37°C for 15 min in the dark;

[0041] (f): Add 50 μL of stop solution to each well, and measure the OD value of each well at 450 nm within 15 min;

[0042] (g): Take the OD value of the measured standard as the abscissa, and the concentration value of the standard as the ordinate, draw a standard curve on the coordinate paper or use related software to obtain a linear regression equation, and substitute the OD value of the sample into the equation to calculate the concentration of the sample;

[0043] (h): Perform correlation analysis between the level of RRM2 and the stage.

[0044] The experimental results are shown in Figure 4 , and Figure 4 The results show that the serum RRM2 level of hepatitis B patients with / without normal ALT gradually increases with the increase of the stage of liver fibrosis.

[0045] Example 5: Diagnostic value of serum RRM2, APRI, FIB-4 and M2BPGi.

[0046] The inventors of the present application quantitatively determined the serum RRM2 and M2BPGi levels of hepatitis B patients with / without normal ALT using an enzyme-linked immunosorbent assay (ELISA) kit, and the experimental steps are as described in Example 4 above. The calculation formula of the score of APRI and FIB-4 is as follows:

[0047] APRI = (AST / upper limit of normal / PLT count (10 9 / l)) x 100;

[0048] FIB-4 = (age x AST) / (PLT count (10 9 / l) x ALT 1 / 2 ).

[0049] The diagnostic values of serum RRM2, APRI, FIB-4 and M2BPGi were evaluated by using receiver operating characteristic (ROC) curve analysis.

[0050] The diagnostic values of serum RRM2, APRI, FIB-4 and M2BPGi are shown in Table 2:

[0051]

[0052]

[0053] Table 2

[0054] As can be seen from Table 2, in the First Affiliated Hospital of Wenzhou Medical University, the Second Affiliated Hospital of Wenzhou Medical University and the First Hospital of Zunyi, there is a higher AUC value in serum RRM2 compared with APRI, FIB-4 and M2BPGi, i.e. it can better diagnose the liver fibrosis staging stage of hepatitis B patients.

[0055] Example 6: Correlation analysis of immune checkpoints between RRM2 low expression group and high expression group.

[0056] The present inventors divided into low-risk group and high-risk group according to the median value of serum RRM2 in each cohort. Then, PD-L1, CTLA4 and LAG3 in each group were detected by PCR technology. The specific steps are as follows:

[0057] The RNA of PD-L1, CTLA4 and LAG3 in serum was extracted using the Trizol kit of Thermo company, and the concentration of extracted RNA was determined using a nucleic acid quantifier, and the ratio of A260 / 280 was required to be between 1.8-2.0. Then the cDNA was synthesized using the RevertAid First Strand cDNA Synthesis Kit reverse transcription kit of Thermo company.

[0058] The FASTA sequence of PD-L1 is as follows:

[0059] > NM_001267706.2 Homo sapiens CD274 molecule (CD274), transcript variant 2, mRNA.

[0060] AGTTCTGCGCAGCTTCCCGAGGCTCCGCACCAGCCGCGCTTCTGTCCGCCTGCAGGGCATTCCAGAAAGA

[0061] TGAGGATATTTGCTGTCTTTATATTCATGACCTACTGGCATTTGCTGAACGCCCCATACAACAAAATCAA

[0062] CCAAAGAATTTTGGTTGTGGATCCAGTCACCTCTGAACATGAACTGACATGTCAGGCTGAGGGCTACCCC

[0063] AAGGCCGAAGTCATCTGGACAAGCAGTGACCATCAAGTCCTGAGTGGTAAGACCACCACCACCAATTCCA

[0064] AGAGAGAGGAGAAGCTTTTCAATGTGACCAGCACACTGAGAATCAACACAACAACTAATGAGATTTTCTA

[0065] CTGCACTTTTAGGAGATTAGATCCTGAGGAAAACCATACAGCTGAATTGGTCATCCCAGAACTACCTCTG

[0066] GCACATCCTCCAAATGAAAGGACTCACTTGGTAATTCTGGGAGCCATCTTATTATGCCTTGGTGTAGCAC

[0067] TGACATTCATCTTCCGTTTAAGAAAAGGGAGAATGATGGATGTGAAAAAATGTGGCATCCAAGATACAAA

[0068] CTCAAAGAAGCAAAGTGATACACATTTGGAGGAGACGTAATCCAGCATTGGAACTTCTGATCTTCAAGCA

[0069] GGGATTCTCAACCTGTGGTTTAGGGGTTCATCGGGGCTGAGCGTGACAAGAGGAAGGAATGGGCCCGTGG

[0070] GATGCAGGCA ATGTGGGACT TAAAAGGCCC AAGCACTGAA AATGGAACCT GGCGAAAGCA GAGGAGGAGA

[0071] ATGAAGAAAG ATGGAGTCAA ACAGGGAGCC TGGAGGGAGA CCTTGATACT TTCAAATGCC TGAGGGGCTC

[0072] ATCGACGCCT GTGACAGGGA GAAAGGATAC TTCTGAACAA GGAGCCTCCA AGCAAATCAT CCATTGCTCA

[0073] TCCTAGGAAG ACGGGTTGAG AATCCCTAAT TTGAGGGTCA GTTCCTGCAG AAGTGCCCTT TGCCTCCACT

[0074] CAATGCCTCA ATTTGTTTTCT GCATGACTGA GAGTCTCAGT GTTGGAACGG GACAGTATTT ATGTATGAG

[0075] TTTTTCCTAT TTATTTTGAG TCTGTGAGGT CTTCTTGTCAT GTGAGTGTGG TTGTGAATGA TTTCTTTTG

[0076] AAGATATATT GTAGTAGATG TTACAATTTT GTCGCCAAAC TAAACTTGCT GCTTAATGAT TTGCTCACAT

[0077] CTAGTAAAAC ATGGAGTATT TGTAAGGTGC TTGGTCTCCT CTATAACTAC AAGTATACAT TGGAAGCATA

[0078] AAGATCAAAC CGTTGGTTGC ATAGGATGTC ACCTTTATTT AACCCATTA ATACTCTGGT TGACCTAATC

[0079] TATTCTCAGA CCTCAAGTGT CTGTGCAGTA CTGTTCCATT TAAATATCAG CTTTACAATT ATGTGGTAG

[0080] CCTACACACATAATCTCATTTCATCGCTGTAACCACCCTGTTGTGATAACCACTATTATTTTACCCATCG

[0081] TACAGCTGAGGAAGCAAACAGATTAAGTAACTTGCCCAAACCAGTAAATAGCAGACCTCAGACTGCCACC

[0082] CACTGTCCTTTTATAATACAATTTACAGCTATATTTTACTTTAAGCAATTCTTTTATTCAAAAACCATTT

[0083] ATTAAGTGCCCTTGCAATATCAATCGCTGTGCCAGGCATTGAATCTACAGATGTGAGCAAGACAAAGTAC

[0084] CTGTCCTCAAGGAGCTCATAGTATAATGAGGAGATTAACAAGAAAATGTATTATTACAATTTAGTCCAGT

[0085] GTCATAGCATAAGGATGATGCGAGGGGAAAACCCGAGCAGTGTTGCCAAGAGGAGGAAATAGGCCAATGT

[0086] GGTCTGGGACGGTTGGATATACTTAAACATCTTAATAATCAGAGTAATTTTCATTTACAAAGAGAGGTCG

[0087] GTACTTAAAATAACCCTGAAAAATAACACTGGAATTCCTTTTCTAGCATTATATTTATTCCTGATTTGCC

[0088] TTTGCCATATAATCTAATGCTTGTTTATATAGTGTCTGGTATTGTTTAACAGTTCTGTCTTTTCTATTTA

[0089] AATGCCACTAAATTTTAAATTCATACCTTTCCATGATTCAAAATTCAAAAGATCCCATGGGAGATGGTTG

[0090] GAAAATCTCCACTTCATCCTCCAAGCCATTCAAGTTTCCTTTCCAGAAGCAACTGCTACTGCCTTTCATT

[0091] CATATGTTCTTCTAAAGATAGTCTACATTTGGAAATGTATGTTAAAAGCACGTATTTTTAAAATTTTTTT

[0092] CCTAAATAGTAACACATTGTATGTCTGCTGTGTACTTTGCTATTTTTATTTATTTTAGTGTTTCTTATAT

[0093] AGCAGATGGAATGAATTTGAAGTTCCCAGGGCTGAGGATCCATGCCTTCTTTGTTTCTAAGTTATCTTTC

[0094] CCATAGCTTTTCATTATCTTTCATATGATCCAGTATATGTTAAATATGTCCTACATATACATTTAGACAA

[0095] CCACCATTTGTTAAGTATTTGCTCTAGGACAGAGTTTGGATTTGTTTATGTTTGCTCAAAAGGAGACCCA

[0096] TGGGCTCTCCAGGGTGCACTGAGTCAATCTAGTCCTAAAAAGCAATCTTATTATTAACTCTGTATGACAG

[0097] AATCATGTCTGGAACTTTTGTTTTCTGCTTTCTGTCAAGTATAAACTTCACTTTGATGCTGTACTTGCAA

[0098] AATCACATTTTCTTTCTGGAAATTCCGGCAGTGTACCTTGACTGCTAGCTACCCTGTGCCAGAAAAGCCT

[0099] CATTCGTTGTGCTTGAACCCTTGAATGCCACCAGCTGTCATCACTACACAGCCCTCCTAAGAGGCTTCCT

[0100] GGAGGTTTCGAGATTCAGATGCCCTGGGAGATCCCAGAGTTTCCTTTCCCTCTTGGCCATATTCTGGTGT

[0101] CAATGACAAGGAGTACCTTGGCTTTGCCACATGTCAAGGCTGAAGAAACAGTGTCTCCAACAGAGCTCCT

[0102] TGTGTTATCTGTTTGTACATGTGCATTTGTACAGTAATTGGTGTGACAGTGTTCTTTGTGTGAATTACAG

[0103] GCAAGAATTGTGGCTGAGCAAGGCACATAGTCTACTCAGTCTATTCCTAAGTCCTAACTCCTCCTTGTGG

[0104] TGTTGGATTTGTAAGGCACTTTATCCCTTTTGTCTCATGTTTCATCGTAAATGGCATAGGCAGAGATGAT

[0105] ACCTAATTCTGCATTTGATTGTCACTTTTTGTACCTGCATTAATTTAATAAAATATTCTTATTTATTTTG

[0106] TTACTTGGTACACCAGCATGTCCATTTTCTTGTTTATTTTGTGTTTAATAAAATGTTCAGTTTAACATCC

[0107] CA

[0108] The FASTA sequence for CTLA4 is as follows:

[0109] > NM_001037631.3 Homo sapiens cytotoxic T-lymphocyte-associated protein 4 (CTLA4), transcript variant 2, mRNA.

[0110] GCTTTCTATTCAAGTGCCTTCTGTGTGTGCACATGTGTAATACATATCTGGGATCAAAGCTATCTATATA

[0111] AAGTCCTTGATTCTGTGTGGGTTCAAACACATTTCAAAGCTTCAGGATCCTGAAAGGTTTTGCTCTACTT

[0112] CCTGAAGACCTGAACACCGCTCCCATAAAGCCATGGCTTGCCTTGGATTTCAGCGGCACAAGGCTCAGCT

[0113] GAACCTGGCTACCAGGACCTGGCCCTGCACTCTCCTGTTTTTTCTTCTCTTCATCCCTGTCTTCTGCAAA

[0114] GCAATGCACGTGGCCCAGCCTGCTGTGGTACTGGCCAGCAGCCGAGGCATCGCCAGCTTTGTGTGTGAGT

[0115] ATGCATCTCCAGGCAAAGCCACTGAGGTCCGGGTGACAGTGCTTCGGCAGGCTGACAGCCAGGTGACTGA

[0116] AGTCTGTGCGGCAACCTACATGATGGGGAATGAGTTGACCTTCCTAGATGATTCCATCTGCACGGGCACC

[0117] TCCAGTGGAAATCAAGTGAACCTCACTATCCAAGGACTGAGGGCCATGGACACGGGACTCTACATCTGCA

[0118] AGGTGGAGCTCATGTACCCACCGCCATACTACCTGGGCATAGGCAACGGAACCCAGATTTATGTAATTGC

[0119] TAAAGAAAAGAAGCCCTCTTACAACAGGGGTCTATGTGAAAATGCCCCCAACAGAGCCAGAATGTGAAAA

[0120] GCAATTTCAGCCTTATTTTATTCCCATCAATTGAGAAACCATTATGAAGAAGAGAGTCCATATTTCAATT

[0121] TCCAAGAGCTGAGGCAATTCTAACTTTTTTGCTATCCAGCTATTTTTATTTGTTTGTGCATTTGGGGGGA

[0122] ATTCATCTCTCTTTAATATAAAGTTGGATGCGGAACCCAAATTACGTGTACTACAATTTAAAGCAAAGGA

[0123] GTAGAAAGACAGAGCTGGGATGTTTCTGTCACATCAGCTCCACTTTCAGTGAAAGCATCACTTGGGATTA

[0124] ATATGGGGATGCAGCATTATGATGTGGGTCAAGGAATTAAGTTAGGGAATGGCACAGCCCAAAGAAGGAA

[0125] AAGGCAGGGAGCGAGGGAGAAGACTATATTGTACACACCTTATATTTACGTATGAGACGTTTATAGCCGA

[0126] AATGATCTTTTCAAGTTAAATTTTATGCCTTTTATTTCTTAAACAAATGTATGATTACATCAAGGCTTCA

[0127] AAAATACTCACATGGCTATGTTTTAGCCAGTGATGCTAAAGGTTGTATTGCATATATACATATATATATA

[0128] TATATATATATATATATATATATATATATATATATATATATATATTTTAATTTGATAGTATTGTGCATAG

[0129] AGCCACGTATGTTTTTGTGTATTTGTTAATGGTTTGAATATAAACACTATATGGCAGTGTCTTTCCACCT

[0130] TGGGTCCCAGGGAAGTTTTGTGGAGGAGCTCAGGACACTAATACACCAGGTAGAACACAAGGTCATTTGC

[0131] TAACTAGCTTGGAAACTGGATGAGGTCATAGCAGTGCTTGATTGCGTGGAATTGTGCTGAGTTGGTGTTG

[0132] ACATGTGCTTTGGGGCTTTTACACCAGTTCCTTTCAATGGTTTGCAAGGAAGCCACAGCTGGTGGTATCT

[0133] GAGTTGACTTGACAGAACACTGTCTTGAAGACAATGGCTTACTCCAGGAGACCCACAGGTATGACCTTCT

[0134] AGGAAGCTCCAGTTCGATGGGCCCAATTCTTACAAACATGTGGTTAATGCCATGGACAGAAGAAGGCAGC

[0135] AGGTGGCAGAATGGGGTGCATGAAGGTTTCTGAAAATTAACACTGCTTGTGTTTTTAACTCAATATTTTC

[0136] CATGAAAATGCAACAACATGTATAATATTTTTAATTAAATAAAAATCTGTGGTGGTCGTTTTCCGGA

[0137] The FASTA sequence for LAG3 is as follows:

[0138] > NM_001414176.1 Homo sapiens Lymphocyte-activating 3 (LAG3), transcript variant 2, mRNA.

[0139] AGAGACCAGCAGAACGGCATCCCAGCCACGACGGCCACTTTGCTCTGTCTGCTCTCCGCCACGGCCCTGC

[0140] TCTGTTCCCTGGGACACCCCCGCCCCCACCTCCTCAGGCTGCCTGATCTGCCCAGCTTTCCAGCTTTCCT

[0141] CTGGATTCCGGCCTCTGGTCATCCCTCCCCACCCTCTCTCCAAGGCCCTCTCCTGGTCTCCCTTCTTCTA

[0142] GAACCCCTTCCTCCACCTCCCTCTCTGCAGAACTTCTCCTTTACCCCCCACCCCCCACCACTGCCCCCTT

[0143] TCCTTTTCTGACCTCCTTTTGGAGGGCTCAGCGCTGCCCAGACCATAGGAGAGATGTGGGAGGCTCAGTT

[0144] CCTGGGCTTGCTGTTTCTGCAGCCGCTTTGGGTGGCTCCAGTGAAGCCTCTCCAGCCAGGGGCTGAGGTC

[0145] CCGGTGGTGTGGGCCCAGGAGGGGGCTCCTGCCCAGCTCCCCTGCAGCCCCACAATCCCCCTCCAGGATC

[0146] TCAGCCTTCTGCGAAGAGCAGGGGTCACTTGGCAGCATCAGCCAGACAGTGGCCCGCCCGCTGCCGCCCC

[0147] CGGCCATCCCCTGGCCCCCGGCCCTCACCCGGCGGCGCCCTCCTCCTGGGGGCCCAGGCCCCGCCGCTAC

[0148] ACGGTGCTGAGCGTGGGTCCCGGAGGCCTGCGCAGCGGGAGGCTGCCCCTGCAGCCCCGCGTCCAGCTGG

[0149] ATGAGCGCGGCCGGCAGCGCGGGGACTTCTCGCTATGGCTGCGCCCAGCCCGGCGCGCGGACGCCGGCGA

[0150] GTACCGCGCCGCGGTGCACCTCAGGGACCGCGCCCTCTCCTGCCGCCTCCGTCTGCGCCTGGGCCAGGCC

[0151] TCGATGACTGCCAGCCCCCCAGGATCTCTCAGAGCCTCCGACTGGGTCATTTTGAACTGCTCCTTCAGCC

[0152] GCCCTGACCGCCCAGCCTCTGTGCATTGGTTCCGGAACCGGGGCCAGGGCCGAGTCCCTGTCCGGGAGTC

[0153] CCCCCATCACCACTTAGCGGAAAGCTTCCTCTTCCTGCCCCAAGTCAGCCCCATGGACTCTGGGCCCTGG

[0154] GGCTGCATCCTCACCTACAGAGATGGCTTCAACGTCTCCATCATGTATAACCTCACTGTTCTGGGTCTGG

[0155] AGCCCCCAACTCCCTTGACAGTGTACGCTGGAGCAGGTTCCAGGGTGGGGCTGCCCTGCCGCCTGCCTGC

[0156] TGGTGTGGGGACCCGGTCTTTCCTCACTGCCAAGTGGACTCCTCCTGGGGGAGGCCCTGACCTCCTGGTG

[0157] ACTGGAGACAATGGCGACTTTACCCTTCGACTAGAGGATGTGAGCCAGGCCCAGGCTGGGACCTACACCT

[0158] GCCATATCCATCTGCAGGAACAGCAGCTCAATGCCACTGTCACATTGGCAATCATCACAGTGACTCCCAA

[0159] ATCCTTTGGGTCACCTGGATCCCTGGGGAAGCTGCTTTGTGAGGTGACTCCAGTATCTGGACAAGAACGC

[0160] TTTGTGTGGAGCTCTCTGGACACCCCATCCCAGAGGAGTTTCTCAGGACCTTGGCTGGAGGCACAGGAGG

[0161] CCCAGCTCCTTTCCCAGCCTTGGCAATGCCAGCTGTACCAGGGGGAGAGGCTTCTTGGAGCAGCAGTGTA

[0162] CTTCACAGAGCTGTCTAGCCCAGGTGCCCAACGCTCTGGGAGAGCCCCAGGTGCCCTCCCAGCAGGCCAC

[0163] CTCCTGCTGTTTCTCATCCTTGGTGTCCTTTCTCTGCTCCTTTTGGTGACTGGAGCCTTTGGCTTTCACC

[0164] TTTGGAGAAGACAGGTGAGCCAGGGACATGGCAACCCCGCCCCCCAGCAGCTCCCGCTCTTCCATCCTCA

[0165] GAGTGCTGATGGCACCCCTTCCTCAGGAAGTGGCGACCAAGACGATTTTCTGCCTTAGAGCAAGGGATTC

[0166] ACCCTCCGCAGGCTCAGAGCAAGATAGAGGAGCTGGAGCAAGAACCGGAGCCGGAGCCGGAGCCGGAACC

[0167] GGAGCCCGAGCCCGAGCCCGAGCCGGAGCAGCTCTGACCTGGAGCTGAGGCAGCCAGCAGATCTCAGCAG

[0168] CCCAGTCCAAATAAACTCCCTGTCAGCAGCAA

[0169] SYBR Green method was used for real-time fluorescent quantitative PCR detection, GAPDH was used as an internal reference gene, and RT-PCR primers specific to PD-L1, CTLA4 and LAG3 were used for real-time fluorescent quantitative PCR to obtain the relative expression of PD-L1, CTLA4 and LAG3.

[0170] The RT-PCR forward primer sequence of PD-L1 (F: CATTTGCTGAACGCCCCATA) and

[0171] the reverse primer sequence (R: TGTCCAGATGACTTCGGCCT).

[0172] The RT-PCR forward primer sequence of CTLA4 (F: CCATGGACACGGGACTCTAC) and

[0173] the reverse primer sequence (R: GGGCTTCTTTTCTTTAGCAATTACA).

[0174] The RT-PCR forward primer sequence of LAG3 (F: CAGCTCCCGCTCTTCCATC) and

[0175] Reverse primer sequence (R:AATCGTCTTGGTCGCCACTTC).

[0176] GAPDH forward primer sequence (F: GCTAGGGACGGCCTGAAG) and

[0177] Reverse primer sequence (R:GCCCAATACGACCAAATCCGT).

[0178] The real-time quantitative PCR system consisted of 10 μl of SYBR Green Realtime PCR Master Mix, 0.5 μl of forward primer (10 μM), 0.5 μl of reverse primer (10 μM), 1 μl of cDNA, and ddH2O added to a final volume of 20 μl.

[0179] The reaction system prepared according to the above system was placed in a 7500 Fast quantitative PCR System for PCR reaction, and the procedure is shown in Table 3 below:

[0180]

[0181] Table 3

[0182] Analysis of Real-time-PCR Experimental Results: Analysis was performed using the software included with the 7500Fast quantitative PCR System. Results are expressed as Mean ± SD. GraphpadPrism software was used to analyze the differences between different sample data and plot the results (Student's T-test was used for statistical analysis of differences between the two groups; P < 0.05 was considered statistically significant).

[0183] Experimental results are as follows Figure 5 As shown, Figure 5 The results indicate that hepatitis B patients with higher RRM2 levels are associated with higher levels of immune checkpoints (PD-L1, CTLA4, and LAG3), suggesting that CHB patients with higher RRM2 levels may benefit from immunotherapy.

[0184] The results of the above embodiments demonstrate that, based on bioinformatics analysis, this invention has identified the key diagnostic biomarker RRM2 for liver fibrosis. By detecting the expression level of RRM2 in the serum of test subjects, the diagnosis of fibrosis staging in hepatitis B patients can be achieved. Compared with other liver fibrosis markers such as APRI, FIB-4, and M2BPGi, RRM2 shows high diagnostic efficiency and can achieve fibrosis staging diagnosis in hepatitis B patients with / without normal ALT levels.

[0185] In summary, the present application takes RRM2 as a diagnostic marker for liver fibrosis staging of hepatitis B patients, and realizes early diagnosis of hepatitis B patients by detecting the expression level of RRM2 in serum of the to-be-tested person. The diagnostic marker provided by the present application has good specificity, and can accurately identify the fibrosis staging of hepatitis B patients with / without normal ALT. The diagnostic marker of the present application has high sensitivity, and the standard of detection level is easy to establish. The detection method is simple, the diagnostic efficiency is high, the reliability is guaranteed, and the rapid screening of liver fibrosis of hepatitis B patients can be realized. The detection technology established by the present application can be used for judging the course of liver fibrosis of hepatitis B patients. In addition, the diagnostic marker disclosed by the present application can be prepared into a reagent or kit for diagnosing liver fibrosis of hepatitis B patients or monitoring the progress of liver fibrosis of hepatitis B patients, and can be prepared into an antiviral drug.

Claims

1. The application of diagnostic markers for liver fibrosis in hepatitis B patients in the preparation of a kit for differentiating the stages of liver fibrosis in hepatitis B patients, characterized in that: The diagnostic marker is RRM2; the kit identifies the stage of liver fibrosis in hepatitis B patients by detecting the expression level of RRM2 in their serum.

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