CN111778355A - TCR sequence marker for hepatitis B virus infection and application thereof - Google Patents

Abstract

The invention relates to a TCR sequence marker for hepatitis B virus infection and application thereof, belonging to the technical field of medicines. The marker includes: a specific amino acid marker selected from the group consisting of: SEQ ID No.1 to SEQ ID No. 39; wherein the amino acid markers associated with good prognosis are selected from: SEQ ID No.1 to SEQ ID No.20, the amino acid markers associated with poor prognosis being selected from the group consisting of: SEQ ID No.21 to SEQ ID No. 38. The marker can acquire the curative effect of the patient in the starting treatment (0 week) and the treatment period (12 weeks and 48 weeks) of the hepatitis B, serve as a novel biomarker for judging the curative effect, pathological changes and prognosis, and also can provide an amino acid sequence of a targeted T cell receptor for the liver disease immunotherapy to promote the precision of the immunotherapy.

Description

TCR sequence marker for hepatitis B virus infection and application thereof

Technical Field

The invention relates to the technical field of biomedicine, in particular to a TCR sequence marker for hepatitis B virus infection and application thereof.

Background

Liver diseases seriously threaten human health, China is a country with high incidence of liver diseases, and the world is more than 1/3 liver disease patients in China; among them, viral hepatitis b (hepatitis b) is the most serious health and hygiene problem, and currently, there are more than 2.4 billion hepatitis b patients worldwide, and complications related to liver diseases can cause about 65 million people to die of liver cirrhosis, liver failure and hepatocellular carcinoma every year, causing a heavy burden to families and society. In 2016, the world health organization has issued a message that 1000 thousands of people in China die of liver diseases by 2030 if necessary measures are not taken to increase the treatment accessibility and improve the curative effect, so that the treatment of liver diseases, especially the treatment of hepatitis B, is highly urgent. Research has confirmed that maximal long-term inhibition of Hepatitis B Virus (HBV) is a key to treatment of chronic hepatitis B and is also a common requirement in the world, including the United states, Europe and Chinese guidelines for prevention and treatment. The first-line antiviral drugs for hepatitis B treatment at present comprise Entecavir (Entecavir, ETV) and Tenofovir Disoproxil Fumarate (TDF), one of the important indexes for evaluating the treatment curative effect is whether HBV E antigen (HBeAg) can turn negative in the treatment process, and is also a milestone for disease control and closely related to the disease progression and the survival rate of patients; therefore, how to achieve the effect of turning HBeAg negative is the key to the curative effect of hepatitis B and the clinical outcome of patients. The core theory of hepatitis B is that the pathological process of the occurrence and development of liver diseases is represented by the action of human body on the immune response of viruses, and if the immune response is good, the disease condition is effectively controlled, and conversely, the disease progresses. T lymphocytes are main cells forming human immune response, and the good T cell immune response plays a role in clearing viruses; many studies suggest that whether T cell responses are closely related to liver disease progression; however, dynamic studies on T cell immune responses in liver disease treatment, particularly in those using first-line antiviral drugs such as entecavir, have been rare to date.

During immune response of diseases, T lymphocytes cannot directly recognize antigens, but can only recognize antigen peptides on cell surfaces through specific T Cell Receptors (TCR) on cell surfaces, and bind to MHC molecules to express antigen peptides on cell surfaces, and TCRs in humans are classified into α chains and β chains according to their peptide chain composition, and have two domains: near the amino terminus (N-terminus) of the peptide chain, which varies widely and is called the variable region (V-region), in which there are three complementarity determining regions (CR1, CR2, CR 3); the part other than the V region is located at the carboxyl terminal (C-terminal) of the peptide chain and is a constant region. The diversity of TCR concentrates on the research of TCR beta chain CR3(TRB CDR3), the length of TRB CDR3 is 12-16 amino acids, and the TRB CDR3 is composed of V gene segments, D gene segments and J gene segments, and CDR3 shows high polymorphism through the random combination of the V-D-J gene segments, thereby fully reflecting the diversity of TCR libraries. The diversity of the TCR library is mainly derived from the diversity of combination and the diversity of connection, each T cell surface can only express an antigen receptor, and in immune response, T cells recognize antigens through TCR and are activated and proliferated, so that a group of T cell clones with identical TCR structures are generated, and the effects of eliminating pathogens and controlling disease progression are achieved.

In the research, we tried to obtain a novel biomarker which can prompt the judgment, pathological change or prognosis of the subsequent curative effect by analyzing the different physiological and pathological response functions of the different TCRs in the treatment.

Disclosure of Invention

In view of the above, it is necessary to provide a TCR sequence marker for hepatitis b virus infection, which can be used to obtain the therapeutic effect of the patient during the initiation of treatment of chronic hepatitis b (0 week) and during the treatment period (12 weeks and 48 weeks), and can be used as a novel biomarker for determining the therapeutic effect, pathological changes and prognosis, and can also provide the targeted amino acid sequence of T cell receptor for the immunotherapy of liver diseases, thereby promoting the accuracy of immunotherapy.

A TCR sequence marker for hepatitis b virus infection comprising: a specific amino acid marker selected from the group consisting of: SEQ ID No.1 to SEQ ID No. 39; wherein the amino acid markers associated with good prognosis are selected from: SEQ ID No.1 to SEQ ID No.20, the amino acid markers associated with poor prognosis being selected from the group consisting of: SEQ ID No.21 to SEQ ID No. 38.

In one embodiment, the amino acid markers that correlate well with prognosis are: SEQ ID No.2, SEQ ID No.3 and SEQ ID No. 8; amino acid markers associated with poor prognosis are: SEQ ID No.21, SEQ ID No.24, SEQ ID No.27 and SEQ ID No. 28.

In one embodiment, the markers further comprise gene segment markers selected from the group consisting of: the high expression of the gene fragment marker is related to good prognosis of the TRBJ2-5 gene of a CD4+ T cell receptor and/or the TRBJ2-1 gene of a CD8+ T cell receptor.

The invention also discloses application of the TCR sequence marker for hepatitis B virus infection in preparing a reagent for accurately treating hepatitis B.

In one embodiment, the treatment is with the first line therapy for hepatitis b, entecavir.

The invention also discloses a system for hepatitis B prognosis evaluation, which comprises:

a data acquisition module: obtaining the content information of the TCR sequence marker in the biological sample;

a data analysis module: comparing the content of the marker with a preset rule, and analyzing;

a result output module: and outputting the result of the hepatitis B prognosis evaluation according to the analysis result.

In one embodiment, the biological sample comprises: peripheral blood samples and/or liver tissue samples.

In one embodiment, the system further comprises a data detection module, wherein the data detection module performs detection according to the following procedures:

1) RNA extraction: taking a biological sample, and extracting RNA in T cells;

2) and (3) cDNA synthesis: synthesizing cDNA from the RNA obtained above;

3) library construction: constructing a TCR library by adopting the cDNA;

4) high-throughput sequencing: performing high-throughput sequencing on the obtained TCR library;

5) data interpretation: analyzing off-line data obtained by high-throughput sequencing by a bioinformatics method, and comparing the off-line data with a database to obtain data information corresponding to the marker of any one of claims 1 to 3.

In one embodiment, in the step 2) cDNA synthesis, the primer sequence of SEQ ID No.39 is used for amplification;

in the step 3) library construction, the primer pair of SEQ ID No.40-41 is used for first round nested PCR amplification, and the primer pair of SEQ ID No.42-43 is used for second round nested PCR amplification.

In one embodiment, in the data analysis module, the preset rule is: amino acid markers that correlate well with prognosis are selected from: SEQ ID No.1 to SEQ ID No. 20; amino acid markers associated with poor prognosis are selected from: SEQ ID No.21 to SEQ ID No. 38; the high expression gene segment markers related to good prognosis are selected from: the TRBJ2-5 gene of a CD4+ T cell receptor and/or the TRBJ2-1 gene of a CD8+ T cell receptor;

the result output module also comprises a guide for adjusting the treatment scheme according to the prognosis evaluation result.

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

the TCR sequence marker for hepatitis B virus infection can acquire the curative effect of treatment of patients when hepatitis B starts treatment (0 week) and during treatment (12 weeks and 48 weeks), serve as a novel biomarker for judging curative effect, pathological change and prognosis, can also provide targeted amino acid sequences of T cell receptors for liver disease immunotherapy, and promotes the accuracy of the immunotherapy.

The marker disclosed by the invention can be used for providing effective information such as pre-treatment evaluation, curative effect evaluation, medication adjustment guide, prognosis evaluation and the like for the precise treatment of the hepatitis B through the analysis of the marker.

The system for the prognosis evaluation of hepatitis B of the invention takes the marker as an analysis object, and can provide effective information such as pre-treatment evaluation, curative effect evaluation, medication adjustment guide, prognosis evaluation and the like for the precise treatment of hepatitis B.

Drawings

FIG. 1 shows CD4⁺T cell, CD8⁺T cell, CD19⁺The cell gating method and flow cytometry represent schematic diagrams.

FIG. 2 shows CD4 in two groups, CR and NCR⁺T cells and CD8⁺T cell surface receptor CDR3 clone frequency distribution and its variation over the course of treatment.

FIG. 3 is a frequency of use thermogram of V.beta.and J.beta.gene fragments on surface receptors of CD4+ T cells and CD8+ T cells in the CR and NCR groups.

FIG. 4 is a graph of CD4 in the CR and NCR groups at each time point during treatment⁺T cells and CD8⁺The T cell expression J β gene fragment level has a significant difference diagram.

FIG. 5 is a graph of CD4 in the CR and NCR groups at each time point during treatment⁺Number of new clones of T cell receptor.

FIG. 6 shows CD4 in the CR and NCR groups⁺T cells and CD8⁺A graphical representation of the correlation of T cell surface receptor clone numbers with serum alanine aminotransferase ALT and HBVDNA levels.

Detailed Description

To facilitate an understanding of the invention, the invention will now be described more fully with reference to the accompanying drawings. Preferred embodiments of the present invention are shown in the drawings. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.

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 terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.

The reagents used in the following examples are all commercially available unless otherwise specified.

Examples

Firstly, a sample source.

60 patients with chronic hepatitis B treated by using an antiviral first-line medicament ETV in a Hospital, Guangzhou are collected, and peripheral blood is reserved when the treatment is started, namely peripheral blood at 0 week, 12 weeks and 48 weeks; and matched liver puncture tissue specimens were retained from the patients, including 0 week and 48 week liver tissues.

The above 60 patients with chronic hepatitis B treated with first-line antiviral drug (entecavir, ETV) were grouped, and the patients who reached HBeAg turning negative at 48 weeks were effective T cell immune response group (CR group), and the patients who did not reach HBeAg turning negative at 48 weeks were ineffective T cell immune response group (NCR group).

II, research method:

1. peripheral Blood Mononuclear Cell (PBMC) isolation:

collecting blood with anticoagulant blood collection tube containing heparin sodium, collecting blood with 60ml fresh blood sample, and separating PBMC according to conventional method, the steps are briefly as follows:

(1) centrifuging: 670g, after centrifuging for 7 minutes at room temperature, the acceleration/deceleration is set to 9;

(2) taking out plasma for subsequent treatment;

(3) diluting: 1:1 configuration using sterile PBS;

(4) adding lymphocyte separation liquid;

(5) density gradient centrifugation: room temperature, 800g, 25 min; acceleration/deceleration is 0;

(6) and (3) white absorbing film: sucking the white membrane into a 50ml centrifuge tube;

(7) centrifuging: room temperature, 1800rpm, 10 minutes; acceleration/deceleration is set to 9;

(8) diluting: adding PBS into the centrifugal precipitate, and slightly blowing, sucking and uniformly mixing;

(9) centrifuging: room temperature, 1800rpm, 10 minutes; acceleration/deceleration is set to 9;

(10) and (6) counting.

2. Antibody labeling and T cell sorting, the steps were as follows:

(1) obtaining viable lymphocytes, each sample containing PBMC (0.1-1 × 10)⁶) After washing with 10% FBS-containing RPMI-1640, dead or dying cells were degraded with DNase to obtain viable lymphA blast cell;

(2) antibody labeling: adding CD4-APC, CD8-FITC and CD8-PE fluorescent antibody into the live lymphocytes in the step (1), placing at 4 ℃ and keeping away from light for labeling for 30-40 minutes;

(3) and (3) computer detection: the antibody-labeled cells of (2) above were subjected to on-line detection and analysis on a BD FACSAria III flow cytometer.

3. RNA extraction in T cells:

(1) weighing and grinding liver tissues: taking 50mg of liver tissue weight of each sample; adding into an enzyme-free 1.5ml EP tube, placing the EP tube on dry ice, and grinding liver tissue into powder;

(2) lymphocyte lysis: respectively adding Trizol lysate into the lymphocytes obtained in the step 3 and the liver tissue powder obtained in the step 4(1) to perform lymphocyte lysis;

(3) RNA precipitation: obtaining white colloidal RNA precipitate by a conventional method, and then cleaning;

(4) RNA lysis and concentration determination: dissolving RNA by using RNase-free water; RNA concentration was determined using a NanoDrop spectrophotometer.

4. And (3) cDNA synthesis:

(1) 5' end cDNA end rapid amplification: adopting a SMARTer PCR cDNA synthesis kit, and operating according to the instruction; the primer sequence is as follows: CAGTATCTGGAGTCATTGA (SEQ ID No. 39).

(2) And (3) PCR amplification system configuration:

5. constructing a TCR library:

(1) nested PCR amplification first round:

(i) the primer sequence is as follows: 5' CACTCTATCCGACAAGCAGTGGTATCAACGCAG (SEQ ID No.40)

3’TGCTTCTGATGGCTCAAACAC(SEQ ID No.41)

(ii) System configuration:

(2) nested PCR amplification second round:

(i) the primer sequence is as follows: 5' CACTCTATCCGACAAGCAGT (SEQ ID No.42)

3’ACACSTTKTTCAGGTCCTC(SEQ ID No.43)

(ii) System configuration:

(3) and (3) glue recovery:

the gel recovery product concentration was measured using a spectrophotometer, operating according to the Qiagen Qiaquick gel extraction kit instructions.

(4) Constructing a sequencing library:

constructing a Library by using a NEBnext μm ultra DNA Library Prep kit for Illumina kit, and operating according to the kit instruction; cutting the target band by about 600 and 700 bp; qiagen Qiaquick gelextraction kit for gel recovery, library products stored at-80 ℃ for use.

6. High-throughput sequencing:

after the quality of the TCR beta ligation library is qualified by a sequencing company, high-throughput sequencing is carried out on an Illumina HiSeq3000 platform, and the readable length is 2x150 bp.

7. Data processing:

(1) original image data obtained by high-throughput sequencing is converted into an original sequencing sequence through base recognition analysis, namely RawReads, and each sample in a TCR beta chain library has a unique label corresponding to a sample of a patient; filtering Raw Reads to obtain Clean Reads, and then performing subsequent data analysis;

(2) uploading the filtered data to miXCR software and an IMGT/High-QUEST database for analysis;

(3) the V, D, J gene segments of all TCR beta chains are identified, and then the CDR3 sequence can be extracted, and the subsequent analysis such as clone identification, calculation and the like is carried out.

8. Statistical analysis:

all statistical analyses were performed using SPSS19.0 software. The normal distribution parameters are expressed by mean ± standard deviation; the non-normal distribution is represented using a median and a quartile; the difference comparison between the CR and the NCR adopts a paired Wilcoxon symbolic rank sum test; counting data by X²A test or Fisher exact probability method. Inspection level alpha 0.05, P<A difference of 0.05 is statistically significant.

And thirdly, obtaining a result.

1. T cell sorting results.

After antibody labeling and T cell sorting, T cells and their subsets CD4+ T cells and CD8+ T cells were successfully sorted from lymphocytes as shown in figure 1. FIG. 1 shows CD4⁺T cell, CD8⁺T cell, CD19⁺Cell gating method and schematic diagram of flow cytometry detection.

Wherein, FIG. 1A shows circled lymphocyte populations; FIG. 1B shows a viable cell population that was harvested after removal of the adhesion body and subsequent labeling of Dead and viable cells with Live/Dead-APC-7; FIG. 1C is a circled CD4⁺T cells and CD8⁺A T cell; FIG. 1D is a circled CD19⁺A cell.

The above results show that the T cell sorting method of the present invention can obtain high purity total T cells and their subpopulations CD4⁺T cells and CD8⁺The T cell is the basis of the invention and also provides technical support for specific immunity related research and diagnosis and treatment.

2. High throughput sequencing results.

(1) Superiority of high-throughput sequencing.

The prior research methods for TCR polymorphism comprise three methods of flow cytometry, immune scanning pattern analysis and PCR combined Sanger sequencing. The flow cytometry technology can analyze the expression of the TCR from the protein level and quantify the expression, but the clonality difference of each family of the TCR cannot be determined, and the monoclonal antibody has high price and limited types, so that the research of the monoclonal antibody in a TCR library has limitation; the immune scanning pattern analysis technology can only research the length polymorphism of CDR3, and cannot reveal the specific sequence and clonotype distribution; PCR coupled with Sanger sequencing although CDR3 length and sequence analysis can be performed, this technique is time consuming, laborious and has a limited number of tests. The project utilizes high-throughput measurement, also called second-generation sequencing and deep sequencing, and can simultaneously sequence hundreds of thousands or even millions of gene molecules at one time, thereby greatly reducing the cost and time required by sequencing; meanwhile, high-throughput sequencing can be performed for deep sequencing, and even the CDR3 sequence with low expression quantity can still be detected.

(2) Number of TCR β of peripheral blood origin.

In this example, the off-line data was obtained by high throughput sequencing, and after data processing and filtering, we obtained 239,784,2144 effective TCR β chain sequences in total, and 11989214 sequences were obtained for each sample on average.

The resulting valid TCR sequences were then subjected to V β and J β gene alignments using the miXCR program to identify and count CDR3 clonotypes (clonotypes refer to the amino acid sequence of each unique TRB CDR3 that occurs in the TCR library, and the nucleotide sequence of the same CDR3 clonotype may not be identical, but the amino acid sequence is identical) on the basis of identifying an acceptable CDR3 region.

Further, we analyzed a total of 1082 and 689 independent VDJ fragments per sample to establish CDR3 sequences on CD4+ T cells and CD8+ T cells, and CDR3 clonotypes assembled from 7675 and 2490 mutually independent proteins, respectively.

(3) Number of tcrp of hepatic tissue origin.

After data processing and filtering, we obtained 17149920 valid TCR β chain sequences in total, 142916 sequences were obtained on average per sample, and 6360VDJ gene fragments were identified using the miXCR program.

(4) Differences in the number of CDR3 clones during treatment between the CR and NCR groups.

At the time of initiation of treatment, the CDR3 clone frequency was comparable between the two groups, with no significant difference.

During the course of treatment, the number of CDRs 3 clones in the effective group (CR group) was gradually decreased, and in the CR group, CD4+ T cells and CD8+ T cells derived from peripheral blood PBMC were present at 12 weeksAnd 48 weeks significantly less TCR CDR3 than the NCR group, and likewise, the number of TCR CDRs 3 of liver tissue-derived CD4+ T cells and CD8+ T cells at 48 weeks in the CR group was significantly less than the NCR group, as shown in fig. 2. FIG. 2 shows CD4 in two groups, CR and NCR⁺T cells and CD8⁺T cell surface receptor CDR3 clone frequency distribution and its variation over the course of treatment.

Wherein, FIG. 2A shows CD4 derived from peripheral blood PBMC⁺Distribution of T cell surface receptor CDR3 clone frequency at 0, 12, 48 weeks, respectively; FIG. 2B is CD8 derived from peripheral blood PBMC⁺Distribution of T cell surface receptor CDR3 clone frequency at 0, 12, 48 weeks, respectively; FIG. 2C shows intrahepatic CD4⁺Distribution of T cell surface receptor CDR3 cloning frequency at 0 weeks, 48 weeks, respectively; FIG. 2D is intrahepatic CD8⁺The T cell surface receptor CDR3 cloning frequency was distributed at 0 weeks and 48 weeks, respectively. Wherein, the data in the effective group and the ineffective group are compared, and P represents<0.001; comparison of data between week 0 and week 12 in the same patient group, # denotes P<0.05; in the same group of patients, 12 weeks were compared with 48 weeks of data, $ denotes P<0.05; in the same group of patients, week 0 was compared to week 48,&represents P<0.05。

The above results suggest that the cellular immune response to treatment is not the same in two groups of patients with different therapeutic effects.

3. Differences in the usage patterns of the V.beta.and J.beta.gene segments between the two groups.

To understand the T cell immune response during treatment in patients in the treatment effective (CR) and ineffective (NCR) groups, especially the pattern of use of V β and J β gene segments in T cell surface receptor TCR, we generated a heat map based on the frequency of use of V β and J β gene segments between the two groups, and the results are shown in fig. 3. FIG. 3 is a frequency of use heat-map of V.beta.and J.beta.gene fragments on surface receptors of CD4+ T cells and CD8+ T cells (B) in the CR and NCR groups.

Wherein, the abscissa is the sample number (CR is the effective group, NCR is the ineffective group), the ordinate is the V beta and J beta gene segments, the state bar on the right side of the hotspot graph shows the use frequency of the gene segments, the color is gradually changed from light color to dark color, and the use frequency of the V beta and J beta gene segments is changed from high to low. The upper panel in fig. 3A is a frequency of use hotspot plot of the V β gene fragment on the CD4+ T cell surface receptor in the CR and NCR groups, with the frequency of use decreasing from 0.3 to 0.05; the lower panel in fig. 3A is a frequency of use hotspot plot of the J β gene fragment on the CD4+ T cell surface receptor in the CR and NCR groups, with the frequency of use decreasing from 0.3 to 0.05. The upper panel in fig. 3B is a frequency of use hotspot plot of the V β gene fragment on the CD8+ T cell surface receptor in the CR and NCR groups, with frequency of use decreasing from 0.5 to 0.1; the lower panel in fig. 3B is a frequency of use hotspot plot of the J β gene fragment on the CD8+ T cell surface receptor in the CR and NCR groups, with the frequency of use decreasing from 0.8 to 0.2.

From the above-described frequency thermogram of VJ gene use, we can find patterns of two groups using different V.beta.and J.beta.genes.

Furthermore, in the use of the J β gene fragment, we found that the frequency of TRBJ2-5 fragment was higher at week 0 of CD4+ T cell receptor than that in NCR group in patients in CR group, that the frequency of TRBJ2-1 fragment was higher at week 0 and week 12 of CD8+ T cell receptor than that in NCR group in patients in CR group, and that the frequency of TRBJ2-4 fragment was lower at week 48 of CD8+ T cell receptor than that in NCR group in patients in CR group, as shown in FIG. 4, FIG. 4 is a graph showing CD4 fragment in CR group and NCR group at each time point during treatment⁺T cells and CD8⁺The T cell expression J β gene fragment level has a significant difference diagram.

4. The patients in CR and NCR groups were cloned with CDR3 amino acid newly during the treatment.

During treatment, the nascent TCR clones suggested a better T cell immune response. We performed dynamic observations of the two groups of patients CR and NCR, and the results are shown in FIG. 5, where FIG. 5 shows CD4 in the CR and NCR groups at each time point during the treatment period⁺Number of new clones of T cell receptor. In the figure, P:<0.05; represents P:<0.001。

the results show that the number of TCR nascent clones in the CR group is obviously higher than that in the NCR group from 0-12 weeks or 48 weeks, and the generation of TCR nascent clones is helpful for improving antiviral immune response and has the expression of good treatment effective prognosis.

5. Correlation of the T cell receptor CDR3 clone with clinical virologic therapy.

Binding of T cell receptor CDR3 clone and clinical virologyThe results of the analysis of the biochemical parameters are shown in FIG. 6, and FIG. 6 shows CD4 in the CR and NCR groups⁺T cells and CD8⁺A graphical representation of the correlation of T cell surface receptor clone numbers with serum alanine aminotransferase ALT and HBVDNA levels.

Wherein FIG. 6A shows CD4 in the CR group of patients⁺T cell clone number is correlated with ALT (upper left) and HBVDNA (upper right), and CR group patient CD8⁺The number of T cell clones correlated with ALT (bottom left) and HBVDNA (bottom right); FIG. 6B shows NCR group patients CD4⁺T cell clone number was independent of ALT (upper left) and HBVDNA (upper right), patient CD8 in NCR group⁺The number of T cell clones was independent of ALT (bottom left) and HBVDNA (bottom right).

The above results show that:

(1) the specific CDR3 clone of the CD4+ T cells of the CR group patients is positively correlated with the change of serum transaminase ALT of the patients in the antiviral treatment process, namely the more CDR3 clones, the faster the ALT is reduced, and the better the liver function is recovered;

(2) the specific CDR3 clone of the CD4+ T cells of the CR group patients is positively correlated with the change of the virus replication level HBVDNA of the patients in the antiviral treatment process, namely, the more CDR3 clones, the faster the HBVDNA is reduced, and the better the antiviral treatment effect is;

(3) the specific CDR3 clone of the CD8+ T cells of the CR group patients is positively correlated with the change of the virus replication level HBVDNA of the patients in the antiviral treatment process, namely, the more CDR3 clones, the faster the HBVDNA is reduced, and the better the antiviral treatment effect is;

(4) in the NCR group, the T cell receptor CDR3 clone was independent of ALT and HBVDNA levels.

The above results suggest that the correlation between TCR β clones and clinical virological indicators during antiviral treatment is different between the NR group and the NCR group, and can provide reference for clinical treatment.

6. TCR sequences which are therapeutically relevant in the treatment of liver diseases.

The present invention examined the TCR clone sequences in the CR and NCR groups that affect therapeutic efficacy, including sequences in peripheral blood and liver tissue.

(1) The TCR sequences associated with better efficacy were obtained as shown in table 1 below:

table 1: TCR sequence with better curative effect

The sequences expressed at 0 week, 12 weeks and 48 weeks among the above sequences were CATSRVAGETQYF (SEQ ID No.2), CASSLGTSNEQFF (SEQ ID No.3) and CASSSGLDSEGNTIYF (SEQ ID No. 9).

The three specific TCR sequences can be expressed in peripheral blood PBMC and liver tissues and penetrate through 0 week, 12 weeks and 48 weeks, so that the appearance of the sequences before and after treatment indicates the effectiveness of treatment, has broad-spectrum sequence characteristics and also provides effective and accurate treatment targets for immunotherapy of liver diseases.

(2) The relevant TCR sequences with poor therapeutic efficacy were obtained as shown in table 2 below:

table 2: TCR sequences with poor therapeutic efficacy

The sequences expressed in 0 week, 12 weeks and 48 weeks are CASSSSSGREQYF (SEQ ID No.21), CASSQDTRANYGYTF (SEQ ID No.24), CASSLTTSGHEQYF (SEQ ID No.27) and CASSPWGRAWTYGYTF (SEQ ID No. 28). The four TCR amino acid sequences are present in patients with poor therapeutic efficacy, suggesting that the appearance of these sequences before and after treatment is indicative of poor therapeutic efficacy with broad spectrum of sequence properties. And throughout weeks 0, 12, 48; and the four specific TCR sequences can be expressed in peripheral blood PBMC and liver tissues.

The sequences are the first discovery of the invention, the curative effect of the treatment of the patient can be obtained by the sequences when the treatment is started (0 week), during the treatment (12 weeks and 48 weeks), the sequences can be used as novel markers for judging the curative effect, pathological changes and prognosis, and the amino acid sequences of targeted T cell receptors can be provided for the liver disease immunotherapy, so that the precision of the immunotherapy is promoted.

The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.

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<211>20

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>13

Cys Ala Ser Ser Ser Gln Asn Leu Phe Thr Gly Thr Gly Ala Arg Tyr

1 5 10 15

Gly Tyr Thr Phe

20

<210>14

<211>12

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>14

Cys Ser Val His Pro Arg Glu Gly Glu Gln Phe Phe

1 5 10

<210>15

<211>12

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>15

Cys Ala Ser Ser Phe Arg Gly Gly Glu Gln Tyr Phe

1 5 10

<210>16

<211>14

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>16

Cys Ala Ser Arg Pro Gly Thr Pro Asn Thr Glu Ala Phe Phe

1 5 10

<210>17

<211>16

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>17

Cys Ala Ser Ser Ser Gly Arg Gly Gln Trp Asn Thr Glu Ala Phe Phe

1 5 10 15

<210>18

<211>13

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>18

Cys Ala Ser Ser Leu Gly Ser Val Gln Pro Gln His Phe

1 5 10

<210>19

<211>14

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>19

Cys Ala Thr Ser Pro Glu Thr Val Asn Thr Glu Ala Phe Phe

1 5 10

<210>20

<211>13

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>20

Cys Ala Thr Ser Gln Ile Ala Gly Glu Thr Gln Tyr Phe

1 5 10

<210>21

<211>13

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>21

Cys Ala Ser Ser Ser Ser Ser Gly Arg Glu Gln Tyr Phe

1 5 10

<210>22

<211>12

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>22

Cys Ser Val Glu Asp Asn Phe Arg Glu Gln Tyr Val

1 5 10

<210>23

<211>15

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>23

Cys Ser Ala Arg Asp Leu Ala Gly Asp Thr Gly Glu Leu Phe Phe

1 5 10 15

<210>24

<211>15

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>24

Cys Ala Ser Ser Gln Asp Thr Arg Ala Asn Tyr Gly Tyr Thr Phe

1 5 10 15

<210>25

<211>13

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>25

Cys Ser Val Glu Ser Arg Glu Ser Tyr Glu Gln Tyr Phe

1 5 10

<210>26

<211>15

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>26

Cys Ala Ser Ser Ser Gly Thr Gly Val Ser Tyr Glu Gln Tyr Phe

1 5 10 15

<210>27

<211>14

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>27

Cys Ala Ser Ser Leu Thr Thr Ser Gly His Glu Gln Tyr Phe

1 5 10

<210>28

<211>16

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>28

Cys Ala Ser Ser Pro Trp Gly Arg Ala Trp Thr Tyr Gly Tyr Thr Phe

1 5 10 15

<210>29

<211>14

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>29

Cys Ala Ser Ser Pro Leu Gly Arg Tyr Asn Glu Gln Phe Phe

1 5 10

<210>30

<211>16

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>30

Cys Ser Ala Arg Ala Gly Thr Gly Gly Ser Thr Asp Thr Gln Tyr Phe

1 5 10 15

<210>31

<211>17

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>31

Cys Ala Ser Ser Leu Tyr Pro Gly Gln Gly Leu Val Tyr Glu Gln Tyr

1 5 10 15

Phe

<210>32

<211>14

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>32

Cys Ser Val Glu Glu Thr Thr Ser Gly Gly Thr Gln Tyr Phe

1 5 10

<210>33

<211>12

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>33

Cys Ser Ala Ser Ser Ile Ser Asp Thr Gln Tyr Phe

1 5 10

<210>34

<211>10

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>34

Cys Ser Val Glu Ala Asn Glu Gln Phe Phe

1 5 10

<210>35

<211>13

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>35

Cys Ser Ala Thr Pro Arg Lys Thr Asp Thr Gln Tyr Phe

1 5 10

<210>36

<211>11

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>36

Cys Ala Ser Ser Leu Trp Gly Glu Ala Phe Phe

1 5 10

<210>37

<211>14

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>37

Cys Ala Ser Ser Gln Ala Gly Ser Ser Tyr Glu Gln Tyr Phe

1 5 10

<210>38

<211>16

<212>PRT

<213> Artificial Sequence (Artificial Sequence)

<400>38

Cys Ala Ser Ser Ser Arg Ile Pro Thr Asn Thr Gly Glu Leu Phe Phe

1 5 10 15

<210>39

<211>19

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>39

cagtatctgg agtcattga 19

<210>40

<211>33

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>40

cactctatcc gacaagcagt ggtatcaacg cag 33

<210>41

<211>21

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>41

tgcttctgat ggctcaaaca c 21

<210>42

<211>20

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>42

cactctatcc gacaagcagt 20

<210>43

<211>19

<212>DNA

<213> Artificial Sequence (Artificial Sequence)

<400>43

acacsttktt caggtcctc 19

Claims (10)

1. A TCR sequence marker for hepatitis b virus infection comprising: a specific amino acid marker selected from the group consisting of: SEQ ID No.1 to SEQ ID No. 39; wherein the amino acid markers associated with good prognosis are selected from: SEQ ID No.1 to SEQ ID No.20, the amino acid markers associated with poor prognosis being selected from the group consisting of: SEQ ID No.21 to SEQ ID No. 38.

2. The TCR sequence marker for hepatitis b virus infection according to claim 1, wherein the amino acid markers with good prognosis are: SEQ ID No.2, SEQ ID No.3 and SEQ ID No. 8; amino acid markers associated with poor prognosis are: SEQ ID No.21, SEQ ID No.24, SEQ ID No.27 and SEQ ID No. 28.

3. A TCR sequence marker for hepatitis b virus infection according to claim 1 further comprising a gene segment marker selected from the group consisting of: the high expression of the gene fragment marker is related to good prognosis of the TRBJ2-5 gene of a CD4+ T cell receptor and/or the TRBJ2-1 gene of a CD8+ T cell receptor.

4. Use of a TCR sequence marker for hepatitis b virus infection according to any of claims 1 to 3 in the manufacture of a medicament for the accurate treatment of hepatitis b.

5. The use of claim 4, wherein the treatment is with entecavir.

6. A system for prognosis evaluation of hepatitis b, comprising:

a data acquisition module: obtaining information on the level of a TCR sequence marker according to any one of claims 1 to 3 in a biological sample;

a data analysis module: comparing and analyzing the content of the marker with a preset rule;

a result output module: and outputting the result of the hepatitis B prognosis evaluation according to the analysis result.

7. The system of claim 6, wherein the biological sample comprises: peripheral blood samples and/or liver tissue samples.

8. The system of claim 6, further comprising a data detection module that detects according to the following procedure:

1) RNA extraction: taking a biological sample, and extracting RNA in T cells;

2) and (3) cDNA synthesis: synthesizing cDNA from the RNA obtained above;

3) library construction: constructing a TCR library by using the cDNA;

4) high-throughput sequencing: performing high-throughput sequencing on the obtained TCR library;

5) data interpretation: analyzing off-line data obtained by high-throughput sequencing by a bioinformatics method, and comparing the off-line data with a database to obtain data information corresponding to the marker of any one of claims 1 to 3.

9. The system of claim 8, wherein in the step 2) cDNA synthesis, the primer sequence of SEQ ID No.39 is used for amplification;

in the step 3) library construction, a first round of nested PCR amplification is carried out by using the primer pairs of SEQ ID Nos. 40-41, and a second round of nested PCR amplification is carried out by using the primer pairs of SEQ ID Nos. 42-43.

10. The system according to claim 6, wherein in the data analysis module, the preset rule is: amino acid markers that correlate well with prognosis are selected from: SEQ ID No.1 to SEQ ID No. 20; amino acid markers associated with poor prognosis are selected from: SEQ ID No.21 to SEQ ID No. 38; the high expression gene segment markers related to good prognosis are selected from: the TRBJ2-5 gene of a CD4+ T cell receptor and/or the TRBJ2-1 gene of a CD8+ T cell receptor;

the result output module also comprises a guide for adjusting the treatment scheme according to the prognosis evaluation result.

Images