Method for obtaining tumor specific T cell receptor

Abstract

The invention discloses a method for obtaining a tumor specific T cell receptor. The method comprises the following steps: firstly, obtaining a T cell receptor gene sequence in an antigen peptide specific T cell which comes from an immunoreactive positive and / or tumor symptom relieved tumor patient after antigen peptide treatment; then, preparing an antigen specific T cell receptor according to the antigen specific T cell receptor gene sequence; introducing the antigen peptide specific T cell receptor gene into the T cell, and expressing the antigen peptide specific T cell receptor gene to obtain the specific TCR-T cell. The specific TCR-T cell can be used for successfully killing gene mutation corresponding to antigen peptide and HLA typed tumor cell, and has high killing efficiency and agood application prospect.

Description

technical field

[0001] The present invention relates to a method for obtaining tumor-specific T cell receptors in the field of biomedicine. Background technique

[0002] The T cell receptor (TCR) is a characteristic marker on the surface of all T cells and has the ability to recognize complexes of processed peptides associated with MHC molecules on antigen presenting cells (APCs). TCR is a heterodimer composed of α and β peptide chains, each peptide chain is divided into several parts such as variable region (V region), constant region (C region), transmembrane region and cytoplasmic region; Its cytoplasmic region is very short, and the signal transmission is mainly carried out through the non-covalently bound CD3 molecule. The TCR molecule belongs to the immunoglobulin superfamily, and its antigen specificity exists in the V region; the V region has three hypervariable regions, CDR1, CDR2, and CDR3. Among them, CDR3 has the greatest variation, which directly determines the...

Examples

Embodiment 1

[0095] Example 1. Acquisition and application of lung adenocarcinoma antigen peptide-specific T cell receptors

[0096] Subject: Right lung adenocarcinoma patient, female, 46 years old.

[0097] The treatment of patients

[0098] The gene mutation and HLA typing of the patient's right lung adenocarcinoma cells were obtained by sequencing, and it was found that the patient's right lung adenocarcinoma cells had EGFR Exon21c.2573T>G p.L858R mutation, with a mutation frequency of 5.3%.

[0099] HLA classification is: A*11:01:01A*23:01:01, B*15:01:01B*45:01:01, C*01:02C*06:02:01, DRB1*07:01DRB1 *14:54:01, DQB1*02:02:01DQB1*05:02:01.

[0100] According to patient gene mutation and HLA type, according to HLA-peptide prediction algorithm NetMHC3.4 (http: / / www.cbs.dtu.dk / services / NetMHC-3.4 / ) and NetMHC2.2 (http: / / www.cbs .dtu.dk / services / NetMHCII / ), predict the affinity of HLA class I and class II molecules and polypeptides in patients, and select polypeptides with high affinity as...

Embodiment 2

[0149] Example 2. Acquisition and application of colorectal cancer antigen peptide-specific T cell receptors

[0150] Subject: Right-sided colorectal cancer patient, male, 63 years old.

[0151] The gene mutation and HLA typing of the patient's tumor cells were obtained by sequencing. The patient was found to have the gene mutation EGFR746_750DEL with a mutation frequency of 12%. HLA classification is A*03:01:01A*11:01:01, B*07:02B*40:02:01, C*07:02:01C*15:02:01, DRB1*01:01DRB1* 16:02:01, DQB1*05:01DQB1*05:02.

[0152] According to patient gene mutation and HLA type, according to HLA-peptide prediction algorithm NetMHC3.4 (http: / / www.cbs.dtu.dk / services / NetMHC-3.4 / ) and NetMHC2.2 (http: / / www.cbs .dtu.dk / services / NetMHCII / ), to predict the affinity of HLA class I and class II molecules and polypeptides in patients, and select the polypeptides with the highest affinity as antigenic peptides for personalized therapy. The obtained antigenic peptide is shown in SEQ ID NO: 6 in ...

Embodiment 3

[0159] Example 3. Acquisition and application of gastric cancer antigen peptide-specific T cell receptors

[0160] Subject: Gastric cancer patients, female, 51 years old.

[0161] The gene mutation and HLA typing of the patient's tumor cells were obtained by sequencing. The patient was found to have the gene mutation TP53G105V with a mutation frequency of 5.2%. HLA classification is A*11:01:01A*31:01:02, B*15:02B*51:02, C*08:01:01C*15:02:01, DRB1*09:01:02DRB1* 12:02:01, DQB1*03:01:01DQB1*03:03:02.

[0162] According to patient gene mutation and HLA type, according to HLA-peptide prediction algorithm NetMHC3.4 (http: / / www.cbs.dtu.dk / services / NetMHC-3.4 / ) and NetMHC2.2 (http: / / www.cbs .dtu.dk / services / NetMHCII / ), to predict the affinity of HLA class I and class II molecules and polypeptides in patients, and select the polypeptides with the highest affinity as antigenic peptides for personalized therapy. The obtained antigenic peptide is shown in SEQ ID NO: 11 in the sequence...

technical field

[0001] The present invention relates to a method for obtaining tumor-specific T cell receptors in the field of biomedicine. Background technique

[0002] The T cell receptor (TCR) is a characteristic marker on the surface of all T cells and has the ability to recognize complexes of processed peptides associated with MHC molecules on antigen presenting cells (APCs). TCR is a heterodimer composed of α and β peptide chains, each peptide chain is divided into several parts such as variable region (V region), constant region (C region), transmembrane region and cytoplasmic region; Its cytoplasmic region is very short, and the signal transmission is mainly carried out through the non-covalently bound CD3 molecule. The TCR molecule belongs to the immunoglobulin superfamily, and its antigen specificity exists in the V region; the V region has three hypervariable regions, CDR1, CDR2, and CDR3. Among them, CDR3 has the greatest variation, which directly determines the...

Examples

Embodiment 1

[0095] Example 1. Acquisition and application of lung adenocarcinoma antigen peptide-specific T cell receptors

[0096] Subject: Right lung adenocarcinoma patient, female, 46 years old.

[0097] The treatment of patients

[0098] The gene mutation and HLA typing of the patient's right lung adenocarcinoma cells were obtained by sequencing, and it was found that the patient's right lung adenocarcinoma cells had EGFR Exon21c.2573T>G p.L858R mutation, with a mutation frequency of 5.3%.

[0099] HLA classification is: A*11:01:01A*23:01:01, B*15:01:01B*45:01:01, C*01:02C*06:02:01, DRB1*07:01DRB1 *14:54:01, DQB1*02:02:01DQB1*05:02:01.

[0100] According to patient gene mutation and HLA type, according to HLA-peptide prediction algorithm NetMHC3.4 (http: / / www.cbs.dtu.dk / services / NetMHC-3.4 / ) and NetMHC2.2 (http: / / www.cbs .dtu.dk / services / NetMHCII / ), predict the affinity of HLA class I and class II molecules and polypeptides in patients, and select polypeptides with high affinity as...

Embodiment 2

[0149] Example 2. Acquisition and application of colorectal cancer antigen peptide-specific T cell receptors

[0150] Subject: Right-sided colorectal cancer patient, male, 63 years old.

[0151] The gene mutation and HLA typing of the patient's tumor cells were obtained by sequencing. The patient was found to have the gene mutation EGFR746_750DEL with a mutation frequency of 12%. HLA classification is A*03:01:01A*11:01:01, B*07:02B*40:02:01, C*07:02:01C*15:02:01, DRB1*01:01DRB1* 16:02:01, DQB1*05:01DQB1*05:02.

[0152] According to patient gene mutation and HLA type, according to HLA-peptide prediction algorithm NetMHC3.4 (http: / / www.cbs.dtu.dk / services / NetMHC-3.4 / ) and NetMHC2.2 (http: / / www.cbs .dtu.dk / services / NetMHCII / ), to predict the affinity of HLA class I and class II molecules and polypeptides in patients, and select the polypeptides with the highest affinity as antigenic peptides for personalized therapy. The obtained antigenic peptide is shown in SEQ ID NO: 6 in ...

Embodiment 3

[0159] Example 3. Acquisition and application of gastric cancer antigen peptide-specific T cell receptors

[0160] Subject: Gastric cancer patients, female, 51 years old.

[0161] The gene mutation and HLA typing of the patient's tumor cells were obtained by sequencing. The patient was found to have the gene mutation TP53G105V with a mutation frequency of 5.2%. HLA classification is A*11:01:01A*31:01:02, B*15:02B*51:02, C*08:01:01C*15:02:01, DRB1*09:01:02DRB1* 12:02:01, DQB1*03:01:01DQB1*03:03:02.

[0162] According to patient gene mutation and HLA type, according to HLA-peptide prediction algorithm NetMHC3.4 (http: / / www.cbs.dtu.dk / services / NetMHC-3.4 / ) and NetMHC2.2 (http: / / www.cbs .dtu.dk / services / NetMHCII / ), to predict the affinity of HLA class I and class II molecules and polypeptides in patients, and select the polypeptides with the highest affinity as antigenic peptides for personalized therapy. The obtained antigenic peptide is shown in SEQ ID NO: 11 in the sequence...

Images