Method for predicting tumor neoantigen and its application

A prediction method and tumor technology, applied in the field of biomedicine, can solve the problems that tumor vaccines cannot meet the needs of non-response to treatment and produce drug-resistant patients, and achieve the effect of improving accuracy

Active Publication Date: 2019-12-20
BEIJING USCI MEDICAL LAB CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Although checkpoint blockade therapy has achieved great clinical success, patient-specific tumor vaccines still cannot meet the clinical needs of patients who do not respond to treatment, develop drug resistance, or cannot tolerate side effects associated with checkpoint blockade drugs

Method used

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  • Method for predicting tumor neoantigen and its application
  • Method for predicting tumor neoantigen and its application
  • Method for predicting tumor neoantigen and its application

Examples

Experimental program
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Effect test

Embodiment 1

[0057] In this example, the whole exome sequencing and RNA-Seq data of melanocytoma patients were used for testing, which can accurately type HLA-I and HLA-II alleles, and predict that they can be compared with HLA-I Class and HLA-II allele tightly bound neoantigens.

[0058] Specific steps are as follows:

[0059] The tumor tissue and plasma white blood cell samples of a melanoma patient were obtained, and the tumor tissue DNA, RNA and plasma white blood cell DNA were extracted to construct a sequencing library, and whole exome sequencing was performed to obtain sequencing data.

[0060] The data analysis is as follows:

[0061] step 1:

[0062] 1) Plasma leukocyte DNA comparison: Use Fastqc (v 0.11.6) (-t 6) software to count the sequencing quality of plasma leukocyte DNA, and use Cutadapter (v1.2.1) software to remove the sequencing adapters connected when building the library. The software uses the default Parameters, remove sequences whose bases with a quality score le...

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Abstract

The invention discloses a method for predicting a tumor neoantigen and its application. The prediction method includes the following steps: S1, obtaining a tumor sample and a plasma leukocyte sample of a tumor patient, constructing a sequencing library, and performing whole genome, whole exome or targeted capture RNA, DNA sequencing; S2, using the plasma leukocyte DNA as a contrast, comparing thetumor sample DNA and detecting somatic mutation, filtering out a missense mutation site, and annotating the filtered missense mutation site; S3, using the plasma leukocyte DNA sequencing data to typeHLA-I and HLA-II alleles; and S4, predicting antigenic polypeptides that can bind to HLA-I and HLA-II alleles. The method of the present invention can more accurately screen out an antigen that can beexpressed genes and that can bind to HLA-I and HLA-II alleles and cause antitumor immune response.

Description

technical field [0001] The invention relates to the field of biomedical technology, in particular to a method for predicting tumor neoantigens and its application. Background technique [0002] Cancer immunotherapy has achieved great success in the clinical application of checkpoint blockade inhibition. Massively parallel sequencing analyzes suggest a link between tumor mutational burden and response to such treatments. To improve the prediction of response to checkpoint blockade inhibitory therapy and to identify targets for tumor vaccines and adoptive T cell therapy, it is necessary to identify which tumor-specific mutant polypeptides (neoantigens) can induce antitumor T cell immunity. These unique antigenic signatures arise from a large number of somatic genetic mutations that are present only in tumors but not in normal cells. Clinical data show that the polypeptide proteins expressed by these mutant sequences can be recognized by the immune system as non-self and elim...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16B20/20G16B20/50G16B25/10G16B30/10G16B50/30
CPCG16B20/20G16B20/50G16B25/10G16B30/10G16B50/30
Inventor 徐冰张静波单光宇伍启熹王建伟刘倩唐宇
Owner BEIJING USCI MEDICAL LAB CO LTD
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