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Prediction method of clinical individualized tumor neoantigen

A prediction method and antigen technology, applied in the field of prediction, to achieve the effects of good code robustness, convenient operability and repeatability

Pending Publication Date: 2020-07-14
SICHUAN UNIV
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Problems solved by technology

[0013] The purpose of the present invention is to overcome the defect that the current tumor neoantigen analysis cannot use one-step method to obtain the final result and to improve the accuracy of prediction based on the feedback of clinical results, and to provide a clinical individualized tumor neoantigen prediction method

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  • Prediction method of clinical individualized tumor neoantigen
  • Prediction method of clinical individualized tumor neoantigen
  • Prediction method of clinical individualized tumor neoantigen

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Embodiment

[0104] In this embodiment, the specific clinical individualized tumor neoantigen sequencing prediction method is as follows:

[0105] Step 0: Preprocessing the original sequencing data of the patient's tumor cells to obtain the sequencing data of the patient's tumor cells.

[0106] Specifically: after obtaining the high-throughput sequencing files (fastq files) of the patient's original tumor cell DNA / RNA and the DNA material of the patient's blood, use Trimmomatic software to trim the sequencing adapter sequence, trim the sequencing tag sequence, and remove the sequencing fastq file. Poor quality.

[0107] The selection of parameters is as follows: 1) Select PE mode, that is, pair-end mode, for data analysis; 2) Set the ILLUMINALIP parameter to TruSeq3-PE.fa:2:30:10, that is, use ILLUMINA's The linker sequence information in the TruSeq3-PE library construction scheme is used to remove the linker. This information exists in the TruSeq3-PE.fa file, and the target sequence and ...

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Abstract

The present invention relates to prediction techniques, and the defects that the final result cannot be obtained by adopting a one-step method and the prediction accuracy cannot be improved accordingto the feedback of a clinical result in the existing tumor neoantigen analysis are overcome; the invention provides a prediction method of a clinical individualized tumor neoantigen. The technical scheme can be summarized as follows: comparing the sequencing data of the tumor cells of the patient with a corresponding reference genome to obtain a DNA and RNA comparison result; after pretreatment, analyzing somatic variation, clone type, tumor purity, gene expression quantity in the tumor cells and expression abundance of somatic variation alleles in the tumor cells to obtain an analysis result;and analyzing the affinity of the potential new antigens and calculating the polypeptide presentation efficacy, and scoring and sequencing the corresponding new antigens according to the analysis result, the affinity of the potential new antigens and the polypeptide presentation efficacy to present the new antigens. The method has the beneficial effects that the accuracy can be improved through the standardized process, and the method has more convenient operability and repeatability and is suitable for predicting clinical individualized tumor neoantigens.

Description

technical field [0001] The present invention relates to prediction technology, in particular to the prediction technology of individualized tumor neoantigen. Background technique [0002] Tumor immunotherapy is considered to be a new generation of tumor treatment after surgery, radiotherapy, chemotherapy and small molecule targeted therapy. The idea of ​​​​transformation is to activate immune cells and treat tumors by enhancing the patient's own anti-tumor immunity. Compared with traditional treatments, it has the advantages of precise killing, small side effects, long-lasting curative effect and high degree of individualization. In addition, the body's immune system has the characteristics of immune memory, so immunotherapy can help patients form memory immunity, which has significant advantages in preventing tumor recurrence and metastasis. [0003] At present, immunotherapy is mainly divided into two categories: immunotherapy based on immune checkpoint inhibitors and cel...

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Application Information

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IPC IPC(8): G16B30/10G16B20/50G16B20/20
CPCG16B30/10G16B20/50G16B20/20
Inventor 许恒舒洋杨莉丁振宇魏于全
Owner SICHUAN UNIV
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