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Neoantigen Activity Prediction and Ranking Method Based on Tumor Neoantigen Characteristic Value

A eigenvalue, antigen technology, applied in genomics, biological testing, instruments, etc., can solve the problem of low tumor neoantigen screening efficiency, and achieve the effect of efficient and accurate tumor neoantigen screening

Active Publication Date: 2020-01-31
王勇
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

In the above scheme, since the activity of the predicted MHC-I binding neoantigens is not sorted, it will bring a huge workload to the experimental verification, resulting in low screening efficiency of tumor neoantigens

Method used

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  • Neoantigen Activity Prediction and Ranking Method Based on Tumor Neoantigen Characteristic Value
  • Neoantigen Activity Prediction and Ranking Method Based on Tumor Neoantigen Characteristic Value
  • Neoantigen Activity Prediction and Ranking Method Based on Tumor Neoantigen Characteristic Value

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Embodiment 1

[0039] Such as figure 1 As shown, a neoantigen activity method and sorting method based on tumor neoantigen characteristic value, comprising the following steps:

[0040] Step 101: Input of WGS / WES and RNA-seq sequencing data of tumor-normal samples (using melanoma patient sample-mel_21, Science 2015: Carreno B M, Magrini V, Beckerhapak M, et al.Cancerimmunotherapy.A dendritic cell vaccine increases the breadth and diversity of melanoma neoantigen-specific T cells.[J].Science,2015,348(6236):803-8.)

[0041] Step 102: Prediction and annotation of tumor somatic mutations, and calculation of related feature values: based on WGS / WES and RNA-seq sequencing data of tumor-normal samples, use tools such as Varscan / Mutect to analyze and calculate tumor somatic mutations, and call VEP The (Variant Effect Prediction) tool completes mutation annotation, and uses PyClone, Kallisto, and Varscan / Mutect tools to calculate the following feature values: mutant gene clone ratio CL, mutant gene ...

Embodiment 2

[0055] Such as figure 1 As shown, a neoantigen activity method and sorting method based on tumor neoantigen characteristic value, comprising the following steps:

[0056] Step 101: Input of WGS / WES and RNA-seq sequencing data of tumor-normal samples (using melanoma patient sample 2 mel_38, Science 2015: Carreno B M, Magrini V, Beckerhapak M, et al.Cancerimmunotherapy.A dendritic cell vaccine increases the breadth and diversity of melanoma neoantigen-specific T cells.[J].Science,2015,348(6236):803-8.)

[0057] Step 102: Prediction and annotation of tumor somatic mutations, and calculation of related feature values: based on WGS / WES and RNA-seq sequencing data of tumor-normal samples, use tools such as Varscan / Mutect to analyze and calculate tumor somatic mutations, and call VEP (Variant Effect Prediction) tool completes the mutation annotation, calls PyClone, Kallisto, Varscan / Mutect tools to calculate the following eigenvalues: mutant gene clone ratio CL, mutant gene expressi...

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Abstract

The present invention discloses a method for scoring and sequencing the neoantigens immunological activity based on eigenvalues of tumor neoantigens. The method comprises the following steps of: inputof WGS / WES and RNA-seq sequencing data of tumor-normal samples, prediction and annotation of tumor cellc mutation, and calculation of related eigenvalues; extraction of neoantigens related eigenvalues; setting of a scoring function of the neoantigen activity; and neoantigen sequencing based on the scoring function of the neoantigen activity. According to the method disclosed by the present invention, the tumor cell mutation is analyzed and calculated, and the mutation annotation is completed to calculate the partial eigenvalue, and the MHC-I binding neoantigen is predicted to calculate the partial eigenvalue; all eigenvalues related to the tumor neoantigens are extracted so as to set the scoring function of the neoantigen activity, and finally through the scoring function of the neoantigen activity, the neoantigens are sequenced. Compared with the traditional screening method, the method is more efficient and precise, and has important application value for tumor immunotherapy.

Description

technical field [0001] The present invention relates to the field of tumor immunotherapy, in particular to a neoantigen activity scoring and sorting method based on characteristic values ​​of tumor neoantigens. Background technique [0002] In recent years, tumor immunotherapy has shined brilliantly, clinical trials have continuously achieved breakthroughs, and the cure rate and effective remission rate have continued to increase. Efficient and precise screening of tumor neoantigens is an extremely important and basic work in tumor immunotherapy, especially for tumor immunotherapy such as TCR-T / TIL and individualized vaccines. [0003] At present, the current scheme for screening tumor neoantigens is two steps: step 1, based on WGS / WES data of tumor-normal tissue, using tools such as Mutect / Varscan to calculate the gene mutation of tumor cells; step 2, calling NetMHCpan et al. algorithms predict MHC-I binding neoantigens. [0004] At present, there is no effective method t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G16B20/00G01N33/53
CPCG01N33/53G16B20/00
Inventor 刘琦周驰刘洪马刘峰陈珂马骏
Owner 王勇
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