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Method for constructing tumor mutation load TMB panel and using method of tumor mutation load TMB panel

A mutation load and panel technology is applied in biochemical equipment and methods, medical data mining, and microbial determination/inspection. The effect of low sequencing cost, short turnaround time, and long detection time

Active Publication Date: 2020-11-17
THE THIRD AFFILIATED HOSPITAL OF SUN YAT SEN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Whole exome sequencing is the gold standard for evaluating tumor mutation burden, but the application of whole exome sequencing to clinical trials has the following difficulties: 1. The number of samples is limited; Low; 4. High cost

Method used

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  • Method for constructing tumor mutation load TMB panel and using method of tumor mutation load TMB panel
  • Method for constructing tumor mutation load TMB panel and using method of tumor mutation load TMB panel

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Embodiment Construction

[0023] The method for constructing a tumor mutation load TMB panel of the present invention comprises the following steps:

[0024] 1) Acquire the transcriptome data of tumor patients, the transcriptome refers to the quantitative transcriptome of miRNA expression, and divide the transcriptome data into high tumor mutation burden group and low tumor mutation burden group according to the optimal tumor mutation burden threshold affecting patient survival mutation load group;

[0025] 2) Screen the immune-related differentially expressed gene DEGs between the high tumor mutation burden group and the low tumor mutation burden group in step 1), and perform enrichment analysis on the gene ontology of the DEGs to obtain the protein interaction PPI between the differential genes Information, draw a PPI network diagram, and use this to filter out several top-ranked nodes;

[0026] 3) The transcriptome expression data of the high tumor mutation burden group and the low tumor mutation b...

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Abstract

The invention discloses a method for constructing a tumor mutation load TMB panel. The method comprises the following steps: 1) acquiring transcriptome data of a tumor patient, and dividing the transcriptome data into a high TMB group and a low TMB group; 2) screening immune-related differential expression genes DEGs between the high TMB group and the low TMB group, and carrying out enrichment analysis; 3) carrying out immune cell infiltration analysis through Immune CellAI, and screening out potential key immune cells; 4) screening out tumor immunity related genes for prognosis of the patient; 5) establishing modules with different colors and a correlation matrix of immune traits possibly influencing prognosis; and 6) selecting genes with better correlation with macrophages, DC, MAIT andinfiltration integration in the WCGNA, and preliminarily obtaining a TMBIF gene panel. The invention also provides a using method of the tumor mutation load TMB panel. The tumor mutation load TMB panel constructed by the invention is low in sequencing cost and low in DNA input requirement in use, has shorter turnover time, can perform deeper sequencing, and improves the mutation detection sensitivity.

Description

technical field [0001] The present invention relates to a method for constructing a tumor mutation load TMB panel and a technique for using the same. Background technique [0002] At present, PD-1 inhibitors are mainly approved for the second-line treatment of patients with advanced liver cancer who do not respond well to sorafenib, but due to differences in treatment responses, biomarkers that can well predict the effect of immunotherapy are still being sought. Current PD-1 / PD-L1 expression levels, tumor mutation burden (TMB), microsatellite instability-high (MSI-H), tumor-infiltrating T cell content, and neutrophil-lymphocyte ratio (NLR) are relative Widely accepted predictor of response to immunotherapy. However, these indicators have different predictive effects in different tumors. They are widely used in lung cancer and melanoma, while their predictiveness in other tumors has been questioned. Subsequent studies and most clinical trials have shown that tumor mutationa...

Claims

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Application Information

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IPC IPC(8): G16B30/00G16B40/00G16H50/20G16H50/70C12Q1/6869C12Q1/6886
CPCG16B30/00G16B40/00G16H50/20G16H50/70C12Q1/6886C12Q1/6869C12Q2600/156C12Q2600/118C12Q2535/122
Inventor 谢婵彭亮吴和维郑杏容高志良
Owner THE THIRD AFFILIATED HOSPITAL OF SUN YAT SEN UNIV
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