Method and application of pan-tumor targeted drug sensitivity state evaluation model constructed based on high-throughput sequencing data and clinical phenotypes

Abstract

The invention relates to the field of gene detection and bioinformatics, and discloses application of a state evaluation model constructed on the basis of high-throughput sequencing data and clinicalphenotypes to evaluation of the sensitivity state of a pan-tumor targeted drug. The invention discloses a method for mining a pan-tumor targeted drug marker based on transcriptome data, exon group / genome data and clinical phenotype, designs a set of calculation method for constructing a pan-tumor targeted drug sensitivity evaluation model by integrating the high-throughput sequencing data and clinical phenotype, screens out biomarkers related to tumor patient targeted drug sensitivity, and forms a pan-tumor targeted drug sensitivity state evaluation model. A marker considering both accuracy and mechanism interpretability is constructed through the method, and the method can be used for predicting a pan-tumor treatment effect, assisting in decision making of a treatment scheme and the like.

Description

technical field [0001] The present invention relates to the technical fields of gene detection and bioinformatics, in particular to a method for evaluating the susceptibility status of pan-tumor targeting drugs based on high-throughput sequencing data and clinical phenotypes, and related detection panel design and implementation application cases. Background technique [0002] The first-generation sequencing technology obtains the base information at a specific position of the sequence through the dideoxy terminal termination method or chemical cleavage method, and reads the nucleic acid sequence by electrophoresis and development. Gene chip technology, by hybridizing with a set of nucleic acid probes of known sequences for nucleic acid sequence determination, has achieved high-throughput parallelization. The disadvantages are that the repeatability and sensitivity need to be enhanced, and the analysis range is not wide enough. Next-generation sequencing technology, also kno...

AI Technical Summary

Problems solved by technology

Gene chip technology, by hybridizing with a set of nucleic acid probes of known sequence for nucleic acid sequence determination, realizes high-throughput parallelization, but the disadvantages are that the repeatability and sensitivity need to be enhanced, and the analysis range is not wide enough

Next-generation sequencing technology, also known as next-generation sequencing technology (next-generation sequencing, NGS), is different from the first-generation sequencing technology. It achieves high-throughput parallel sequencing through in vitro fragment amplification and sequencing while synthesizing. The main disadvantages are read length

2) Detection and evaluation content is relatively single, with limited functions

At present, due to gene collection and screening capabilities and sequencing costs, the same marker detection scheme covers relatively few genes. In practical applications, single site or small fragment mutations are used as the main evaluation index. In recent years, gene expression levels and detection of all genes in the panel The overall mutation level as a marker evaluation scheme has attracted increasing attention; in terms of function, it mainly predicts the effect of site- or gene-related targeted drugs, and has limited guiding significance for a wider range of surgery, chemotherapy, radiotherapy, and immunotherapy

3) Marker design and supporting data analysis tools do not make full use of multivariate information

At present, most of the design schemes only focus on drug guidelines, labels and limited literature collection. The technical route focuses on a single omics level, and there are few comprehensive analyzes based on large-scale sequencing results, public databases and text mining technologies. It covers a variety of molecular omics and Multivariate data integration analysis of clinical phenotype information is seriously insufficient

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