Construction method and application of pancreatic ductal cancer state evaluation model

Abstract

The invention relates to the field of gene detection and bioinformatics and discloses application of a complex disease state evaluation method constructed based on high-throughput sequencing data andclinical phenotypes in a pancreatic ductal carcinoma state evaluation model. The invention also provides a method for mining pancreatic ductal cancer complex disease markers based on transcriptome data, exon group / genome data and clinical phenotypes, designs a calculation method for constructing a pancreatic ductal cancer state evaluation model by integrating high-throughput sequencing data and clinical phenotypes, screens out biomarkers related to pancreatic ductal cancer and creates the corresponding disease state evaluation model. The markers having both accuracy and mechanism interpretability are constructed through the method, and can be used for pancreatic ductal cancer prognosis evaluation, treatment effect prediction, assistant decision making of treatment schemes and the like.

Description

technical field [0001] The present invention relates to the technical fields of gene detection and bioinformatics, and relates to a construction method and application of a pancreatic ductal carcinoma state assessment model, in particular to a method and application for constructing a pancreatic ductal carcinoma state assessment model 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 ...

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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