Method of determining tumor marker based on transcriptome data

A tumor marker and data determination technology, applied in the field of bioinformatics, can solve the problems of difficulty in finding molecular markers for accurately predicting disease prognosis and complex regulatory systems from omics data.

Active Publication Date: 2017-06-20
中国医学科学院医学信息研究所
View PDF6 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The existing method of predicting the risk of tumor prognosis based on a single type of molecular marker has certain limitations, because tumors have strong heterogeneity, and the internal regulatory system is very complex, and different ty...

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method of determining tumor marker based on transcriptome data
  • Method of determining tumor marker based on transcriptome data
  • Method of determining tumor marker based on transcriptome data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0056] 1. Data description

[0057] mRNA, lncRNA and miRNA microarray expression data (Agilent RNA expression microarray) of normal tissue and tumor tissue of 119 ESCC samples.

[0058] 2. Data pre-processing

[0059] For miRNAs, the expression data of 208 miRNAs in 119 samples were selected after removing missing values; for lncRNAs, the probes annotated to specific data sets (UCSC, ENCODE, Cabili, etc.) were screened, followed by log transformation to screen for active expression and in For molecules differentially expressed in tumor and normal tissues, the expression data of 149 lncRNAs in 119 samples were finally obtained; for mRNA, the screening method was similar to lncRNA processing, and finally the expression data of 175 mRNAs in 119 samples were obtained. RNA expression data were normalized and used for subsequent analyses.

[0060] 3. Using group-lasso-based logistic for feature screening of miRNA, lncRNA and mRNA

[0061] 3.1 Sample grouping: 119 ESCC samples wer...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a method of determining a tumor marker based on transcriptome data, comprising: (1) acquiring transcriptome data, including first and second transcriptome data which comprise mRNA, LncRNA and miRNA expression data of first and second individual sample respectively, wherein differences of the first and second individual samples include one of paired relative phenotypic features; (2) establishing regularization logic regression models wherein each individual has phenotypic feature relationship with expression of three RNAs, and using the models to regress expression data of the three RNAs respectively to obtain molecular regression coefficients of the three RNAs; (3) performing grid searching, and determining three RAN thresholds according to the molecular regression coefficients of the three RNAs; (4) comparing the molecular regression coefficient of each RNA to a corresponding threshold, and determining three RNA candidate markers; (5) mixing the three RNA candidate markers to obtain RAN mixture data, and replacing transcriptome data with the RAN mixture data to carry out the steps (2) to (4) so as to determine a tumor marker.

Description

technical field [0001] The present invention relates to the field of bioinformatics, specifically, the present invention relates to a method for determining tumor markers based on transcriptome data and a group of tumor markers. Background technique [0002] Every cell has a complex gene expression regulation system, which cooperates with each other to perform normal biological functions. For the study of complex disease biological systems, it is necessary to integrate experimental and computational methods to analyze multi-level regulatory relationship data, thereby discovering pathogenic mechanisms and promoting disease diagnosis and treatment. Studies have found that the abnormal expression of some genes in tumor tissue is closely related to the occurrence and development of tumors, and thus become important tumor markers. In addition, some non-coding RNAs (such as microRNA, lncRNA, etc.) also have important regulatory functions in life activities, mediating and particip...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F19/18
CPCG16B20/00
Inventor 李姣郑思
Owner 中国医学科学院医学信息研究所
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap