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Construction method and application of gastric cancer prognosis model based on alternative splicing events

A construction method, a variable technology, applied in the fields of biomedicine and medical informatics, which can solve the problems of the lack of clinical reference for the prognostic value of alternative splicing events, etc.

Pending Publication Date: 2020-11-06
GUIZHOU MEDICAL UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there is still a lack of clinical reference on the prognostic value of alternative splicing events, and the regulatory mechanism and prognostic value of survival-related alternative splicing events need further study

Method used

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  • Construction method and application of gastric cancer prognosis model based on alternative splicing events
  • Construction method and application of gastric cancer prognosis model based on alternative splicing events
  • Construction method and application of gastric cancer prognosis model based on alternative splicing events

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0051] Example 1: Analysis of Alternative Splicing Events in Gastric Cancer Samples

[0052] TCGA's SpliceSeq provides a map of alternative splicing events based on whole-transcriptome sequencing data (Ryan M, WongWC, Brown R, Akbani R, Su X, Broom B, Melott J and Weinstein J.TCGASpliceSeq acompendium of alternative mRNA splicing in cancer.Nucleic Acids Res. 2016;44(D1):D1018-22). More than 75% of the alternative splicing events in gastric cancer samples were downloaded from the SpliceSeq database, and the corresponding clinical data of gastric cancer patients were downloaded from the TCGA pan-cancer atlas database. Data and clinical data of alternative splicing events were confirmed and matched by TCGA ID, and only gastric cancer patients with both clinical follow-up and alternative splicing event data were finally included in this study. The clinical data of the patients with gastric cancer are shown in Table 1. For the process of data processing, see figure 1 . 48,141 a...

Embodiment 2

[0065] Example 2: Alternative splicing events associated with survival in gastric cancer

[0066] In the survival correlation analysis, 47 patients with an overall survival of less than 30 days were excluded, and then the remaining 368 patients were matched with the corresponding entries in the SpliceSeq database, 31 patients were missing more than 20% of the alternative splicing Events are excluded again. Therefore, a total of 337 patients were included in this study. After excluding alternative splicing events with standard deviation (SD) figure 2 ). Reactome was used to map the protein network interaction to explore the interaction between survival-related alternative splicing events and corresponding genes. image 3 The 20 most important survival-related genes among the 7 alternative splicing events are shown. It is worth noting that most of these alternative splicing events are associated with prognosis, and a gene may have two or more survival-related splicing events...

Embodiment 3

[0068] Construction of the prognostic model for patients with gastric cancer

[0069] Survival-related alternative splicing events were selected for LASSO and multivariate Cox analysis, and prognostic models were established according to AA, AD, AP, AT, ES, ME, and RI events. Subsequently, Kaplan-Meier analysis was employed to plot the survival rates over time for the prognostic models of the seven types of alternative splicing events. Then, the seven alternative splicing events were integrated to construct the final prognostic model. At the same time, the receiver operating characteristic curve (Receiver operating characteristic curve, ROC) was drawn to evaluate the effectiveness of the prognostic model, and a prognostic model was constructed to predict the clinical outcome of gastric cancer patients. LASSO and multivariate Cox analyzes were performed based on AA, AD, AP, AT, ES, ME and RI events ( Figure 5 ), developed seven prognostic models based on a single alternative...

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Abstract

The invention belongs to the technical field of biomedicine and medical informatics, and particularly relates to a construction method and application of a gastric cancer prognosis model based on alternative splicing events. According to the invention, a sample is reasonably selected, alternative splicing events significantly related to the total lifetime of patients with gastric cancer are determined through single-factor Cox regression analysis, and then the prognosis model is established by using a minimum absolute constriction and selection operator (LASSO) and multi-factor Cox analysis; and the final prognosis model based on seven types of alternative splicing events can be used as an independent prognosis index of a patient with gastric cancer.

Description

technical field [0001] The invention belongs to the technical field of biomedicine and medical informatics, and in particular relates to a construction method and application of a gastric cancer prognosis model based on alternative splicing events. Background technique [0002] Alternative splicing (AS) can edit a single pre-mRNA molecule and produce different mature mRNAs in eukaryotes, and these transcript variants can subsequently produce proteins with different structures and biological functions. Therefore, alternative splicing is an important mechanism for the post-transcriptional regulation of gene expression and plays a crucial role in the diversity of transcriptomes and encoded proteins. Generally, there are seven main types of alternative splicing events, such as exon skipping (Exon skip, ES), intron retention (Retained intron, RI), alternative donor site (Alternate donor, AD), alternative recipient Body site (Alternate acceptor, AA), variable promoter (Alternate ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/70G16H50/30G16B40/00
CPCG16H50/70G16H50/30G16B40/00
Inventor 胡祖权欧阳燕张世超曾柱
Owner GUIZHOU MEDICAL UNIV
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