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Construction of a Novel Risk Model Based on the Random Forest Algorithm to Distinguish Pancreatic Cancers with Different Prognoses and Immune Microenvironment Features

Authors :
Chen Liang
Rong Tang
Jin Xu
Jiang Liu
Wei Wang
Qingcai Meng
Jie Hua
Si Shi
Xianjun Yu
Bo Zhang
Yalan Lei
Source :
Bioengineered, article-version (VoR) Version of Record, Bioengineered, Vol 12, Iss 1, Pp 3593-3602 (2021)
Publication Year :
2021
Publisher :
Research Square Platform LLC, 2021.

Abstract

Immune-related long noncoding RNAs (irlncRNAs) are actively involved in regulating the immune status. This study aimed to establish a risk model of irlncRNAs and further investigate the roles of irlncRNAs in predicting prognosis and the immune landscape in pancreatic cancer. The transcriptome profiles and clinical information of 176 pancreatic cancer patients were retrieved from The Cancer Genome Atlas (TCGA). Immune-related genes (irgenes) downloaded from ImmPort were used to screen 1903 immune-related lncRNAs (irlncRNAs) using Pearson’s correlation analysis (R > 0.5; p<br />Graphical abstract

Details

Database :
OpenAIRE
Journal :
Bioengineered, article-version (VoR) Version of Record, Bioengineered, Vol 12, Iss 1, Pp 3593-3602 (2021)
Accession number :
edsair.doi.dedup.....24217bc73bf7ae089111068a9d95eddc