2020
DOI: 10.1111/cpr.12861
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RNA processing genes characterize RNA splicing and further stratify colorectal cancer

Abstract: Objectives Due to the limited evaluation of the prognostic value of RNA processing genes (RPGs), which are regulators of alternative splicing events (ASEs) that have been shown to be associated with tumour progression, this study sought to determine whether colorectal cancer (CRC) could be further stratified based on the expression pattern of RPGs. Materials and Methods The gene expression profiles of CRCs were collected from TCGA (training set) and three external validation cohorts, representing 1060 cases to… Show more

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Cited by 5 publications
(3 citation statements)
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“…RNA processing factors also function in intron removal and regulate alternative splicing events (ASEs) of individual genes ( 10 ). Aberrant selective RNA processing, especially alternative splicing, could cause a series of consequences, from changing the stability to adding or deleting structural domains and modifying the interactive relationship between proteins ( 11 ).…”
Section: Introductionmentioning
confidence: 99%
“…RNA processing factors also function in intron removal and regulate alternative splicing events (ASEs) of individual genes ( 10 ). Aberrant selective RNA processing, especially alternative splicing, could cause a series of consequences, from changing the stability to adding or deleting structural domains and modifying the interactive relationship between proteins ( 11 ).…”
Section: Introductionmentioning
confidence: 99%
“…They first reported that high expression of the COL6A3 E5‐E6 junction and HKDC1 E1‐E2 was associated with better overall survival of CRC164 165 . Lu et al 166 developed a method, the RNA processing gene (RPG) index, to evaluate the correlation of RPG with prognosis, and they found that it had significant prognostic value in CRC patients.…”
Section: The Role Of As In Crcmentioning
confidence: 99%
“…Most often, the univariable estimates are primarily used to filter genes before the multivariable analysis and reduce the size of the gene set (Wu et al, 2020). Obtaining risk scores [e.g., RNA processing genes in colorectal cancer (Lu et al, 2020)] as well as predicting the best subsets of a given gene set (e.g., netrins and their receptors (Ozhan et al, 2021)) are among many advantages of using multivariable Cox regression models.…”
Section: Introductionmentioning
confidence: 99%