Prognosis prediction model based on competing endogenous RNAs for recurrence of colon adenocarcinoma.

ABSTRACT:

Background

Colon adenocarcinoma (COAD) patients who develop recurrence have poor prognosis. Our study aimed to establish effective prognosis prediction model based on competing endogenous RNAs (ceRNAs) for recurrence of COAD.

Methods

COAD expression profilings downloaded from The Cancer Genome Atlas (TCGA) were used as training dataset, and expression profilings of GSE29623 retrieved from Gene Expression Omnibus (GEO) were set as validation dataset. Differentially expressed RNAs (DERs) between non-recurrent and recurrent specimens in training dataset were screened, and optimum prognostic signature DERs were revealed to establish prognostic score (PS) model. Kaplan-Meier survival analysis was conducted for PS model, and GEO dataset was used for validation. Prognosis predictio

SUBMITTER: Jin LP 

PROVIDER: S-EPMC7541229 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature