Literature DB >> 31335180

Prediction of Overall Survival in Gastric Cancer Using a Nine-lncRNA.

Congbo Cai1, Lei Yang1, Yeli Tang1, Houxing Wang1, Yi He2, Honggang Jiang2, Kena Zhou2.   

Abstract

Long noncoding RNA (lncRNA) was closely attached to various cancers according to previous studies. In this study we aimed to investigate an lncRNA signature with prognostic value of over survival (OS) outcomes of gastric cancer (GC). Profiles of mRNAs expression and clinical information of 381 GC tissues and 32 nontumor gastric tissues were downloaded from The Cancer Genome Atlas database. Comparison of various lncRNA expression between cancer tissue and normal tissue was made among these data. In the end, a nine-lncRNA signature was discovered using univariate and multivariate Cox regression analyses, with a prospect possibility of the OS in GC patients. Receiver operating characteristic (ROC) was used to evaluate the accuracy of survival model. The gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were used to predict the possible functions and pathways of these lncRNAs. Altogether 720 distinctively expressed lncRNAs were selected between GC and normal tissues. By univariate and multivariate Cox regression analyses, nine lncRNAs were eventually filtered to set a predictive model, distributing patients into high-risk and low-risk groups with extraordinary different OS. Area under the curve of the ROC curve for the nine-lncRNA signature's prediction of 5-year OS was 0.795. Further functional enrichment analyses indicated that these lncRNAs may be associated with biological processes such as protein binding, DNA replication, and cell cycle. Our study identified a nine-lncRNA signature, which could act as a potential prognostic biomarker in the prediction of GC patients' OS.

Entities:  

Keywords:  TCGA; gastric cancer; lncRNA; overall survival; signature

Mesh:

Substances:

Year:  2019        PMID: 31335180     DOI: 10.1089/dna.2019.4832

Source DB:  PubMed          Journal:  DNA Cell Biol        ISSN: 1044-5498            Impact factor:   3.311


  11 in total

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