Published online Nov 28, 2020. doi: 10.3748/wjg.v26.i44.6929
Peer-review started: April 18, 2020
First decision: July 29, 2020
Revised: August 6, 2020
Accepted: September 17, 2020
Article in press: September 17, 2020
Published online: November 28, 2020
Gastric cancer (GC) is one of the most frequently diagnosed gastrointestinal cancers throughout the world. Novel prognostic biomarkers are required to predict the prognosis of GC.
To identify a multi-long noncoding RNA (lncRNA) prognostic model for GC.
Transcriptome data and clinical data were downloaded from The Cancer Genome Atlas. COX and least absolute shrinkage and selection operator regression analyses were performed to screen for prognosis associated lncRNAs. Receiver operating characteristic curve and Kaplan-Meier survival analyses were applied to evaluate the effectiveness of the model.
The prediction model was established based on the expression of AC007991.4, AC079385.3, and AL109615.2 Based on the model, GC patients were divided into “high risk” and “low risk” groups to compare the differences in survival. The model was re-evaluated with the clinical data of our center.
The 3-lncRNA combination model is an independent prognostic factor for GC.
Core Tip: A model to predict survival of patients with gastric cancer was developed and validated by RNA sequencing and real-time reverse transcription-polymerase chain reaction assays. The model had an excellent performance: The areas under the curves for 3-year and 5-year survival were 0.78 and 0.75, respectively. The C-index was 0.72 (se = 0.022, 95% confidence interval: 0.67-0.76). The model contributed as a poor independent prognostic factor both in disease free survival and overall survival.