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. It is necessary to identify a multi-long noncoding RNA (lncRNA) prognostic model for GC.
Abnormal expression of lncRNAs may indirectly reflect the occurrence and development of GC. As genes do not usually act alone, it is necessary to select suitable lncRNAs and establish a multi-lncRNA prediction model.
To construct a multi-lncRNA combination model to predict the prognosis of gastric cancer patients.
The RNA-seq dataset and clinical dataset of GC in The Cancer Genome Atlas were used in this study. The least absolute shrinkage and selection operator and COX models were used to identify meaningful modules and hub genes. Clinical data of 200 patients were used to evaluate the clinical significance of the multi-lncRNA combination model via survival analysis.
We found a 3-lncRNA combination prediction model: AC007991.4, AC079385.3, and AL109615.2. It could effectively predict the prognosis of GC. AC079385.3 was found to be a prognostic risk factor for GC, and it may play an important role in the development of GC. Least absolute shrinkage and selection operator improved prediction accuracy and interpretability through variable selection and regularization.
The 3-lncRNA combination model (risk score = -0.92 × AC007991.4 + 1.18 × AC079385.3 + 1.17 × AL109615.2) is an independent prognostic factor for GC.
Clinicians can obtain the expression levels of AC007991.4, AC079385.3, and AL109615.2 in tissue samples by real-time reverse transcription-polymerase chain reaction and calculate the corresponding risk values.