Abstract
Gastric cancer (GC) is one of the most common cancer worldwide. Although emerging evidence indicates that autophagy-related long non-coding RNA (lncRNA) plays an important role in the progression of GC, the prognosis of GC based on autophagy is still deficient. The Cancer Genome of Atlas stomach adenocarcinoma (TCGA-STAD) dataset was downloaded and separated into a training set and a testing set randomly. Then, 24 autophagy-related lncRNAs were found strongly associated with the survival of the TCGA-STAD dataset. 11 lncRNAs were selected to build the risk score model through the least absolute shrinkage and selection operator (LASSO) regression. Every patient got a risk score (RS), and patients were separated into a high-risk group and a low-risk group due to the median RS. The multivariate Cox analysis showed that the RS could be an independent prognosis predictor. The Kaplan-Meier survival analysis and the Receiver Operating Characteristic (ROC) curve indicated the model had an excellent prediction effect. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that the mRNAs in the prognostic network were mainly involved in the autophagy and ubiquitin-like protein ligase binding. Gene Set Enrichment Analysis (GSEA) analysis uncovered that the differentially expressed genes (DEGs) in the high-risk group partially participated in the ECM receptor interaction and other signaling pathways. Our results indicated that the risk score model based on the autophagy-related lncRNAs performed well in the prediction of prognosis for patients with GC.
Highlights
Gastric cancer (GC) is the fifth most prevalent tumor and one of the deadliest carcinomas worldwide (Bray et al, 2018), among which 90% are adenocarcinomas (Crew and Neugut, 2006)
Characteristics of patients The Cancer Genome Atlas (TCGA)-STAD dataset was patients diagnosed with stomach adenocarcinoma, which consisted of a total of 350 patients
Selecting of prognostic autophagy-related LncRNA for TCGASTAD dataset The autophagy-related long non-coding RNA (lncRNA) were obtained by using the correlation test of autophagy-related genes (Pearson correlation coefficient > 0.3, p < 0.001)
Summary
Gastric cancer (GC) is the fifth most prevalent tumor and one of the deadliest carcinomas worldwide (Bray et al, 2018), among which 90% are adenocarcinomas (Crew and Neugut, 2006). It is critical to construct an accurate prediction system for GC, which has the ability for early. Autophagy is a highly conserved and evolutionarily ancient catabolic process that can degrade the misfolded proteins and damaged organelles (Mizushima, 2007). It has been found that autophagy participated in plenty of physiological processes in mammals, including quality control of proteins and organelles, immunity, nutrient deprivation, hypoxia, drug stimuli, stress, and prevention of neurodegeneration (Mizushima and Komatsu, 2011). Autophagy can regulate biological process including apoptosis, protein synthesis, cell growth, and proliferation through the AMPK/mTOR pathway, PI3K/Akt/mTOR pathway, P53 pathway, and other signaling pathways (Chang et al, 2017; Ren et al, 2016; Zhao et al, 2015). The role of autophagy in the progression of carcinoma has several breakthroughs
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