Abstract
Pancreatic cancer (PC) is a highly malignant tumor in the digestive system. Both long noncoding RNAs (lncRNAs) and autophagy play vital roles in the development and progress of PC. Here, we constructed a prognostic risk score system based on the expression profile of autophagy-associated lncRNAs for prognostic prediction in PC patients. Firstly, we extracted the expression profile of lncRNA and clinical information from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. The autophagy-associated genes were from The Human Autophagy Database. Through Cox regression and survival analysis, we screened out seven autophagy-associated lncRNAs and built the risk score system in which the patients with PC were distinguished into high- and low-risk groups in both training and validation datasets. PCA plot displayed distinct discrimination, and risk score system displayed independently predictive value for PC patient survival time by multivariate Cox regression. Then, we built a lncRNA and mRNA co-expression network via Cytoscape and Sankey diagram. Finally, we analyzed the function of lncRNAs in high- and low-risk groups by gene set enrichment analysis (GSEA). The results showed that autophagy and metabolism might make significant effects on PC patients of low-risk groups. Taken together, our study provides a new insight to understand the role of autophagy-associated lncRNAs and finds novel therapeutic and prognostic targets in PC.
Highlights
Pancreatic cancer (PC) is a poorly prognostic malignant tumor
The RNA-seq data and clinical information of PC patients were downloaded from the The Cancer Genome Atlas (TCGA) data portal and International Cancer Genome Consortium (ICGC) databases, respectively
We extracted a total of 14,142 long noncoding RNAs (lncRNAs) expression data of tumors from PC tissues in the TCGA database
Summary
Pancreatic cancer (PC) is a poorly prognostic malignant tumor. Current treatments cannot significantly improve the prognosis of PC patients; the development of pancreatic cancer treatment is relatively slow compared to other tumors, so surgery still represents the most effective treatment to cure resectable pancreatic cancer. Due to the lack of diagnosis at the early stage and the highly malignant characteristics of PC, PC patients frequently exhibit lymph node metastasis and local invasion when the diagnosis is made, leading to approximately 80% of patients losing surgical chances [3]. The exploration of more effective innovative targets for pancreatic cancer is urgent and necessary. Autophagy plays a significant tumorigenic role in keeping cancer cell survival and promoting metabolism [5]. Researching new biomarkers related to autophagy to improve early diagnosis and assess prognosis is a promising avenue for PC patients
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