An Independent Prognostic Model Based on Ten Autophagy-Related Genes in Pancreatic Cancer

Tian, Jiahui; Wu, Yi; Zhang, Xuan; Fang, Xiaoxiao; Fu, Chunyan

doi:10.21203/rs.3.rs-634359/v1

Cited by 1 publication

(1 citation statement)

References 22 publications

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“…The authors express their sincere gratitude to all the contributors who provided data to them, and the authors appreciate the fact that the TCGA database is available for free download and use. A preprint has been published previously at https://www.researchsquare.com/article/rs-634359/v1 [ 46 ]. The funding was provided by Hunan Provincial Health Commission (No.…”

Section: Acknowledgmentsmentioning

confidence: 99%

An Independent Prognostic Model Based on Ten Autophagy-Related Long Noncoding RNAs in Pancreatic Cancer Patients

Tian

Zeng

et al. 2022

Genetics Research

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Purpose. Pancreatic cancer (PC) is a common, highly lethal cancer with a low survival rate. Autophagy is involved in the occurrence and progression of PC. This study aims to explore the feasibility of using an autophagy-related long noncoding RNA (lncRNA) signature for assessing PC patient survival. Methods. We obtained RNA sequencing and clinical data of patients from the TCGA website. Autophagy genes were obtained from the Human Autophagy Database. The prognostic model, generated through univariate and multivariate Cox regression analyses, included 10 autophagy-related lncRNAs. Receiver operating characteristic (ROC) curves and forest plots were generated for univariate and multivariate Cox regression analyses, to examine the predictive feasibility of the risk model. Gene set enrichment analysis (GSEA) was used to screen enriched gene sets. Results. Twenty-eight autophagy-related lncRNAs were filtered out through univariate Cox regression analysis ( P < 0.001 ). Ten autophagy-related lncRNAs, including 4 poor prognosis factors and 6 beneficial prognosis factors, were further screened via multivariate Cox regression analysis. The AUC value of the ROC curve was 0.815. GSEA results demonstrated that cancer-related gene sets were significantly enriched. Conclusion. A signature based on ten autophagy-related lncRNAs was identified. This signature could be potentially used for evaluating clinical prognosis and might be used for targeted therapy against PC.

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Section: Acknowledgmentsmentioning

confidence: 99%