Open AccessConstruction of autophagy prognostic signature and analysis of prospective molecular mechanisms in skin cutaneous melanoma patients
Author(s) -
Shijie Liao,
Juan He,
Chong Liu,
Zide Zhang,
Hongyu Liao,
Zuo-Wei Liao,
Chaojie Yu,
Jian Guan,
Hao Yuan Mo,
Zhenchao Yuan,
Tuo Liang,
Zhaojun Lu,
Guoyong Xu,
Zequn Wang,
Jiarui Chen,
Jie Jiang,
Xinli Zhan
Publication year - 2021
Publication title -
medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.59
H-Index - 148
eISSN - 1536-5964
pISSN - 0025-7974
DOI - 10.1097/md.0000000000026219
Subject(s) - medicine , autophagy , immunohistochemistry , nomogram , gene signature , bioinformatics , gene , gene expression , oncology , cancer research , biology , genetics , apoptosis
Background: Autophagy is closely related to skin cutaneous melanoma (SKCM), but the mechanism involved is unclear. Therefore, exploration of the role of autophagy-related genes (ARGs) in SKCM is necessary. Materials and methods: Differential expression autophagy-related genes (DEARGs) were first analysed. Univariate and multivariate Cox regression analyses were used to evaluate the expression of DEARGs and prognosis of SKCM. Further, the expression levels of prognosis-related DEARGs were verified by immunohistochemical (IHC) staining. Finally, gene set enrichment analysis (GSEA) was used to explore the underlying molecular mechanisms of SKCM. Results: Five ARGs ( APOL1 , BIRC5, EGFR, TP63, and SPNS1 ) were positively correlated with the prognosis of SKCM. IHC verified the results of the differential expression of these 5 ARGs in the bioinformatics analysis. According to the receiver operating characteristic curve, the signature had a good performance at predicting overall survival in SKCM. The signature could classify SKCM patients into high-risk or low-risk groups according to distinct overall survival. The nomogram confirmed that the risk score has a particularly large impact on the prognosis of SKCM. Calibration plot displayed excellent agreement between nomogram predictions and actual observations. Principal component analysis indicated that patients in the high-risk group could be distinguished from those in low-risk group. Results of GSEA indicated that the low-risk group is enriched with aggressiveness-related pathways such as phosphatidylinositol-3-kinase/protein kinase B and mitogen-activated protein kinase signalling pathways. Conclusion: Our study identified a 5-gene signature. It revealed the mechanisms of autophagy that lead to the progression of SKCM and established a prognostic nomogram that can predict overall survival of patients with SKCM. The findings of this study provide novel insights into the relationship between ARGs and prognosis of SKCM.