A new metabolic signature contributes to disease progression and predicts worse survival in melanoma. Issue 1 (1st January 2020)

• Record Type: Journal Article
• Authors: Wan, Mengdi; Zhuang, Binyu; Dai, Xiao; Zhang, Liang; Zhao, Fangqing; You, Yan
• Is Part Of: Bioengineered. Volume 11:Issue 1(2020)
• Page Start: 1099
• Page End: 1111
• Publication Date: 2020-01-01
• Subjects: Metabolism -- progression -- prognosis -- melanoma -- immune; Biomedical engineering -- Periodicals; Biotechnology -- Periodicals; Microbiology -- Periodicals; 660.6
• DOI: 10.1080/21655979.2020.1822714
• Languages: English
• ISSNs: 2165-5987

Abstract

ABSTRACT: Metabolic reprogramming is a common hallmark of tumor cells and is a crucial mediator of resistance toward anticancer therapies. The pattern of a metabolism-related signature in melanoma remains unknown. Here, we explored the role of a multi-metabolism-related gene signature in melanoma.We used the training and validation sets to develop a multi-metabolism-related gene signature. Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) method were used for constructing a model. The predictive role of the metabolic signature with clinicopathological features of melanoma was also analyzed. Functional analysis of this metabolic signature was also investigated.A ten metabolism-related gene signature was identified and can stratify melanoma into high- and low- risk groups. The signature was correlated with progressive T stage, Breslow thickness, Clark level, and worse survival (all Ps < 0.01). This metabolic signature was shown as an independent prognostic factor and was also a predictive indicator for worse survival in various clinical and molecular features of melanoma. Furthermore, the metabolic signature was implicated in immune responses such as the regulation of T cell activation and cytokine activity. The metabolic signaturewas associated with the progression and worse survival of melanoma. Our study offered a valuable metabolism-targeted therapy approach for melanoma. Graphical abstract: