ArticleBioengineered2020
A new metabolic signature contributes to disease progression and predicts worse survival in melanoma.
Article in Bioengineered, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 11 citations in OpenAlex.
- Metabolism-associated molecular classification of cervical cancer.BMC women's health · 2023Article
- Overcoming chemoresistance to b-raf inhibitor in melanoma via targeted inhibition of phosphoenolpyruvate carboxykinase1 using 3-mercaptopropionic acid.Bioengineered · 2022Article
- MCT4/Lactate Promotes PD-L1 Glycosylation in Triple-Negative Breast Cancer Cells.Journal of oncology · 2022Article
- Identification of TYR, TYRP1, DCT and LARP7 as related biomarkers and immune infiltration characteristics of vitiligo via comprehensive strategies.Bioengineered · 2021Article
- Value of glycogen synthase 2 in intrahepatic cholangiocarcinoma prognosis assessment and its influence on the activity of cancer cells.Bioengineered · 2021Article
- Novel natural inhibitors targeting B-RAF(V600E) by computational study.Bioengineered · 2021Article
- Comprehensive Analysis of Monocarboxylate Transporter 4 (MCT4) expression in breast cancer prognosis and immune infiltration via integrated bioinformatics analysis.Bioengineered · 2021Article
- Transcriptome Analyses Identify a Metabolic Gene Signature Indicative of Antitumor Immunosuppression of EGFR Wild Type Lung Cancers With Low PD-L1 Expression.Frontiers in oncology · 2021Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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
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