中文版 | English
Title

A novel Cuprotosis-related signature predicts the prognosis and selects personal treatments for melanoma based on bioinformatics analysis

Author
Corresponding AuthorWang, Zheng; Qi, Min; Zhang, Jianglin
Publication Years
2023-02-06
DOI
Source Title
ISSN
2234-943X
Volume13
Abstract
BackgroundMelanoma is a common and aggressive cutaneous malignancy characterized by poor prognosis and a high fatality rate. Recently, due to the application of Immune-checkpoint inhibitors (ICI) in melanoma treatment, melanoma patients' prognosis has been tremendously improved. However, the treatment effect varies quite differently from patient to patient. In this study, we aim to construct and validate a Cuproptosis-related risk model to improve outcome prediction of ICIs in melanoma and divide patients into subtypes with different Cuproptosis-related genes. MethodsHere, according to differentially expressed genes from four melanoma datasets in GEO (Gene Expression Omnibus), and one in TCGA (The Cancer Genome Atlas) database, a novel signature was developed through LASSO and Cox regression analysis. We used 781 melanoma samples to examine the molecular subtypes associated with Cuproptosis-related genes and studied the related gene mutation and TME cell infiltration. Patients with melanoma can be divided into at least three subtypes based on gene expression profile. Survival pan-cancer analysis was also conducted for melanoma patients. ResultsThe Cuproptosis risk score can predict tumor immunity, subtype, survival, and drug sensitivity for melanoma. And Cuproptosis-associated subtypes can help predict therapeutic outcomes. ConclusionCuproptosis risk score is a promising potential biomarker in cancer diagnosis, molecular subtypes determination, TME cell infiltration characteristics, and therapy response prediction in melanoma patients.
Keywords
URL[Source Record]
Indexed By
Language
English
SUSTech Authorship
Corresponding
WOS Research Area
Oncology
WOS Subject
Oncology
WOS Accession No
WOS:000937979500001
Publisher
Data Source
Web of Science
Citation statistics
Cited Times [WOS]:0
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/501464
DepartmentShenzhen People's Hospital
Affiliation
1.Cent South Univ, Xiangya Hosp, Dept Dermatol, Changsha, Hunan, Peoples R China
2.Cent South Univ, Sch Math & Stat, Changsha, Peoples R China
3.Hunan First Normal Univ, Sch Comp Sci, Changsha, Peoples R China
4.Cent South Univ, Xiangya Hosp, Dept Plast Surg, Changsha, Peoples R China
5.Southern Univ Sci & Technol, Jinan Univ, Shenzhen Peoples Hosp, Affiliated Hosp 1,Clin Med Coll 2,Dept Dermatol, Shenzhen, Guangdong, Peoples R China
6.Shenzhen Peoples Hosp, Candidate Branch, Natl Clin Res Ctr Skin Dis, Shenzhen, Guangdong, Peoples R China
Corresponding Author AffilicationShenzhen People's Hospital
Recommended Citation
GB/T 7714
Hu, Bingqian,Hounye, Alphonse Houssou,Wang, Zheng,et al. A novel Cuprotosis-related signature predicts the prognosis and selects personal treatments for melanoma based on bioinformatics analysis[J]. Frontiers in Oncology,2023,13.
APA
Hu, Bingqian,Hounye, Alphonse Houssou,Wang, Zheng,Qi, Min,&Zhang, Jianglin.(2023).A novel Cuprotosis-related signature predicts the prognosis and selects personal treatments for melanoma based on bioinformatics analysis.Frontiers in Oncology,13.
MLA
Hu, Bingqian,et al."A novel Cuprotosis-related signature predicts the prognosis and selects personal treatments for melanoma based on bioinformatics analysis".Frontiers in Oncology 13(2023).
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