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

Hu, Bingqian1; Hounye, Alphonse Houssou2; Wang, Zheng3; Qi, Min4; Zhang, Jianglin5,6

2023-02-06

10.3389/fonc.2023.1108128

Frontiers in Oncology   Impact Factor & Quartile

2234-943X

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.

bioinformatic tumor immune microenvironment melanoma cuproptosis immune-checkpoint inhibitors

SCI

English

Corresponding

Oncology

Oncology

WOS:000937979500001

FRONTIERS MEDIA SA

Web of Science

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

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.

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.

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).