Bibliographic Details
| Title: |
Construction of a prognostic model for cutaneous melanoma based on ferroptosis related genes in the TCGA database |
| Authors: |
Jinglong LIAO, Hanshen LUO, Bo HUO |
| Source: |
Pifu-xingbing zhenliaoxue zazhi, Vol 30, Iss 4, Pp 307-313 (2023) |
| Publisher Information: |
editoiral office of Journal of Diagnosis and Therapy on Dermato-venereology, 2023. |
| Publication Year: |
2023 |
| Collection: |
LCC:Dermatology |
| Subject Terms: |
skin cutaneous melanoma, ferroptosis-related genes, prediction model, Dermatology, RL1-803 |
| More Details: |
Objective A ferroptosis-related prognostic model for skin melanoma was constructed based on the TCGA database to reveal the relationship between ferroptosis and the prognosis of skin melanoma. Methods The ferroptosis-related genes were obtained from the KEGG database, and the data of skin melanoma were obtained from the TCGA database. The R package was used to obtain the clinical information of the corresponding samples from the TCGA database. Univariate Cox regression analysis was used to screen prognosis-related genes. Lasso regression was used for further variable selection, and the prognostic model was constructed based on the ggrisk package. The survival and the survminer packages were used to draw the survival curve. Results After removal of the overfitting genes, 12 prognosis-related ferroptosis genes were identified. Seven out of the 12 ferroptosis-related genes, including NOX4, VDAC2, POR, CHMP5, GCH1, CP, and ACSL4, were finally used to construct prognostic model. Survival analysis showed that the survival time of patients at the high-risk was significantly shorter than that at the low-risk (P |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
Chinese |
| ISSN: |
1674-8468 |
| Relation: |
http://pfxbzlx.gdvdc.com/EN/10.3969/j.issn.1674-8468.2023.04.002; https://doaj.org/toc/1674-8468 |
| DOI: |
10.3969/j.issn.1674-8468.2023.04.002 |
| Access URL: |
https://doaj.org/article/a09ec394de7c47459f519b528599a595 |
| Accession Number: |
edsdoj.09ec394de7c47459f519b528599a595 |
| Database: |
Directory of Open Access Journals |
