Construction of Prognostic Risk Model of Patients with Skin Cutaneous Melanoma Based on TCGA-SKCM Methylation Cohort

Abstract

Skin cutaneous melanoma (SKCM) is a common malignant skin cancer. Early diagnosis could effectively reduce SKCM patient’s mortality to a large extent. We managed to construct a model to examine the prognosis of SKCM patients. The methylation-related data and clinical data of The Cancer Gene Atlas- (TCGA-) SKCM were downloaded from TCGA database. After preprocessing the methylation data, 21,861 prognosis-related methylated sites potentially associated with prognosis were obtained using the univariate Cox regression analysis and multivariate Cox regression analysis. Afterward, unsupervised clustering was used to divide the patients into 4 clusters, and weighted correlation network analysis (WGCNA) was applied to construct coexpression modules. By overlapping the CpG sites between the clusters and turquoise model, a prognostic model was established by LASSO Cox regression and multivariate Cox regression. It was found that 9 methylated sites included cg01447831, cg14845689, cg20895058, cg06506470, cg09558315, cg06373660, cg17737409, cg21577036, and cg22337438. After constructing the prognostic model, the performance of the model was validated by survival analysis and receiver operating characteristic (ROC) curve, and the independence of the model was verified by univariate and multivariate regression. It was represented that the prognostic model was reliable, and riskscore could be used as an independent prognostic factor in SKCM patients. At last, we combined clinical data and patient’s riskscore to establish and testify the nomogram that could determine patient’s prognosis. The results found that the reliability of the nomogram was relatively good. All in all, we constructed a prognostic model that could determine the prognosis of SKCM patients and screened 9 key methylated sites through analyzing data in TCGA-SKCM dataset. Finally, a prognostic nomogram was established combined with clinical diagnosed information and riskscore. The results are significant for improving the prognosis of SKCM patients in the future.

Experimentally validated oxidative stress -associated prognostic signatures describe the immune landscape and predict the drug response and prognosis of SKCM

“…SKCM continues to challenge oncology, with its heterogeneity in clinicopathological and cytological features complicating prognosis and treatment ( 30 ). Recent advancements have highlighted the role of oxidative stress in melanoma progression, metastasis, and resistance to therapy ( 31 ). This study leveraged high-throughput data to unravel the complex interplay between hub genes, oxidative stress, and the immune landscape in SKCM, offering novel insights into its pathogenesis and potential therapeutic targets.…”

Deciphering the role of wound healing genes in skin cutaneous melanoma: Insights into expression, methylation, mutations, and therapeutic implications

“…SKCM is primarily caused by exposure to ultraviolet (UV) radiation from sunlight, making fair‐skinned individuals more vulnerable. Genetic factors, including mutations in genes like BRAF and NRAS, contribute to susceptibility 3,4 . UV‐induced DNA damage and immune responses also play pivotal roles in the initiation and progression of this aggressive form of skin cancer 5 .…”

“…Genetic factors, including mutations in genes like BRAF and NRAS, contribute to susceptibility. 3 , 4 UV‐induced DNA damage and immune responses also play pivotal roles in the initiation and progression of this aggressive form of skin cancer. 5 Among the pivotal contributors to SKCM pathogenesis are Matrix Metalloproteinase family members, particularly Matrix Metalloproteinase 2 (MMP2) and Matrix Metalloproteinase 9 (MMP9), known for their critical roles in tumour development and metastasis by delaying wound healing.…”

A novel risk model based on anoikis: Predicting prognosis and immune infiltration in cutaneous melanoma

“…Cutaneous melanoma (CM) is a devastatingly aggressive malignancy with increasing incidence and poor prognosis ( Dika et al, 2019 ; Yu et al, 2022 ). The estimated annual incidence is approximatelymore than 100,000 cases globally and the mortality of CM accounts for 80%–85% of all skin cancer related death ( Yang et al, 2022 ).…”