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Updated: Jun 1, 2025

Analysis of Lymph Node Volume by Ultra-High-Frequency Ultrasound Imaging in the Braf/Pten Genetically Engineered Mouse Model of Melanoma
Published on: September 8, 2021
Dual role of Cathepsin S in cutaneous melanoma: insights from mendelian randomization and bioinformatics analysis
Linsa Zhou1, Qiang Zhou2, Qian Guo3
1Department of Burns and Plastic Surgery, The Second Affiliated Hospital of Shantou, University Medical College, Shantou, 515000, China.
Background:
Cutaneous melanoma (CM) is strongly associated with ultraviolet (UV) radiation, which contributes to the transformation of melanocytes into melanoma by inducing specific DNA damage. Here, we investigated the causal relationship between CM and genes related to sun-damaged skin, exploring specific target genes through various bioinformatics analyses.
Methods:
The Gene Expression Omnibus (GEO) database was used to obtain differential genes for CM and normal skin, and the Genome-Wide Association Studies (GWAS) analysis offered summary-level melanoma data for CM. Mendelian randomization (MR) analyses were used to examine the correlated linkage between CM and sun-exposed skin genes. The MR studies were conducted mainly using Inverse Variance Weighting (IVW), MR-Egger, Weighted Median, simple and weighted patterns to predict the correlation between sun-exposed skin and CM. Finally, the role of target genes in CM was revealed by pan-cancer analysis, expression and immune-infiltration evaluations, immuno-checking targeting analysis, immunotherapy response analysis, survival analysis, and protein-protein interactions (PPI) network and enrichment analyses.
Result:
Using matrix data from the GSE15605, GSE46517, and GSE111452 datasets, bioinformatics analysis revealed 232 differentially expressed genes (DEGs) between CM and typical tissues. MR analysis indicated that only CTSS has a deleterious effect linking skin exposure to sunlight and CM. Analysis of CTSS expression in tumors and tissues, along with the construction of a prognostic model, revealed that CTSS expression was higher in both primary CM and metastatic CM compared to normal skin tissue. However, patients with higher CTSS expression had a higher prognosis. In addition, high CTSS expression was significantly and positively correlated with tumor mutation rate, tumor microenvironment, immune cell infiltration, immune checkpoints and immunotherapy efficacy.
Conclusion:
Using MR analysis, we found a positive causal relationship between the CTSS gene in sun-exposed skin and CM. Additionally, increased CTSS may provide a basis for biomarker prediction of CM prognosis, immune status and immunotherapy.
Insights
This study reveals a causal link between the CTSS gene in sun-exposed skin and cutaneous melanoma (CM). Increased CTSS expression may serve as a biomarker for CM prognosis and immunotherapy response.
Area of Science:
- Oncology
- Dermatology
- Genetics
Background:
- Cutaneous melanoma (CM) is strongly linked to ultraviolet (UV) radiation-induced DNA damage.
- Investigating genes in sun-damaged skin is crucial for understanding CM development.
Purpose of the Study:
- To explore the causal relationship between CM and genes associated with sun-exposed skin.
- To identify specific target genes and their roles in CM pathogenesis and patient outcomes.
Main Methods:
- Utilized Gene Expression Omnibus (GEO) and Genome-Wide Association Studies (GWAS) data.
- Employed Mendelian Randomization (MR) analyses to assess gene-CM linkage.
- Conducted pan-cancer analysis, expression, immune-infiltration, and survival analyses for target genes.
Main Results:
- Identified 232 differentially expressed genes (DEGs) between CM and normal skin.
- MR analysis pinpointed CTSS as a gene with a deleterious effect linking sun exposure to CM.
- Higher CTSS expression correlated with better prognosis, increased tumor mutation rate, and enhanced immunotherapy efficacy.
Conclusions:
- Established a positive causal relationship between CTSS in sun-exposed skin and CM via MR analysis.
- CTSS shows potential as a biomarker for predicting CM prognosis, immune status, and immunotherapy response.

