Identification of a metabolism-linked genomic signature for prognosis and immunotherapeutic efficiency in metastatic skin cutaneous melanoma

Area of Science:

• Oncology
• Genomics
• Cancer Metabolism

Background:

• Metastatic skin cutaneous melanoma (MSCM) is an aggressive malignancy with poor prognosis.
• Metabolic dysregulation is implicated in MSCM progression, but its genetic links to patient outcomes remain unclear.
• Understanding metabolism-linked genes (MRGs) is crucial for identifying novel prognostic markers in MSCM.

Purpose of the Study:

• To identify and validate a genomic signature based on differentially expressed MRGs (DE-MRGs) for predicting prognosis in MSCM.
• To develop a nomogram for survival prediction incorporating the genomic signature and clinical factors.
• To explore the relationship between the genomic signature and the tumor micro-environment (TME) in MSCM.

Main Methods:

• Utilized The Cancer Genome Atlas (TCGA) as a training set and Gene Expression Omnibus (GEO) as a validation set.
• Developed a 3-gene genomic signature (CD38, DHRS3, TYRP1) based on DE-MRGs between primary and metastatic melanoma.
• Constructed a nomogram for overall survival prediction and analyzed correlations with TME characteristics using Gene Set Variation Analysis (GSVA).

Main Results:

• A 3-gene genomic signature (CD38, DHRS3, TYRP1) was established, classifying MSCM patients into high-risk and low-risk groups.
• High-risk patients exhibited significantly poorer survival rates compared to low-risk patients across all datasets.
• The nomogram demonstrated high accuracy in predicting MSCM patient survival.
• The genomic signature was associated with immune-related processes and negatively correlated with immune cell infiltration and immune checkpoint expression in the TME.

Conclusions:

• The novel 3-gene genomic signature is a reliable predictor of outcomes in MSCM.
• The signature's association with the TME suggests a role for the tumor micro-environment in influencing prognosis.
• This genomic signature holds potential for facilitating personalized immunotherapy strategies in MSCM management.