Analysis of Melanoma Gene Expression Signatures at the Single-Cell Level Uncovers 45-Gene Signature Related to Prognosis.
Mohamed Nabil BakrHaruko TakahashiYutaka KikuchiPublished in: Biomedicines (2022)
Since the current melanoma clinicopathological staging system remains restricted to predicting survival outcomes, establishing precise prognostic targets is needed. Here, we used gene expression signature (GES) classification and Cox regression analyses to biologically characterize melanoma cells at the single-cell level and construct a prognosis-related gene signature for melanoma. By analyzing publicly available scRNA-seq data, we identified six distinct GESs (named: "Anti-apoptosis", "Immune cell interactions", "Melanogenesis", "Ribosomal biogenesis", "Extracellular structure organization", and "Epithelial-Mesenchymal Transition (EMT)"). We verified these GESs in the bulk RNA-seq data of patients with skin cutaneous melanoma (SKCM) from The Cancer Genome Atlas (TCGA). Four GESs ("Immune cell interactions", "Melanogenesis", "Ribosomal biogenesis", and "Extracellular structure organization") were significantly correlated with prognosis ( p = 1.08 × 10 -5 , p = 0.042, p = 0.001, and p = 0.031, respectively). We identified a prognostic signature of melanoma composed of 45 genes (MPS_45). MPS_45 was validated in TCGA-SKCM (HR = 1.82, p = 9.08 × 10 -6 ) and three other melanoma datasets (GSE65904: HR = 1.73, p = 0.006; GSE19234: HR = 3.83, p = 0.002; and GSE53118: HR = 1.85, p = 0.037). MPS_45 was independently associated with survival ( p = 0.002) and was proved to have a high potential for predicting prognosis in melanoma patients.
Keyphrases
- single cell
- rna seq
- gene expression
- genome wide
- epithelial mesenchymal transition
- skin cancer
- dna methylation
- end stage renal disease
- high throughput
- newly diagnosed
- chronic kidney disease
- machine learning
- squamous cell carcinoma
- peritoneal dialysis
- cell death
- cell proliferation
- soft tissue
- drug induced
- data analysis
- artificial intelligence
- endoplasmic reticulum stress
- cell cycle arrest