ArticleFrontiers in cell and developmental biology2021
The Identification of the Metabolism Subtypes of Skin Cutaneous Melanoma Associated With the Tumor Microenvironment and the Immunotherapy.
Article in Frontiers in cell and developmental biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 14 citations in OpenAlex.
- Pan-cancer characterization of the pyrimidine catabolic enzyme UPB1 identifies a tumor-suppressive prognostic biomarker in skin cutaneous melanoma.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Tumor Microenvironmental Dynamics in Shaping Resistance to Therapeutic Interventions in Melanoma: A Narrative Review.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Integrated Meta-Analysis Identifies Keratin Family Genes and Associated Genes as Key Biomarkers and Therapeutic Targets in Metastatic Cutaneous Melanoma.Diagnostics (Basel, Switzerland) · 2025Article
- Research progress on the role of cationic amino acid transporter (CAT) family members in malignant tumors and immune microenvironment.Amino acids · 2023Review
- Imaging Mass Spectrometry for the Classification of Melanoma Based onInternational journal of molecular sciences · 2023Article
- TREM2 as a Potential Immune-Related Biomarker of Prognosis in Patients with Skin Cutaneous Melanoma Microenvironment.Disease markers · 2023Article
- Integrated analysis reveals the pivotal interactions between immune cells in the melanoma tumor microenvironment.Scientific reports · 2022Article
- Identification and Comprehensive Analysis of FREM2 Mutation as a Potential Prognostic Biomarker in Colorectal Cancer.Frontiers in molecular biosciences · 2022Article
- A novel prognostic model for prostate cancer based on androgen biosynthetic and catabolic pathways.Frontiers in oncology · 2022Article
- Identification of cell senescence molecular subtypes in prediction of the prognosis and immunotherapy of hepatitis B virus-related hepatocellular carcinoma.Frontiers in immunology · 2022Article
- Signal pathways of melanoma and targeted therapy.Signal transduction and targeted therapy · 2021Review
- Comparative Analysis of the Effect of the BRAF Inhibitor Dabrafenib in 2D and 3D Cell Culture Models of Human Metastatic Melanoma Cells.In vivo (Athens, Greece)Article
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Skin cutaneous melanoma (SKCM) is a highly aggressive and resistant cancer with immense metabolic heterogeneity. Here, we performed a comprehensive examination of the diverse metabolic signatures of SKCM based on non-negative matrix factorization (NMF) categorization, clustering SKCM into three distinct metabolic subtypes (C1, C2, and C3). Next, we evaluated the metadata sets of the metabolic signatures, prognostic values, transcriptomic features, tumor microenvironment signatures, immune infiltration, clinical features, drug sensitivity, and immunotherapy response of the subtypes and compared them with those of prior publications for classification. Subtype C1 was associated with high metabolic activity, low immune scores, and poor prognosis. Subtype C2 displayed low metabolic activity, high immune infiltration, high stromal score, and high expression of immune checkpoints, demonstrating the drug sensitivity to PD-1 inhibitors. The C3 subtype manifested moderate metabolic activity, high enrichment in carcinogenesis-relevant pathways, high levels of CpG island methylator phenotype (CIMP), and poor prognosis. Eventually, a 90-gene classifier was produced to implement the SKCM taxonomy and execute a consistency test in different cohorts to validate its reliability. Preliminary validation was performed to ascertain the role of SLC7A4 in SKCM. These results indicated that the 90-gene signature can be replicated to stably identify the metabolic classification of SKCM. In this study, a novel SKCM classification approach based on metabolic gene expression profiles was established to further understand the metabolic diversity of SKCM and provide guidance on precisely targeted therapy to patients with the disease.
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