ArticleHuman genomics2021
Identification of subgroups along the glycolysis-cholesterol synthesis axis and the development of an associated prognostic risk model.
Article in Human genomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- The Genetic Architecture of Vitamin D Deficiency among an Elderly Lebanese Middle Eastern Population: An Exome-Wide Association Study.Nutrients · 2023Pooled it
- Metabolic gene expression-based stratification and prognostic risk predictive model of head and neck squamous cell carcinoma.NPJ systems biology and applications · 2026Article
- Glycolytic-Cholesterol Subtypes of Severe Asthma Reveal Distinct Immune-Inflammatory and Metabolic Phenotypes.Journal of inflammation research · 2026Article
- Pan-cancer analysis and oncogenic implications ofJournal of cell communication and signaling · 2025Article
- Single-cell profiling deciphering cholesterol metabolism dysregulation in metastatic uveal melanoma and implicating SLC45A2 in its prognosis.Frontiers in immunology · 2025Article
- Exploring a specialized programmed-cell death patterns to predict the prognosis and sensitivity of immunotherapy in cutaneous melanoma via machine learning.Apoptosis : an international journal on programmed cell death · 2024Article
- Research on molecular characteristics of ADME-related genes in kidney renal clear cell carcinoma.Scientific reports · 2024Article
- Creatine kinase mitochondrial 2 promotes the growth and progression of colorectal cancerPeerJ · 2024Article
- A deep learning approach based on multi-omics data integration to construct a risk stratification prediction model for skin cutaneous melanoma.Journal of cancer research and clinical oncology · 2023Article
- Interaction between glycolysis‒cholesterol synthesis axis and tumor microenvironment reveal that gamma-glutamyl hydrolase suppresses glycolysis in colon cancer.Frontiers in immunology · 2022Article
- Comprehensive analysis of a glycolysis and cholesterol synthesis-related genes signature for predicting prognosis and immune landscape in osteosarcoma.Frontiers in immunology · 2022Article
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Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSkin cutaneous melanoma (SKCM) is one of the most highly prevalent and complicated malignancies. Glycolysis and cholesterogenesis pathways both play important roles in cancer metabolic adaptations. The main aims of this study are to subtype SKCM based on glycolytic and cholesterogenic genes and to build a clinical outcome predictive algorithm based on the subtypes.
methodsA dataset with 471 SKCM specimens was downloaded from The Cancer Genome Atlas (TCGA) database. We extracted and clustered genes from the Molecular Signatures Database v7.2 and acquired co-expressed glycolytic and cholesterogenic genes. We then subtyped the SKCM samples and validated the efficacy of subtypes with respect to simple nucleotide variations (SNVs), copy number variation (CNV), patients' survival statuses, tumor microenvironment, and proliferation scores. We also constructed a risk score model based on metabolic subclassification and verified the model using validating datasets. Finally, we explored potential drugs for high-risk SKCM patients.
resultsSKCM patients were divided into four subtype groups: glycolytic, cholesterogenic, mixed, and quiescent subgroups. The glycolytic subtype had the worst prognosis and MGAM SNV extent. Compared with the cholesterogenic subgroup, the glycolytic subgroup had higher rates of DDR2 and TPR CNV and higher proliferation scores and MK167 expression levels, but a lower tumor purity proportion. We constructed a forty-four-gene predictive signature and identified MST-321, SB-743921, Neuronal Differentiation Inducer III, romidepsin, vindesine, and YM-155 as high-sensitive drugs for high-risk SKCM patients.
conclusionsSubtyping SKCM patients via glycolytic and cholesterogenic genes was effective, and patients in the glycolytic-gene enriched group were found to have the worst outcome. A robust prognostic algorithm was developed to enhance clinical decisions in relation to drug administration.
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