ArticleOncology reports2020
Identification of a prognosis‑associated signature associated with energy metabolism in triple‑negative breast cancer.
Article in Oncology reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 18 citations in OpenAlex.
- Glucose oxidase-powered nanocatalytic medicine: Rewiring tumor metabolism for multimodal cancer therapy.Materials today. Bio · 2026Review
- Metabolic Adaptations in Cancer Progression: Optimization Strategies and Therapeutic Targets.Cancers · 2025Review
- Identification of Energy Metabolism-Related Subtypes and Diagnostic Biomarkers for Osteoarthritis by Integrating Bioinformatics and Machine Learning.Journal of multidisciplinary healthcare · 2025Article
- Identification and panoramic analysis of drug response-related genes in triple negative breast cancer using as an example NVP-BEZ235.Scientific reports · 2023Article
- Immature natural killer cells promote progression of triple-negative breast cancer.Science translational medicine · 2023Article
- Male triple negative axillary accessory breast cancer-a case report.Translational cancer research · 2022Article
- Development of a Gene Risk Signature for Patients of Pancreatic Cancer.Journal of healthcare engineering · 2022Article
- Facts and Perspectives: Implications of tumor glycolysis on immunotherapy response in triple negative breast cancer.Frontiers in oncology · 2022Review
- Construction and Validation of a Prognostic Risk Model for Triple-Negative Breast Cancer Based on Autophagy-Related Genes.Frontiers in oncology · 2022Article
- Review
- Diclofenac impairs the proliferation and glucose metabolism of triple-negative breast cancer cells by targeting the c-Myc pathway.Experimental and therapeutic medicine · 2021Article
- Case Report of a Breast Mass with Three Types of Malignant Tumors-Squamous Cell Carcinoma, Invasive Ductal Carcinoma, and Breast Sarcoma.OncoTargets and therapy · 2021Article
- Glucose Metabolism in Cancer: The Warburg Effect and Beyond.Advances in experimental medicine and biology · 2021Article
- Identification of a Novel Glycolysis-Related Gene Signature for Predicting Breast Cancer Survival.Frontiers in oncology · 2020Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
At present, a large number of exciting results have been found regarding energy metabolism within the triple‑negative breast cancer (TNBC) field. Apart from aerobic glycolysis, a number of other catabolic pathways have also been demonstrated to participate in energy generation. However, the prognostic value of energy metabolism for TNBC currently remains unclear. In the present study, the association between gene expression profiles of energy metabolism and outcomes in patients with TNBC was examined using datasets obtained from the Gene Expression Omnibus and The Cancer Genome Atlas. In total, four robust TNBC subtypes were identified on the basis of negative matrix factorization clustering and gene expression patterns, which exhibited distinct immunological, molecular and prognostic (disease‑free survival) features. The differentially expressed genes were subsequently identified from the subgroup that demonstrated the poorest prognosis compared with the remaining 3 subgroups, where their biological functions were assessed further by means of gene ontology enrichment analysis. Any signatures found to be associated with energy metabolism were then established using the Cox proportional hazards model to assess patient prognosis. According to results of Kaplan‑Meier analysis, the constructed signature consisting of eight genes that were associated with energy metabolism distinguished patient outcomes into low‑ and high‑risk groups. In addition, this signature, which was found to be markedly associated with the clinical characteristics of the patients, served as an independent factor in predicting TNBC patient prognosis. According to gene set enrichment analysis, the gene sets related to the high‑risk group participated in the MAPK signal transduction pathway, focal adhesion and extracellular matrix receptor interaction, whilst those related to the low‑risk group were revealed to be mainly associated with mismatch repair and propanoate metabolism. Findings from the present study shed new light on the role of energy metabolism within TNBC, where the eight‑gene signature associated with energy metabolism constructed can be utilized as a new prognostic marker for predicting survival in patients with TNBC.
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