ArticleFrontiers in immunology2023
Comprehensive analysis of nicotinamide metabolism-related signature for predicting prognosis and immunotherapy response in breast cancer.
Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- An Integrative Strategy Delineates Modular Metabolic Remodeling and Potential Therapeutic Targets Across Metabolic Diseases.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Recognition and confirmation of key genes associated with nicotinamide metabolism in acute myocardial infarction.Hereditas · 2026Article
- Unlocking precision diagnostics: A multimodal framework integrating metabolomics with advanced machine learning techniques.PloS one · 2026Article
- Metabolic syndrome-related gene signature for prognosis and immune microenvironment prediction in hepatocellular carcinoma.Scientific reports · 2025Article
- Recent Advances in the Application of Cucurbitacin B as an Anticancer Agent.International journal of molecular sciences · 2025Review
- Deciphering the role of nicotinamide metabolism and melanin-related genes in acute myocardial infarction: a machine learning approach integrating bioinformatics analysis.The Korean journal of physiology & pharmacology : official journal of the Korean Physiological Society and the Korean Society of Pharmacology · 2025Article
- Construction of molecular subtypes and prognostic model for breast cancer based on sulfur metabolism-related genes.Translational cancer research · 2025Article
- Development of a m6A- and ferroptosis-related LncRNA signature for forecasting prognosis and treatment response in cervical cancer.BMC cancer · 2025Article
- Comprehensive analysis of lipid metabolic signatures identified CEBPD promotes breast cancer cell proliferation.Scientific reports · 2025Article
- Investigating the relevance of nucleotide metabolism in the prognosis of glioblastoma through bioinformatics models.Scientific reports · 2025Article
- NCellular and molecular life sciences : CMLS · 2025Article
- Construction of the bromodomain-containing protein-associated prognostic model in triple-negative breast cancer.Cancer cell international · 2025Article
- A prognostic model for breast cancer survival based on PCD and m6A gene interactions.Frontiers in immunology · 2025Article
- Article
- Prognostic and Immunological Significance of NMNAT1 in Colorectal and Pan-Cancer Contexts.OncoTargets and therapy · 2025Article
- The Role of PANoptosis-Related Genes in Predicting Breast Cancer Survival and Immune Prospect.BioMed research international · 2025Article
- Integrative modeling of malignant epithelial programs in EGFR-mutant LUAD via single-cell transcriptomics and multi-algorithm machine learning.Frontiers in immunology · 2025Article
- Identification and validation of biomarkers related to nicotinamide metabolic pathway activity in heart failure.Frontiers in genetics · 2025Article
- Integrating machine learning and multi-omics analysis to develop an asparagine metabolism immunity index for improving clinical outcome and drug sensitivity in lung adenocarcinoma.Immunologic research · 2024Article
- Identification of a PANoptosis-related Gene Signature for Predicting the Prognosis, Tumor Microenvironment and Therapy Response in Breast Cancer.Journal of Cancer · 2024Article
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Authors and funding
8 authors.
Funding
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Abstract
Background: Breast cancer (BC) is the most common malignancy among women. Nicotinamide (NAM) metabolism regulates the development of multiple tumors. Herein, we sought to develop a NAM metabolism-related signature (NMRS) to make predictions of survival, tumor microenvironment (TME) and treatment efficacy in BC patients. Methods: Transcriptional profiles and clinical data from The Cancer Genome Atlas (TCGA) were analyzed. NAM metabolism-related genes (NMRGs) were retrieved from the Molecular Signatures Database. Consensus clustering was performed on the NMRGs and the differentially expressed genes between different clusters were identified. Univariate Cox, Lasso, and multivariate Cox regression analyses were sequentially conducted to develop the NAM metabolism-related signature (NMRS), which was then validated in the International Cancer Genome Consortium (ICGC) database and Gene Expression Omnibus (GEO) single-cell RNA-seq data. Further studies, such as gene set enrichment analysis (GSEA), ESTIMATE, CIBERSORT, SubMap, and Immunophenoscore (IPS) algorithm, cancer-immunity cycle (CIC), tumor mutation burden (TMB), and drug sensitivity were performed to assess the TME and treatment response. Results: We identified a 6-gene NMRS that was significantly associated with BC prognosis as an independent indicator. We performed risk stratification according to the NMRS and the low-risk group showed preferable clinical outcomes ( Conclusions: The novel signature offers a promising way to evaluate the prognosis and treatment efficacy in BC patients, which may facilitate clinical practice and management.
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