High Glycolytic Activity Signature Reveals CCNB2 as a Key Therapeutic Target in Triple-Negative Breast Cancer
- PMID: 39206892
- DOI: 10.31083/j.fbl2908308
High Glycolytic Activity Signature Reveals CCNB2 as a Key Therapeutic Target in Triple-Negative Breast Cancer
Abstract
Background: Aerobic glycolysis and the cell cycle are well-established tumor hallmarks. Understanding their relationship could help to unravel the pathogenic mechanisms of breast cancer (BC) and suggest potential new strategies for treatment.
Methods: Glycolysis-related genes (GRGs) were downloaded from the Reactome database and screened using univariate Cox analysis. The consensus clustering method was employed to identify a glycolytic activity signature (GAS) using the Gene Expression Omnibus (GEO) dataset. A nomogram risk prediction model was constructed using coefficients from univariate Cox analysis. Immune cell infiltration was evaluated using single-sample gene set enrichment analysis (ssGSEA) and the ESTIMATE algorithm. Gene co-expression modules were created using weighted correlation network analysis (WGCNA) to identify hub genes. Gene expression in three BC cell lines was quantified using Quantitative Reverse Transcriptase Polymera (qRT-PCR). Single-cell RNA sequencing (scRNA-seq) data was used to examine the relationship between GAS and hub genes. The sensitivity of different groups to cell cycle-related clinical drugs was also examined.
Results: BC with high GAS (HGAS) showed high tumor grade and recurrence rate. HGAS was a prognostic indicator of worse overall survival (OS) in BC patients. HGAS BC showed more abundant immune cells and significantly higher expression of immunomodulators compared to BC with low GAS (LGAS). HGAS BC also showed enhanced cell cycle pathway, with high mRNA and protein expression levels of Cyclin B2 (CCNB2), a key component of the cell cycle pathway. Importantly, scRNA-seq analysis revealed that elevated CCNB2 expression was positively correlated with HGAS in triple-negative BC (TNBC). This was validated in clinical samples from TNBC patients. High expression of CCNB2 was found in three BC cell lines, and was also an indicator of poor prognosis. HGAS BC showed high sensitivity to several cell cycle-related clinical drugs, with 9 of these also showing activity in BC with high CCNB2 expression.
Conclusions: HGAS was associated with enhanced cell cycle pathway and immune activity in BC. These results suggest that CCNB2 is a potential key therapeutic target in BC patients.
Keywords: CCNB2; cell cycle; glycolytic activity signature; immune cell infiltration; prognosis.
© 2024 The Author(s). Published by IMR Press.
Conflict of interest statement
The authors declare no conflict of interest.
Similar articles
-
Construction of a stromal cell-related prognostic signature based on a 101-combination machine learning framework for predicting prognosis and immunotherapy response in triple-negative breast cancer.Front Immunol. 2025 May 14;16:1544348. doi: 10.3389/fimmu.2025.1544348. eCollection 2025. Front Immunol. 2025. PMID: 40438115 Free PMC article.
-
Cyclin B2 (CCNB2) Stimulates the Proliferation of Triple-Negative Breast Cancer (TNBC) Cells In Vitro and In Vivo.Dis Markers. 2021 Jul 26;2021:5511041. doi: 10.1155/2021/5511041. eCollection 2021. Dis Markers. 2021. PMID: 34354775 Free PMC article.
-
A prognostic glycolysis-related gene signature in osteosarcoma: implications for metabolic programming, immune microenvironment, and drug response.PeerJ. 2025 Apr 29;13:e19369. doi: 10.7717/peerj.19369. eCollection 2025. PeerJ. 2025. PMID: 40321814 Free PMC article.
-
Proposing a novel molecular subtyping scheme for predicting distant recurrence-free survival in breast cancer post-neoadjuvant chemotherapy with close correlation to metabolism and senescence.Front Endocrinol (Lausanne). 2023 Oct 12;14:1265520. doi: 10.3389/fendo.2023.1265520. eCollection 2023. Front Endocrinol (Lausanne). 2023. PMID: 37900131 Free PMC article. Review.
-
Prognostic value of cyclin B1 and cyclin B2 expression in breast cancer: A systematic review and updated meta-analysis.Medicine (Baltimore). 2024 Jan 19;103(3):e37016. doi: 10.1097/MD.0000000000037016. Medicine (Baltimore). 2024. PMID: 38241547 Free PMC article.
MeSH terms
Substances
Grants and funding
LinkOut - more resources
Full Text Sources