High Glycolytic Activity Signature Reveals CCNB2 as a Key Therapeutic Target in Triple-Negative Breast Cancer

被引:0
作者
Liang, Jing [1 ,2 ,3 ]
Ma, Haodi [2 ]
Zhang, Shunshun [2 ]
Dong, Yirui [2 ]
Zheng, Jiayu [2 ]
Zeng, Li [2 ]
Xiong, Xin [4 ]
Huang, Wenbin [1 ,3 ]
Yin, Qinan [1 ,2 ,3 ]
Zheng, Xuewei [1 ,2 ,3 ]
机构
[1] Henan Univ Sci & Technol, Dept Pathol, Affiliated Hosp 1, Luoyang 471003, Henan, Peoples R China
[2] Henan Univ Sci & Technol, Sch Med Technol & Engn, Precis Med Lab, Luoyang 471003, Henan, Peoples R China
[3] Henan Univ Sci & Technol, Henan Engn Res Ctr Digital Pathol & Artificial Int, Affiliated Hosp 1, Luoyang 471003, Henan, Peoples R China
[4] Nanchang Univ, Affiliated Hosp 1, Jiangxi Med Coll, Dept Pathol, Nanchang 330008, Jiangxi, Peoples R China
来源
FRONTIERS IN BIOSCIENCE-LANDMARK | 2024年 / 29卷 / 08期
关键词
glycolytic activity signature; cell cycle; CCNB2; immune cell infiltration; prognosis; CELL-GROWTH; INHIBITION; EXPRESSION; PROTEIN;
D O I
10.31083/j.fbl2908308
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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.
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页数:13
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