{"title":"高糖酵解活性特征揭示 CCNB2 是三阴性乳腺癌的关键治疗靶点","authors":"Jing Liang, Haodi Ma, Shunshun Zhang, Yirui Dong, Jiayu Zheng, Li Zeng, Xin Xiong, Wenbin Huang, Qinan Yin, Xuewei Zheng","doi":"10.31083/j.fbl2908308","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":73069,"journal":{"name":"Frontiers in bioscience (Landmark edition)","volume":"29 8","pages":"308"},"PeriodicalIF":3.3000,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"High Glycolytic Activity Signature Reveals CCNB2 as a Key Therapeutic Target in Triple-Negative Breast Cancer.\",\"authors\":\"Jing Liang, Haodi Ma, Shunshun Zhang, Yirui Dong, Jiayu Zheng, Li Zeng, Xin Xiong, Wenbin Huang, Qinan Yin, Xuewei Zheng\",\"doi\":\"10.31083/j.fbl2908308\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":73069,\"journal\":{\"name\":\"Frontiers in bioscience (Landmark edition)\",\"volume\":\"29 8\",\"pages\":\"308\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2024-08-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in bioscience (Landmark edition)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.31083/j.fbl2908308\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in bioscience (Landmark edition)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31083/j.fbl2908308","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
背景:有氧糖酵解和细胞周期是公认的肿瘤特征。了解它们之间的关系有助于揭示乳腺癌(BC)的发病机制,并提出潜在的治疗新策略:方法:从 Reactome 数据库下载糖酵解相关基因(GRGs),并使用单变量 Cox 分析进行筛选。采用共识聚类法,利用基因表达总库(GEO)数据集确定糖酵解活性特征(GAS)。利用单变量 Cox 分析的系数构建了一个提名图风险预测模型。利用单样本基因组富集分析(ssGSEA)和ESTIMATE算法对免疫细胞浸润进行了评估。利用加权相关网络分析(WGCNA)创建了基因共表达模块,以确定枢纽基因。使用定量逆转录酶聚合反应(qRT-PCR)对三种 BC 细胞系中的基因表达进行量化。单细胞 RNA 测序(scRNA-seq)数据用于研究 GAS 与枢纽基因之间的关系。此外,还研究了不同组别对细胞周期相关临床药物的敏感性:结果:高GAS(HGAS)BC表现出高肿瘤分级和高复发率。HGAS是BC患者总生存期(OS)较差的预后指标。与低GAS BC(LGAS)相比,HGAS BC的免疫细胞更丰富,免疫调节剂的表达明显更高。HGAS BC还表现出细胞周期通路的增强,细胞周期通路的关键成分Cyclin B2(CCNB2)的mRNA和蛋白表达水平较高。重要的是,scRNA-seq 分析显示,CCNB2 表达的升高与三阴性 BC(TNBC)的 HGAS 呈正相关。这一点在 TNBC 患者的临床样本中得到了验证。在三种 BC 细胞系中发现了 CCNB2 的高表达,这也是预后不良的指标。HGAS BC对几种细胞周期相关的临床药物表现出高度敏感性,其中9种药物在CCNB2高表达的BC中也显示出活性:结论:HGAS 与 BC 中细胞周期通路和免疫活性的增强有关。这些结果表明,CCNB2 是治疗 BC 患者的潜在关键靶点。
High Glycolytic Activity Signature Reveals CCNB2 as a Key Therapeutic Target in Triple-Negative Breast Cancer.
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.