PDF(Pubmed)
Abstract：
OBJECTIVE: Bladder cancer (BLCA) is a prevalent malignancy. Dysregulated propionate metabolism, a key cancer factor, suggests a potential target for treating metastatic cancer. However, a complete understanding of the link between propionate metabolism-related genes (PMRGs) and bladder cancer is lacking.
METHODS: From the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we gathered BLCA patient data, which was classified into distinct subgroups using non-negative matrix factorization (NMF). Survival and pathway analyses were conducted between these clusters. The PMRGs model, created through univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses, was assessed for prognostic significance using Kaplan-Meier and receiver operating characteristic (ROC) curves. A comprehensive evaluation included clinical, tumor microenvironment (TME), drug sensitivity, and immunotherapy analyses. Finally, the expression of HSD17B1 essential genes was confirmed via quantitative real-time polymerase chain reaction (qRT-PCR), with further validation through Transwell, wound healing, colony-formation, and EDU assays.
RESULTS: We discovered two distinct subcategories (CA and CB) within BLCA using NMF analysis, with CA demonstrating significantly better overall survival compared to CB. Additionally, six PMRGs emerged as critical factors associated with propionate metabolism and prognosis. Kaplan-Meier analysis revealed that high-risk PMRGs were correlated with a poorer prognosis in BLCA patients. Moreover, significant differences were observed between the two groups in terms of infiltrated immune cells, immune checkpoint expression, TME scores, and drug sensitivity. Notably, we found that suppressing HSD17B1 gene expression inhibited the invasion of bladder cancer cells.
CONCLUSIONS: Our study proposes molecular subtypes and a PMRG-based score as promising prognostic indicators in BLCA. Additionally, cellular experiments underscore the pivotal role of HSD17B1 in bladder cancer metastasis and invasion, suggesting its potential as a novel therapeutic target.
METHODS: From the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we gathered BLCA patient data, which was classified into distinct subgroups using non-negative matrix factorization (NMF). Survival and pathway analyses were conducted between these clusters. The PMRGs model, created through univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses, was assessed for prognostic significance using Kaplan-Meier and receiver operating characteristic (ROC) curves. A comprehensive evaluation included clinical, tumor microenvironment (TME), drug sensitivity, and immunotherapy analyses. Finally, the expression of HSD17B1 essential genes was confirmed via quantitative real-time polymerase chain reaction (qRT-PCR), with further validation through Transwell, wound healing, colony-formation, and EDU assays.
RESULTS: We discovered two distinct subcategories (CA and CB) within BLCA using NMF analysis, with CA demonstrating significantly better overall survival compared to CB. Additionally, six PMRGs emerged as critical factors associated with propionate metabolism and prognosis. Kaplan-Meier analysis revealed that high-risk PMRGs were correlated with a poorer prognosis in BLCA patients. Moreover, significant differences were observed between the two groups in terms of infiltrated immune cells, immune checkpoint expression, TME scores, and drug sensitivity. Notably, we found that suppressing HSD17B1 gene expression inhibited the invasion of bladder cancer cells.
CONCLUSIONS: Our study proposes molecular subtypes and a PMRG-based score as promising prognostic indicators in BLCA. Additionally, cellular experiments underscore the pivotal role of HSD17B1 in bladder cancer metastasis and invasion, suggesting its potential as a novel therapeutic target.
摘要：
目的：膀胱癌（BLCA）是一种常见的恶性肿瘤。丙酸代谢失调，一个关键的癌症因素，提示治疗转移性癌症的潜在靶点。然而,目前尚缺乏对丙酸代谢相关基因(PMRGs)与膀胱癌之间联系的全面了解.
方法：来自癌症基因组图谱（TCGA）和基因表达综合（GEO）数据库，我们收集了BLCA患者数据,使用非负矩阵分解(NMF)将其分为不同的子组。在这些簇之间进行存活和途径分析。PMRGs模型，通过单变量Cox和最小绝对收缩和选择运算符(LASSO)分析创建，使用Kaplan-Meier和受试者工作特征（ROC）曲线评估预后意义。综合评价包括临床，肿瘤微环境（TME），药物敏感性,和免疫疗法分析。最后,通过定量实时聚合酶链反应（qRT-PCR）确认HSD17B1必需基因的表达，通过Transwell进一步验证,伤口愈合，菌落形成,和EDU检测。
结果：我们使用NMF分析在BLCA中发现了两个不同的子类别（CA和CB），与CB相比，CA表现出明显更好的总体生存率。此外,6个PMRGs是与丙酸代谢和预后相关的关键因素。Kaplan-Meier分析显示，高危PMRGs与BLCA患者预后较差相关。此外，在浸润的免疫细胞方面，两组之间观察到显著差异，免疫检查点表达，TME得分,和药物敏感性。值得注意的是,我们发现抑制HSD17B1基因的表达抑制膀胱癌细胞的侵袭。
结论：我们的研究提出分子亚型和基于PMRG的评分作为BLCA的有希望的预后指标。此外,细胞实验强调了HSD17B1在膀胱癌转移和侵袭中的关键作用，表明其作为一种新的治疗靶点的潜力。
方法：来自癌症基因组图谱（TCGA）和基因表达综合（GEO）数据库，我们收集了BLCA患者数据,使用非负矩阵分解(NMF)将其分为不同的子组。在这些簇之间进行存活和途径分析。PMRGs模型，通过单变量Cox和最小绝对收缩和选择运算符(LASSO)分析创建，使用Kaplan-Meier和受试者工作特征（ROC）曲线评估预后意义。综合评价包括临床，肿瘤微环境（TME），药物敏感性,和免疫疗法分析。最后,通过定量实时聚合酶链反应（qRT-PCR）确认HSD17B1必需基因的表达，通过Transwell进一步验证,伤口愈合，菌落形成,和EDU检测。
结果：我们使用NMF分析在BLCA中发现了两个不同的子类别（CA和CB），与CB相比，CA表现出明显更好的总体生存率。此外,6个PMRGs是与丙酸代谢和预后相关的关键因素。Kaplan-Meier分析显示，高危PMRGs与BLCA患者预后较差相关。此外，在浸润的免疫细胞方面，两组之间观察到显著差异，免疫检查点表达，TME得分,和药物敏感性。值得注意的是,我们发现抑制HSD17B1基因的表达抑制膀胱癌细胞的侵袭。
结论：我们的研究提出分子亚型和基于PMRG的评分作为BLCA的有希望的预后指标。此外,细胞实验强调了HSD17B1在膀胱癌转移和侵袭中的关键作用，表明其作为一种新的治疗靶点的潜力。
