上尿路上皮癌(UTUC)是一种异质性较高的恶性肿瘤,占尿路上皮肿瘤的5%~10%,其预后受到患者特征、肿瘤病理特性及治疗方式等多种因素的综合影响。尽管根治性肾输尿管切除术(RNU)是治疗UTUC的金标准,但术后复发率和远期生存率差异显著。构...上尿路上皮癌(UTUC)是一种异质性较高的恶性肿瘤,占尿路上皮肿瘤的5%~10%,其预后受到患者特征、肿瘤病理特性及治疗方式等多种因素的综合影响。尽管根治性肾输尿管切除术(RNU)是治疗UTUC的金标准,但术后复发率和远期生存率差异显著。构建个体化的预后模型对于优化临床决策具有重要意义。近年来,诺模图、机器学习驱动模型、分子生物标志物模型及联合影像学与临床数据的多变量模型在UTUC预后预测中逐渐应用。其中,诺模图凭借直观性和高整合性成为临床预测的常用工具,机器学习模型在处理多模态数据方面表现出优势,分子生物标志物模型揭示了疾病的分子机制,而联合影像学模型通过融合影像和临床数据进一步提升了预测精准性。然而,现有模型的普适性和动态预测能力仍面临挑战,模型依赖于高质量的大规模数据,而临床实践中数据获取和整合存在难点。未来研究应聚焦于多中心、大样本的前瞻性研究以验证模型的可靠性,同时深入探索UTUC的分子机制,开发新的分子标志物,优化辅助治疗的适应症,并推动影像学技术与分子诊断手段的结合,为UTUC患者的精准医学和个体化治疗提供更可靠的工具和方法。Upper tract urothelial carcinoma (UTUC) is a highly heterogeneous malignancy, accounting for 5%~10% of urothelial tumors. Its prognosis is influenced by a combination of patient characteristics, tumor pathology, and treatment strategies. Despite radical nephroureterectomy (RNU) being the gold standard treatment for UTUC, significant variability in postoperative recurrence rates and long-term survival outcomes exists. Developing individualized prognostic models is crucial for optimizing clinical decision-making. Recently, nomograms, machine learning-based models, biomarker-driven molecular models, and multivariate models integrating imaging and clinical data have been increasingly utilized in UTUC prognostic prediction. Among these, nomograms have become widely used for their intuitive and integrative capabilities, machine learning models excel in handling multimodal data, biomarker-driven models uncover the molecular mechanisms of disease, and imaging-based models improve prediction accuracy by combining radiological and clinical data. However, existing models face challenges regarding generalizability and dynamic prediction capabilities, as they often rely on large-scale, high-quality datasets, which are difficult to obtain and integrate in clinical practice. Future research should focus on conducting multicenter, large-scale prospective studies to validate model reliability, exploring molecular mechanisms of UTUC, developing novel biomarkers, optimizing indications for adjuvant therapies, and promoting the integration of advanced imaging.展开更多
晚期尿路上皮癌严重影响患者生存。长期以来,以顺铂为基础的化疗方案作为晚期转移性尿路上皮癌的一线标准治疗方案,患者中位生存期仅8~14个月[1-3]。随着免疫时代的到来,多个程序性死亡-受体1(programmed cell death protein 1,PD-1)/...晚期尿路上皮癌严重影响患者生存。长期以来,以顺铂为基础的化疗方案作为晚期转移性尿路上皮癌的一线标准治疗方案,患者中位生存期仅8~14个月[1-3]。随着免疫时代的到来,多个程序性死亡-受体1(programmed cell death protein 1,PD-1)/程序性死亡-配体1(programmed cell death ligand 1,PD-L1)抑制剂被美国食品药品监督管理局(Food and Drug Administration,FDA)和国家药品监督管理局(National Medical Products Administration,NMPA)批准用于治疗晚期尿路上皮癌[4-6]。另外,成纤维生长因子受体(fibroblast growth factor receptor,FGFR)抑制剂与抗体偶联(antibody-drug conjugate,ADC)药物的研究取得突破,并先后被批准用于临床[7-11]。展开更多
铜死亡是一种特殊的细胞死亡形式。膀胱癌,特别是膀胱尿路上皮癌(BLCA),是全球十大最常见癌症之一。迄今为止,铜死亡在BLCA中的潜在作用尚不明确。在本研究中,我们基于从癌症基因组图谱(TCGA)和基因表达综合(GEO)数据库下载的数据,系统...铜死亡是一种特殊的细胞死亡形式。膀胱癌,特别是膀胱尿路上皮癌(BLCA),是全球十大最常见癌症之一。迄今为止,铜死亡在BLCA中的潜在作用尚不明确。在本研究中,我们基于从癌症基因组图谱(TCGA)和基因表达综合(GEO)数据库下载的数据,系统评估了509个BLCA样本中19个经过验证的与铜中毒相关基因(CRGs)介导的铜中毒模式。使用Kaplan-Meier方法分析不同风险组的总体生存率(OS)。使用基因集变异分析(GSVA)研究不同铜死亡簇(CR簇)之间的差异。使用单样本基因集富集分析(ssGSEA)讨CRG簇与免疫状态之间的潜在关系。我们使用GO (基因本体)和KEGG (京都基因与基因组百科全书)富集分析研究各种细胞生化过程。最后,我们建立了一个预后模型,以预测患者的生存结果,并进一步分析BLCA患者的预测特征与各种治疗反应之间的相关性。在本研究中,我们得出了两个CRG簇和基因簇,并建立了一个模型来量化个体BLCA患者的风险评分,发现其与多种临床特征密切相关,并能够准确预测BLCA患者的预后。我们相信,通过本研究,对单个样本中铜死亡介导模式的定量分析可能有助于提高我们对BLCA多组学特征的理解,并指导未来的治疗方案。Cuproptosis is a special form of cell death. Bladder cancer, especially Bladder Urothelial Carcinoma (BLCA), is one of the ten most common cancer types in the world. So far, the potential role of cuproptosis in BLCA is unclear. In the present study, we systematically evaluated the copper poisoning-mediated patterns of 509 BLCA samples based on 19 validated copper poisoning-related genes (CRGs) using data downloaded from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. Kaplan Meier method was used to analyze the overall survival rate (OS) of different risk groups. Gene Set Variation Analysis (GSVA) was used to study the functional differences between different cuproptosis clusters (CRG clusters). Single sample gene set enrichment analysis (ssGSEA) was used to explore the potential relationship between CRG clusters and immune status. We used GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis to study various cellular biochemical processes. Finally, we established a prognostic model to predict patients’ survival outcomes and to further analyze the correlation between the predictive characteristics of BLCA patients and various treatment responses. In this study, we derived two CRG clusters and gene clusters and also established a model to quantify the risk score of individual BLCA patients, which was found to be closely associated with various clinical characteristics and could precisely predict the prognosis of BLCA patients. We believe that through our study, quantitative analysis of cuproptosis-mediated patterns in a single sample may help to improve our understanding of the multi-omics characteristics of BLCA and guide future treatment regimens.展开更多
目的探讨尿路上皮癌(UC)患者术前天冬氨酸转氨酶/丙氨酸转氨酶(AST/ALT)比值与预后的关系。方法系统检索Web of Science、PubMed和Embase数据库,收集2024年8月前发表的关于术前AST/ALT预测UC预后的相关研究,根据纳入排除标准筛选文献,...目的探讨尿路上皮癌(UC)患者术前天冬氨酸转氨酶/丙氨酸转氨酶(AST/ALT)比值与预后的关系。方法系统检索Web of Science、PubMed和Embase数据库,收集2024年8月前发表的关于术前AST/ALT预测UC预后的相关研究,根据纳入排除标准筛选文献,提取数据后使用STATA 15.0软件分析患者总生存期(OS)、肿瘤特异性生存期(CSS)和无复发生存期(RFS)的风险比(HR)及其95%可信区间(CI)。结果共纳入14篇文献,涉及8190例患者。术前AST/ALT比值升高的UC患者OS(合并HR=1.92,95%CI:1.38~2.67,P<0.001)、CSS(合并HR=2.12,95%CI:1.48~3.05,P<0.001)和RFS(合并HR=1.63,95%CI:1.27~2.10,P<0.001)均较差。在亚组分析中,相对于上尿路尿路上皮癌(UTUC),术前AST/ALT比值对膀胱癌(BCa)患者的OS、CSS和RFS有更高的预测价值(P≤0.001);而与高加索人群相比,术前AST/ALT比值对亚洲人群的OS、CSS和RFS有更高的预测价值(P<0.001)。结论在UC患者中,特别是亚洲UC患者,术前较高的AST/ALT比值与不良的OS、CSS和RFS显著相关。展开更多
文摘上尿路上皮癌(UTUC)是一种异质性较高的恶性肿瘤,占尿路上皮肿瘤的5%~10%,其预后受到患者特征、肿瘤病理特性及治疗方式等多种因素的综合影响。尽管根治性肾输尿管切除术(RNU)是治疗UTUC的金标准,但术后复发率和远期生存率差异显著。构建个体化的预后模型对于优化临床决策具有重要意义。近年来,诺模图、机器学习驱动模型、分子生物标志物模型及联合影像学与临床数据的多变量模型在UTUC预后预测中逐渐应用。其中,诺模图凭借直观性和高整合性成为临床预测的常用工具,机器学习模型在处理多模态数据方面表现出优势,分子生物标志物模型揭示了疾病的分子机制,而联合影像学模型通过融合影像和临床数据进一步提升了预测精准性。然而,现有模型的普适性和动态预测能力仍面临挑战,模型依赖于高质量的大规模数据,而临床实践中数据获取和整合存在难点。未来研究应聚焦于多中心、大样本的前瞻性研究以验证模型的可靠性,同时深入探索UTUC的分子机制,开发新的分子标志物,优化辅助治疗的适应症,并推动影像学技术与分子诊断手段的结合,为UTUC患者的精准医学和个体化治疗提供更可靠的工具和方法。Upper tract urothelial carcinoma (UTUC) is a highly heterogeneous malignancy, accounting for 5%~10% of urothelial tumors. Its prognosis is influenced by a combination of patient characteristics, tumor pathology, and treatment strategies. Despite radical nephroureterectomy (RNU) being the gold standard treatment for UTUC, significant variability in postoperative recurrence rates and long-term survival outcomes exists. Developing individualized prognostic models is crucial for optimizing clinical decision-making. Recently, nomograms, machine learning-based models, biomarker-driven molecular models, and multivariate models integrating imaging and clinical data have been increasingly utilized in UTUC prognostic prediction. Among these, nomograms have become widely used for their intuitive and integrative capabilities, machine learning models excel in handling multimodal data, biomarker-driven models uncover the molecular mechanisms of disease, and imaging-based models improve prediction accuracy by combining radiological and clinical data. However, existing models face challenges regarding generalizability and dynamic prediction capabilities, as they often rely on large-scale, high-quality datasets, which are difficult to obtain and integrate in clinical practice. Future research should focus on conducting multicenter, large-scale prospective studies to validate model reliability, exploring molecular mechanisms of UTUC, developing novel biomarkers, optimizing indications for adjuvant therapies, and promoting the integration of advanced imaging.
文摘晚期尿路上皮癌严重影响患者生存。长期以来,以顺铂为基础的化疗方案作为晚期转移性尿路上皮癌的一线标准治疗方案,患者中位生存期仅8~14个月[1-3]。随着免疫时代的到来,多个程序性死亡-受体1(programmed cell death protein 1,PD-1)/程序性死亡-配体1(programmed cell death ligand 1,PD-L1)抑制剂被美国食品药品监督管理局(Food and Drug Administration,FDA)和国家药品监督管理局(National Medical Products Administration,NMPA)批准用于治疗晚期尿路上皮癌[4-6]。另外,成纤维生长因子受体(fibroblast growth factor receptor,FGFR)抑制剂与抗体偶联(antibody-drug conjugate,ADC)药物的研究取得突破,并先后被批准用于临床[7-11]。
文摘铜死亡是一种特殊的细胞死亡形式。膀胱癌,特别是膀胱尿路上皮癌(BLCA),是全球十大最常见癌症之一。迄今为止,铜死亡在BLCA中的潜在作用尚不明确。在本研究中,我们基于从癌症基因组图谱(TCGA)和基因表达综合(GEO)数据库下载的数据,系统评估了509个BLCA样本中19个经过验证的与铜中毒相关基因(CRGs)介导的铜中毒模式。使用Kaplan-Meier方法分析不同风险组的总体生存率(OS)。使用基因集变异分析(GSVA)研究不同铜死亡簇(CR簇)之间的差异。使用单样本基因集富集分析(ssGSEA)讨CRG簇与免疫状态之间的潜在关系。我们使用GO (基因本体)和KEGG (京都基因与基因组百科全书)富集分析研究各种细胞生化过程。最后,我们建立了一个预后模型,以预测患者的生存结果,并进一步分析BLCA患者的预测特征与各种治疗反应之间的相关性。在本研究中,我们得出了两个CRG簇和基因簇,并建立了一个模型来量化个体BLCA患者的风险评分,发现其与多种临床特征密切相关,并能够准确预测BLCA患者的预后。我们相信,通过本研究,对单个样本中铜死亡介导模式的定量分析可能有助于提高我们对BLCA多组学特征的理解,并指导未来的治疗方案。Cuproptosis is a special form of cell death. Bladder cancer, especially Bladder Urothelial Carcinoma (BLCA), is one of the ten most common cancer types in the world. So far, the potential role of cuproptosis in BLCA is unclear. In the present study, we systematically evaluated the copper poisoning-mediated patterns of 509 BLCA samples based on 19 validated copper poisoning-related genes (CRGs) using data downloaded from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. Kaplan Meier method was used to analyze the overall survival rate (OS) of different risk groups. Gene Set Variation Analysis (GSVA) was used to study the functional differences between different cuproptosis clusters (CRG clusters). Single sample gene set enrichment analysis (ssGSEA) was used to explore the potential relationship between CRG clusters and immune status. We used GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis to study various cellular biochemical processes. Finally, we established a prognostic model to predict patients’ survival outcomes and to further analyze the correlation between the predictive characteristics of BLCA patients and various treatment responses. In this study, we derived two CRG clusters and gene clusters and also established a model to quantify the risk score of individual BLCA patients, which was found to be closely associated with various clinical characteristics and could precisely predict the prognosis of BLCA patients. We believe that through our study, quantitative analysis of cuproptosis-mediated patterns in a single sample may help to improve our understanding of the multi-omics characteristics of BLCA and guide future treatment regimens.
文摘目的探讨尿路上皮癌(UC)患者术前天冬氨酸转氨酶/丙氨酸转氨酶(AST/ALT)比值与预后的关系。方法系统检索Web of Science、PubMed和Embase数据库,收集2024年8月前发表的关于术前AST/ALT预测UC预后的相关研究,根据纳入排除标准筛选文献,提取数据后使用STATA 15.0软件分析患者总生存期(OS)、肿瘤特异性生存期(CSS)和无复发生存期(RFS)的风险比(HR)及其95%可信区间(CI)。结果共纳入14篇文献,涉及8190例患者。术前AST/ALT比值升高的UC患者OS(合并HR=1.92,95%CI:1.38~2.67,P<0.001)、CSS(合并HR=2.12,95%CI:1.48~3.05,P<0.001)和RFS(合并HR=1.63,95%CI:1.27~2.10,P<0.001)均较差。在亚组分析中,相对于上尿路尿路上皮癌(UTUC),术前AST/ALT比值对膀胱癌(BCa)患者的OS、CSS和RFS有更高的预测价值(P≤0.001);而与高加索人群相比,术前AST/ALT比值对亚洲人群的OS、CSS和RFS有更高的预测价值(P<0.001)。结论在UC患者中,特别是亚洲UC患者,术前较高的AST/ALT比值与不良的OS、CSS和RFS显著相关。
