Crocetto Felice, Amicuzi Ugo, Musone Michele, Magliocchetti Marco, Di Lieto Dario, Tammaro Simone, Pastore Antonio Luigi, Fuschi Andrea, Falabella Roberto, Ferro Matteo, Bianchi Roberto, Finati Marco, Busetto Gian Maria, Lucarelli Giuseppe, Del Giudice Francesco, Caputo Vincenzo Francesco, Balsamo Raffaele, Terracciano Daniela
Department of Neurosciences, Reproductive Sciences and Odontostomatology, University of Naples "Federico II", Naples, Italy.
Urology Unit, Department of Medico-Surgical Sciences and Biotechnologies, Faculty of Pharmacy and Medicine, Sapienza University of Rome, 04100, Latina, Italy.
J Liq Biopsy. 2025 Jul 8;9:100310. doi: 10.1016/j.jlb.2025.100310. eCollection 2025 Sep.
Bladder cancer is the ninth most common malignancy worldwide, with two clinically distinct forms: non-muscle-invasive disease, characterized by high recurrence and excellent long-term survival, and muscle-invasive disease, associated with poorer outcomes. Current surveillance-cystoscopy and urine cytology-offers high specificity but is invasive, costly, and insensitive to low-grade tumors, underscoring the need for reliable, non-invasive biomarkers. Liquid biopsy approaches in urine and blood have demonstrated promise for real-time assessment of tumor burden, molecular heterogeneity, and early recurrence. Circulating tumor DNA (ctDNA) assays detect tumor-derived genetic and epigenetic alterations, enabling dynamic monitoring of minimal residual disease and treatment response. Methylation-based tests and CpG-targeted sequencing in urine achieve high diagnostic accuracy, potentially reducing dependence on cystoscopy. Molecular classification of bladder tumors into luminal and basal subtypes has refined therapeutic strategies: FGFR inhibitors for luminal-papillary tumors, EGFR-targeted and chemotherapy approaches for basal/squamous cases, and immune-checkpoint inhibitors guided by immune-infiltration profiles. Integration of artificial intelligence with multi-omic liquid biopsy data further enhances predictive modeling for recurrence, treatment response, and minimal residual disease detection. Despite these advances, clinical implementation faces challenges including pre-analytical variability, lack of standardized assays, limited prospective validation, and unclear cost-effectiveness. Harmonized protocols, large multicenter trials, and health-economic evaluations are essential to translate liquid biopsy technologies into routine practice. Future integration with advanced imaging, tissue biopsy, and digital pathology-supported by multidisciplinary collaboration and formal guideline endorsement-holds the potential to personalize bladder cancer management, reduce invasive procedures, and improve patient outcomes.
膀胱癌是全球第九大常见恶性肿瘤,有两种临床特征不同的类型:非肌层浸润性疾病,其特点是高复发率和良好的长期生存率;以及肌层浸润性疾病,预后较差。目前的监测性膀胱镜检查和尿液细胞学检查具有高特异性,但具有侵入性、成本高且对低级别肿瘤不敏感,这突出表明需要可靠的非侵入性生物标志物。尿液和血液中的液体活检方法已显示出对肿瘤负荷、分子异质性和早期复发进行实时评估的前景。循环肿瘤DNA(ctDNA)检测可检测肿瘤衍生的基因和表观遗传改变,从而能够动态监测微小残留疾病和治疗反应。尿液中基于甲基化的检测和靶向CpG的测序可实现高诊断准确性,有可能减少对膀胱镜检查的依赖。将膀胱肿瘤分子分类为管腔型和基底型亚型已完善了治疗策略:管腔乳头状肿瘤使用FGFR抑制剂,基底/鳞状病例使用EGFR靶向治疗和化疗方法,以及根据免疫浸润谱指导使用免疫检查点抑制剂。人工智能与多组学液体活检数据的整合进一步增强了对复发、治疗反应和微小残留疾病检测的预测模型。尽管取得了这些进展,但临床应用面临挑战,包括分析前变异性、缺乏标准化检测方法、前瞻性验证有限以及成本效益不明确。统一的方案、大型多中心试验和卫生经济评估对于将液体活检技术转化为常规实践至关重要。未来与先进成像、组织活检和数字病理学的整合——在多学科合作和正式指南认可的支持下——有可能实现膀胱癌管理的个性化,减少侵入性程序,并改善患者预后。