Neagu Mihai Cristian, David Vlad Laurenţiu, Iacob Emil Radu, Chiriac Sorin Dan, Muntean Florin Lucian, Boia Eugen Sorin
Department of Pediatric Surgery and Orthopedics, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy Timisoara, 2nd Eftimie Murgu Square, 300041 Timisoara, Romania.
Department X-Surgery II, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy Timisoara, 2nd Eftimie Murgu Square, 300041 Timisoara, Romania.
Medicina (Kaunas). 2025 Mar 12;61(3):491. doi: 10.3390/medicina61030491.
Nephroblastoma is a complex childhood cancer with a generally favorable prognosis, well-defined incidence, and demographic profile but with significant challenges in terms of recurrence and long-term health outcomes. Although the management of this pathology has evolved, leading to improved survival rates, continued research into the long-term effects of treatment and the genetic factors influencing its development is still required. The survival landscape for Wilms tumor is evolving, with emerging research focusing on therapeutic biomarkers and genetic predispositions that influence treatment efficacy and survival rates. Identifying predictors for treatment response, such as specific genetic markers and histologic features, emerges as a critical area of study that could refine future interventions. The management of Wilms tumor is complex, taking into account the stage of the disease, histological classification, and individual patient factors, including age and the presence of syndromic associations. As treatment paradigms evolve, the integration of precision medicine approaches may enhance the ability of clinicians to personalize treatment to improve long-term survival outcomes for a broader range of patients. Recent advances in technology, including machine-learning approaches, have facilitated the identification of therapeutic biomarkers that correlate with clinical outcomes. This innovative method enhances the ability to integrate clinical and genetic data to predict disease trajectory and therapeutic response.
肾母细胞瘤是一种复杂的儿童癌症,其总体预后良好,发病率和人口统计学特征明确,但在复发和长期健康结局方面存在重大挑战。尽管对这种疾病的治疗方法已经有所发展,生存率有所提高,但仍需要继续研究治疗的长期影响以及影响其发展的遗传因素。威尔姆斯瘤的生存情况正在不断变化,新出现的研究聚焦于影响治疗效果和生存率的治疗生物标志物和遗传易感性。识别治疗反应的预测指标,如特定的基因标记和组织学特征,已成为一个关键的研究领域,有望优化未来的干预措施。威尔姆斯瘤的治疗很复杂,需要考虑疾病分期、组织学分类以及个体患者因素,包括年龄和综合征关联情况。随着治疗模式的发展,精准医学方法的整合可能会增强临床医生根据患者个体情况制定个性化治疗方案的能力,从而提高更广泛患者群体的长期生存结局。包括机器学习方法在内的技术最新进展,有助于识别与临床结局相关的治疗生物标志物。这种创新方法增强了整合临床和基因数据以预测疾病发展轨迹和治疗反应的能力。