The identification of individual or clusters of predictive genetic alterations might help in defining the outcome of cancer treatment, allowing for the stratification of patients into distinct cohorts for selective therapeutic protocols. Neuroblastoma (NB) is the most common extracranial childhood tumour, clinically defined in five distinct stages (1–4 & 4S), where stages 3–4 define chemotherapy-resistant, highly aggressive disease phases. NB is a model for geneticists and molecular biologists to classify genetic abnormalities and identify causative disease genes. Despite highly intensive basic research, improvements on clinical outcome have been predominantly observed for less aggressive cancers, that is stages 1,2 and 4S. Therefore, stages 3–4 NB are still complicated at the therapeutic level and require more intense fundamental research. Using neuroblastoma as a model system, here we herein outline how cancer prediction studies can help at steering preclinical and clinical research toward the identification and exploitation of specific genetic landscape. This might result in maximising the therapeutic success and minimizing harmful effects in cancer patients.

中文翻译：

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癌症预测研究

识别单个或一组预测性遗传改变可能有助于确定癌症治疗的结果，允许将患者分层为不同的队列以进行选择性治疗方案。神经母细胞瘤 (NB) 是最常见的儿童颅外肿瘤，临床上定义为五个不同的阶段（1-4 和 4S），其中 3-4 阶段定义为耐药性、高度侵袭性疾病阶段。NB 是遗传学家和分子生物学家对遗传异常进行分类和识别致病基因的模型。尽管进行了高度密集的基础研究，但主要观察到侵袭性较低的癌症（即 1,2 和 4S 期）临床结果的改善。因此，3-4 阶段 NB 在治疗层面仍然很复杂，需要更深入的基础研究。使用神经母细胞瘤作为模型系统，我们在这里概述了癌症预测研究如何帮助引导临床前和临床研究朝向特定遗传景观的识别和开发。这可能会最大限度地提高治疗成功率并最大限度地减少对癌症患者的有害影响。