Tan Si Yan Melanie, Sandanaraj Edwin, Tang Carol, Ang Beng Ti Christopher
Department of Research, National Neuroscience Institute, Singapore, 308433, Singapore.
School of Biological Sciences, Nanyang Technological University, Singapore, 637551, Singapore.
Adv Exp Med Biol. 2016;951:47-56. doi: 10.1007/978-3-319-45457-3_4.
The Cancer Genome Atlas effort has generated significant interest in a new paradigm shift in tumor tissue analysis, patient diagnosis and subsequent treatment decision. Findings have highlighted the limitation of sole reliance on histology, which can be confounded by inter-observer variability. Such studies demonstrate that histologically similar grade IV brain tumors can be divided into four molecular subtypes based on gene expression, with each subtype demonstrating unique genomic aberrations and clinical outcome. These advances indicate that curative therapeutic strategies must now take into account the molecular information in tumor tissue, with the goal of identifying molecularly stratified patients that will most likely to receive treatment benefit from targeted therapy. This in turn spares non-responders from chemotherapeutic side effects and financial costs. In advancing clinical stage drug candidates, the banking of brain tumor tissue necessitates the acquisition of not just tumor tissue with clinical history and robust follow-up, but also high quality molecular information such as somatic mutation, transcriptomic and DNA methylation profiles which have been shown to predict patient survival independent of current clinical indicators. Additionally, the derivation of cell lines from such tumor tissue facilitates the development of clinically relevant patient-derived xenograft mouse models that can prospectively reform the tumor for further studies, yet have retrospective clinical history to associate bench and in vivo findings with clinical data. This represents a core capability of Precision Medicine where the focus is on understanding inter- and intra-tumor heterogeneity so as to best tailor therapies that will result in improved treatment outcomes.
癌症基因组图谱计划引发了人们对肿瘤组织分析、患者诊断及后续治疗决策新范式转变的浓厚兴趣。研究结果凸显了单纯依赖组织学的局限性，观察者间的差异可能会混淆组织学诊断。此类研究表明，组织学上相似的IV级脑肿瘤可根据基因表达分为四种分子亚型，每种亚型都有独特的基因组畸变和临床结果。这些进展表明，根治性治疗策略现在必须考虑肿瘤组织中的分子信息，目标是识别出最有可能从靶向治疗中获益的分子分层患者。这反过来又使无反应者免受化疗副作用和经济成本的影响。在推进临床阶段的候选药物时，脑肿瘤组织库不仅需要获取有临床病史和完善随访的肿瘤组织，还需要高质量的分子信息，如体细胞突变、转录组和DNA甲基化谱，这些已被证明可独立于当前临床指标预测患者生存。此外，从这种肿瘤组织中衍生细胞系有助于开发具有临床相关性的患者来源的异种移植小鼠模型，这些模型可以前瞻性地重塑肿瘤以便进一步研究，但具有回顾性临床病史，可将实验室和体内研究结果与临床数据相关联。这代表了精准医学的一项核心能力，其重点是了解肿瘤间和肿瘤内的异质性，以便最好地定制治疗方案，从而改善治疗结果。
