利用RPPA技术平台进行疾病信号通路全景扫描及分子机理挖掘

癌症是世界范围内疾病负担的一个主要因素,预计全球癌症负担至少将在未来20年呈持续增长的状态。癌症和肿瘤基因图谱(The Cancer Genome Atlas,TCGA)计划于2006年在全世界范围内联合启动,全世界无数顶尖肿瘤学家经过10多年的辛苦工作,于近期公布的“Pan-Cancer Atlas”泛癌症图谱的相关研究分为三个领域:肿瘤细胞起源(Cell-of-Origin Patterns)、致癌过程(Oncogenic Processes)和癌症信号通路(Signaling Pathways)。Pan-Cancer Atlas也提供了导致人类癌症的致癌过程的全景图,它揭示了种系基因变异体和体细胞突变如何在癌症进展中相互协作,并探索突变对细胞信号传导和免疫细胞组成的影响,为优先开发新疗法和免疫疗法提供了新观点。其中,反相蛋白微阵列(Reverse Phase Protein Array,RPPA)作为临床队列大规模样品高通量分析的独特技术平台,在基于大规模临床疾病样品的疾病信号通路全景扫描及分子机理信息挖掘工作当中提供了不可或缺的关键信息。

RPPA是一种结合平面高精度大规模样品蛋白抗原微阵列打印和抗体检测的高通量蛋白组学技术,该平台由MD安德森个体化治疗中心(IPCT)创始人Gordon Mills博士一手打造,并作为The Cancer Genome Atlas (TCGA)的核心蛋白组学技术平台,承担了33种癌种、超过10000例临床样本的数据的采集与分析工作,其相关研究成果发表在Nature、Cell、Cancer Cell、New England Journal of Medicine、Nature Biotechnology等学术杂志的高水平论文多达500篇以上。

RPPA技术平台设计严谨精密,流程高度自动化,质量控制极其严格,每次进行样品蛋白抗原微阵列打印,都会将多种阳性标准细胞系样品与待分析样品一起进行点阵,确保实验结果的高度可追溯、高度可信度与可重复性。RPPA可在15毫克组织中(米粒大小)一次性分析多达500种以上低丰度蛋白,且抗体反应过程及靶点信号采集彼此独立,避免了不同靶标抗体反应之间的串扰及不同靶标丰度差异较大带来的信号采集无法兼容的问题,具有其它高通量蛋白组学所无可比拟的超高特异性和灵敏度,可以对大量细胞表面受体蛋白、细胞信号关键蛋白及蛋白修饰(磷酸化、乙酰化、甲基化等)、蛋白酶类、转录因子等各类代表性靶标进行分门别类的系统深度检测,也可根据需求定制所需研究的靶点蛋白进行分析,包括直接和间接的上下游蛋白网络分析。RPPA可应用于蛋白功能与调控机理分析、细胞信号转导全景扫描、肿瘤标志物及蛋白分子分型、药物靶标发现与药物机理分析等不同领域。

肿瘤细胞具有很多关键性特征,包括自给自足生长信号(Self-Sufficiency in Growth Signals)、抗生长信号的不敏感(Insensitivity to Antigrowth Signals)、抵抗细胞死亡(Resisting Cell Death)、潜力无限的复制能力(Limitless Replicative Potential)、持续的血管生成(Sustained Angiogenesis)、组织浸润和转移(Tissue Invasion and Metastasis)、避免免疫摧毁(Avoiding Immune Destruction)、促进肿瘤的炎症(Tumor Promotion Inflammation)、细胞能量异常(Deregulating Cellular Energetics)、基因组不稳定和突变(Genome Instability and Mutation)等。这些肿瘤细胞区别于正常细胞的特征所涉及的信号通路靶点,是生物靶向治疗的基础。

全球的TCGA的科学家利用RPPA技术平台,已经对多达33个不同癌种大量病人样品的10个关键信号通路对肿瘤细胞的影响,其中就包括PI3K、RTK/RAS、MYC、DNA损伤修复、Cell Cycle、p53、TGF-β、Hippo、Notch、Wnt等通路。并且RPPA联合其他组学分析数据(如肿瘤标本的突变、拷贝数变化、mRNA表达和DNA甲基化数据),可以更为全面地分析肿瘤相关信号通路中显著存在个体和共同发生的可操作变异,还可以对这些肿瘤进行分子分型(分为64种类型),并提示靶向和联合治疗的机会。

  • 肿瘤全景信号通路扫描代表性信号通路及不同靶点肿瘤发生当中不同的突变频率(颜色强度表示平均变化的频率,致癌激活标注为红色,肿瘤抑制剂失活标注为蓝色)。

  • 不同肿瘤亚型的不同通路当中最常见基因突变频率。红色:激活事件;蓝色:失活事件;发生频率随颜色强度的变化。每一个通路的最后一行显示每种肿瘤类型中该通路的总体改变频率。

毫无疑问,Pan-Cancer Atlas的绘制完成,为肿瘤在人体内如何、何处以及为何出现,提供了一个相互关联的独特且全面深入的理解,必将会成为肿瘤精准医疗研发新疗法所需的重要资源,使得人们在战胜肿瘤的道路上前进了一大步。 但是,尽管TCGA以及Pan-Cancer Atlas为肿瘤学研究提供了宝贵的第一手资料,然而临床医学研究者往往因缺乏生物信息学基础,而在处理这些大规模的具有巨大潜在价值的癌症数据时感到心有余而力不足。作为RPPA在中国唯一授权的技术服务平台,非因生物提供与TCGA完全相同的RPPA标准化大规模样品制备、点阵、检测及相关生物信息学联合分析全套解决方案,并提供个性化的附加靶点分析服务,为中国临床转化医学研究和药物研发提供独特而强大的技术平台支持。



应用案例

根据疾病基因突变机理,构建动物和细胞模型

利用多种模拟疾病基因突变的工程化细胞系样品,进行RPPA微阵列全景信号通路扫描

确定肿瘤相关免疫调节机理为重点研究方向,进行多组学水平分析

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