<b>The Precision Oncology Approach to Molecular Cancer Therapeutics Targeting Oncogenic Signaling Pathways Is a Means to an End</b>

The TCGA Research Network started in 2005 has profiled and analyzed a large number of human tumors to discover molecular aberrations at the DNA, RNA, protein, and epigenetic levels and thereby provided reliable diagnostic and prognostic biomarkers for different cancer types since then. The presence of mutated genes is strongly correlated with cancer incidence, very specific causative genes or a small set of genes for most cancers have not been confirmed after decades of genomic studies. Nobel laureate James D. Watson opined at Cancer World 2013: "We can go ahead and sequence every piece of DNA that has ever existed, but I don't think we'll find the Achilles heel of cancer. Importantly, it is not only necessary to associate genetic mutations with different cancers but also to work on the mechanism of action of mutagens by focusing on enzymes which could invariably mediate oncogenic transformations. For example, overexpression of the ribonucleotide reductase (RnR) enzyme which catalyzes the formation of deoxyribonucleotides from ribonucleotides necessary for cell division, is implicated in many forms of cancer and the genes for the components of the enzyme are often mutated, leading to hyperactivity of the enzyme. But there are instances indicating that cytoplasmic material rather than the karyoplast would be responsible for cellular transformation that might be better explained as a consequence of certain epigenetic modulation than purely genetic changes. RnR active site inhibitors have been developed accordingly to biophysically deactivate the enzyme when necessary, with positive results A comprehensive analysis of tumors based on their genomic studies must reveal the alterations in signaling pathways indicating patterns of vulnerabilities and the means to identify prospective targets for the development of personalized treatments and new combination therapies. In this regard, the Cancer Cell Map Initiative (CCMI), launched in 2015 by researchers at the University of California, San Francisco and the University of California, San Diego, allowed researchers to determine how hundreds of genetic mutations involved in a few types of cancer affect the activity of certain crucial proteins which ultimately lead to the manifestation of cancer. As there is a large amount of sequence data from many different cancer types, efforts are being made to extract mechanistic insights from the available information, requiring an integrated computational and experimental strategy that will help place these alterations in the higher order contexts of signaling mechanisms in cancer cells. This is the defined goal of the CCMI and has the potential to create a resource that can be used for cancer genome interpretation, enabling the identification of key complexes and pathways to better understand the biology underlying different cancer types and conditions for precise treatment of the disease.癌症基因组图谱（TCGA）研究网络于2005年启动，已对大量人类肿瘤样本开展组学表征与分析，旨在揭示DNA、RNA、蛋白质及表观遗传层面的分子畸变，自此为各类癌症提供了可靠的诊断与预后生物标志物。基因突变的存在与癌症发生高度相关，但历经数十年基因组学研究，学界仍未明确绝大多数癌症的特异性致病基因或少量核心致病基因集。诺贝尔奖得主詹姆斯·D·沃森（James D. Watson）在2013年癌症世界大会（Cancer World 2013）上曾指出："即便我们对所有曾存在过的DNA片段进行测序，我也不认为能找到癌症的‘阿喀琉斯之踵’。至关重要的是，我们不仅需要将基因突变与各类癌症建立关联，还应聚焦于可介导致癌转化的酶类，以此阐明诱变剂的作用机制。例如，核糖核苷酸还原酶（RnR）可催化核糖核苷酸转化为细胞分裂所需的脱氧核糖核苷酸，该酶的过表达与多种癌症密切相关，且其组成亚基的编码基因常发生突变，导致酶活性异常升高。但已有研究证实，部分细胞转化的诱因并非源自细胞核，而是细胞质成分，此类现象或许通过表观遗传调控即可得到更合理的解释，而非单纯依赖基因突变。据此，科研人员已开发出针对RnR活性位点的抑制剂，可在必要时通过生物物理手段使该酶失活，且已取得积极效果。基于基因组学研究的肿瘤全面分析，应能揭示信号通路的异常改变，从而明确癌症的脆弱性特征，并为个性化治疗与新型联合疗法的开发识别潜在靶点。为此，加州大学旧金山分校与加州大学圣地亚哥分校的研究人员于2015年发起了癌症细胞图谱计划（CCMI），该计划可帮助研究人员明确，涉及少数癌症类型的数百种基因突变如何影响关键蛋白质的活性，最终导致癌症的发生发展。鉴于目前已积累了大量不同癌症类型的测序数据，学界正致力于从现有数据中挖掘机制层面的认知，这需要整合计算与实验策略，以将这些基因异常置于癌细胞信号通路的高阶调控网络中进行解析。这正是CCMI的既定目标，该计划有望构建一个可用于癌症基因组解读的资源库，助力研究人员识别关键复合物与信号通路，从而更深入地阐明各类癌症及相关病症的生物学本质，最终实现癌症的精准治疗。