Replication Data for: Precision Oncology, Signaling Pathways Reprogramming and Targeted Therapy: A Holistic Approach to Molecular Cancer Therapeutics

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.始建于2005年的TCGA研究网络（TCGA Research Network）已对大量人类肿瘤开展分型与分析，以发掘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密切相关，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数核心致病基因组合。2013年癌症世界峰会（Cancer World 2013）上，诺贝尔奖得主詹姆斯·D·沃森（James D. Watson）曾发表观点：“我们可以对所有曾存在过的DNA片段进行测序，但我认为我们无法找到癌症的阿喀琉斯之踵。”尤为重要的是，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，以此研究诱变剂的作用机制。例如，核糖核苷酸还原酶（ribonucleotide reductase, RnR）可催化由核糖核苷酸生成细胞分裂所需脱氧核糖核苷酸的反应，该酶的过表达与多种癌症相关，且其组成亚基的编码基因常发生突变，导致酶活性过度升高。但已有研究表明，细胞转化的诱因可能是细胞质物质而非细胞核，这一现象或许更适合通过表观遗传调控而非单纯的基因改变来解释。基于此，科研人员已开发出核糖核苷酸还原酶活性位点抑制剂，可在必要时通过生物物理手段使该酶失活，并已取得积极效果。基于基因组学研究对肿瘤开展的全面分析，应当能够揭示信号通路的异常，这些异常可反映癌症的易感特征，并为个性化治疗与新型联合疗法的开发提供潜在靶点的识别途径。为此，由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年发起的癌细胞图谱计划（Cancer Cell Map Initiative, CCMI），可帮助研究人员明确少数癌症相关的数百种基因突变如何影响特定关键蛋白质的活性，最终推动癌症的发生发展。鉴于目前已积累了大量不同癌症类型的序列数据，学界正致力于从现有信息中挖掘机制层面的见解，这需要整合计算与实验策略，以将这些异常置于癌细胞信号机制的高阶调控语境中进行分析。这正是癌细胞图谱计划的既定目标，其有望构建一个可用于癌症基因组解读的资源库，助力识别关键复合物与信号通路，从而更深入地理解各类癌症的生物学基础，最终实现癌症的精准治疗。