Onco-Multi-OMICS Approach: A New Frontier in Cancer Research.
Onco-Multi-OMICS Approach: A New Frontier in Cancer Research.
复制标题
DOI：
10.1155/2018/9836256
复制
发表时间：
2018
影响因子：
--
通讯作者：
Shekhar HU
中科院分区：
文献类型：
--
作者：
Chakraborty S;Hosen MI;Ahmed M;Shekhar HU
癌症标志的获得需要多个水平的分子改变，包括基因组、表观基因组、转录组、蛋白质组和代谢组。在过去的十年中，已经进行了许多尝试来解开致癌的分子机制，涉及单一的OMICS方法，如扫描基因组中的癌症特异性突变和识别癌细胞内改变的表观遗传景观或通过转录组学和蛋白质组学技术分别探索mRNA和蛋白质的差异表达。虽然这些单水平OMICS方法有助于基于基因/蛋白质表达鉴定癌症特异性突变、表观遗传改变和肿瘤的分子亚型，但它们缺乏建立分子特征与癌症标志的表型表现之间的因果关系的分辨能力。相比之下，涉及在多个维度上询问癌细胞/组织的多OMICS方法有可能揭示癌症标志（例如转移和血管生成）的不同表型表现背后的复杂分子机制。此外，多OMICS方法可用于剖析细胞对化疗或免疫治疗的反应，并发现具有诊断/预后价值的候选分子。在这篇综述中，我们重点介绍了不同的多OMICS方法在癌症研究领域的应用，并讨论了这些方法如何塑造个性化肿瘤治疗领域。我们重点介绍了来自“癌症基因组图谱（TCGA）”联盟的开创性研究，其中包括对33种最常见癌症的11，000多个肿瘤的综合OMICS分析。在像TCGA这样的存储库中积累大量癌症特异性多OMICS数据，为系统生物学方法提供了一个独特的机会，通过统一实验数据和计算/数学模型来解决癌细胞的复杂性。在未来，基于系统生物学的方法很可能预测化疗/免疫治疗后癌细胞的表型变化。这篇综述旨在鼓励研究人员将这些不同的方法结合在一起，在分子，细胞和系统水平上询问癌症。
The acquisition of cancer hallmarks requires molecular alterations at multiple levels including genome, epigenome, transcriptome, proteome, and metabolome. In the past decade, numerous attempts have been made to untangle the molecular mechanisms of carcinogenesis involving single OMICS approaches such as scanning the genome for cancer-specific mutations and identifying altered epigenetic-landscapes within cancer cells or by exploring the differential expression of mRNA and protein through transcriptomics and proteomics techniques, respectively. While these single-level OMICS approaches have contributed towards the identification of cancer-specific mutations, epigenetic alterations, and molecular subtyping of tumors based on gene/protein-expression, they lack the resolving-power to establish the casual relationship between molecular signatures and the phenotypic manifestation of cancer hallmarks. In contrast, the multi-OMICS approaches involving the interrogation of the cancer cells/tissues in multiple dimensions have the potential to uncover the intricate molecular mechanism underlying different phenotypic manifestations of cancer hallmarks such as metastasis and angiogenesis. Moreover, multi-OMICS approaches can be used to dissect the cellular response to chemo- or immunotherapy as well as discover molecular candidates with diagnostic/prognostic value. In this review, we focused on the applications of different multi-OMICS approaches in the field of cancer research and discussed how these approaches are shaping the field of personalized oncomedicine. We have highlighted pioneering studies from “The Cancer Genome Atlas (TCGA)” consortium encompassing integrated OMICS analysis of over 11,000 tumors from 33 most prevalent forms of cancer. Accumulation of huge cancer-specific multi-OMICS data in repositories like TCGA provides a unique opportunity for the systems biology approach to tackle the complexity of cancer cells through the unification of experimental data and computational/mathematical models. In future, systems biology based approach is likely to predict the phenotypic changes of cancer cells upon chemo-/immunotherapy treatment. This review is sought to encourage investigators to bring these different approaches together for interrogating cancer at molecular, cellular, and systems levels.
登录
查看更多内容
DOI：
10.1007/978-1-4939-1258-2_1
发表时间：
2014
期刊：
Methods in molecular biology (Clifton, N.J.)
影响因子：
--
作者：
Gowda, G A Nagana;Djukovic, Danijel
通讯作者：
Djukovic, Danijel
影响因子：
64.5
作者：
Cancer Genome Atlas Research Network
通讯作者：
Cancer Genome Atlas Research Network
PKCepsilon 磷酸化 MIIP，并通过抑制 RelA 脱乙酰化促进结直肠癌转移。
影响因子：
16.6
作者：
Chen T;Li J;Xu M;Zhao Q;Hou Y;Yao L;Zhong Y;Chou PC;Zhang W;Zhou P;Jiang Y
通讯作者：
Jiang Y
影响因子：
50.3
作者：
Figueroa ME;Abdel-Wahab O;Lu C;Ward PS;Patel J;Shih A;Li Y;Bhagwat N;Vasanthakumar A;Fernandez HF;Tallman MS;Sun Z;Wolniak K;Peeters JK;Liu W;Choe SE;Fantin VR;Paietta E;Löwenberg B;Licht JD;Godley LA;Delwel R;Valk PJ;Thompson CB;Levine RL;Melnick A
通讯作者：
Melnick A
影响因子：
4.6
作者：
Auslander N;Yizhak K;Weinstock A;Budhu A;Tang W;Wang XW;Ambs S;Ruppin E
通讯作者：
Ruppin E