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Report on EU–USA Workshop: How Systems Biology Can Advance Cancer Research (27 October 2008)

机译:欧盟-美国研讨会报告:系统生物学如何促进癌症研究(2008年10月27日)

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摘要

The main conclusion is that systems biology approaches can indeed advance cancer research, having already proved successful in a very wide variety of cancer‐related areas, and are likely to prove superior to many current research strategies. Major points include: class="unordered" style="list-style-type:disc">Systems biology and computational approaches can make important contributions to research and development in key clinical aspects of cancer and of cancer treatment, and should be developed for understanding and application to diagnosis, biomarkers, cancer progression, drug development and treatment strategies.Development of new measurement technologies is central to successful systems approaches, and should be strongly encouraged. The systems view of disease combined with these new technologies and novel computational tools will over the next 5–20years lead to medicine that is predictive, personalized, preventive and participatory (P4 medicine).Major initiatives are in progress to gather extremely wide ranges of data for both somatic and germ‐line genetic variations, as well as gene, transcript, protein and metabolite expression profiles that are cancer‐relevant. Electronic databases and repositories play a central role to store and analyze these data. These resources need to be developed and sustained.Understanding cellular pathways is crucial in cancer research, and these pathways need to be considered in the context of the progression of cancer at various stages. At all stages of cancer progression, major areas require modelling via systems and developmental biology methods including immune system reactions, angiogenesis and tumour progression.A number of mathematical models of an analytical or computational nature have been developed that can give detailed insights into the dynamics of cancer‐relevant systems. These models should be further integrated across multiple levels of biological organization in conjunction with analysis of laboratory and clinical data.Biomarkers represent major tools in determining the presence of cancer, its progression and the responses to treatments. There is a need for sets of high‐quality annotated clinical samples, enabling comparisons across different diseases and the quantitative simulation of major pathways leading to biomarker development and analysis of drug effects.Education is recognized as a key component in the success of any systems biology programme, especially for applications to cancer research. It is recognized that a balance needs to be found between the need to be interdisciplinary and the necessity of having extensive specialist knowledge in particular areas.A proposal from this workshop is to explore one or more types of cancer over the full scale of their progression, for example glioblastoma or colon cancer. Such an exemplar project would require all the experimental and computational tools available for the generation and analysis of quantitative data over the entire hierarchy of biological information. These tools and approaches could be mobilized to understand, detect and treat cancerous processes and establish methods applicable across a wide range of cancers.
机译:主要结论是,系统生物学方法确实已经可以在许多与癌症相关的领域中证明成功,并且可以促进癌症研究的发展,并且有可能优于许多当前的研究策略。要点包括: class =“ unordered” style =“ list-style-type:disc”> <!-list-behavior = unordered prefix-word = mark-type = disc max-label-size = 0-系统生物学和计算方法可以为癌症和癌症治疗的关键临床方面的研究和开发做出重要贡献,因此应发展为理解和应用于诊断,生物标志物,癌症进展,药物开发和治疗策略。 开发新的测量技术对于成功的系统方法至关重要,应大力鼓励。系统的疾病观点与这些新技术和新颖的计算工具的结合将在未来5-20年内带来可预测,个性化,预防和参与性的医学(P4医学)。 正在进行中的重大举措收集有关体细胞和种系遗传变异以及与癌症相关的基因,转录本,蛋白质和代谢产物表达谱的极其广泛的数据。电子数据库和存储库在存储和分析这些数据方面起着核心作用。这些资源需要开发和维持。 了解细胞通路在癌症研究中至关重要,并且需要在癌症各个阶段的发展过程中考虑这些通路。在癌症进展的所有阶段,主要领域都需要通过系统和发育生物学方法(包括免疫系统反应,血管生成和肿瘤进展)进行建模。 已开发出许多具有分析或计算性质的数学模型,它们可以提供有关癌症相关系统动力学的详细见解。这些模型应在实验室和临床数据分析之间跨多个层次的生物组织进一步整合。 生物标志物是确定癌症的存在,其进展和对治疗的反应的主要工具。需要一套高质量的带批注的临床样本,以便进行不同疾病的比较以及对导致生物标记物发展和药物作用分析的主要途径进行定量模拟。 教育被认为是关键要素任何系统生物学计划的成功,特别是在癌症研究中的应用。人们认识到,需要跨学科的知识与在特定领域拥有广泛专业知识的必要性之间需要找到一种平衡。 本次研讨会的一项建议是探讨一种或多种癌症。完整程度的进展,例如胶质母细胞瘤或结肠癌。这样的示例项目将需要所有可用于生成和分析整个生物信息层次上的定量数据的实验和计算工具。可以动员这些工具和方法来理解,检测和治疗癌变过程,并建立适用于广泛癌症的方法。

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