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阅读信息📕 难度：★★★☆☆ 类型：总论 字数：5,693 The Precision Cancer Treatment Movement: What Has Been Learned? 精准化癌症治疗运动：已经学到了什么？ The age of personalization really began with the precision cancer movement. A diagnosis of cancer is traditionally defined by the anatomical site of origin, but in 2017 we witnessed regulatory approval of the first cancer drug focused on disturbed cellular function, with the identification of the cancer type linked to a specific mutation of the cancer cell rather than to an organ.18 As recently as the 1990s, treatment for many cancer patients came in the form of relatively ineffective toxic chemotherapy because 'evidence” -as it was defined in that era- supported the use of these medications. Today, the field of oncology has significantly evolved as a result of the advancement in understanding of the molecular genetic etiology of cancer, which in turn has made it possible to personalize therapeutic interventions in a manner that is more efficient for both physicians and patients.19 New clinical trial designs were instrumental in forging this new era of cancer treatment. One- an adaptive study design that features 'umbrellas' and 'baskets'-allows for the stratification of patients into various cohorts that are assigned treatments based on personalized genetic information. This type of protocol assists researchers in collecting evidence of a drug's effectiveness in terms of unique patient sensitivity and response to an intervention.20 Stratifying a study population according to specific biomarkers and then using combined cellular and biochemical profiling to identify predictive responses to specific therapies is a pioneering approach.21 The increased use of genomic sequencing and profiling has fundamentally changed the nature of diagnosis from that of the population to that of the individual. It is a logical and needed next step for clinical trial design to change in a responsive manner, and for the parameters that guide how evidence in support of therapy is defined to be reexamined as well.22 个性化时代真正开始于精准化的癌症治疗运动。癌症的诊断传统上是由解剖部位来定义的，但在2017年，我们见证了第一种监管机构批准的以细胞功能紊乱为切入点的癌症治疗药物，确定了与癌细胞的特定基因突变相关的癌症类型，而不是与器官相关的癌症类型。18-20世纪90年代，对于许多癌症患者来说，治疗癌症的方法实际上是相对无效的毒性的化学疗法，但是因为存在“证据”（依据那个时代的定义）而支持使用这些药物。如今，随着对癌症分子遗传学病因学理解的进步，肿瘤学领域取得了长足的进步，从而使个性化治疗干预成为可能，使医生和患者都能更有效地进行治疗干预19。新的临床试验设计有助于构建一个癌症治疗的新时代。借助于一种以“雨伞”和“篮子”为特征的适应性研究设计，可以允许根据个性化的遗传信息将患者分成不同的队列，并相应分配治疗。这种类型的研究方案有助于研究人员收集有关药物有效性的证据，包括患者对治疗干预的独特敏感性和反应20。开拓性的方法是，根据特定的生物标志物对研究人群进行分层，然后使用细胞和生物化学特征相结合的方式，来确定可以对特定疗法的反应进行预测的方法21。基因组测序分析方法使用的增加，从根本上改变了诊断的性质，即从人群转变到个体的方法。临床试验设计转变为针对治疗反应，针对可以指导证据如何支持治疗的研究参数，是逻辑和必要的下一步骤，并定义以进行重复检测22。 Diet studies related to cancer therapy have proven to be difficult in terms of demonstrating evidence of effectiveness. There are various reasons for this, including the significant heterogeneity of responses to nutrient signals, as well as the low signal strength of nutritionally derived, biological, response modifying substances.23 Siddhartha Mukheriee, MD. PhD, and Lewis C Cantley, PhD, both highly respected researchers, have recently announced a collaboration among Weill Cornell Medical College, Columbia University Medical Center, and New York-Presbyterian to evaluate specific dietary interventions in cancer. Previous work done in tumor models in mice revealed key findings about the role of glucose and fructose in enhancing the tumor-promoting effects of insulin through the PI3 kinase signaling network.24,25 Earlier this year- -in 2019- -a group led by Dr Cantley reported that high-fructose corn syrup enhances intestinal tumor growth in mice.26 This animal work, in combination with clinical observations that low-sugar diets appear to be helpful in reducing the progression of a number of types of cancer, has culminated in a crowdsourcing initiative to fund a human clinical trial.27 Engaging the public in the support and execution of research has been described as 'leveraging the citizen scientist' It is a novel model- one that highlights a new kind of transparency and openness- and it is being now being applied not only to cancer research,but also to the study of diseases such as rheumatoid arthritis, amyotrophic lateral sclerosis, and multiple sclerosis.28,29,30,31 与癌症治疗相关的饮食干预研究在证明其有效性方面是很困难的。这有多种原因，包括个体对营养信号反应的显著异质性，以及营养来源的、生物的、反应修饰物质信号的低强度性质相关23。Siddhartha Mukheriee和Lewis C Cantley博士，这两位备受尊敬的研究人员最近宣布了一项合作研究项目，即在韦尔康奈尔医学院、哥伦比亚大学医学中心和纽约长老会医院合作评估癌症的具体饮食干预措施。先前在小鼠肿瘤模型中所做的工作揭示了葡萄糖和果糖通过PI3激酶信号网络系统增强胰岛素促肿瘤作用的关键性发现24,25。今年早些时候，由Cantley博士领导的一个小组报告说，高果糖玉米糖浆可增强小鼠肠道肿瘤的生长26。这些动物研究结论，结合临床观察表明低糖饮食似乎有助于减少多种癌症的进展，最终促成了多家机构的合作倡议，以为在人类的临床试验提供资金27。引导公众参与支持和执行研究被称为“利用公民科学家”的模式。这是一种强调透明和开放的新的模式 - 现在不仅应用于癌症研究，也可被应用于类风湿性关节炎、肌萎缩侧索硬化和多发性硬化等的研究28,29,30,31。 N-of-1 Trials and Personalized Evidence N-of-1研究和个性化的证据 Stratified trial designs using new biometric and genomic tools are now being applied to the evaluation of epigenetic effects related to a range of interventions, including physical exercise, Ayurvedic practices, and meditation.32,33,34 Progress has been made in the documentation of individualized responses, which has resulted in the codification of specific procedures for N-of-1 study designs.35 Factors that have been linked to the usefulness of this type of study include the following: the mechanism of action of the treatment is pleomorphic; the study population is heterogeneous; and the clinical endpoints variable in type, duration, frequency, and intensity. Multi-person N-of-1 trials can be designed and effectively executed if the objectives, functional variables, reasons for stratifying the cohorts, and specific intervention rationale are clearly defined. 36 使用新的生物学特征和基因组工具进行分层的试验设计，现在被应用于与一系列干预措施相关的表观遗传学效应的评估，包括体育锻炼、印度吠陀修习和冥想32,33,34。在文献中有报告个体化反应的进展，这导致对N-of-1研究设计的特定程序的编码35。与这类研究有用性相关的因素包括：治疗的作用机制是多样性的；研究人群是异质的；临床终点在类型、持续时间、频率和强度上是可变的。如果明确了研究目标、功能变量、队列分层因素和具体的干预理由，就可以设计并有效执行多人的N-of-1试验36。 There is evidence that single -subject N-of-1 studies can be useful in establishing evidence of effectiveness in translational nutrition research.37 Optimally, these N-of-1 designs should employ integrated use of multiple functional assessments, in combination with biometric assays and omics tools, to identify individual metabolic phenotypes. Using this array of assessment tools to identify the functional status of the individual before and after nutritional intervention allows for the development of valid evidence. Multiple individual N-of-1 studies using the same assessment tools and outcome measures can provide additional evidentiary support for use of the intervention in patients who share similar metabolic phenotypes. 有证据表明，单受试者N-of-1研究可有助于证明营养干预转化研究的有效性37。最理想的情况是，这些N-of-1设计应综合使用多种功能性评估，结合生物学测定和组学工具，以确定个体的代谢表型。利用这一系列的评估工具来识别营养干预前后个体的功能状态，从而形成有效性的证据。使用相同评估工具和结果测量方法的多个体N-of-1研究可为具有相似代谢表型的患者使用干预提供额外的证据支持。 Obesity is a condition marked by complex physiology and psychology. As such, the application of gene –based personalization of dietary advice for nutritional weight management in patients with this condition has historically resulted in only limited success.38 This field of studying the relationship between genes and weight, which is now commonly referred to as nutrigenomics, recently took a major step forward. Amit Khera, MD, and Sekar Kathiresan, MD, who are both affiliated with the Center for Genomic Medicine at Massachusetts General Hospital, the Broad Institute at MIT, and Harvard Medical School, have worked with a team of collaborators to create a polygenic prediction algorithm to track weight and obesity trajectories from birth to adulthood based on the analysis of 2.1 million common genetic variants.39 This work is truly groundbreaking because it relates to establishing specific genetically determined risk categories for complex health issues such as obesity. Interestingly, when the number of genetic variants in the computational algorithm only included those that had been identified by GWAS studies on obesity , no significant predictive ability was noted. However, when the larger set of 2.1 million common variants was used, the predictive ability of the algorithm became significant, even though most of the gens had not been identified a being associated with obesity. This fact demonstrates the high level of biological heterogeneity that exists in an individual’s response to diet . AIi Torkamani, PhD. and Eric Topol, MD, of the Scripps Research Translational Institute, jointly authored a commentary about the work of Khera et al and suggest it is an important illustration of why nutritional intervention trials often fail to produce clear evidence of improved outcome.40 In the future, use of the polygenic risk score in combination with biometric information, functional data related to the impact of the gut microbiome on metabolism, and lifestyle and dietary factors may frame the design of N-of-1 approaches that will provide us with evidence about the relationship between a personalized diet and health outcomes. 肥胖是一种以复杂的生理和心理为特征的疾病。因此，基于基因的个性化饮食建议在这种疾患的营养学体重管理中的应用，在历史上获得的成功是有限的38。这一研究基因与体重之间关系的领域，现在通常被称为基因营养学，最近取得了重大进展。Amit Khera和Sekar Kathiresan医学博士都隶属于马萨诸塞州总医院基因组医学中心、麻省理工学院布罗德研究所和哈佛医学院，他们与一组研究者合作，创建了一个多基因预测算法来跟踪从出生到成年的体重和肥胖轨迹。在对210万种常见基因变异的分析中，这项工作确实是开创性的，因为它涉及到为诸如肥胖等复杂的健康问题建立特定的以基因确定风险类别的方法。有趣的是，当计算算法中的遗传变异数仅包括那些通过GWAS肥胖研究确定的变异数时，没有发现显著的预测能力。然而，当使用210万个常见突变的较大集合时，算法的预测能力变得显著，即使大多数基因没有被确定为与肥胖有关。这一事实表明，个体对饮食的反应存在高度的生物异质性。Scripps研究转化研究所的Ai Torkamani博士和Eric Topol医学博士，联合撰写了一篇关于Khera等人研究工作的评论，并建议这是一个重要的例证，说明为什么营养干预试验往往不能产生明显的改善结果的证据40。未来，多基因风险评分结合生物特征学、肠道微生物群对新陈代谢、生活方式和饮食因素影响相关的功能性数据，可能构成N-of-1方法的设计，这将为我们提供个性化饮食与健康结果之间关系的证据。 The Nested Case Report as a Source of Evidence 作为证据来源的嵌套式案例报告 N-of-1 studies provide information from which a nested series of case reports can be developed to serve as additional supporting evidence for defining outcome. There is now an established format for publishing case reports under consensus-based guidelines called the Case REport (CARE) Statement and Checklist.41 The CARE approach includes the following: development of an appropriate abstract; an introduction; patient information; assessment criteria; therapeutic intervention; outcomes; discussion of strengths and weaknesses of the report; patient perspectives on their experience with the intervention; and informed consent.42 N-of-1研究提供了一系列嵌套式病例报告的信息，这些报告可作为确认结果的额外支持证据。现在已经有一种基于共识的指南发布的病例报告的既定格式，称为Case REport (CARE)声明和列表41。CARE方法包括以下内容：制定合适的摘要；前言；患者信息；评估标准；治疗干预；结果；报告强项和弱点的讨论；患者对干预体验性的看法和知情同意42。 Empirical evaluations have indicated that important treatment effects are often revealed through well-designed small studies that are properly stratified for participants within specific functional categories.43 It is well understood that population-based RCTs have value in identifying specific, single-agent effects in acute disease states, but have limited application to personalized interventions in complex chronic disease. There are now a number of study designs available to assess the impact of personalized interventions and provide the evidence necessary to support the use of systems biology precepts and the application of Functional Medicine approaches to chronic disease management.44 经验性评估表明，重要的治疗效果往往通过精心设计的小规模研究来揭示，这些小规模研究对特定功能类别的参与者进行了适当的分层43。众所周知，基于人群的RCT在识别急性疾病状态下的特定单效应因素方面具有价值，但在应用于复杂慢性疾病的个性化干预时，RCT的意义有限。现在有许多研究设计可用于评估个性化干预的影响，并提供支持使用系统生物学规则和将功能医学方法应用于慢性病管理的必要证据44。 The April 9, 2019 issue of the Journal of the American Medical Association features an editorial titled 'The Evolving Uses of ‘Real-World’ Data.' As the article outlines, real-world data (RWD) and real world evidence (RWE) constitutes information that is not derived from RCTs or similar experiments. And yet- the authors point out- such information is now considered to have value in establishing the landscape related to the effectiveness of specific clinical interventions They write: The frenzy of interest in RWD has also been fueled by the Food and Drug Administration (FDA) signaling receptiveness to consider these data sources in regulatory review, and recent publication of a framework for doing so.45 在美国医学会杂志（JAMA） 2019年4月9日一期上刊载了一篇社论，题为：不断发展的“ 真实世界 ”数据的使用。正如文章所述， 真实世界数据（RWD）和真实世界证据（RWE） 构成了非RCT或类似试验的信息。然而，作者指出，这些信息现在被认为在建立与特定临床干预有效性相关的更为全面的视角方面具有价值。他们写道：对RWD的狂热也受到食品药品管理局（FDA）的推动，FDA发出了在监管方面考虑接受该类数据的信号，并在最近出版一个框架性的指导意见45。 In addition to this new interest in real-world data, patient-experience information has also become an increasingly important contributor to the evaluation of treatment effectiveness.46 In a recently published editorial about evidence supporting cardiovascular clinical guidelines, authors Robert O. Bonow, MD, MS, and Eugene Braunwald, MD, state: “There will never be enough time, effort, or funding to implement RCTs to address all clinical scenarios that confront physicians. Moreover, RCTS are usually confined to patients of specific ages with single conditions. .... Individual patients are unique and many differ from those enrolled in RCTs on which the guidelines are based.' They continue:“This results in the common need to extrapolate guideline recommendations built upon ideal patients to the real patients seen in practice...”47 The 21st century has already demonstrated itself to be an era of change for medicine and science. There is a new openness -to ideas, to a shift in perspectives, to a redefinition of evidence and the many ways it can be gathered. It is a fertile time on many fronts, including an expanded reach for a systems biology formalism and the Functional Medicine movement. 除了对真实世界数据的这种新的兴趣外，患者体验信息也日益成为评价治疗效果的重要因素46。作者Robert O.Bonow和Eugene Braunwald医学博士在最近出版的一篇关于支持心血管临床指南证据的社论中指出：“永远不会有足够的时间、努力或资金来实施RCT，以解决医生面临的所有临床情况。此外，RCT通常仅限于特定年龄、有单一疾病的患者…个体患者是独一无二的，许多患者与RCT中的患者不同”。他们继续说：“这导致人们需要普遍将建立在理想患者基础上的指南建议，外推到实践中所见到的真正患者身上…”47。21世纪已经证明了自己在医学和科学方面是一个变革的时代。现在有了新的开放性的视角 - 思想的开放，观点的转变，对证据的重新定义以及收集证据的多种方式。这是一个产出颇丰的时期，包括了系统生物学的广泛运用和功能医学的兴起。 参考文献 References 1. Schork NI. Personalized medicine: Time for one person trials. Nature. 2015 Apr 30;520(7549):609-11. 2 Bland, Jeffrey S. The Disease Delusion: Conquering the Causes of Chronic illness for a Healthier, Longer, and Happier Life. New York: HarperWave, 2014. 3. Schork NI. Randomized clinical trial and personalized medicine: A commentary on deaton and cartwright. Soc Sci Med. 2018 Aug;210:71-73. 4. Mathias MG, Coelho-Landell CA. Scott Boyer MP, et al. 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