UNCOVER: underlying novel causes of onset of very early cancer research

最近的研究，包括我们自己的研究表明，在年轻人中，某些癌症的发病率急剧上升。 使用美国SEER数据，我们发现三种主要癌症在年轻人中的发病率一直在上升 过去十年的成年人：318,781名年龄在25-49岁的成年人被诊断为结直肠癌(n=114,220)， 甲状腺癌(n=146,977)和肾癌(n=57,584)，年增长率分别为2.44%、4.81%和3.83%， 分别在2006-2015年间。每年变化超过1%的百分比通常被归类为流行病 癌症的威胁。因此，公共卫生迫切需要了解这些早发性癌症的驱动因素。我们 还建立了年龄-时期-队列效应的模型，并发现年轻时患这三种癌症的风险 在过去的几十年里，年龄(25-49岁)按出生年份显著增加。此外，这些 在大多数种族亚群以及局部和晚期癌症中都出现了持续的上升。这些 研究结果表明，由于越来越多的外在因素(即环境和生活方式)，这些癌症的风险增加 风险因素，如果发现，是可以预防的。然而，尽管这些早发性疾病急剧增加， 癌症相对罕见，再加上较长的诱导时间，这使得传统的流行病学方法 找出根本原因效率低下。例如，一个超过76万人的人口样本将 需要在5年内观察500例50岁以下成年人的结直肠癌。 因此，我们建议利用一种新颖而有效的数学框架来调查三个早期- 发病癌症(即结直肠癌、甲状腺癌和肾癌)。这个框架将使用机械论的数学模型来 捕捉生命过程中潜在的癌症生物学，并进一步将这些模型与高级数据相结合 基于癌症发病率和暴露测试各种假想风险机制的同化方法 记录在具有全国代表性的数据集中。项目团队拥有丰富的数据使用经验 理解包括癌症在内的疾病系统的同化方法和数学模型。这个 框架还将创新性地考虑随时间变化的癌症检测率、观察误差、 多种风险因素之间的相互作用，以及生命过程中风险影响的变化。使用这一新的 框架，对于三种关键癌症，我们的目标是1)系统地检查和识别关键风险因素， 特别是，在50岁的年轻人中，2)推断风险机制(例如，癌症的启动与促进)，3) 检查联合暴露之间的动态交互作用(例如，由于联合暴露的协同效应而导致的风险放大) 暴露)，以及4)量化个人风险因素和共同暴露在生命的不同阶段和 尤其是检查敏感的关键窗口。此外，我们将量化已确定的病因是否 综合起来，这些因素的大小足以用来开发一个较早开始的风险计算器 癌症筛查。因此，完成这些目标将为初级预防提供重要的病因学证据。 在人口层面，以及协助临床医生和他们的病人制定癌症筛查策略。

Recent studies, including our own, have shown dramatic increases in selected cancers among young adults. Using U.S. SEER data, we showed that incidence rates of three key cancers have been increasing in younger adults in the past decade: 318,781 adults aged 25–49 years were diagnosed with colorectal (n=114,220), thyroid (n=146,977), and kidney (n=57,584) cancer with increases per year at 2.44%, 4.81%, and 3.83%, respectively, during 2006–2015. Annual percent change over 1% per year is usually classified as an epidemic of cancer. Thus, there is urgent public health need to understand the drivers of these early-onset cancers. We have also modelled age-period-cohort effects and found that risks of developing these three cancers at younger ages (25–49 years) have increased significantly by birth year for the last several decades. In addition, these increases were consistently seen in most racial subgroups and in both localized and advanced cancers. These findings suggest increased risks for these cancers due to increasing extrinsic (i.e., environmental and lifestyle) risk factors, which, if identified, can be prevented. However, despite the dramatic increases in these early-onset cancers, their relative rarity coupled with a long induction time make traditional epidemiologic approaches inefficient to identify the underlying causes. For example, a population sample of more than 0.76 million would be needed to observe 500 cases of colorectal cancer in adults under 50 over a 5-year period. We thus propose to utilize a novel, and efficient, mathematical framework to investigate drivers of the three early- onset cancers (i.e. colorectal, thyroid, and kidney). This framework will use mechanistic mathematical models to capture the underlying cancer biology over the life course, and further couple these models with advanced data assimilation methods to test various hypothesized risk mechanisms based on cancer incidence and exposures recorded in nationally representative datasets. The project team has extensive experience using data assimilation methods and mathematical models to understand disease systems including cancers. The framework will also innovatively account for changing cancer detection rates over time, observation errors, interactions among multiple risk factors, and changes in risk impact over the life course. Using this new framework, for each of the three key cancers, we aim to 1) systematically examine and identify key risk factors, in particular, in younger adults <50 years, 2) infer the risk mechanisms (e.g., cancer initiation vs. promotion), 3) examine the dynamic interactions among co-exposures (e.g., risk amplification due to synergistic effect of co- exposures), and 4) quantify the impact of individual risk factors and co-exposures in different stages of life and particularly to examine critical windows of susceptibility. Further, we will quantify whether the identified etiological factors when combined are of high enough magnitude to be used to develop a risk calculator for starting earlier cancer screening. Completing these aims will thus provide important etiologic evidence for primary prevention at the population-level as well as aid clinicians and their patients in devising cancer screening strategies.