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

揭秘：极早期癌症研究开始的潜在新原因

• 批准号: 10482393
• 负责人: Wan Yang
• 金额: $ 39.13万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-06 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10482393
• 关键词: Address; Adult; Advanced Malignant Neoplasm; Age; Antibiotics; Assimilations; Biological Process; Birth; Cancer Biology; Cancer Detection; Carcinogenesis Mechanism; Clonal Expansion; Cohort Effect; Colorectal; Colorectal Cancer; Coupled; Data; Data Set; Detection; Diagnosis; Diet; Disease; Environmental Risk Factor; Epidemic; Epidemiology; Etiology; Evaluation; Exclusion; Exposure to; Household; Incidence; Individual; Kidney; Life; Life Cycle Stages; Life Style; Localized Malignant Neoplasm; Malignant Neoplasms; Mathematics; Methodology; Methods; Modeling; Mutation; National Health Interview Survey; National Health and Nutrition Examination Survey; Obesity; Outcome; Patients; Population; Predisposition; Prevention; Primary Prevention; Process; Public Health; Risk; Risk Assessment; Risk Estimate; Risk Factors; SEER Program; Sampling; Screening for cancer; Smoke; Subgroup; Sum; System; Testing; Thyroid Gland; Time; Validation; Work; aged; anticancer research; base; cancer initiation; cancer risk; carcinogenesis; clinical investigation; community-level factor; data modeling; early onset; experience; flexibility; innovation; mathematical model; novel; personalized approach; prevent; response; trend; young adult

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.

最近的研究，包括我们自己的研究，表明年轻人中某些癌症的发病率急剧上升。 使用美国SEER数据，我们发现三种关键癌症的发病率在年轻人中一直在增加， 过去十年中的成年人：318，781名年龄在25-49岁的成年人被诊断患有结肠直肠（n= 114，220）， 甲状腺癌（n= 146，977）和肾癌（n= 57，584），每年增加2.44%、4.81%和3.83%， 分别在2006-2015年期间。年变化率超过1%通常被归类为流行病 癌症。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 他们还模拟了年龄-时期-队列效应，发现年轻人患这三种癌症的风险 在过去几十年中，按出生年份分列的年龄（25-49岁）显著增加。另外这些 在大多数种族亚组中以及在局部和晚期癌症中均持续观察到增加。这些 研究结果表明，由于外在因素的增加，这些癌症的风险增加（即，环境和生活方式） 风险因素，如果确定，可以预防。然而，尽管这些早发性 癌症相对罕见，加上诱导时间长，使得传统的流行病学方法 无法有效识别根本原因。例如，一个超过76万的人口样本将 需要在5年内观察500例50岁以下成年人的结直肠癌。 因此，我们建议利用一个新颖的，有效的，数学框架来研究三个早期的驱动因素- 初发癌症（即结直肠癌、甲状腺癌和肾癌）。该框架将使用机械数学模型， 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结合起来 同化方法，以测试基于癌症发病率和暴露的各种假设风险机制 记录在具有国家代表性的数据集中。项目团队拥有丰富的数据使用经验 同化方法和数学模型，以了解疾病系统，包括癌症。的 框架还将创新地考虑癌症检测率随时间的变化，观察误差， 多个风险因素之间的相互作用，以及生命周期中风险影响的变化。使用这种新 框架，对于三种主要癌症中的每一种，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，癌症起始与促进），3） 检查共同暴露之间的动态相互作用（例如，风险放大由于协同效应， 4）量化个体风险因素和共同风险在生命不同阶段的影响， 特别是检查敏感性的临界窗口。此外，我们将量化是否确定病因 当这些因素结合在一起时，它们具有足够高的量级，可以用来开发一个风险计算器， 癌症筛查完成这些目标将为一级预防提供重要的病原学证据 在人群水平上，以及帮助临床医生和他们的病人设计癌症筛查策略。