27 Risk, Detection and Outcomes

27 风险、检测和结果

• 批准号: 10655563
• 负责人: Paul A Scheet
• 金额: $ 1.87万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-08-28 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10655563
• 关键词: Address; Affect; Atlases; Automobile Driving; Behavior Therapy; Behavioral; Big Data; Bioinformatics; Biological Assay; Biological Factors; Biological Markers; Biometry; Breast; Cancer Burden; Cancer Center; Cancer Center Support Grant; Cancer Detection; Cancer Etiology; Cancer Patient; Cancer Survivor; Carcinogen exposure; Catchment Area; Clinical; Clinical Trials; Collaborations; Complement; Computational Biology; Computer Analysis; Computing Methodologies; DNA; Data Sources; Decision Making; Demography; Detection; Diagnosis; Diagnostic; Discipline; Disease; Early Diagnosis; Economic Factors; Economics; Elderly; Environmental Risk Factor; Epidemiologic Factors; Epidemiology; Etiology; Family; Funding; Genetic; Genets; Genome; Genomics; Goals; Health; Health Policy; Human Genetics; Individual; Institution; Investigation; Journals; Light; Lung; Malignant Childhood Neoplasm; Malignant Neoplasms; Malignant neoplasm of lung; Marker Discovery; Mathematics; Mexican Americans; Modeling; Molecular; Nucleic Acids; Oncology; Organ; Outcome; Ovary; Paper; Pathology; Pathway interactions; Patient-Focused Outcomes; Patients; Pattern; Peer Review; Phase; Policies; Policy Maker; Population; Population Database; Population Sciences; Predisposing Factor; Prevention program; Proteins; Proteomics; Public Health; Publishing Peer Reviews; Quality of life; RNA; Research; Research Personnel; Resource Sharing; Resources; Risk; Risk Assessment; Role; Sampling; Statistical Models; Surveys; Survivors; Techniques; Technology; Testing; Texas; Tissues; Treatment Effectiveness; Treatment Efficacy; Underinsured; Uninsured; Variant; X-Ray Computed Tomography; biobehavior; biomarker discovery; biomarker identification; blood-based biomarker; cancer care; cancer health disparity; cancer initiation; cancer prevention; cancer risk; care delivery; care outcomes; chemotherapy; childhood cancer survivor; cohort; comparative effectiveness; cost-effectiveness evaluation; design; early detection biomarkers; effective intervention; ethnic minority; exome; follow-up; genetic epidemiology; genetic variant; health care delivery; high risk; improved; improved outcome; individualized prevention; innovation; insight; low dose computed tomography; low socioeconomic status; member; metabolomics; microbiome; modifiable behavior; neoplasm registry; next generation sequencing; novel; novel strategies; population health; preclinical study; premalignant; programs; racial minority; risk prediction; screening; social; social factors; successful intervention; survivorship; tool; treatment response; tumor progression; whole genome

PROJECT SUMMARY/ABSTRACT The newly-formed Risk, Detection and Outcomes (RDO) Program has 49 members (47 primary, 2 associate) from 19 departments and is led by Drs. Paul Scheet (human genetics, computational biology) with co-leaders Sanjay Shete (biostatistics, genetic epidemiology, population health), Samir Hanash (early detection, proteomics), and Sharon Giordano (health care delivery, outcomes). The major scientific goal of the RDO Program is to reduce the cancer burden in the population and improve quality of life in survivors through innovative research aimed at optimizing cancer risk assessment, screening, early detection, and treatment- associated outcomes from diagnosis through survivorship, with an ultimate goal of informing successful interventions (e.g., in the Cancer Prevention Program). To achieve this goal, the RDO Program is organized into 3 specific aims focusing on 1) Cancer Etiology, 2) Early Detection, and 3) Care Delivery and Outcomes. Aim 1: To discover genetic, behavioral, and environmental factors for cancer initiation. Aim 2: To perform biomarker discovery for personalized risk assessment and early detection. Aim 3: To identify biological and social factors influencing care delivery and patient outcomes. The annual direct peer-reviewed funding of the RDO Program totals $11.4M, including 4 U01s, of which $5.4M (47%) is from the NCI. Over the past 6 years, program members have authored 1211 published peer-reviewed papers, with 373 (31%) intra-programmatic, 594 (49%) inter- programmatic, and 877 (72%) external collaborations. Forty-five percent of articles appeared in journals with IF >5, and 14% appeared in journals with IF >10, including Nat Biotechnol, Nat Genet and J Clin Oncol. Program members used all 14 shared resources. Over this period, the RDO Program has had several major accomplishments. First, in whole-genome genetic epidemiology studies, we identified genetic variants that predispose to disease initiation, affect outcomes, or predict adverse responses to therapy. In multiple whole- exome next-generation sequencing studies, the first of their kind, we are powered to discover variants of higher, intermediate cancer risk. We have also surveyed genomic changes in precancerous tissues, shedding light on early disease pathology. Second, we have uncovered novel blood-based biomarkers for early detection through state-of-the-art profiling technologies. Key hits identified from proteomics and metabolomics promise to complement low-dose CT scans in individuals at high risk for lung cancer. Third, as leaders in a consortium of Texas academic institutions and the Texas Cancer Registry, we have studied patterns of screening, diagnosis, treatment (e.g., chemotherapy and associated decision-making), and follow-up to impact state-wide policy. For all of these endeavors, we continue to develop and enhance unique cohorts, including Cancer Patients and Survivors, Mexican American, Premalignant Genome Atlas, Childhood Cancer Survivors, and organ-specific cohorts of the lung, breast, and ovary.

项目总结/摘要 新成立的风险、检测和结果（RDO）计划有49名成员（47名主要成员，2名副成员） 来自19个部门，由Paul Scheet博士（人类遗传学，计算生物学）领导， Sanjay Shete（生物统计学，遗传流行病学，人口健康），Samir Hanash（早期检测， 蛋白质组学）和Sharon Giordano（卫生保健交付，结果）。研究发展条例的主要科学目标 该计划旨在通过以下措施减轻人群的癌症负担，提高幸存者的生活质量 创新研究旨在优化癌症风险评估，筛查，早期发现和治疗- 从诊断到生存的相关结果，最终目标是告知成功的 干预（例如，癌症预防计划）。为了实现这一目标，RDO计划分为 3个具体目标，重点是1）癌症病因学，2）早期检测，3）护理交付和结果。目标1： 发现癌症发生的遗传、行为和环境因素。目的2：进行生物标志物 个性化的风险评估和早期发现。目标3：确定生物和社会因素 影响护理交付和患者结果。RDO计划的年度直接同行评审资金 总计1140万美元，包括4个U 01，其中540万美元（47%）来自NCI。在过去的6年里，项目成员 发表了1211篇同行评审论文，其中373篇（31%）是计划内的，594篇（49%）是计划间的， 877项（72%）外部合作。45%的文章出现在期刊上， IF >5的期刊占14%，其中包括Nat Biotechnol、Nat Genet和J Clin Oncol。程序 成员使用了所有14个共享资源。在此期间，RDO计划有几个主要的 成就。首先，在全基因组遗传流行病学研究中，我们发现了 易诱发疾病，影响结果或预测对治疗的不良反应。在多个整体中- 外显子组下一代测序研究，这是第一次，我们有能力发现更高， 中度癌症风险。我们还调查了癌前组织的基因组变化， 早期疾病病理学其次，我们已经发现了新的基于血液的生物标志物，用于早期检测， 最先进的侧写技术从蛋白质组学和代谢组学中确定的关键命中承诺， 补充低剂量CT扫描在肺癌高危人群中的应用。第三，作为一个联合体的领导者， 德克萨斯学术机构和德克萨斯癌症登记处，我们研究了筛查，诊断， 治疗（例如，化疗和相关的决策），并采取后续行动，以影响全州的政策。为 所有这些努力，我们继续发展和加强独特的队列，包括癌症患者和 幸存者，墨西哥裔美国人，癌前基因组图谱，儿童癌症幸存者，和器官特异性 肺、乳腺和卵巢的队列。