Understanding Ancestral Contribution to Lung Adenocarcinoma

项目摘要/摘要 尽管现有的流行病学研究表明癌症发病率和预后存在差异，但仍有 很少有关于癌症基因组差异的研究，这需要种系、体细胞和临床数据 同样的病人。然而，研究特定祖先的基因组改变是最有效的方法之一 了解癌症差异的基础机制，并开发潜在的预防和治疗方法 战略。Carot-Zhang博士和其他人评估了10,678人中遗传祖先对体细胞变化的影响 来自癌症基因组图谱的33种癌症患者，并突出了新的特定祖先 来自泛癌和组织特异性分析的进化轨迹。我们还建议我们的祖先 相关性是组织特有的，因此需要来自不同祖先的更多样本。 用于特定组织的分析。在这种程度上，这一建议是基于由以下组成的大型测序数据集 来自墨西哥和哥伦比亚的1153名肺癌患者，以及来自基金会的60085份肺癌样本 医学。我们的总体目标是了解广为人知但神秘的种群特有基因组 肺腺癌的差异。我们的第一个目标是系统地描述祖先的图景 对肺腺癌基因组特征的影响，因为我们有能力检测新的关联。然后 在第二个目标中，胡萝卜-张博士将开发一种利用当地血统的新统计方法 (基因组区域的祖先)从祖先混合群体中推断与祖先相关的遗传力 躯体特征。我们还将探索与以下相关的基因组差异的潜在机制 血统。我们的第三个目标是阐明血统对临床结果的影响，以便改进。 少数民族人群的预后和精准医学。 胡萝卜-张博士的长期职业目标是通过以下方式提高癌症预防、早期发现和治疗 结合计算生物学、生殖系遗传学和体细胞基因组学方法来理解 癌症发生和发展的潜在机制。K99奖将进一步为她成功地 独立研究生涯。胡萝卜-张博士的培训将在非凡的指导下进行 Matthew Meyerson博士(癌症基因组学)，以及由Alexander博士(Sasha)组成的咨询委员会 Gusev(群体遗传学和统计遗传学)，Rameen Beroukhim(癌症生物学)，Heng Li (计算方法开发)和David Kwiatkowski(临床肿瘤学)。拟议的研究计划 将在达纳-法伯癌症研究所和博德基金会杰出的机构环境的推动下进行 研究所。与基金会医学的科学合作将为癌症提供特殊的资源 基因组学和与祖先相关的分析。拟议的专业发展计划将提升胡萝卜博士- 张在实验室管理、赠款撰写和领导力方面的职业发展。

PROJECT SUMMARY/ABSTRACT Although there are existing epidemiological studies of disparities in cancer incidence and outcomes, there are very few studies of disparities in cancer genomes, which requires both germline, somatic, and clinical data from the same patients. However, studying ancestry-specific genomic alterations is one of the most effective ways to understand the underpinning mechanisms in cancer disparity, and develop potential prevention and therapeutics strategies. Dr. Carrot-Zhang and others evaluated genetic ancestry effects on somatic alterations among 10,678 patients across 33 cancer types from The Cancer Genome Atlas, and highlighted novel ancestry-specific evolutionary trajectories from pan-cancer and tissue-specific analyses. We also suggested that ancestry associations were profoundly tissue specific, and therefore, more samples from diverse ancestries are required for tissue-specific analyses. To that extent, this proposal is based on large sequencing data sets composed of 1,153 lung cancer patients from Mexico and Colombia, and 60,085 lung cancer samples from Foundation Medicine. Our overall goal is to understand the well-known, but mysterious, population-specific genomic differences in lung adenocarcinoma. Our first aim is to systematically characterize the landscape of ancestry effects on genomic features of lung adenocarcinoma, as we are well powered to detect new associations. Then in the second aim, Dr. Carrot-Zhang will develop a novel statistical method leveraging the local ancestry (ancestry of a genomic region) from ancestry-admixed populations to infer the heritability of ancestry-associated somatic features. We will also explore the potential mechanisms underlying genomic differences related to ancestry. Our third aim is to elucidate the influence of ancestry on clinical outcome, in order to improve prognostics and precision medicine for the minority populations. Dr. Carrot-Zhang’s long-term career goal is to improve cancer prevention, early detection and treatment by integrating computational biology, germline genetics, and somatic genomics approaches to understand the mechanisms underlying cancer initiation and progression. The K99 award will further prepare her for a successful independent research career. Dr. Carrot-Zhang’s training will be carried out under the extraordinary mentorship of Dr. Matthew Meyerson (cancer genomics), and an advisory committee consisting of Drs. Alexander (Sasha) Gusev (population genetics and statistical genetics), Rameen Beroukhim (cancer biology), Heng Li (computational method development), and David Kwiatkowski (clinical oncology). The proposed research plan will be facilitated by the outstanding institutional environment of the Dana-Farber Cancer Institute and the Broad Institute. The scientific collaboration with Foundation Medicine will provide exceptional resources for cancer genomics and ancestry-related analyses. The proposed professional development plan will enhance Dr. Carrot- Zhang’s career advancement in laboratory management, grant-writing and leadership.