Deep molecular and cellular profiling of colorectal cancer tumor and immune microenvironment in Alaska Native people

项目总结 阿拉斯加原住民的结直肠癌发病率和死亡率是全球最高的， 发病率是美国普通人群的两倍多(发病率：89.0比38.6/10万； 死亡率：39.6/10万比13.8/10万)。这些高比率不能用获得筛查来解释，因为 致力于增加结直肠癌筛查的努力使阿拉斯加原住民的筛查率达到了 与美国平均水平相当。这些差距已经持续了40多年，值得注意的是 社区成员和部落卫生领袖一样，使这成为阿拉斯加原住民的优先研究领域 人民。一个关键的知识缺口是缺乏对分子特征的大规模和全面的研究 阿拉斯加原住民结直肠肿瘤的特点。因此，我们提出了一种综合的方法来更好地 了解这一高危人群中结直肠癌的发生和分子亚型，并评估 各种肿瘤和肿瘤微环境特征促进了疾病的进展。具体来说，我们的目标是 深入研究结直肠癌肿瘤及其免疫的突变、转录和细胞格局 500名阿拉斯加原住民患者的微环境，并将这些特征与结直肠癌特有的死亡率联系起来。我们 将建立在阿拉斯加土著部落健康联盟(ANTHC)和 弗雷德·哈钦森癌症中心。我们将利用ANTHC独特的生物资源库(可链接到全面的 医疗记录)，其中包含大多数阿拉斯加原住民CRC患者的肿瘤组织样本 阿拉斯加。使用来自该资源的生物标本并利用拟议的相同平台生成的试点数据 这里展示了高质量数据，并确保IRB和部落批准到位，以实现快速 执行拟议的工作。为了确定有临床意义的人群差异，我们将比较 使用现有数据与非西班牙裔白人结直肠癌患者的分子图谱进行比较。在目标1中，我们将 对结直肠癌和配对的正常样本进行全外显子组测序，以确定驱动基因和 临床上可操作的突变，尤其与阿拉斯加土著人口有关。为了获得病因学方面的洞察， 我们将分析可能与环境暴露有关的突变特征，并确定生殖系 高外显性结直肠癌风险基因突变在阿拉斯加原住民结直肠癌风险增加中的作用 人民。在目标2中，我们将应用两种互补的尖端空间剖面图技术来充分表征 肿瘤免疫反应和发现免疫逃避机制。我们将在空间上整体表演 使用NanoString公司的GeoMx数字空间图谱技术对结直肠癌进行转录组图谱分析。我们将使用 Akoya Biosciences的PhenoCycler平台用于空间分辨单个免疫细胞表型。我们期待着 通过这项工作获得的见解可以为高价值、新的治疗策略的开发提供信息。在AIM 3，我们将利用这些分子数据来开发新的结直肠癌特异性死亡率预测指标，这可能有助于 指导临床决策，改善结果，减少长期存在的差异。

PROJECT SUMMARY Alaska Native people have the highest incidence and mortality rates of colorectal cancer (CRC) globally, with rates that are more than double those observed in the general U.S. population (incidence: 89.0 vs. 38.6/100,000; mortality: 39.6/100,000 vs. 13.8/100,000). These high rates cannot be explained by access to screening, as dedicated efforts to increase CRC screening have resulted in screening rates in Alaska Native people that are comparable to the US average. These disparities have persisted for over 40 years and are of noted concern to community members and Tribal health leaders alike, making this a priority research area for Alaska Native people. A key knowledge gap is the lack of sizable and comprehensive studies characterizing the molecular features of colorectal tumors in Alaska Native patients. Accordingly, we propose an integrative approach to better understand CRC tumorigenesis and molecular subtypes in this high-risk population, and to evaluate whether various tumor and tumor microenvironment features contribute to disease progression. Specifically, we aim to deeply characterize the mutational, transcriptional, and cellular landscapes of CRC tumors and their immune microenvironments in 500 Alaska Native patients and link these characteristics to CRC-specific mortality. We will build on our existing collaboration between the Alaska Native Tribal Health Consortium (ANTHC) and the Fred Hutchinson Cancer Center. We will capitalize on ANTHC’s unique biorepository (linkable to comprehensive medical records) that contains tumor tissue samples of the majority of Alaska Native CRC patients diagnosed in Alaska. Pilot data generated using biospecimens from this resource and utilizing the same platforms as proposed here demonstrate high-quality data and ensure that IRB and tribal approvals are in place to enable rapid execution of the proposed work. To identify clinically meaningful population differences, we will compare molecular profiles with those from non-Hispanic White CRC patients using available data. In Aim 1, we will perform whole-exome sequencing of CRC tumors and paired normal samples to identify driver genes and clinically actionable mutations particularly relevant to the Alaska Native population. To gain etiological insight, we will analyze mutational signatures that may be linked to environmental exposures and identify germline mutations in high-penetrance CRC risk genes to investigate their role in the increased CRC risk in Alaska Native people. In Aim 2, we will apply two complementary cutting-edge spatial profiling technologies to fully characterize the tumoral immune response and discover mechanisms of immune evasion. We will perform spatial whole transcriptome profiling of CRC tumors using Nanostring’s GeoMx Digital Spatial Profiling technology. We will use Akoya Biosciences’ PhenoCycler platform for spatially resolved single immune cell phenotyping. We expect that insights gained through this work can inform the development of high-value, novel therapeutic strategies. In Aim 3, we will leverage these molecular data to develop novel predictors of CRC-specific mortality that could help guide clinical decision making, improve outcomes, and reduce long-standing disparities.