Transcriptome and spatial analyses of tumor environment in addressing colorectal cancer racial and ethnical disparities

肿瘤环境的转录组和空间分析在解决结直肠癌种族和民族差异方面的作用

• 批准号: 10743201
• 负责人: Hang Yin
• 金额: $ 4.92万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10743201
• 关键词: Address; African American; African American population; Age; Alaska Native; Algorithms; Automobile Driving; Biological; Biological Markers; Cancer Biology; Cancer Control; Cancer Etiology; Cancer Prognosis; Cells; Cellular biology; Cessation of life; Characteristics; Clinical; Collaborations; Colorectal Cancer; Complex; Computer Analysis; Computing Methodologies; Consensus; Data; Dedications; Development; Dimensions; Disease Outcome; Disease Progression; Disparity; Environment; Epidemiology; Ethnic Origin; Ethnic Population; Family; Formalin; Gene Expression Profile; Gene set enrichment analysis; General Population; Genes; Genetic Transcription; Goals; Hand; Health Services Accessibility; Heterogeneity; High-Frequency Microsatellite Instability; Hispanic; Image; Imaging technology; Immune; Immune Evasion; Investigation; Knowledge; Life Style; Linear Regressions; Logistic Regressions; Malignant Neoplasms; Medical Records; Microsatellite Instability; Modeling; Molecular; Molecular Epidemiology; Molecular Profiling; Mutation; Native Americans; Native-Born; Neighborhoods; Nested Case-Control Study; Normal tissue morphology; Not Hispanic or Latino; Outcome; Paraffin Embedding; Pathway Analysis; Pathway interactions; Patients; Persons; Phase; Population Heterogeneity; Postdoctoral Fellow; Probability; Prognosis; Prognostic Factor; Protocols documentation; Public Health; Race; Recording of previous events; Recurrence; Research; Research Personnel; Risk Factors; Role; Sampling; Shapes; Smoking Status; Statistical Data Interpretation; Statistical Methods; T-cell inflamed; Training; Tumor Immunity; Tumor Tissue; United States; Validation; Weight; cancer health disparity; cancer immunotherapy; cancer survival; cell type; cellular imaging; colon cancer patients; density; differential expression; ethnic disparity; ethnic diversity; experience; immune cell infiltrate; improved outcome; insight; lens; machine learning algorithm; molecular marker; molecular subtypes; mortality; mortality disparity; multidimensional data; multidisciplinary; novel; novel marker; patient population; patient stratification; personalized medicine; pre-doctoral; predictive tools; prognostic index; racial disparity; racial diversity; racial population; response; screening; sex; single cell analysis; single cell technology; skills; therapeutic target; training opportunity; transcriptome; transcriptome sequencing; transcriptomics; translational research program; tumor; tumor heterogeneity; tumor immunology; tumor microenvironment; tumor progression; tumorigenesis

PROJECT ABSTRACT Colorectal cancer (CRC) is the third leading cause of cancer-related death in the US, with pronounced disparities in mortality by race and ethnicity. Disparities are particularly pronounced in Alaska Native and African American people with mortality rates being 2 to 3 times higher. These disparities cannot be explained by access to care alone, suggesting other contributing factors like molecular subtypes and cellular heterogeneity, need to be uncovered. Tumor profiling study in patients from multiple racial and ethnic groups will lead to novel biological insight into CRC, which greatly overcomes the limitation of previous studies that were conducted predominantly in non-Hispanic white people only. Tumor immune contexture, which refers to the spatial organization and density of the immune infiltrates within the tumor microenvironment, is complex and associated with cancer prognosis. Beyond bulk analysis, cutting-edge spatial single-cell analyses enable us to evaluate tumor immune contexture within different regions of tumor tissues (e.g. margin, center), which will add our knowledge of immune evasion and antitumor immunity that is critical for CRC survival. My objective is to better understand the molecular and cellular landscapes driving tumor progression in a racial- and ethnic-sensitive manner. This will provide me with hand-on, multi-disciplinary training in the new field of integrative tumor epidemiology. I will leverage data from a nested case-control study that includes 840 Alaska Native, African American, Hispanic and non-Hispanic White CRC patients. Each racial and ethnic group includes 70 lethal cases who died of CRC and 140 CRC controls who survived at least as long as the case to which they are matched for age, sex and stage. In the F99 phase, I will examine molecular signatures and develop a prognostic index across four racial and ethnic groups using RNAseq data. I will evaluate tumor immune contexture among Alaska Native patients using spatial-resolved single-cell technology (Akoya PhenoCycler). In the K00 phase, I will integrate transcriptomic and single-cell data into patient-level data to characterize tumor heterogeneity and its role in other prognostic factors (e.g. treatment, recurrence). Results from this project will capture a full spectrum of CRC transcriptional and cellular biology and their relationship to disease outcomes through a spatial lens and provide clinical-useful prediction tools for prognosis that can be tailored to racially- and ethnically-diverse patients. This will help to address longstanding racial and ethnic disparities in CRC mortality. This project provides me with training opportunities to develop expertise in 1) molecular epidemiologic working with racial and ethnic diverse populations, especially with the engagement of Alaska Native people, 2) cancer immunology, 3) statistical and computational analysis in high- dimensional data. Those experiences will greatly help my transition into a post-doctoral fellow and eventually an independent cancer researcher in the rapidly growing field of integrative tumor epidemiology.

项目摘要 结直肠癌（CRC）是美国癌症相关死亡的第三大原因， 按种族和族裔分列的死亡率差异。在阿拉斯加原住民和 非裔美国人的死亡率高出2到3倍。这些差异无法解释 通过单独获得护理，这表明其他因素，如分子亚型和细胞 异质性，需要被发现。在多个人种和种族组患者中进行的肿瘤特征分析研究 将导致新的生物学见解CRC，这大大克服了以往研究的局限性， 主要仅在非西班牙裔白色人中进行。肿瘤免疫结构，指的是 肿瘤微环境中免疫浸润的空间组织和密度是复杂的 并与癌症预后相关。除了批量分析之外，尖端的空间单细胞分析还能 我们评估肿瘤组织不同区域（例如边缘、中心）内的肿瘤免疫结构， 将增加我们对免疫逃避和抗肿瘤免疫的了解，这对CRC生存至关重要。 我的目标是更好地了解分子和细胞景观驱动肿瘤进展， 种族敏感的方式这将为我提供新的实践，多学科培训 综合肿瘤流行病学领域我将利用来自嵌套病例对照研究的数据， 阿拉斯加土著、非裔美国人、西班牙裔和非西班牙裔白色CRC患者。每个种族和族裔群体 包括70例死于CRC的致命病例和140例CRC对照，这些病例的存活时间至少与 他们的年龄性别和所处阶段都是匹配的在F99阶段，我将检查分子特征， 使用RNAseq数据在四个种族和民族群体中开发预后指数。我会评估肿瘤 使用空间分辨单细胞技术研究阿拉斯加原住民患者的免疫结构（Akoya PhenoCycler）。在K00阶段，我将把转录组和单细胞数据整合到患者水平的数据中， 描述肿瘤异质性及其在其他预后因素（如治疗、复发）中的作用。 该项目的结果将捕获CRC转录和细胞生物学的全谱， 通过空间透镜与疾病结果的关系，并提供临床有用的预测工具， 预后，可以定制种族和民族多样化的患者。这将有助于解决长期以来 CRC死亡率的种族和族裔差异。这个项目为我提供了培训机会， 专业知识1）分子流行病学与种族和民族不同的人群，特别是与 阿拉斯加原住民的参与，2）癌症免疫学，3）高水平的统计和计算分析， 维度数据这些经历将极大地帮助我过渡到博士后研究员，并最终 在快速发展的综合肿瘤流行病学领域的独立癌症研究人员。