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）是美国与癌症相关死亡的第三大主要原因，明显 种族和种族死亡率差异。在阿拉斯加本地人和 死亡率死亡率的非裔美国人高2至3倍。这些差异无法解释 通过单独使用护理，建议其他促成因素（例如分子亚型和细胞） 异质性，需要发现。来自多个种族和种族的患者的肿瘤分析研究 将导致对CRC的新生物学见解，这极大地克服了以前的研究的局限性 仅在非西班牙裔白人中主要进行。肿瘤免疫情节，指的是 肿瘤微环境内免疫浸润的空间组织和密度很复杂 并与癌症预后有关。除了批量分析之外，尖端的空间单细胞分析启用 美国评估肿瘤组织不同区域内的肿瘤免疫情节（例如边缘，中心），这 将增加我们对CRC生存至关重要的免疫逃避和抗肿瘤免疫力的了解。 我的目标是更好地了解驱动肿瘤进展的分子和细胞景观 种族和种族敏感的方式。这将为我提供新的，多学科的培训 综合肿瘤流行病学领域。我将利用包括840的嵌套病例对照研究的数据 阿拉斯加人，非裔美国人，西班牙裔和非西班牙裔白人CRC患者。每个种族和种族 包括70例死于CRC的致命病例和140个CRC对照，至少在案件中幸存下来 它们适合年龄，性别和舞台。在F99阶段，我将检查分子特征和 使用RNASEQ数据在四个种族和种族之间开发预后指数。我将评估肿瘤 使用空间分辨的单细胞技术（Akoya 现场生物）。在K00阶段，我将将转录组和单细胞数据集成到患者级数据中 表征肿瘤异质性及其在其他预后因素中的作用（例如治疗，复发）。 该项目的结果将捕获一大批CRC转录和细胞生物学及其它们 通过空间镜头与疾病结局的关系，并为临床可用的预测工具提供 可以针对种族和种族多样的患者量身定制的预后。这将有助于解决长期存在 CRC死亡率中的种族和种族差异。这个项目为我提供了发展的培训机会 1）分子流行病学与种族和种族多样性的人群合作，尤其是在 阿拉斯加土著人的参与，2）癌症免疫学，3）高级统计和计算分析 维数据。这些经历将极大地帮助我过渡到博士后研究员，并最终 综合肿瘤流行病学迅速增长领域的独立癌症研究员。