Evaluating Etiological Impact of Metatranscriptomic and Immunological Features for Lung Cancer

评估宏转录组学和免疫学特征对肺癌的病因学影响

• 批准号: 10290463
• 负责人: Yanhong Liu
• 金额: $ 8万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10290463
• 关键词: B-Lymphocytes; Biological Process; Biology; Cancer Patient; Cells; Classification; Clinical; Clinical Data; Complex; Data; Data Set; Dendritic Cells; Development; Diagnosis; Discriminant Analysis; Disease; Early identification; Enrollment; Equilibrium; Etiology; Evolution; Future; Gene Expression Profile; Genes; Goals; Histologic; Histology; Human; Immune; Immune system; Immunologics; Immunophenotyping; Immunotherapy; Infiltration; Inflammatory; Linear Regressions; Link; Lung; Lung Adenocarcinoma; Lung Neoplasms; Machine Learning; Malignant Neoplasms; Malignant neoplasm of lung; Maps; Medicine; Metabolic; Metabolic Pathway; Microbe; Microbiology; Nature; Operative Surgical Procedures; Outcome; Patients; Population; Public Health Schools; RNA; Recurrence; Reproducibility; Resolution; Role; Smoking; Structure of parenchyma of lung; T memory cell; Taxonomy; Testing; Tissues; Tumor Tissue; Tumor-associated macrophages; Tumor-infiltrating immune cells; Validation; base; college; computed tomography screening; cost; design; differential expression; dysbiosis; epidemiologic data; high risk; low dose computed tomography; lung microbiome; lung microbiota; lung tumorigenesis; metatranscriptome; metatranscriptomics; microbial; microbiome; microbiota; neutrophil; novel; novel therapeutic intervention; pathogen; pathogenic microbe; patient stratification; patient subsets; personalized cancer therapy; public health relevance; transcriptome; transcriptome sequencing; tumor; tumor microenvironment; tumor progression; tumorigenesis

ABSTRACT There is increasing evidence that the evolution of cancer is strongly dependent on the complex tumor microenvironment (TME) in which it develops. Despite the important roles of both microbiota and immune cells within TME, there are huge gaps in linking specific lung-residing microbiota changes with immune cell subpopulations. To date, no human lung cancer studies have been performed to characterize the host-pathogen dynamic changes and dissecting the microbiome-immune interaction in an integrated manner. We hypothesize that the dysbiosis of lung-residing microbe (microbiota expression changes) triggers dysregulated balance in the lung immune system (immune cells infiltration levels), which results in an inflammatory TME, and further promotes lung tumorigenesis and tumor progression. We propose to capitalize on existing RNA-Seq (tumor and adjacent tissue) from 200 early-stage (I–IIIA) lung adenocarcinoma patients, from a Baylor College of Medicine (BCM) study (discovery, n = 100) and a Harvard School of Public Health study (external validation, n = 100), with no cost to this application. Our goal is to reveal the impact of the lung microbiota on host immune cell profiles and how their interaction contributes to tumorigenesis and tumor progression. To accomplish our goals, we will utilize a Dual RNA-Seq analytical approach: 1) to identity intratumoral metatranscriptomic signatures, and 2) to characterize immune infiltration profiles and microbiome- immune interaction. Specifically, the unmapped quality-filtered RNA reads (non-human, putative microbial reads) aligned to microbial reference transcriptomes will be used for metatranscriptome analysis (Aim 1); whereas reads that map to human reference will be used for computational immune profiling analysis (Aim 2). This is the first study to simultaneously profile lung tissue-specific microbiota expression and immune infiltrates in lung adenocarcinoma. This project could contribute significantly to our understanding of the biological processes before/during (adjacent/tumor tissue) lung adenocarcinoma development, in particular the complex microbiome-immune interaction. Elucidating the nature of interactions between lung microbiome and immune cells comprising the TME could guide the development of novel therapeutic interventions.

抽象的 越来越多的证据表明癌症的进化强烈依赖于复杂的肿瘤 它发展的微环境（TME）。尽管微生物群和免疫细胞都发挥着重要作用 在 TME 中，将特定的肺部微生物群变化与免疫细胞联系起来存在巨大差距 亚人群。迄今为止，尚未进行人类肺癌研究来表征宿主病原体 动态变化并以综合方式剖析微生物组-免疫相互作用。 我们假设肺内微生物的生态失调（微生物群表达变化）触发 肺部免疫系统平衡失调（免疫细胞浸润水平），导致 炎症性TME，并进一步促进肺部肿瘤发生和肿瘤进展。我们建议资本化 对 200 名早期 (I–IIIA) 肺腺癌患者的现有 RNA-Seq（肿瘤和邻近组织）进行分析， 来自贝勒医学院 (BCM) 研究（发现，n = 100）和哈佛大学公共卫生学院研究 （外部验证，n = 100），此应用程序无需任何成本。我们的目标是揭示肺部的影响 微生物群对宿主免疫细胞谱的影响以及它们的相互作用如何促进肿瘤发生和肿瘤 进展。为了实现我们的目标，我们将利用双 RNA-Seq 分析方法：1) 鉴定 瘤内宏转录组学特征，2) 表征免疫浸润特征和微生物组- 免疫相互作用。具体来说，未映射的质量过滤 RNA 读数（非人类、假定的微生物读数） 与微生物参考转录组对齐将用于元转录组分析（目标 1）；而读 该人类参考图谱将用于计算免疫分析（目标 2）。 这是第一项同时分析肺组织特异性微生物群表达和免疫浸润的研究 在肺腺癌中。该项目可以极大地促进我们对生物的理解 （邻近/肿瘤组织）肺腺癌发展之前/期间的过程，特别是复杂的 微生物组-免疫相互作用。阐明肺微生物组与免疫之间相互作用的本质 构成 TME 的细胞可以指导新型治疗干预措施的开发。