Integration of Immunology and Microbiology into Molecular Pathological Epidemiology of Colorectal Cancer
将免疫学和微生物学整合到结直肠癌的分子病理流行病学中
基本信息
- 批准号:10732976
- 负责人:
- 金额:$ 16.88万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-08-17 至 2028-07-31
- 项目状态:未结题
- 来源:
- 关键词:Biological AssayBiological MarkersCancer ScienceCancer and Leukemia Group BCellsCharacteristicsClinicalCohort StudiesColonoscopyColorectal AdenomaColorectal CancerComputational algorithmComputing MethodologiesDataData SetDatabasesDevelopmentDietDiseaseEpidemiologyEtiologyFollow-Up StudiesFoundationsGeneticHealth ProfessionalHealth SciencesImage AnalysisImmuneImmunityImmunologyIncidenceMediationMicrobiologyMolecularNurses&apos Health StudyOutcomePathologicPatternPopulationPrevention strategyProcessPrognostic FactorPublic HealthResearchRisk FactorsRoleSomatic MutationSouthwest Oncology GroupStatistical MethodsTumor ImmunityTumor SubtypeTumor TissueVariantadenomacarcinogenicitycohortdigital imagingearly onset colorectal cancerhigh dimensionalityinsightlifestyle factorsmachine learning algorithmmicrobialmicrobiotamicroorganismmodifiable lifestyle factorsmolecular pathologymulti-ethnicneoplastic cellnovelpredictive modelingtumortumor microbiotatumor microenvironment
项目摘要
Summary
Colorectal cancer is a heterogenous disease influenced by somatic mutations, microbiota, host immunity,
and risk factor exposures, necessitating integrative research approaches to better understand the etiology.
The proposed project plans to integrates immunology and microbiology into molecular pathological
epidemiology (MPE) to gain insights into the interactive role of exposures, microbiota, immune cells, and
tumor cells in colorectal cancer and adenoma. This project also plans to develop novel statistical and
computational methods for such research. This project leverages tumor tissue datasets in various
populations, including the Nurses' Health Study (NHS), NHS2, Health Professionals Follow-up Study,
Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO), Multiethnic Cohort Study (MEC),
Partners Colonoscopy Cohort (PCC), and CALGB/SWOG 80702 trials. Our multi-level databases have
accumulated information on long-term lifestyle factors and tumoral features of colorectal cancer (CRC) and
adenoma. Our research involves the assessment of various immune cells and microbiota in tumor tissue
using multispectral assays combined with digital image analyses and machine learning algorithms.
Characteristics of molecular pathology, microorganisms, and immunity in tumor tissue will shed light on the
carcinogenic process. Diet and lifestyle factors will be assessed in relation to incidence of CRC (or
adenoma) subtyped by microbial and/or immune features, and in relation to clinical outcomes of these tumor
subtypes. The MPE approach is expected to reveal currently unknown risk and prognostic factors for CRC
and early-onset CRC, the incidence of which has increased globally for uncertain reasons. Moreover,
examining effects of modifiable lifestyle factors on immune cells and microorganisms in tumor tissue will
open new ways to develop personalized preventive strategies. Efforts will be made to replicate findings
using other independent datasets whenever possible. New statistical methods will address analytical issues
such as continuous subtyping, missing biomarker data, intratumor spatial variations, high-dimensional tumor
data, mediation analyses, and prediction models. Furthermore, novel computational algorithms will be
developed to decipher the spatial patterns of immune cell subsets and tumor cells in the tumor
microenvironment. Integrative epidemiological analyses of immunology and microbiology will generate
provide the scientific foundation for exploring roles of anti-tumor immunity and microbiota in CRC
development. In addition, this project will advance population cancer sciences via the development of new
statistical and computational methods.
总结
结直肠癌是一种受体细胞突变、微生物群、宿主免疫,
和风险因素暴露,需要综合研究方法,以更好地了解病因。
拟议的项目计划将免疫学和微生物学纳入分子病理学
流行病学(MPE),以深入了解暴露、微生物群、免疫细胞和
结直肠癌和腺瘤中的肿瘤细胞。该项目还计划开发新的统计和
计算方法进行这种研究。该项目利用各种肿瘤组织数据集
人群,包括护士健康研究(NHS),NHS 2,卫生专业人员随访研究,
结直肠癌遗传学和流行病学联盟(GECCO),多种族队列研究(MEC),
结肠镜检查队列(PCC)和CALGB/SWOG 80702试验。我们的多级数据库
积累了长期生活方式因素和结直肠癌(CRC)肿瘤特征的信息,
腺瘤我们的研究涉及评估肿瘤组织中的各种免疫细胞和微生物群
使用多光谱分析结合数字图像分析和机器学习算法。
肿瘤组织中的分子病理学、微生物和免疫学特征将揭示肿瘤的分子病理学特征。
致癌过程将评估饮食和生活方式因素与CRC发生率的关系(或
腺瘤)通过微生物和/或免疫特征进行亚型,并与这些肿瘤的临床结果相关
亚型MPE方法有望揭示目前未知的CRC风险和预后因素
和早发性CRC,其发病率由于不确定的原因在全球范围内增加。此外,委员会认为,
检查可改变的生活方式因素对肿瘤组织中免疫细胞和微生物的影响,
开辟新的途径来制定个性化的预防策略。将努力推广调查结果
尽可能使用其他独立数据集。新的统计方法将解决分析问题
例如连续分型、缺失生物标记数据、肿瘤内空间变化、高维肿瘤
数据、中介分析和预测模型。此外,新的计算算法将
开发用于破译肿瘤中免疫细胞亚群和肿瘤细胞的空间模式,
微环境免疫学和微生物学的综合流行病学分析将产生
为探讨抗肿瘤免疫和微生物群在结直肠癌中的作用提供科学依据
发展此外,该项目还将通过开发新的
统计和计算方法。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Tomotaka Ugai的其他文献
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