Annotation of cell types in human colon tissue using Boolean analysis

使用布尔分析注释人类结肠组织中的细胞类型

• 批准号: 10450780
• 负责人: Debashis Sahoo
• 金额: $ 35.55万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10450780
• 关键词: ALCAM gene; Activated-Leukocyte Cell Adhesion Molecule; Adjuvant Therapy; Area; B cell differentiation; Bioinformatics; Biological Markers; CDX2 gene; Cancer Patient; Cell Differentiation process; Cells; Clinical; Clinical Research; Colon; Colon Carcinoma; Colonic Diseases; Computer Analysis; Data; Data Set; Databases; Developmental Biology; Disease; Dropout; Enterocytes; Epithelial; Epithelial Cells; Fluorescence-Activated Cell Sorting; Future; Gene Chips; Gene Expression; Gene Expression Profile; Genes; Goals; Goblet Cells; Guidelines; Human; Immunohistochemistry; Inflammatory Bowel Diseases; Intestines; Investigation; Knowledge; Link; Logic; Malignant Neoplasms; Malignant neoplasm of urinary bladder; Mathematics; Measurement; Methods; Modeling; Mus; Organoids; Outcome; Patients; Phenotype; Play; Population; Prognostic Marker; RNA; Randomized; Research; Role; Sampling; Systems Biology; Therapy trial; Tissue Differentiation; Tissues; Tumor Tissue; Work; Xenograft procedure; adenoma; base; cancer cell; cell type; colon cancer patients; colonic crypt; combat; diagnostic assay; diagnostic biomarker; human disease; improved; insight; mathematical model; novel; single-cell RNA sequencing; spatiotemporal; stem cell biology; stem cell biomarkers; stem cell population; stem cells; therapeutic target; tool; tumor; tumorigenic

Title: Annotation of cell types in human colon tissue using Boolean analysis Abstract: Despite 50 years of extensive investigations to characterize the stem cell population in human colon crypts, we still do not have a clear definition of cells that maintain the colon crypts. Identification of specific markers of stem and progenitor cells in human colon tissue not only contribute to the field of (intestinal) stem cell biology but also provides insight into colon cancer, adenoma and other diseases of the colon tissue. We have a new method that has the ability to predict differentiation hierarchy using unbiased systems biology perspective and mathematical models of large patient-derived gene expression datasets. We have mathematical models that can predict the terminally-differentiated cells. The mathematical principle we use is based on Boolean implication logic that has not been commonly applied to study tissue cell populations. The Boolean analysis assigns a parameter (e.g. RNA level of a gene) with only two values, i.e., high/low, 1/0, or positive/negative. Applying the Boolean principle, it is possible to determine the relationship between the expression levels of any pair of genes.1 As shown in Fig 2, the Boolean principle dictates only six different relationships: two are symmetric (equivalent or opposite) (Fig. 2A, B) and four are asymmetric (low => low, high => low, low => high, and high => high)(Fig. 2C-F). Preliminary work based on Boolean implication has been shown to produce results in B cell differentiation, bladder cancer and colon cancer. Boolean analysis was used to search for biomarkers of colon epithelial differentiation across gene-expression arrays by identifying genes that have relationship with the activated leukocyte-cell adhesion molecule (ALCAM/CD166) and fulfilled the “X low => ALCAM high” Boolean implication. ALCAM is a marker of immature colon epithelial cells that is preferentially expressed at the bottom of colon crypts2,3 and on human colon-cancer cells with enriched tumorigenic capacity in mouse xenotransplantation models.4 The search yield 16 genes that includes CDX2, for which clinical grade diagnostic assays were readily available. In large pooled database of randomized-adjuvant therapy trials CDX2 low stage II tumors responded favorably when they are treated.5 The primary goal of this proposal is to use Boolean implication relationships to decode the tissue organization of human colon. Based on our preliminary data the overall hypothesis is that Boolean principles can be used to specifically characterize the population of cell types in human colon tissue. These studies are expected to yield information about markers of specific cell types in the colon tissue, cell differentiation, diagnostic and prognostic biomarkers. Consequently, they have the potential to impact current guidelines about how to treat and manage colon cancer patients and even help identify potential future therapeutic targets.

标题：使用布尔分析注释人类结肠组织中的细胞类型 翻译后摘要：尽管50年的广泛调查，以表征干细胞群体在人类结肠 但是，对于维持结肠隐窝的细胞，我们仍然没有一个明确的定义。确定具体 人结肠组织中的干细胞和祖细胞标记物不仅有助于（肠）干细胞领域 生物学，而且还提供了深入了解结肠癌，腺瘤和其他疾病的结肠组织。我们有一个 一种新的方法，有能力预测分化层次使用无偏系统生物学的观点 和大型患者源性基因表达数据集的数学模型。我们有数学模型 可以预测终末分化细胞。我们使用的数学原理是基于布尔蕴涵 这一逻辑尚未普遍应用于研究组织细胞群。布尔分析指定一个 参数（例如基因的RNA水平）只有两个值，即，高/低、1/0或正/负。应用 布尔原理，可以确定任何一对基因表达水平之间的关系。 如图2所示，布尔原理只规定了六种不同的关系：两种是对称的（等价的 或相反）（图2A，B）和四个是不对称的（低=>低，高=>低，低=>高，高=>高）（图2B）。 图2C-F）。基于布尔蕴涵的初步工作已经显示出在B细胞分化中产生结果， 膀胱癌和结肠癌。布尔分析用于搜索结肠上皮细胞的生物标志物， 通过鉴定与激活的基因相关的基因， 白细胞-细胞粘附分子（ALCAM/CD 166），并满足“X低=> ALCAM高”布尔含义。 ALCAM是未成熟结肠上皮细胞的标志物，其优先在结肠底部表达 crypts 2，3和对小鼠异种移植中具有富集致瘤能力的人结肠癌细胞的影响 4搜索产生了包括CDX 2的16个基因，对于这些基因，临床级诊断测定很容易地被应用于临床。 available.在随机辅助治疗试验的大型汇总数据库中，CDX 2低II期肿瘤缓解 当他们被对待的时候， 这个建议的主要目标是使用布尔蕴涵关系来解码组织 人类结肠组织。根据我们的初步数据，总体假设是布尔原理 可用于特异性表征人结肠组织中的细胞类型群体。 这些研究有望产生关于结肠组织中特定细胞类型标记的信息， 细胞分化、诊断和预后生物标志物。因此，它们有可能影响电流 关于如何治疗和管理结肠癌患者的指南，甚至有助于确定潜在的未来 治疗目标