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

基本信息

批准号：
9974241
负责人：
Debashis Sahoo
金额：
$ 35.44万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
依托单位国家：
美国
项目类别：
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/9974241
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 Computer Analysis Data Data Set Databases Developmental Biology Disease Dropout Enterocytes Epithelial Epithelial Cells Epithelium 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 population stem cells therapeutic target tool tumor tumorigenic

项目摘要

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摘要：尽管对人类结肠干细胞群的特征进行了 50 年的广泛研究对于维持结肠隐窝的细胞，我们仍然没有明确的定义。人类结肠组织中干细胞和祖细胞的标记不仅有助于（肠道）干细胞领域我们还提供了对结肠癌、腺瘤和其他结肠组织疾病的深入了解。能够使用无偏系统生物学角度预测分化层次的新方法以及大型患者基因表达数据集的数学模型我们有数学模型。我们使用的数学原理是基于布尔蕴涵的。布尔分析分配一个尚未普遍应用于研究组织细胞群的逻辑。仅具有两个值的参数（例如基因的 RNA 水平），即高/低、1/0 或正/负。布尔原理，可以确定任意一对基因表达水平之间的关系1 如图 2 所示，布尔原理仅规定了六种不同的关系：其中两种是对称的（等价的）或相反）（图2A，B），并且四个是不对称的（低=>低，高=>低，低=>高，高=>高）（图2A，B）。 2C-F）基于布尔蕴涵的初步工作已被证明可以产生 B 细胞分化的结果，膀胱癌和结肠癌用于寻找结肠上皮的生物标志物。通过识别与激活的基因相关的基因来区分基因表达阵列白细胞-细胞粘附分子（ALCAM/CD166）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，优先在结肠底部表达 crypts2,3 以及在小鼠异种移植中具有丰富致瘤能力的人结肠癌细胞 4 搜索结果包括 CDX2 在内的 16 个基因，可以轻松进行临床级诊断分析在随机辅助治疗试验的大型汇总数据库中，CDX2 低 II 期肿瘤有反应。当他们受到待遇时，他们会得到有利的待遇。5 该提案的主要目标是使用布尔蕴涵关系来解码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类结肠组织中的细胞类型群体。这些研究预计将产生有关结肠组织中特定细胞类型标记的信息，经过细胞分化、诊断和预后生物标志物测试，它们有可能影响当前的情况。有关如何治疗和管理结肠癌患者的指南，甚至帮助确定潜在的未来治疗目标。