Annotation of cell types in human colon tissue using Boolean analysis

标题：使用布尔分析对人类结肠组织中的细胞类型进行注释 摘要：尽管50年来人们对人类结肠干细胞群体进行了广泛的研究 关于结肠隐窝，我们对维持结肠隐窝的细胞仍没有一个明确的定义。识别特定的 人类结肠组织中干细胞和祖细胞的标记物不仅有助于(肠道)干细胞领域 生物学还提供了对结肠癌、腺瘤和其他结肠组织疾病的洞察。我们有一个 用无偏系统生物学观点预测分化等级的新方法 以及患者衍生的大型基因表达数据集的数学模型。我们有数学模型， 可以预测终末分化的细胞。我们使用的数学原理是基于布尔蕴涵的 一种尚未被普遍应用于研究组织细胞群体的逻辑。布尔分析将一个 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的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)，并且四个是不对称的(低=低，高=低，低=高，和高=高)(图 2C-F)。基于布尔蕴涵的初步工作已被证明在B细胞分化中产生结果， 膀胱癌和结肠癌。用布尔分析寻找结肠上皮细胞的生物标志物 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-细胞黏附分子(alcam/CD166)，满足“X low=&gt；alcam High”布尔蕴涵。 Alcam是未成熟结肠上皮细胞的标志物，优先表达于结肠底部。 在小鼠异种移植中对致瘤能力增强的人结肠癌细胞的作用 4搜索得到包括CDX2在内的16个基因，对这些基因进行临床分级诊断分析很容易 可用。在大型随机辅助治疗试验数据库中，CDX2低期II期肿瘤有反应 当他们得到治疗时，他们会表现得很好 这个提议的主要目标是使用布尔蕴含关系来解码组织 人结肠的组织。根据我们的初步数据，总体假设是布尔原则 可以用来专门描述人类结肠组织中细胞类型的群体。 这些研究有望获得有关结肠组织中特定细胞类型的标志物的信息， 细胞分化、诊断和预后的生物标志物。因此，它们有可能冲击电流。 如何治疗和管理结肠癌患者的指导方针，甚至有助于确定潜在的未来 治疗靶点。

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.