Computational and Biological Deconvolution of Epigenomic Datasets

描述（由申请人提供）：本申请的目标是开发方法来解卷积基于组织的分子特征的计算复杂性。在这一建议中，我们将把重点放在人类乳房作为一个模型器官和一个原理的方法证明上。然而，我们期望我们开发的方法将广泛适用于所有组织和肿瘤类型。B.意义：我们发现人类乳房由11种细胞类型和4种激素状态（HR0-3）组成。重要的是，HR0和HR3乳腺肿瘤患者的预后存在高达7倍的生存差异。我们的初步工作表明，HR组之间的许多表型差异是表观遗传的。因此，全面表征HR0-3特异性表观遗传特征可能具有重要的临床意义。C.挑战：绝大多数现有的正常和恶性人体组织的高通量分子特征来自未分离的组织片段。因此，现有的数据是一个复合反映组织马赛克是由许多细胞类型组成。我们在这里要解决的问题是如何将现有的表观基因组学和TCGA组织特异性特征解卷积为它们的单个细胞类型特异性成分（HR0-3）。这是对RFA-RM-14-001规定的目的的响应：(1)“使用参考表观基因组数据来识别区分细胞类型的特定特征的分析”和(2)“将参考表观基因组图谱与其他公共或研究者生成的数据集结合起来的综合分析”。C.假设：(1)鉴定谱系特异性乳腺细胞表面标记将允许分离特异性细胞系，促进下游研究；(2)谱系特异性表观遗传标记的鉴定将促进计算技术的发展，这对于复杂的表观基因组特征的反卷积是必要的。目的1：人正常乳腺和恶性乳腺HR0-3细胞系的分离和分析。我们将使用细胞内标记ER， AR， VDR从正常和恶性乳腺组织中分离HR0-3细胞亚型。我们将鉴定正常乳腺癌和乳腺癌中对应HR0-3细胞亚型的细胞表面标记物，允许分离活的ER+、AR+、VDR+、HR0和HR3细胞类型。目标2。人类乳腺组织中谱系特异性和肿瘤特异性DNA甲基化标记的计算测定。2 A。我们将描述肿瘤特异性和谱系特异性DNA甲基化标记。2 .我们将通过分析正常乳腺组织样本的甲基化数据来验证DNA甲基化标记的谱系和肿瘤特异性。2 .我们将通过整合其他基因组类型来研究计算确定谱系特异性和肿瘤特异性DNA甲基化标记的可行性。

DESCRIPTION (provided by applicant): The goal of this application is to develop methods to deconvolute the computational complexity of tissue based molecular signatures. In this proposal we will concentrate on the human breast as a model organ and as a methodological proof-of-principle. However, we expect that the approaches we develop will be widely applicable to all tissue and tumor types. B. SIGNIFICANCE: We discovered that the human breast is composed of 11 cell types and 4 hormonal states (HR0-3). Importantly, there was up to 7-fold survival difference in the outcome of patients with HR0 vs. HR3 breast tumors. Our preliminary work suggests that much of the phenotypic differences between HR groups are epigenetic. Thus, a comprehensive characterization of HR0-3 specific epigenetic signatures may have great clinical significance. C. CHALLENGE: The vast majority of existing high-throughput molecular signatures of normal and malignant human tissues are derived from unfractionated tissue fragments. Thus, the existing data is a composite reflecting a tissue mosaic that is composed of many cell types. The question we are tackling here is how to deconvolute the existing Epigenomics and TCGA tissue-specific signatures into their single cell-type-specific components (HR0-3). This is responsive to RFA-RM-14-001 stated purposes: (1) "Analyses that use reference epigenomic data to identify specific features that distinguish cell types" and (2) "Integrative analyses that combine reference epigenomic maps with other public or investigator-generated data sets". C. HYPOTHESIS: (1) identification of lineage specific breast cell-surface markers would permit the isolation of specific cell lineages, facilitating downstream research; and (2) identification of lineage specific epigenetic markers will facilitate development of computational techniques that are necessary for deconvolution of complex epigenomic signatures. AIM 1: Isolation and profiling of HR0-3 cell lineage from normal and malignant human breast 1 A. We will isolate HR0-3 cell subtypes from normal and malignant breast tissues using intracellular markers ER, AR, VDR. 1 B. We will identify cell surface markers that correspond to HR0-3 cell subtypes in normal breast and breast cancers, permitting isolation of viable ER+, vs. AR+ vs. VDR+ vs. HR0 vs. HR3 cell types. AIM 2. Computational determination of lineage-specific and tumor-specific DNA methylation markers in human breast tissue. 2 A. We will characterize tumor-specific and lineage-specific DNA methylation markers. 2 B. We will validate the lineage and tumor specificity of DNA methylation markers by analyzing methylation data from normal breast tissue samples. 2 C. We will investigate the feasibility of computational determination of lineage-specific and tumor-specific DNA methylation markers by integration with other genomic types.