Use of Micro-RNA Arrays to Identify MDSC Functional Pathways and Markers

描述（由申请人提供）：髓源性抑制细胞（MDSC）是一种异质的、定义不清的免疫调节细胞群，是抑制肿瘤免疫和控制炎症过程的关键细胞群。目前，MDSC的功能是基于对包含抑制性和非抑制性细胞的表型定义细胞群的研究。没有明确定义功能性MDSC的标记物，也没有描述MDSC特有的功能途径。我们最近发现，小鼠脾脏Gr1+CD11b+细胞，即典型的MDSC表型，是前体MDSC，而活性调节性MDSC仅存在于肿瘤内或炎症部位。只有肿瘤或炎症来源的MDSC表达精氨酸酶I （Arg-I）和诱导型一氧化氮合酶（iNOS）并抑制T细胞反应，明确将功能性MDSC定位于活跃的炎症部位。因此，我们对来自脾脏和肿瘤的MDSC进行了阵列分析，以确定肿瘤来源的（功能性）MDSC的基因和微rna （miRNA）表达模式。基因阵列分析显示，与脾脏（前体）MDSC相比，肿瘤源性（功能性）MDSC中有150个基因上调至少5倍，包括Arg-I（129倍）和iNOS（33倍）。在这些差异表达的新基因中，迄今为止有两个，slc7a2和维生素D受体，被观察到调节MDSC T细胞抑制活性。因此，我们假设鉴定与MDSC功能相关的mirna将鉴定新的靶标，从而能够鉴定和调节活性MDSC。此外，将miRNA分析与基因阵列数据相结合将增强功能性MDSC特有的途径发现。在用于基因阵列分析的同一脾脏和肿瘤来源的MDSC上进行差异miRNA阵列。miRNA阵列显示46个miRNA有2倍或以上的显著上调，40个miRNA有2倍或以上的下调。我们建议将差异miRNA阵列与基因阵列结合使用，以鉴定与MDSC功能相关的新的MDSC特异性基因和途径。调控mirna和相关途径的鉴定将为更好地理解MDSC功能的分子基础提供基础，也将为更好地靶向MDSC和/或识别活性MDSC的存在提供机会。提出了两个具体目标：(1)确定与区分功能性和前体MDSC显著相关的基因、基因集、途径和网络模块，以获得生物学过程及其与癌症的相关性的全局见解。假设：功能性MDSC与前体MDSC使用不同的功能途径，这将区分两个群体。通过通路/网络建模和综合表达谱，可以在系统水平上检测到与功能相关的差异通路表达。(2)验证通过Aim 1中进行的分析鉴定的选择miRNA的生物学相关性。

DESCRIPTION (provided by applicant): Myeloid derived suppressor cells (MDSC) are a heterogeneous, ill-defined population of immune regulatory cells that are a critical cell population in suppressing tumor immunity and controlling inflammatory processes. Currently, MDSC function is based on studies of phenotypically defined cell populations that contain both suppressive and non-suppressive cells. Markers clearly defining functional MDSC are not available nor have functional pathways unique to MDSC been described. We recently showed that spleen Gr1+CD11b+ cells in mice, the prototypical MDSC phenotype, are precursor MDSC and that active regulatory MDSC are present only within a tumor or at the site of inflammation. Only tumor- or inflammation-derived MDSC to express Arginase I (Arg-I) and inducible nitric oxide synthase (iNOS) and suppress T cell responses, clearly localizing functional MDSC to active inflammatory sites. Thus, array analyses on MDSC both from spleen and tumor were performed to identify gene and micro-RNA (miRNA) expression patterns restricted to tumor-derived (functional) MDSC. Gene array analysis showed 150 genes to be upregulated at least 5-fold, including Arg-I (129-fold) and iNOS (33-fold), in tumor-derived (functional) MDSC compared to spleen (precursor) MDSC. Among the novel genes differentially expressed, to date two, slc7a2 and vitamin D receptor, were observed to regulate MDSC T cell suppressor activity. Thus we hypothesize that identifying miRNAs linked to MDSC function will identify new targets that will enable identification and modulation of active MDSC. Additionally, integrating the miRNA analysis with the gene array data will enhance pathway discovery unique to functional MDSC. Differential miRNA arrays were performed on the same spleen- and tumor-derived MDSC that were used for the gene array analysis. The miRNA arrays show a statistically significant 2-fold or greater up-regulation of 46 miRNAs and similarly a 2-fold or more down- regulation of 40 miRNAs. We propose to utilize the differential miRNA arrays in conjunction with the gene arrays to identify novel MDSC-specific genes and pathways that are associated with MDSC function. The identification of regulatory miRNAs and associated pathways will provide the foundation for better understanding the molecular basis for MDSC function and also will provide opportunity to better target MDSC and/or identify the presence of active MDSC. Two specific aims are proposed: (1) Identify genes, gene sets, pathways, and network modules that are significantly related to differentiating between functional and precursor MDSC to gain global insights of the biological process and its relevance to cancer. Hypothesis: functional MDSC utilize distinct functional pathways from precursor MDSC that will distinguish the two populations. The differential pathway expression linked to function can be detected at the systems level through pathway/network modeling and integrative expression profiling and (2) Validate the biological relevance of select miRNA identified via the analyses performed in Aim 1.