Gene expression biomarkers of immune recovery in HIV infected patients

描述（由申请人提供）：高效抗逆转录病毒治疗（HAART）后免疫恢复不良是影响很大比例（30%）艾滋病毒感染患者的重大健康问题。尽管抑制HIV复制，但不能充分增加CD4+ T细胞数量的患者仍有显著的临床进展风险（艾滋病定义事件或死亡）。目前迫切需要确定有助于CD4+ T细胞恢复的宿主基因，以便确定免疫调节疗法的靶点。此外，为了最大限度地恢复CD4+ T细胞并增加现有疗法的效用，确定可用于针对单个hiv感染患者定制不同haart治疗方案的生物标志物是至关重要的。在本提案的目的1中，将使用微阵列识别48周HAART治疗后结果良好（DCD4 3200细胞/mm3）与不良（DCD4 <200细胞/mm3）的hiv感染患者（表现出完全病毒学抑制）之间差异表达的基因。我们假设参与免疫恢复的基因会诱导CD4+ T细胞增殖并阻止细胞凋亡，这将在体外通过siRNA敲低和基因过表达分析得到证实。在Aim 2中，我们将扩展我们的初步研究，表明HAART之前的基因表达可以100%准确地预测HIV感染患者在48周药物治疗后的预后是好是坏。预测免疫恢复的基因表达分类器将专门用于接受基于蛋白酶抑制剂（PI）的HAART方案治疗的hiv感染者，然后用于接受基于非核苷逆转录酶抑制剂（NNRTI）方案治疗的患者。使用一种创新的方法，我们将使用基于pi的基因表达分类器来确定使用基于NNRTI的方案治疗的任何不良结果患者在基于pi的方案下是否预测具有良好的结果，反之亦然。通过这种方式，我们将确定在CD4+ T细胞恢复方面被放置在错误方案的患者总数。在未来，我们将能够为个体患者量身定制不同的HAART方案，以增加免疫恢复的程度。在Aim 3中，将研究microRNAs （miRNAs）在免疫恢复中的作用。我们假设miRNA靶点的降解是导致预后良好和不良组之间基因表达差异的一种机制（Aim 3A），并且miRNA表达与基因表达的结合将导致更准确的分类（Aim 3B）。当这些研究完成后，我们将确定宿主基因（即细胞因子），这些基因在接受HAART治疗的艾滋病毒感染者中引起免疫恢复，并可能在未来制定免疫调节疗法。我们还将开发能够指导hiv感染患者治疗方案的基因表达生物标志物，以最大限度地增加CD4+ T细胞数量。

DESCRIPTION (provided by applicant): Poor immune recovery following highly active antiretroviral treatment (HAART) represents a significant health problem affecting a large proportion (30%) of HIV-infected patients. Despite suppressing HIV replication, patients that are unable to sufficiently increase their CD4+ T cell numbers are at significant risk of clinical progression (AIDS-defining event or death). Currently there is a critical need to define the host genes that contribute to CD4+ T cell recovery in order to identify targets for immune modulating therapies. In addition, it is essential to identify biomarkers that can be used to tailor different HAART-regimens to the individual HIV-infected patient in order to maximize CD4+ T cell recovery and increase the utility of existing therapies. In Aim 1 of this proposal differentially expressed genes between HIV-infected patients (exhibiting complete virological suppression) with a good (DCD4 3200 cells/mm3) versus a poor (DCD4 <200 cells/mm3) outcome after 48 weeks of HAART will be identified using microarrays. We hypothesize that genes contributing to immune recovery will induce CD4+ T cell proliferation and prevent apoptosis and this will be confirmed in vitro by siRNA knockdown and gene over expression analysis. In Aim 2 we will expand upon our preliminary studies that showed gene expression prior to HAART can predict with 100% accuracy which HIV- infected patients progress to good versus poor outcome after 48 weeks of drug treatment. Gene expression classifiers predictive of immune recovery will be constructed exclusively for HIV-infected patients treated with a protease inhibitor (PI)-based HAART regimen, and then for patients treated with a non-nucleoside reverse transcriptase inhibitor (NNRTI)-based regimen. Using an innovative approach we will then use the PI-based gene expression classifier to determine if any of the poor outcome patients that were treated with an NNRTI- based regimen were predicted as having a good outcome under a PI-based regimen, and vice versa. In this way we will identify the total number of patients that were placed on the wrong regimen with respect to CD4+ T cell recovery. In the future we will be able to tailor different HAART regimens to the individual patient to increase the extent of immune recovery. In Aim 3 the role of microRNAs (miRNAs) in immune recovery will be investigated. We hypothesize that miRNA degradation of mRNA targets represents one mechanism contributing to the differential gene expression between good and poor outcome groups (Aim 3A), and that a combination of miRNA expression with gene expression will result in more accurate classifiers (Aim 3B). When these studies are complete we will have identified the host genes (i.e. cytokines) that cause immune recovery in HIV-infected patients treated with HAART and may be formulated into immune modulating therapies in the future. We will also have developed gene expression biomarkers capable of guiding the treatment options for HIV-infected patients in order to maximize increases in CD4+ T cell numbers.