Chronic Graft-Versus-Host Disease Biomarkers: Prediction of Resistance to Therapy

慢性移植物抗宿主病生物标志物：治疗耐药性的预测

• 批准号: 10751970
• 负责人: Sophie Paczesny
• 金额: $ 22.65万
• 依托单位: MEDICAL UNIVERSITY OF SOUTH CAROLINA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-23 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10751970
• 关键词: Academia; Acute Graft Versus Host Disease; Address; Adopted; Aftercare; Allogenic; Antibody Affinity; Award; Biological; Biological Assay; Biological Markers; Biology; Blood; Blood Tests; Blood specimen; Bone Marrow Transplantation; CXCL10 gene; Clinical; Clinical Trials Network; Collaborations; Complex; Complication; Data; Dependence; Development; Disease; Disease Pathway; Disease Resistance; Enzyme-Linked Immunosorbent Assay; Exposure to; Future; Hematologic Neoplasms; IRAK1 gene; In complete remission; Individual; Inherited; Interleukins; JAK2 gene; Lead; Ligands; Macrophage Colony-Stimulating Factor Receptor; Malignant - descriptor; Measures; Monitor; Pathology; Pathway interactions; Patients; Peripheral Blood Mononuclear Cell; Pharmaceutical Preparations; Phase I/II Trial; Phosphotransferases; Plasma; Plasma Proteins; Prognosis; Progressive Disease; Proteins; Proteomics; Refractory; Research; Resistance; Risk; Risk Marker; Sampling; Sensitivity and Specificity; Specificity; Steroids; Stromelysin 1; Testing; Therapeutic; Time; Transplant Recipients; Validation; biomarker panel; candidate identification; candidate marker; chemokine; chronic graft versus host disease; clinically relevant; cohort; curative treatments; disorder risk; experience; experimental study; hematopoietic cell transplantation; inhibitor; kinase inhibitor; mortality; novel; novel therapeutic intervention; partial response; personalized medicine; predicting response; predictive marker; predictive panel; prognostic; prognostic value; proteomic signature; receptor; response; risk stratification; secondary endpoint; specific biomarkers; success; tandem mass spectrometry; therapy resistant; treatment response

Major barriers to chronic graft-versus-host disease (cGVHD) research are the inability to predict the likelihood of response to cGVHD therapy and subsequent patient survival. This absence of predictive biomarkers is partly due to the complex pathology of cGVHD, which involves both soluble and cellular factors but mostly due to the paucity, so far, of samples collected when specific cGVHD treatments are initiated, particularly as novel and more targeted treatments for cGVHD are now available. Thus, major questions remaining in the field are: Can we target more than one cGVHD pathway with a single drug? Can we detect biomarkers to predict future resistance to treatment using already validated cGVHD biomarkers? Can we discover more specific markers through a high throughput proteomics pipeline? Can we validate and utilize these predictive biomarkers to provide strong support for FDA approval of these biomarkers? For this project, we will use samples (plasma and PBMCs) collected during Dr. Pavletic trial testing Pacritanib, a multi-kinase inhibitor with specificity for JAK2 and IRAK1, in patients with steroid-refractory/steroid-dependent (SR/D) cGVHD to analyze proteomic signatures associated with prediction of cGVHD therapy nonresponse, and with prognosis of nonrelapse mortality (NRM). Proposed markers are based on previous studies and will include other novel or hypothesized factors. We will test the hypothesis that plasma proteomic panels measured prior to the start of cGVHD treatment with pacritinib (PAC) will stratify HCT patients for prediction of resistance, and NRM at 1 year. We will determine the thresholds of different biomarkers and panels that provide best sensitivity and specificity. Our overarching hypothesis addresses gaps remaining by addressing two specific aims (SA): SA1: Are five previously identified plasma cGVHD biomarkers [chemokine (C-X-C motif) ligand 9 (CXCL9), CXCL10, matrix metalloproteinase 3 (MMP3), Dickkopf-related protein 3 (DKK3), and Stimulation 2 (ST2; the interleukin (IL)-33 receptor)] predictive of resistance to PAC therapy? We will measure them using ELISA from fresh blood samples collected during this award: ~35 samples pre-treatment and 3- and 6-months post-treatment. SA2: Can additional plasma biomarkers that are key biologic drivers of cGVHD resistance be discovered through our proteomics pipeline comparing responders vs. non responders? We will address this question using our well- established proteomic workflow that can identify and quantify more than 2000 proteins. Upon completion, these studies will result in biomarker panels that may facilitate prediction of response and resistance to therapy and identify candidates for new therapeutic approaches.

慢性移植物抗宿主病(CGVHD)研究的主要障碍是无法预测 对cGVHD治疗的反应和随后的患者存活率。这种预测性生物标志物的缺乏在一定程度上是 由于cGVHD的复杂病理，涉及到可溶性和细胞因素，但主要是由于 到目前为止，在启动特定的cGVHD治疗时收集的样本很少，特别是作为新的和 现在有了更有针对性的治疗cGVHD的方法。因此，该领域仍然存在的主要问题是： 我们用一种药物靶向不止一个cGVHD途径？我们能通过检测生物标志物来预测未来吗 使用已经验证的cGVHD生物标志物治疗的耐药性？我们能发现更具体的标记吗？ 通过高通量的蛋白质组学管道？我们能否验证和利用这些预测生物标记物来 为FDA批准这些生物标记物提供强有力的支持？对于这个项目，我们将使用样本(血浆 和PBMCs)在Pavletic博士试验测试Pacritanib期间收集，Pacritanib是一种对 类固醇耐药/类固醇依赖(SR/D)cGVHD患者JAK2和IRAK1的蛋白质组学分析 与cGVHD治疗无反应预测和无复发预后相关的信号 死亡率(NRM)。建议的标记是基于以前的研究，并将包括其他小说或假设 各种因素。我们将测试在cGVHD开始之前测量的血浆蛋白质组的假设 帕利替尼(PAC)的治疗将对HCT患者进行分层以预测耐药性，并在1年内对NRM进行分层。我们 将确定提供最佳敏感度和特异度的不同生物标志物和面板的阈值。 我们的总体假设通过解决两个具体目标(SA)来解决剩余的差距：SA1：有五个 先前发现的血浆cGVHD生物标志物[趋化因子(C-X-C基序)配体9(CXCL9)，CXCL10，基质 金属蛋白酶3(MMP3)、Dickkopf相关蛋白3(DKK3)和刺激因子2(ST2；白介素33 受体)]预测耐药的PAC治疗？我们将用酶联免疫吸附试验从新鲜血液中检测它们 在此奖项期间收集的样本：治疗前和治疗后3个月和6个月的大约35个样本。SA2： 作为cGVHD耐药性关键生物驱动因素的更多血浆生物标记物能否通过我们的 蛋白质组学流水线比较应答者和非应答者？我们将用我们的油井来解决这个问题- 建立了蛋白质组学工作流程，可以识别和量化2000多种蛋白质。建成后，这些 研究将导致生物标志物小组的结果，这些小组可能有助于预测治疗和 确定新的治疗方法的候选者。