Serum Antibody Profiling with a Carbohydrate Microarray
使用碳水化合物微阵列进行血清抗体分析
基本信息
- 批准号:10262213
- 负责人:
- 金额:$ 31.42万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:
- 资助国家:美国
- 起止时间:至
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Biomarkers play a critical role in cancer diagnosis and treatment. Serum antibodies represent an important class of biomarkers with many advantageous features such as good stability, accessibility in biofluids, and easy detection. There has been extensive research on identifying changes in antibody levels to protein antigens; however, analysis of antibodies that binding carbohydrate antigens have been largely underutilized. Our carbohydrate microarray is well-suited to monitor the repertoire of anti-glycan antibodies in human serum and to study changes in their levels in response to disease or treatment of disease. The high-throughput approach can be used to identify new single biomarkers or to identify combinations of changes or profiles that are useful as biomarkers. Over the last few years, we have developed and validated a carbohydrate microarray assay for measuring antibody levels in human serum. We are now applying this technology in a variety of areas. In collaboration with Dr. Schlom and colleagues, we have been using the array to evaluate immune responses to the PSA-TRICOM prostate cancer vaccine (PROSTVAC-VF). We have found the pre-vaccination IgM antibody levels to blood group A trisaccharide correlate with survival on PROSTVAC-VF. In addition, we have found that antibody response to the Forssman antigen correlate with overall survival. Both correlations are consistent in two independent patient groups encompassing over 100 patients. These are promising new biomarkers for determining which patients should receive PROSTVAC-VF and which patients on PROSTVAC-VF are having a favorable immune response. Finally, in collaboration with Elizabeth Jaffee, we have profiled immune responses induced by GVAX Pancreas whole cell vaccine. We also began studying antibody responses to carbohydrate antigens induced by SARS-CoV-2 infection.
生物标志物在癌症诊断和治疗中起关键作用。血清抗体代表了重要的生物标志物类,具有许多有利的特征,例如良好的稳定性,生物流体中的可及性和易于检测。关于鉴定蛋白质抗原抗体水平的变化,已经进行了广泛的研究。然而,对结合碳水化合物抗原的抗体的分析在很大程度上不足。我们的碳水化合物微阵列非常适合监测人血清中抗聚糖抗体的曲目,并研究其对疾病或疾病治疗的水平的变化。高通量方法可用于识别新的单个生物标志物或识别有用的变化或轮廓的组合。在过去的几年中,我们开发了并验证了一种碳水化合物微阵列测定法,用于测量人血清中的抗体水平。我们现在正在各个领域应用这项技术。与Schlom博士及其同事合作,我们一直在使用该阵列评估对PSA-TRICOM前列腺癌疫苗(ProstVAC-VF)的免疫反应。我们已经发现,疫苗接种的IgM抗体水平与ProstVAC-VF上的生存率相关。此外,我们发现对福斯曼抗原的抗体反应与总生存率相关。在两个独立患者组中,两种相关性均一致,包括100多名患者。这些是确定哪些患者应接受ProstVAC-VF的新生物标志物以及ProstVAC-VF中哪些患者的免疫反应良好。最后,与伊丽莎白·贾菲(Elizabeth Jaffee)合作,我们介绍了GVAX胰腺全细胞疫苗引起的免疫反应。我们还开始研究SARS-COV-2感染诱导的碳水化合物抗原的抗体反应。
项目成果
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数据更新时间:2024-06-01
Jeffrey Gildersle...的其他基金
Serum Antibody Profiling with a Carbohydrate Microarray
使用碳水化合物微阵列进行血清抗体分析
- 批准号:1001451510014515
- 财政年份:
- 资助金额:$ 31.42万$ 31.42万
- 项目类别:
Carbohydrate Microarray Profiling of Glycan-Binding Antibodies and Lectins
聚糖结合抗体和凝集素的碳水化合物微阵列分析
- 批准号:1026214210262142
- 财政年份:
- 资助金额:$ 31.42万$ 31.42万
- 项目类别:
Development of a Carbohydrate Microarray
碳水化合物微阵列的开发
- 批准号:1026213010262130
- 财政年份:
- 资助金额:$ 31.42万$ 31.42万
- 项目类别:
Serum Antibody Profiling with a Carbohydrate Microarray
使用碳水化合物微阵列进行血清抗体分析
- 批准号:1070246210702462
- 财政年份:
- 资助金额:$ 31.42万$ 31.42万
- 项目类别:
Development of a Carbohydrate Microarray
碳水化合物微阵列的开发
- 批准号:1092605410926054
- 财政年份:
- 资助金额:$ 31.42万$ 31.42万
- 项目类别:
Carbohydrate Microarray Profiling of Glycan-Binding Antibodies and Lectins
聚糖结合抗体和凝集素的碳水化合物微阵列分析
- 批准号:97796969779696
- 财政年份:
- 资助金额:$ 31.42万$ 31.42万
- 项目类别:
Serum Antibody Profiling with a Carbohydrate Microarray
使用碳水化合物微阵列进行血清抗体分析
- 批准号:97797789779778
- 财政年份:
- 资助金额:$ 31.42万$ 31.42万
- 项目类别:
Carbohydrate Microarray Profiling of Glycan-Binding Antibodies and Lectins
聚糖结合抗体和凝集素的碳水化合物微阵列分析
- 批准号:1070239910702399
- 财政年份:
- 资助金额:$ 31.42万$ 31.42万
- 项目类别:
Serum Antibody Profiling with a Carbohydrate Microarray
使用碳水化合物微阵列进行血清抗体分析
- 批准号:1092611910926119
- 财政年份:
- 资助金额:$ 31.42万$ 31.42万
- 项目类别:
Carbohydrate Microarray Profiling of Glycan-Binding Antibodies and Lectins
聚糖结合抗体和凝集素的碳水化合物微阵列分析
- 批准号:1001443110014431
- 财政年份:
- 资助金额:$ 31.42万$ 31.42万
- 项目类别:
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