Jozwik Catherine E, Pollard Harvey B, Srivastava Meera, Eidelman Ofer, Fan QingYuan, Darling Thomas N, Zeitlin Pamela L
Department of Anatomy, Physiology and Genetics, Uniformed Services University School of Medicine, Bethesda, MD, USA.
Methods Mol Biol. 2012;823:179-200. doi: 10.1007/978-1-60327-216-2_12.
Cystic fibrosis (CF) is the most common autosomal recessive disease in the USA and Europe, whose life-limiting phenotype is manifest on epithelial cells throughout the body. The principal cause of morbidity and mortality is a massively proinflammatory condition in the lung. The mutation responsible for most cases of CF is [ΔF508]CFTR. However, the penetrance of the disease is quite variable, and adverse events leading to hospitalization cannot be easily predicted. Thus, there is a strong need for prognostic endpoints that might serve to identify impending clinical problems long before they happen. Our approach has been to search for proteomic signatures in easily accessed biological fluids that might identify the molecular basis for adverse events. We describe here a workflow that begins with patient-derived bronchial brush biopsies and progresses to analysis of serum and plasma from patients on antibody microarrays.
囊性纤维化(CF)是美国和欧洲最常见的常染色体隐性疾病,其危及生命的表型在全身上皮细胞中表现出来。发病和死亡的主要原因是肺部严重的促炎状态。导致大多数CF病例的突变是[ΔF508]CFTR。然而,该疾病的外显率差异很大,导致住院的不良事件难以轻易预测。因此,迫切需要能够在临床问题发生前很久就识别出即将出现的临床问题的预后终点。我们的方法是在易于获取的生物体液中寻找蛋白质组学特征,以确定不良事件的分子基础。我们在此描述一种工作流程,该流程从患者来源的支气管刷检活检开始,进而对抗体微阵列上患者的血清和血浆进行分析。