Cummings Michele, Mappa Georgia, Orsi Nicolas M
Leeds Institute of Cancer and Pathology, St. James's University Hospital, Leeds, UK.
Methods Mol Biol. 2018;1723:155-166. doi: 10.1007/978-1-4939-7558-7_8.
Laser capture microdissection (LCM) allows expression profiling of specific cell populations within tissues. However, isolation of high-quality RNA from laser capture microdissected frozen tissue is beset by problems arising from intrinsic tissue RNase activity. Herein, we describe an optimized staining/LCM/RNA extraction protocol developed for the isolation of epithelial RNA from frozen tissue sections using human endometrial cancer as a model tissue. This method combines excellent, reproducible visualization of tissue morphology with the isolation of high-integrity RNA suitable for downstream applications such as expression microarray analysis. We present quantitative and qualitative RNA data obtained from >200 endometrial epithelial samples (normal, hyperplastic, and cancerous), where 92% of samples had RIN values of 7 and above and highlight common pitfalls faced by investigators. This method should also be broadly applicable to a range of other tissue types.
激光捕获显微切割(LCM)技术能够对组织内特定细胞群体进行表达谱分析。然而,从经激光捕获显微切割的冷冻组织中分离高质量RNA,却因组织内源性核糖核酸酶(RNase)活性引发的问题而受到困扰。在此,我们描述了一种优化的染色/LCM/RNA提取方案,该方案以人子宫内膜癌作为模型组织,用于从冷冻组织切片中分离上皮RNA。此方法将出色且可重复的组织形态可视化与分离适用于下游应用(如表达微阵列分析)的高完整性RNA相结合。我们展示了从200多个子宫内膜上皮样本(正常、增生和癌性)中获得的定量和定性RNA数据,其中92%的样本RNA完整性数(RIN)值为7及以上,并强调了研究人员面临的常见陷阱。该方法也应广泛适用于一系列其他组织类型。