A Fast-Tracking Sample Preparation Protocol for Proteomics of Formalin-Fixed Paraffin-Embedded Tumor Tissues

协议(科学) 跟踪(教育) 样品(材料) 计算机科学 生物医学工程 材料科学 色谱法 医学 化学 病理 心理学 教育学 替代医学
作者
Lancia Darville,John H. Lockhart,Sudhir Putty Reddy,Bin Fang,Victoria Izumi,Theresa A. Boyle,Eric B. Haura,Elsa R. Flores,John M. Koomen
出处
期刊:Methods in molecular biology [Springer Science+Business Media]
卷期号:: 193-223 被引量:1
标识
DOI:10.1007/978-1-0716-3922-1_13
摘要

Archived tumor specimens are routinely preserved by formalin fixation and paraffin embedding. Despite the conventional wisdom that proteomics might be ineffective due to the cross-linking and pre-analytical variables, these samples have utility for both discovery and targeted proteomics. Building on this capability, proteomics approaches can be used to maximize our understanding of cancer biology and clinical relevance by studying preserved tumor tissues annotated with the patients' medical histories. Proteomics of formalin-fixed paraffin-embedded (FFPE) tissues also integrates with histological evaluation and molecular pathology strategies, so that additional collection of research biopsies or resected tumor aliquots is not needed. The acquisition of data from the same tumor sample also overcomes concerns about biological variation between samples due to intratumoral heterogeneity. However, the protein extraction and proteomics sample preparation from FFPE samples can be onerous, particularly for small (i.e., limited or precious) samples. Therefore, we provide a protocol for a recently introduced kit-based EasyPep method with benchmarking against a modified version of the well-established filter-aided sample preparation strategy using laser-capture microdissected lung adenocarcinoma tissues from a genetically engineered mouse model. This model system allows control over the tumor preparation and pre-analytical variables while also supporting the development of methods for spatial proteomics to examine intratumoral heterogeneity. Data are posted in ProteomeXchange (PXD045879).

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