Optimized ChIP-seq method facilitates transcription factor profiling in human tumors
Abhishek A. Singh (Nederlands Kanker Instituut - Antoni van Leeuwenhoek ziekenhuis)
Karianne Schuurman (Nederlands Kanker Instituut - Antoni van Leeuwenhoek ziekenhuis)
E Nevedomskaya (Nederlands Kanker Instituut - Antoni van Leeuwenhoek ziekenhuis)
S. Stelloo (Nederlands Kanker Instituut - Antoni van Leeuwenhoek ziekenhuis)
Simon Linder (Nederlands Kanker Instituut - Antoni van Leeuwenhoek ziekenhuis)
Marjolein Droog (Nederlands Kanker Instituut - Antoni van Leeuwenhoek ziekenhuis)
Yongsoo Kim (Nederlands Kanker Instituut - Antoni van Leeuwenhoek ziekenhuis)
J. Sanders (Nederlands Kanker Instituut - Antoni van Leeuwenhoek ziekenhuis)
Henk van der Poel (Nederlands Kanker Instituut - Antoni van Leeuwenhoek ziekenhuis)
Andries M. Bergman (Nederlands Kanker Instituut - Antoni van Leeuwenhoek ziekenhuis)
Lodewyk F. Wessels (TU Delft - Pattern Recognition and Bioinformatics, Nederlands Kanker Instituut - Antoni van Leeuwenhoek ziekenhuis)
Wilbert Zwart (Nederlands Kanker Instituut - Antoni van Leeuwenhoek ziekenhuis, Eindhoven University of Technology)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
Chromatin immunoprecipitation (ChIP)-seq analyses of transcription factors in clinical specimens are challenging due to the technical limitations and low quantities of starting material, often resulting in low enrichments and poor signal-to-noise ratio. Here, we present an optimized protocol for transcription factor ChIP-seq analyses in human tissue, yielding an ~100% success rate for all transcription factors analyzed. As proof of concept and to illustrate general applicability of the approach, human tissue from the breast, prostate, and endometrial cancers were analyzed. In addition to standard formaldehyde fixation, disuccinimidyl glutarate was included in the procedure, greatly increasing data quality. To illustrate the sensitivity of the optimized protocol, we provide high-quality ChIP-seq data for three independent factors (AR, FOXA1, and H3K27ac) from a single core needle prostate cancer biopsy specimen. In summary, double-cross-linking strongly improved transcription factor ChIP-seq quality on human tumor samples, further facilitating and enhancing translational research on limited amounts of tissue.