Transcriptomic profiling of human skin biopsies in the clinical trial setting: A protocol for high quality RNA extraction from skin tumours .

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Abstract

Transcriptomic profiling of skin disease using next generation sequencing allows for detailed information on aspects of RNA biology including gene expression, non-coding regulatory elements and gene splicing. The application of RNA sequencing to human skin disease and cancer is often hampered by degraded RNA. Here we describe a protocol that allows for consistently intact RNA to be extracted from snap frozen skin biopsy samples, which has been validated in a clinical trial setting. Human skin tumour punch biopsies (n=28) ranging from 4-6mm in diameter were obtained from 14 patients with an inherited skin tumour syndrome (CYLD cutaneous syndrome) and frozen in liquid nitrogen prior to being stored at -80°C. These samples were then subject to cyrostat sectioning, allowing for histological assessment, and were homogenised using a bead-based lysis platform. RNA extraction was performed using a silica column-based system. RNA concentration was measured using fluorescent quantitation and RNA integrity assessed using microfluidic gel electrophoresis. We also processed normal skin biopsies using the same protocol (n=10). The mean RNA integrity score of the tumour and normal samples was 9.5, and the quantity of RNA obtained from the small amounts of tissue used exceeded requirements for RNA-seq library generation. We propose that the method of RNA extraction suggested here allows for transcriptomic profiling from small pieces of human tissue without the need for PCR amplification during library preparation. This protocol could be utilised in healthy and diseased skin to improve mechanistic understanding in a range of human skin diseases.

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CITATION STYLE

APA

Rajan, N., Danilenko, M., & Stones, R. (2018). Transcriptomic profiling of human skin biopsies in the clinical trial setting: A protocol for high quality RNA extraction from skin tumours . Wellcome Open Research, 3. https://doi.org/10.12688/wellcomeopenres.14360.1

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