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Biochim Biophys Acta Rev Cancer. 2017 Aug;1868(1):258-272. doi: 10.1016/j.bbcan.2017.05.005. Epub 2017 May 23.

Standardising RNA profiling based biomarker application in cancer-The need for robust control of technical variables.

Author information

1
Centre for Cancer Research and Cell Biology, Queen's University Belfast, UK; Northern Ireland Molecular Pathology Laboratory, Queen's University Belfast, UK.
2
Department of Pathology and Tumour Biology, St James University Hospital, Leeds, UK.
3
CRUK/MRC Oxford Institute for Radiation Oncology, University of Oxford, UK.
4
Centre for Cancer Research and Cell Biology, Queen's University Belfast, UK.
5
Centre for Cancer Research and Cell Biology, Queen's University Belfast, UK; Northern Ireland Molecular Pathology Laboratory, Queen's University Belfast, UK. Electronic address: m.salto-tellez@qub.ac.uk.

Abstract

Histopathology-based staging of colorectal cancer (CRC) has utility in assessing the prognosis of patient subtypes, but as yet cannot accurately predict individual patient's treatment response. Transcriptomics approaches, using array based or next generation sequencing (NGS) platforms, of formalin fixed paraffin embedded tissue can be harnessed to develop multi-gene biomarkers for predicting both prognosis and treatment response, leading to stratification of treatment. While transcriptomics can shape future biomarker development, currently <1% of published biomarkers become clinically validated tests, often due to poor study design or lack of independent validation. In this review of a large number of CRC transcriptional studies, we identify recurrent sources of technical variability that encompass collection, preservation and storage of malignant tissue, nucleic acid extraction, methods to quantitate RNA transcripts and data analysis pipelines. We propose a series of defined steps for removal of these confounding issues, to ultimately aid in the development of more robust clinical biomarkers.

KEYWORDS:

Biomarker; FFPE; Microarray; NGS; RNA profiling; Transcriptome

PMID:
28549623
DOI:
10.1016/j.bbcan.2017.05.005
[Indexed for MEDLINE]
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