Extracellular matrix gene expression profiling using microfluidics for colorectal carcinoma stratification
Author(s) -
Christopher J. Hayes,
Catríona M. Dowling,
Susan Dwane,
Mary McCumiskey,
Shona Tormey,
Brigid Anne Merrigan,
John Calvin Coffey,
Patrick A. Kiely,
Tara Dalton
Publication year - 2016
Publication title -
biomicrofluidics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.634
H-Index - 63
ISSN - 1932-1058
DOI - 10.1063/1.4966245
Subject(s) - biomarker , colorectal cancer , extracellular matrix , taqman , real time polymerase chain reaction , gene expression profiling , computational biology , gene expression , biology , gene , cancer research , cancer , bioinformatics , microbiology and biotechnology , genetics
peer-reviewedThe full text of this article will not be available on ULIR until the embargo expires on the 31/10/2016In cancer, biomarkers have many potential applications including generation of a differential diagnosis, prediction of response to treatment, and monitoring disease progression. Many molecular biomarkers have been put forward for different diseases but most of them do not possess the required specificity and sensitivity. A biomarker with a high sensitivity has a low specificity and vice versa. The inaccuracy of the biomarkers currently in use has led to a compelling need to identify more accurate markers with diagnostic and prognostic significance. The aim of the present study was to use a novel, droplet-based, microfluidic platform to evaluate the prognostic value of a panel of thirty-four genes that regulate the composition of extracellular matrices in colorectal carcinoma. Our method is a novel approach as it uses using continuous-flowing Polymerase Chain Reaction for the sensitive detection and accurate quantitation of gene expression. We identified a panel of relevant extracellular matrix genes whose expression levels were measured by real-time quantitative polymerase chain reaction using Taqman VR reagents in twenty-four pairs of matched colorectal cancer tumour and associated normal tissue. Differential expression patterns occurred between the normal and malignant tissue and correlated with histopathological parameters and overall surgical staging. The findings demonstrate that a droplet-based microfluidic quantitative PCR system enables biomarker classification. It was further possible to sub-classify colorectal cancer based on extracellular matrix protein expressing groups which in turn correlated with prognosis. (C) 2016 Author(s).PUBLISHEDpeer-reviewe
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