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MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer

BACKGROUND: Advances in high-throughput technologies and bioinformatics have transformed gene expression profiling methodologies. The results of microarray experiments are often validated using reverse transcription quantitative PCR (RT-qPCR), which is the most sensitive and reproducible method to q...

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Autores principales: Chang, Kah Hoong, Mestdagh, Pieter, Vandesompele, Jo, Kerin, Michael J, Miller, Nicola
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2873395/
https://www.ncbi.nlm.nih.gov/pubmed/20429937
http://dx.doi.org/10.1186/1471-2407-10-173
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author Chang, Kah Hoong
Mestdagh, Pieter
Vandesompele, Jo
Kerin, Michael J
Miller, Nicola
author_facet Chang, Kah Hoong
Mestdagh, Pieter
Vandesompele, Jo
Kerin, Michael J
Miller, Nicola
author_sort Chang, Kah Hoong
collection PubMed
description BACKGROUND: Advances in high-throughput technologies and bioinformatics have transformed gene expression profiling methodologies. The results of microarray experiments are often validated using reverse transcription quantitative PCR (RT-qPCR), which is the most sensitive and reproducible method to quantify gene expression. Appropriate normalisation of RT-qPCR data using stably expressed reference genes is critical to ensure accurate and reliable results. Mi(cro)RNA expression profiles have been shown to be more accurate in disease classification than mRNA expression profiles. However, few reports detailed a robust identification and validation strategy for suitable reference genes for normalisation in miRNA RT-qPCR studies. METHODS: We adopt and report a systematic approach to identify the most stable reference genes for miRNA expression studies by RT-qPCR in colorectal cancer (CRC). High-throughput miRNA profiling was performed on ten pairs of CRC and normal tissues. By using the mean expression value of all expressed miRNAs, we identified the most stable candidate reference genes for subsequent validation. As such the stability of a panel of miRNAs was examined on 35 tumour and 39 normal tissues. The effects of normalisers on the relative quantity of established oncogenic (miR-21 and miR-31) and tumour suppressor (miR-143 and miR-145) target miRNAs were assessed. RESULTS: In the array experiment, miR-26a, miR-345, miR-425 and miR-454 were identified as having expression profiles closest to the global mean. From a panel of six miRNAs (let-7a, miR-16, miR-26a, miR-345, miR-425 and miR-454) and two small nucleolar RNA genes (RNU48 and Z30), miR-16 and miR-345 were identified as the most stably expressed reference genes. The combined use of miR-16 and miR-345 to normalise expression data enabled detection of a significant dysregulation of all four target miRNAs between tumour and normal colorectal tissue. CONCLUSIONS: Our study demonstrates that the top six most stably expressed miRNAs (let-7a, miR-16, miR-26a, miR-345, miR-425 and miR-454) described herein should be validated as suitable reference genes in both high-throughput and lower throughput RT-qPCR colorectal miRNA studies.
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spelling pubmed-28733952010-05-20 MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer Chang, Kah Hoong Mestdagh, Pieter Vandesompele, Jo Kerin, Michael J Miller, Nicola BMC Cancer Research Article BACKGROUND: Advances in high-throughput technologies and bioinformatics have transformed gene expression profiling methodologies. The results of microarray experiments are often validated using reverse transcription quantitative PCR (RT-qPCR), which is the most sensitive and reproducible method to quantify gene expression. Appropriate normalisation of RT-qPCR data using stably expressed reference genes is critical to ensure accurate and reliable results. Mi(cro)RNA expression profiles have been shown to be more accurate in disease classification than mRNA expression profiles. However, few reports detailed a robust identification and validation strategy for suitable reference genes for normalisation in miRNA RT-qPCR studies. METHODS: We adopt and report a systematic approach to identify the most stable reference genes for miRNA expression studies by RT-qPCR in colorectal cancer (CRC). High-throughput miRNA profiling was performed on ten pairs of CRC and normal tissues. By using the mean expression value of all expressed miRNAs, we identified the most stable candidate reference genes for subsequent validation. As such the stability of a panel of miRNAs was examined on 35 tumour and 39 normal tissues. The effects of normalisers on the relative quantity of established oncogenic (miR-21 and miR-31) and tumour suppressor (miR-143 and miR-145) target miRNAs were assessed. RESULTS: In the array experiment, miR-26a, miR-345, miR-425 and miR-454 were identified as having expression profiles closest to the global mean. From a panel of six miRNAs (let-7a, miR-16, miR-26a, miR-345, miR-425 and miR-454) and two small nucleolar RNA genes (RNU48 and Z30), miR-16 and miR-345 were identified as the most stably expressed reference genes. The combined use of miR-16 and miR-345 to normalise expression data enabled detection of a significant dysregulation of all four target miRNAs between tumour and normal colorectal tissue. CONCLUSIONS: Our study demonstrates that the top six most stably expressed miRNAs (let-7a, miR-16, miR-26a, miR-345, miR-425 and miR-454) described herein should be validated as suitable reference genes in both high-throughput and lower throughput RT-qPCR colorectal miRNA studies. BioMed Central 2010-04-29 /pmc/articles/PMC2873395/ /pubmed/20429937 http://dx.doi.org/10.1186/1471-2407-10-173 Text en Copyright ©2010 Chang et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Chang, Kah Hoong
Mestdagh, Pieter
Vandesompele, Jo
Kerin, Michael J
Miller, Nicola
MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer
title MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer
title_full MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer
title_fullStr MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer
title_full_unstemmed MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer
title_short MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer
title_sort microrna expression profiling to identify and validate reference genes for relative quantification in colorectal cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2873395/
https://www.ncbi.nlm.nih.gov/pubmed/20429937
http://dx.doi.org/10.1186/1471-2407-10-173
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