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

KH Chang, Pieter Mestdagh UGent, Jo Vandesompele UGent, MJ Kerin and N Miller (2010) BMC CANCER. 10.
abstract
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.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
RT-PCR, TIME QUANTITATIVE PCR, HOUSEKEEPING GENES, RIBOSOMAL-RNA, NORMALIZATION, IDENTIFICATION, COLON, DIFFERENTIATION, TISSUES, POLYMERASE CHAIN-REACTION
journal title
BMC CANCER
BMC Cancer
volume
10
article_number
173
pages
13 pages
publisher
BIOMED CENTRAL LTD
place of publication
LONDON
Web of Science type
Article
Web of Science id
000277804400001
JCR category
ONCOLOGY
JCR impact factor
3.153 (2010)
JCR rank
66/181 (2010)
JCR quartile
2 (2010)
ISSN
1471-2407
DOI
10.1186/1471-2407-10-173
language
English
UGent publication?
yes
classification
A1
copyright statement
I have retained and own the full copyright for this publication
id
1004323
handle
http://hdl.handle.net/1854/LU-1004323
date created
2010-07-06 16:17:13
date last changed
2010-07-15 09:39:39
@article{1004323,
  abstract     = {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.},
  articleno    = {173},
  author       = {Chang, KH and Mestdagh, Pieter and Vandesompele, Jo and Kerin, MJ and Miller, N},
  issn         = {1471-2407},
  journal      = {BMC CANCER},
  keyword      = {RT-PCR,TIME QUANTITATIVE PCR,HOUSEKEEPING GENES,RIBOSOMAL-RNA,NORMALIZATION,IDENTIFICATION,COLON,DIFFERENTIATION,TISSUES,POLYMERASE CHAIN-REACTION},
  language     = {eng},
  pages        = {13},
  publisher    = {BIOMED CENTRAL LTD},
  title        = {MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer},
  url          = {http://dx.doi.org/10.1186/1471-2407-10-173},
  volume       = {10},
  year         = {2010},
}

Chicago
Chang, KH, Pieter Mestdagh, Jo Vandesompele, MJ Kerin, and N Miller. 2010. “MicroRNA Expression Profiling to Identify and Validate Reference Genes for Relative Quantification in Colorectal Cancer.” Bmc Cancer 10.
APA
Chang, K., Mestdagh, P., Vandesompele, J., Kerin, M., & Miller, N. (2010). MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer. BMC CANCER, 10.
Vancouver
1.
Chang K, Mestdagh P, Vandesompele J, Kerin M, Miller N. MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer. BMC CANCER. LONDON: BIOMED CENTRAL LTD; 2010;10.
MLA
Chang, KH, Pieter Mestdagh, Jo Vandesompele, et al. “MicroRNA Expression Profiling to Identify and Validate Reference Genes for Relative Quantification in Colorectal Cancer.” BMC CANCER 10 (2010): n. pag. Print.