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A 19-Gene expression signature as a predictor of survival in colorectal cancer

BACKGROUND: Histopathological assessment has a low potential to predict clinical outcome in patients with the same stage of colorectal cancer. More specific and sensitive biomarkers to determine patients’ survival are needed. We aimed to determine gene expression signatures as reliable prognostic ma...

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Autores principales: Abdul Aziz, Nurul Ainin, Mokhtar, Norfilza M., Harun, Roslan, Mollah, Md Manir Hossain, Mohamed Rose, Isa, Sagap, Ismail, Mohd Tamil, Azmi, Wan Ngah, Wan Zurinah, Jamal, Rahman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5016995/
https://www.ncbi.nlm.nih.gov/pubmed/27609023
http://dx.doi.org/10.1186/s12920-016-0218-1
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author Abdul Aziz, Nurul Ainin
Mokhtar, Norfilza M.
Harun, Roslan
Mollah, Md Manir Hossain
Mohamed Rose, Isa
Sagap, Ismail
Mohd Tamil, Azmi
Wan Ngah, Wan Zurinah
Jamal, Rahman
author_facet Abdul Aziz, Nurul Ainin
Mokhtar, Norfilza M.
Harun, Roslan
Mollah, Md Manir Hossain
Mohamed Rose, Isa
Sagap, Ismail
Mohd Tamil, Azmi
Wan Ngah, Wan Zurinah
Jamal, Rahman
author_sort Abdul Aziz, Nurul Ainin
collection PubMed
description BACKGROUND: Histopathological assessment has a low potential to predict clinical outcome in patients with the same stage of colorectal cancer. More specific and sensitive biomarkers to determine patients’ survival are needed. We aimed to determine gene expression signatures as reliable prognostic marker that could predict survival of colorectal cancer patients with Dukes’ B and C. METHODS: We examined microarray gene expression profiles of 78 archived tissues of patients with Dukes’ B and C using the Illumina DASL assay. The gene expression data were analyzed using the GeneSpring software and R programming. RESULTS: The outliers were detected and replaced with randomly chosen genes from the 90 % confidence interval of the robust mean for each group. We performed three statistical methods (SAM, LIMMA and t-test) to identify significant genes. There were 19 significant common genes identified from microarray data that have been permutated 100 times namely NOTCH2, ITPRIP, FRMD6, GFRA4, OSBPL9, CPXCR1, SORCS2, PDC, C12orf66, SLC38A9, OR10H5, TRIP13, MRPL52, DUSP21, BRCA1, ELTD1, SPG7, LASS6 and DUOX2. This 19-gene signature was able to significantly predict the survival of patients with colorectal cancer compared to the conventional Dukes’ classification in both training and test sets (p < 0.05). The performance of this signature was further validated as a significant independent predictor of survival using patient cohorts from Australia (n = 185), USA (n = 114), Denmark (n = 37) and Norway (n = 95) (p < 0.05). Validation using quantitative PCR confirmed similar expression pattern for the six selected genes. CONCLUSION: Profiling of these 19 genes may provide a more accurate method to predict survival of patients with colorectal cancer and assist in identifying patients who require more intensive treatment. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12920-016-0218-1) contains supplementary material, which is available to authorized users.
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spelling pubmed-50169952016-09-10 A 19-Gene expression signature as a predictor of survival in colorectal cancer Abdul Aziz, Nurul Ainin Mokhtar, Norfilza M. Harun, Roslan Mollah, Md Manir Hossain Mohamed Rose, Isa Sagap, Ismail Mohd Tamil, Azmi Wan Ngah, Wan Zurinah Jamal, Rahman BMC Med Genomics Research Article BACKGROUND: Histopathological assessment has a low potential to predict clinical outcome in patients with the same stage of colorectal cancer. More specific and sensitive biomarkers to determine patients’ survival are needed. We aimed to determine gene expression signatures as reliable prognostic marker that could predict survival of colorectal cancer patients with Dukes’ B and C. METHODS: We examined microarray gene expression profiles of 78 archived tissues of patients with Dukes’ B and C using the Illumina DASL assay. The gene expression data were analyzed using the GeneSpring software and R programming. RESULTS: The outliers were detected and replaced with randomly chosen genes from the 90 % confidence interval of the robust mean for each group. We performed three statistical methods (SAM, LIMMA and t-test) to identify significant genes. There were 19 significant common genes identified from microarray data that have been permutated 100 times namely NOTCH2, ITPRIP, FRMD6, GFRA4, OSBPL9, CPXCR1, SORCS2, PDC, C12orf66, SLC38A9, OR10H5, TRIP13, MRPL52, DUSP21, BRCA1, ELTD1, SPG7, LASS6 and DUOX2. This 19-gene signature was able to significantly predict the survival of patients with colorectal cancer compared to the conventional Dukes’ classification in both training and test sets (p < 0.05). The performance of this signature was further validated as a significant independent predictor of survival using patient cohorts from Australia (n = 185), USA (n = 114), Denmark (n = 37) and Norway (n = 95) (p < 0.05). Validation using quantitative PCR confirmed similar expression pattern for the six selected genes. CONCLUSION: Profiling of these 19 genes may provide a more accurate method to predict survival of patients with colorectal cancer and assist in identifying patients who require more intensive treatment. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12920-016-0218-1) contains supplementary material, which is available to authorized users. BioMed Central 2016-09-08 /pmc/articles/PMC5016995/ /pubmed/27609023 http://dx.doi.org/10.1186/s12920-016-0218-1 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Abdul Aziz, Nurul Ainin
Mokhtar, Norfilza M.
Harun, Roslan
Mollah, Md Manir Hossain
Mohamed Rose, Isa
Sagap, Ismail
Mohd Tamil, Azmi
Wan Ngah, Wan Zurinah
Jamal, Rahman
A 19-Gene expression signature as a predictor of survival in colorectal cancer
title A 19-Gene expression signature as a predictor of survival in colorectal cancer
title_full A 19-Gene expression signature as a predictor of survival in colorectal cancer
title_fullStr A 19-Gene expression signature as a predictor of survival in colorectal cancer
title_full_unstemmed A 19-Gene expression signature as a predictor of survival in colorectal cancer
title_short A 19-Gene expression signature as a predictor of survival in colorectal cancer
title_sort 19-gene expression signature as a predictor of survival in colorectal cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5016995/
https://www.ncbi.nlm.nih.gov/pubmed/27609023
http://dx.doi.org/10.1186/s12920-016-0218-1
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