Cargando…
A molecular signature for the prediction of recurrence in colorectal cancer
BACKGROUND: Several clinical and pathological factors have an impact on the prognosis of colorectal cancer (CRC), but they are not yet adequate for risk assessment. We aimed to identify a molecular signature that can reliably identify CRC patients at high risk for recurrence. RESULTS: Two hundred ei...
Autores principales: | , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4320628/ https://www.ncbi.nlm.nih.gov/pubmed/25645394 http://dx.doi.org/10.1186/s12943-015-0296-2 |
_version_ | 1782356157454614528 |
---|---|
author | Wang, Lisha Shen, Xiaohan Wang, Zhimin Xiao, Xiuying Wei, Ping Wang, Qifeng Ren, Fei Wang, Yiqin Liu, Zebing Sheng, Weiqi Huang, Wei Zhou, Xiaoyan Du, Xiang |
author_facet | Wang, Lisha Shen, Xiaohan Wang, Zhimin Xiao, Xiuying Wei, Ping Wang, Qifeng Ren, Fei Wang, Yiqin Liu, Zebing Sheng, Weiqi Huang, Wei Zhou, Xiaoyan Du, Xiang |
author_sort | Wang, Lisha |
collection | PubMed |
description | BACKGROUND: Several clinical and pathological factors have an impact on the prognosis of colorectal cancer (CRC), but they are not yet adequate for risk assessment. We aimed to identify a molecular signature that can reliably identify CRC patients at high risk for recurrence. RESULTS: Two hundred eighty-one CRC samples (stage II/III) were included in this study. A two-step gene expression profiling study was conducted. First, gene expression measurements from 81 fresh frozen CRC samples were obtained using Affymetrix Human Genome U133 Plus 2.0 Arrays. Second, a focused gene expression assay, including prognostic genes and genes of interest from literature reviews, was performed using 200 fresh frozen samples and a Taqman low-density array (TLDA) analysis. An optimal 31-gene expression classifier for the prediction of recurrence among patients with stage II/III CRC was developed using logistic regression analysis. This gene expression signature classified 58.5% of patients as low-risk and 41.5% as high-risk (P < 0.001). The signature was the strongest independent prognostic factor in the multivariate analysis. The five-year relapse-free survival (RFS) rates for the low-risk patients and the high-risk patients were 88.5% and 41.3% (P < 0.001), respectively. CONCLUSION: We identified a 31-gene expression signature that is closely associated with the clinical outcome of stage II/III CRC patients. |
format | Online Article Text |
id | pubmed-4320628 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-43206282015-02-08 A molecular signature for the prediction of recurrence in colorectal cancer Wang, Lisha Shen, Xiaohan Wang, Zhimin Xiao, Xiuying Wei, Ping Wang, Qifeng Ren, Fei Wang, Yiqin Liu, Zebing Sheng, Weiqi Huang, Wei Zhou, Xiaoyan Du, Xiang Mol Cancer Research BACKGROUND: Several clinical and pathological factors have an impact on the prognosis of colorectal cancer (CRC), but they are not yet adequate for risk assessment. We aimed to identify a molecular signature that can reliably identify CRC patients at high risk for recurrence. RESULTS: Two hundred eighty-one CRC samples (stage II/III) were included in this study. A two-step gene expression profiling study was conducted. First, gene expression measurements from 81 fresh frozen CRC samples were obtained using Affymetrix Human Genome U133 Plus 2.0 Arrays. Second, a focused gene expression assay, including prognostic genes and genes of interest from literature reviews, was performed using 200 fresh frozen samples and a Taqman low-density array (TLDA) analysis. An optimal 31-gene expression classifier for the prediction of recurrence among patients with stage II/III CRC was developed using logistic regression analysis. This gene expression signature classified 58.5% of patients as low-risk and 41.5% as high-risk (P < 0.001). The signature was the strongest independent prognostic factor in the multivariate analysis. The five-year relapse-free survival (RFS) rates for the low-risk patients and the high-risk patients were 88.5% and 41.3% (P < 0.001), respectively. CONCLUSION: We identified a 31-gene expression signature that is closely associated with the clinical outcome of stage II/III CRC patients. BioMed Central 2015-02-03 /pmc/articles/PMC4320628/ /pubmed/25645394 http://dx.doi.org/10.1186/s12943-015-0296-2 Text en © Wang et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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 Wang, Lisha Shen, Xiaohan Wang, Zhimin Xiao, Xiuying Wei, Ping Wang, Qifeng Ren, Fei Wang, Yiqin Liu, Zebing Sheng, Weiqi Huang, Wei Zhou, Xiaoyan Du, Xiang A molecular signature for the prediction of recurrence in colorectal cancer |
title | A molecular signature for the prediction of recurrence in colorectal cancer |
title_full | A molecular signature for the prediction of recurrence in colorectal cancer |
title_fullStr | A molecular signature for the prediction of recurrence in colorectal cancer |
title_full_unstemmed | A molecular signature for the prediction of recurrence in colorectal cancer |
title_short | A molecular signature for the prediction of recurrence in colorectal cancer |
title_sort | molecular signature for the prediction of recurrence in colorectal cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4320628/ https://www.ncbi.nlm.nih.gov/pubmed/25645394 http://dx.doi.org/10.1186/s12943-015-0296-2 |
work_keys_str_mv | AT wanglisha amolecularsignatureforthepredictionofrecurrenceincolorectalcancer AT shenxiaohan amolecularsignatureforthepredictionofrecurrenceincolorectalcancer AT wangzhimin amolecularsignatureforthepredictionofrecurrenceincolorectalcancer AT xiaoxiuying amolecularsignatureforthepredictionofrecurrenceincolorectalcancer AT weiping amolecularsignatureforthepredictionofrecurrenceincolorectalcancer AT wangqifeng amolecularsignatureforthepredictionofrecurrenceincolorectalcancer AT renfei amolecularsignatureforthepredictionofrecurrenceincolorectalcancer AT wangyiqin amolecularsignatureforthepredictionofrecurrenceincolorectalcancer AT liuzebing amolecularsignatureforthepredictionofrecurrenceincolorectalcancer AT shengweiqi amolecularsignatureforthepredictionofrecurrenceincolorectalcancer AT huangwei amolecularsignatureforthepredictionofrecurrenceincolorectalcancer AT zhouxiaoyan amolecularsignatureforthepredictionofrecurrenceincolorectalcancer AT duxiang amolecularsignatureforthepredictionofrecurrenceincolorectalcancer AT wanglisha molecularsignatureforthepredictionofrecurrenceincolorectalcancer AT shenxiaohan molecularsignatureforthepredictionofrecurrenceincolorectalcancer AT wangzhimin molecularsignatureforthepredictionofrecurrenceincolorectalcancer AT xiaoxiuying molecularsignatureforthepredictionofrecurrenceincolorectalcancer AT weiping molecularsignatureforthepredictionofrecurrenceincolorectalcancer AT wangqifeng molecularsignatureforthepredictionofrecurrenceincolorectalcancer AT renfei molecularsignatureforthepredictionofrecurrenceincolorectalcancer AT wangyiqin molecularsignatureforthepredictionofrecurrenceincolorectalcancer AT liuzebing molecularsignatureforthepredictionofrecurrenceincolorectalcancer AT shengweiqi molecularsignatureforthepredictionofrecurrenceincolorectalcancer AT huangwei molecularsignatureforthepredictionofrecurrenceincolorectalcancer AT zhouxiaoyan molecularsignatureforthepredictionofrecurrenceincolorectalcancer AT duxiang molecularsignatureforthepredictionofrecurrenceincolorectalcancer |