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Analysis of differential gene expression profile identifies novel biomarkers for breast cancer

Breast cancer is the most prevalent cancer diagnosis in women. We aimed to identify biomarkers for breast cancer prognosis. mRNA expression profiling was performed using Gene Chip Human Transcriptome Array 2.0. Microarray analysis and series test of cluster (STC) analysis were used to screen the dif...

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Autores principales: Pan, Yunbao, Liu, Guohong, Yuan, Yufen, Zhao, Jin, Yang, Yong, Li, Yirong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5777718/
https://www.ncbi.nlm.nih.gov/pubmed/29383106
http://dx.doi.org/10.18632/oncotarget.23061
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author Pan, Yunbao
Liu, Guohong
Yuan, Yufen
Zhao, Jin
Yang, Yong
Li, Yirong
author_facet Pan, Yunbao
Liu, Guohong
Yuan, Yufen
Zhao, Jin
Yang, Yong
Li, Yirong
author_sort Pan, Yunbao
collection PubMed
description Breast cancer is the most prevalent cancer diagnosis in women. We aimed to identify biomarkers for breast cancer prognosis. mRNA expression profiling was performed using Gene Chip Human Transcriptome Array 2.0. Microarray analysis and series test of cluster (STC) analysis were used to screen the differential expressed mRNAs and the expression trend of genes. Immumohistochemical staining with 100 clinical specimens was used to validate two differentially expressed genes, ITGA11 and Jab1. In the present study, significantly enriched Gene Ontology (GO) terms and pathways were identified. 26 model profiles were used to summarize the expression pattern of differentially expressed genes. Results of immunohistochemistry were consistent with those of the microarray, in that ITGA11 and Jab1 were differentially expressed with the same trend. Survival analyses using the Kaplan–Meier method demonstrated that breast cancer patients with high levels of either ITGA11 or Jab1 had a significant association with worse prognosis. Our study identified ITGA11 and Jab1 as novel biomarkers for breast cancer.
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spelling pubmed-57777182018-01-30 Analysis of differential gene expression profile identifies novel biomarkers for breast cancer Pan, Yunbao Liu, Guohong Yuan, Yufen Zhao, Jin Yang, Yong Li, Yirong Oncotarget Research Paper Breast cancer is the most prevalent cancer diagnosis in women. We aimed to identify biomarkers for breast cancer prognosis. mRNA expression profiling was performed using Gene Chip Human Transcriptome Array 2.0. Microarray analysis and series test of cluster (STC) analysis were used to screen the differential expressed mRNAs and the expression trend of genes. Immumohistochemical staining with 100 clinical specimens was used to validate two differentially expressed genes, ITGA11 and Jab1. In the present study, significantly enriched Gene Ontology (GO) terms and pathways were identified. 26 model profiles were used to summarize the expression pattern of differentially expressed genes. Results of immunohistochemistry were consistent with those of the microarray, in that ITGA11 and Jab1 were differentially expressed with the same trend. Survival analyses using the Kaplan–Meier method demonstrated that breast cancer patients with high levels of either ITGA11 or Jab1 had a significant association with worse prognosis. Our study identified ITGA11 and Jab1 as novel biomarkers for breast cancer. Impact Journals LLC 2017-12-08 /pmc/articles/PMC5777718/ /pubmed/29383106 http://dx.doi.org/10.18632/oncotarget.23061 Text en Copyright: © 2017 Pan et al. http://creativecommons.org/licenses/by/3.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) (CC-BY), which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Research Paper
Pan, Yunbao
Liu, Guohong
Yuan, Yufen
Zhao, Jin
Yang, Yong
Li, Yirong
Analysis of differential gene expression profile identifies novel biomarkers for breast cancer
title Analysis of differential gene expression profile identifies novel biomarkers for breast cancer
title_full Analysis of differential gene expression profile identifies novel biomarkers for breast cancer
title_fullStr Analysis of differential gene expression profile identifies novel biomarkers for breast cancer
title_full_unstemmed Analysis of differential gene expression profile identifies novel biomarkers for breast cancer
title_short Analysis of differential gene expression profile identifies novel biomarkers for breast cancer
title_sort analysis of differential gene expression profile identifies novel biomarkers for breast cancer
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5777718/
https://www.ncbi.nlm.nih.gov/pubmed/29383106
http://dx.doi.org/10.18632/oncotarget.23061
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