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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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Detalles Bibliográficos
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
Descripción
Sumario: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.