Analysis of differential gene expression profile identifies novel biomarkers for breast cancer
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Yunbao Pan1,2,*, Guohong Liu3,4,*, Yufen Yuan5, Jin Zhao1, Yong Yang6 and Yirong Li1
1Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, Hubei, China
2Breast Tumor Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China
3Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, China
4School of Materials Science and Engineering and School of Electronics and Information technology, Sun Yat-Sen University, Guangzhou, Guangdong, China
5Department of Pathology, Anyang Tumor Hospital, Anyang, Henan, China
6Key Laboratory Zoonsis Research Ministry of Education, Institute of Zoonosis, Jilin University, Changchun, Jilin, China
*These authors contributed equally to this work and should be considered as co-first authors
Yirong Li, email: firstname.lastname@example.org
Keywords: breast cancer; microarray; ITGA11; Jab1/COPS5; biomarker
Received: July 28, 2017 Accepted: November 14, 2017 Published: December 08, 2017
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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