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Journal of Cancer Research and Clinical Oncology

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01-09-2019 | Breast Cancer | Original Article – Clinical Oncology

Co-expression network analysis identified candidate biomarkers in association with progression and prognosis of breast cancer

Authors: Qiang Zhou, Jiangbo Ren, Jinxuan Hou, Gang Wang, Lingao Ju, Yu Xiao, Yan Gong

Published in: Journal of Cancer Research and Clinical Oncology | Issue 9/2019

Abstract

Purpose

Breast cancer is one of the most common malignancies among females, and its prognosis is affected by a complex network of gene interactions. Weighted gene co-expression network analysis was used to construct free-scale gene co-expression networks and to identify potential biomarkers for breast cancer progression.

Methods

The gene expression profiles of GSE42568 were downloaded from the Gene Expression Omnibus database. RNA-sequencing data and clinical information of breast cancer from TCGA were used for validation.

Results

A total of ten modules were established by the average linkage hierarchical clustering. We identified 58 network hub genes in the significant module (R² = 0.44) and 6 hub genes (AGO2, CDC20, CDCA5, MCM10, MYBL2, and TTK), which were significantly correlated with prognosis. Receiver-operating characteristic curve validated that the mRNA levels of these six genes exhibited excellent diagnostic efficiency in the test data set of GSE42568. RNA-sequencing data from TCGA showed that the expression levels of these six genes were higher in triple-negative tumors. One-way ANOVA suggested that these six genes were upregulated at more advanced stages. The results of independent sample t test indicated that MCM10 and TTK were associated with tumor size, and that AGO2, CDC20, CDCA5, MCM10, and MYBL2 were overexpressed in lymph-node positive breast cancer.

Conclusions

AGO2, CDC20, CDCA5, MCM10, MYBL2, and TTK were identified as candidate biomarkers for further basic and clinical research on breast cancer based on co-expression analysis.

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Title: Co-expression network analysis identified candidate biomarkers in association with progression and prognosis of breast cancer
Authors: Qiang Zhou
Jiangbo Ren
Jinxuan Hou
Gang Wang
Lingao Ju
Yu Xiao
Yan Gong
Publication date: 01-09-2019
Publisher: Springer Berlin Heidelberg
Keywords: Breast Cancer
Breast Cancer
Biomarkers
Published in: Journal of Cancer Research and Clinical Oncology / Issue 9/2019
Print ISSN: 0171-5216
Electronic ISSN: 1432-1335
DOI: https://doi.org/10.1007/s00432-019-02974-4

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