Screening of biomarkers for prediction of response to and prognosis after chemotherapy for breast cancers
Authors Bing F, Zhao Y
Received 14 July 2015
Accepted for publication 12 February 2016
Published 2 May 2016 Volume 2016:9 Pages 2593—2600
Checked for plagiarism Yes
Review by Single-blind
Peer reviewers approved by Dr Ashok Kumar Pandurangan
Peer reviewer comments 3
Editor who approved publication: Dr Faris Farassati
Feng Bing, Yu Zhao
Department of Vascular Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of China
Objective: To screen the biomarkers having the ability to predict prognosis after chemotherapy for breast cancers.
Methods: Three microarray data of breast cancer patients undergoing chemotherapy were collected from Gene Expression Omnibus database. After preprocessing, data in GSE41112 were analyzed using significance analysis of microarrays to screen the differentially expressed genes (DEGs). The DEGs were further analyzed by Differentially Coexpressed Genes and Links to construct a function module, the prognosis efficacy of which was verified by the other two datasets (GSE22226 and GSE58644) using Kaplan–Meier plots. The involved genes in function module were subjected to a univariate Cox regression analysis to confirm whether the expression of each prognostic gene was associated with survival.
Results: A total of 511 DEGs between breast cancer patients who received chemotherapy or not were obtained, consisting of 421 upregulated and 90 downregulated genes. Using the Differentially Coexpressed Genes and Links package, 1,244 differentially coexpressed genes (DCGs) were identified, among which 36 DCGs were regulated by the transcription factor complex NFY (NFYA, NFYB, NFYC). These 39 genes constructed a gene module to classify the samples in GSE22226 and GSE58644 into three subtypes and these subtypes exhibited significantly different survival rates. Furthermore, several genes of the 39 DCGs were shown to be significantly associated with good (such as CDC20) and poor (such as ARID4A) prognoses following chemotherapy.
Conclusion: Our present study provided a serial of biomarkers for predicting the prognosis of chemotherapy or targets for development of alternative treatment (ie, CDC20 and ARID4A) in breast cancer patients.
Keywords: breast cancer, differentially coexpressed expressed genes, prognosis, chemotherapy
This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.Download Article [PDF] View Full Text [HTML][Machine readable]