Abstract
BackgroundCopy number variation (CNVs) is a key factor in breast cancer development. This study determined prognostic molecular characteristics to predict breast cancer through performing a comprehensive analysis of copy number and gene expression data.MethodsBreast cancer expression profiles, CNV and complete information from The Cancer Genome Atlas (TCGA) dataset were collected. Gene Expression Omnibus (GEO) chip data sets (GSE20685 and GSE31448) containing breast cancer samples were used as external validation sets. Univariate survival COX analysis, multivariate survival COX analysis, least absolute shrinkage and selection operator (LASSO), Chi square, Kaplan-Meier (KM) survival curve and receiver operating characteristic (ROC) analysis were applied to build a gene signature model and assess its performance.ResultsA total of 649 CNV related-differentially expressed gene obtained from TCGA-breast cancer dataset were related to several cancer pathways and functions. A prognostic gene sets with 9 genes were developed to stratify patients into high-risk and low-risk groups, and its prognostic performance was verified in two independent patient cohorts (n = 327, 246). The result uncovered that 9-gene signature could independently predict breast cancer prognosis. Lower mutation of PIK3CA and higher mutation of TP53 and CDH1 were found in samples with high-risk score compared with samples with low-risk score. Patients in the high-risk group showed higher immune score, malignant clinical features than those in the low-risk group. The 9-gene signature developed in this study achieved a higher AUC.ConclusionThe current research established a 5-CNV gene signature to evaluate prognosis of breast cancer patients, which may innovate clinical application of prognostic assessment.
Highlights
Copy number variations (CNVs), which are DNA fragments with varied copy number from 1 kb to several Mb in the human genome, include DNA fragment deletions, insertions, duplications, and compound multipoint variants [1]
We examined the correlation between CNV-associated gene expression profiles and clinical outcomes in 1069 breast cancer patients recorded in the Cancer Genome Atlas (TCGA)
Genes with CNV and expression differences were screened Bedtools was used to detect CNV genes related to breast cancer progression, here we screened 5696 significant differential CNV gene between breast cancer sample and normal sample
Summary
Copy number variations (CNVs), which are DNA fragments with varied copy number from 1 kb to several Mb in the human genome, include DNA fragment deletions, insertions, duplications, and compound multipoint variants [1]. CNVs are often present in various types of tumors, and are currently considered as a key factor in genetic variation of tumors [2,3,4,5]. CNVs at multiple sites in the genome can cause heterogeneity of the genome and molecular phenotype, leading to the occurrence and development of complex diseases including cancers [2, 6, 7]. Ding et al reported the diversity of genomes of patients with primary breast cancer that are manifested as frequent gene rearrangements and copy number changes [8]. Copy number variation (CNVs) is a key factor in breast cancer development. This study determined prognostic molecular characteristics to predict breast cancer through performing a comprehensive analysis of copy number and gene expression data
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
