Biomarker expression analysis in different age groups revealed age was a risk factor for breast cancer. Issue 5 (14th October 2019)

• Record Type: Journal Article
• Authors: Ma, Xiaoran; Liu, Cun; Xu, Xiaowei; Liu, Lijuan; Gao, Chundi; Zhuang, Jing; Li, Huayao; Feng, Fubin; Zhou, Chao; Liu, Zhen; Li, Jie; Wei, Junyu; Wang, Lu; Sun, Changgang
• Is Part Of: Journal of cellular physiology. Volume 235:Issue 5(2020:May)
• Page Start: 4268
• Page End: 4278
• Publication Date: 2019-10-14
• Subjects: age -- breast cancer -- GEO -- lncRNA–mRNA -- TCGA; Physiology -- Periodicals; Cell physiology -- Periodicals; 571.6
• DOI: 10.1002/jcp.29304
• Languages: English
• ISSNs: 0021-9541

Abstract

Abstract: The relationship between age and breast cancer is ambiguous. Here, we analyzed the differential expression pattern of long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) in different age groups to provide an effective association between age and breast cancer risk at the molecular level. We integrated the microarray information from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data sets. The patients were divided into young ( < 50 years) and old ( ≥ 50 years) age groups and evaluated by differential gene expression, weighted gene correlation network analysis (WGCNA), functional enrichment analyses, and coexpression analysis. To determine their potential clinical significance, univariate Cox regression analysis and survival assessment were conducted. We identified two lncRNAs (AL139280.1 and AP000851.1) and three mRNAs (MT1M, HBB, and TFPI2) as the risk markers, and Gene set enrichment analysis (GSEA) focusing on a single gene revealed that "pyrimidine metabolism, " "cell cycle, " and "P53 signaling pathway" were coenriched. These data demonstrated that age may be a risk factor for breast carcinogenesis and prognosis and provide an in‐depth molecular characterization based on the expression patterns of lncRNAs and mRNAs. Abstract : Breast cancer is one of the most common malignant tumors and continuous to be a serious health threat for women. Whether age is a risk factor for breast cancer remains unclear. However, determining the impact of age on the onset of breast cancer is critical for women's health and cancer prevention. In this study, we constructed a long noncoding RNA‐messenger RNA model and identified age‐stratified markers that were differentially expressed. We obtained evidence for age as a risk factor at the molecular level.