Biomarker expression analysis in different age groups revealed age was a risk factor for breast cancer

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. K E Y W O R D Sage, breast cancer, GEO, lncRNA-mRNA, TCGA

Epidemiological and sociodemographic transitions of female breast cancer incidence, death, case fatality and DALYs in 21 world regions and globally, from 1990 to 2017: An Age-Period-Cohort Analysis

“…Global cancer burden 2017 attributed the variations in BC incident rates to population growth and aging process [32] . Various other studies have also supported the findings that being a complex chronic systemic disease, BC likely to have significant association with age, as disease incidence increases with increased age [33] , [34] , [35] , [36] , [37] . Decreased deaths and DALYs among developed countries were attributed to the adoption of widespread mammographic screening of the disease [15] , [33] .…”

Genomic Expression Profiling of Colorectal Cancer in Silico

“…As a major member of the metallothionein family, MT1M is a cysteine-rich metal-binding protein that is induced by in ammation and protects the cell against carcinogens. Emerging evidence has shown that MT1M is related to pancreatic ductal adenocarcinoma [36], breast cancer [37], renal cell carcinoma [38] and colorectal carcinoma [39]. In colorectal cancer, MT1M was a highly expressed isoform in tumor epithelia.…”

COL3A1, COL6A3, and SERPINH1 Are Related to Glucocorticoid-Induced Osteoporosis Occurrence According to Integrated Bioinformatics Analysis

“…We believe the reason for the inconsistent results was due to different microarray platforms of the 2 datasets, different sample sizes, and heterogeneities between the species and tissues. Consequently, to further identify the potential function of the hub genes in GIOP, GSEA was conducted to search KEGG pathways enriched in the highly expressed samples, as previously reported [ 34 , 35 ]. In our results, the focal adhesion and the ECM receptor interaction pathways notably showed significant enrichment within samples showing high COL1A3 and COL6A3 expression levels.…”