Significant prognostic values of differentially expressed-aberrantly methylated hub genes in breast cancer

Abstract

Introduction: Abnormal status of gene expression plays an important role in tumorigenesis, progression and metastasis of breast cancer. Mechanisms of gene silence or activation were varied. Methylation of genes may contribute to alteration of gene expression. This study aimed to identify differentially expressed hub genes which may be regulated by DNA methylation and evaluate their prognostic value in breast cancer by bioinformatic analysis. Methods: GEO2R was used to obtain expression microarray data from GSE54002, GSE65194 and methylation microarray data from GSE20713, GSE32393. Differentially expressed-aberrantly methylated genes were identified by FunRich. Biological function and pathway enrichment analysis were conducted by DAVID. PPI network was constructed by STRING and hub genes was sorted by Cytoscape. Expression and DNA methylation of hub genes was validated by UALCAN and MethHC. Clinical outcome analysis of hub genes was performed by Kaplan Meier-plotter database for breast cancer. IHC was performed to analyze protein levels of EXO1 and Kaplan-Meier was used for survival analysis. Results: 677 upregulated-hypomethylated and 361 downregulated-hypermethylated genes were obtained from GSE54002, GSE65194, GSE20713 and GSE32393 by GEO2R and FunRich. The most significant biological process, cellular component, molecular function enriched and pathway for upregulated-hypomethylated genes were viral process, cytoplasm, protein binding and cell cycle respectively. For downregulated-hypermethylated genes, the result was peptidyl-tyrosine phosphorylation, plasma membrane, transmembrane receptor protein tyrosine kinase activity and Rap1 signaling pathway (All p< 0.05). 12 hub genes (TOP2A, MAD2L1, FEN1, EPRS, EXO1, MCM4, PTTG1, RRM2, PSMD14, CDKN3, H2AFZ, CCNE2) were sorted from 677 upregulated-hypomethylated genes. 4 hub genes (EGFR, FGF2, BCL2, PIK3R1) were sorted from 361 downregulated-hypermethylated genes. Differential expression of 16 hub genes was validated in UALCAN database (p<0.05). 7 in 12 upregulated-hypomethylated and 2 in 4 downregulated-hypermethylated hub genes were confirmed to be significantly hypomethylated or hypermethylated in breast cancer using MethHC database (p<0.05). Finally, 12 upregulated hub genes (TOP2A, MAD2L1, FEN1, EPRS, EXO1, MCM4, PTTG1, RRM2, PSMD14, CDKN3, H2AFZ, CCNE2) and 3 downregulated genes (FGF2, BCL2, PIK3R1) contributed to significant unfavorable clinical outcome in breast cancer (p<0.05). High expression level of EXO1 protein was significantly associated with poor OS in breast cancer patients (p=0.03).

Genome-Wide Analysis of Methylation-Driven Genes and Identification of an Eight-Gene Panel for Prognosis Prediction in Breast Cancer

“…However, the prognostic predicting power of conventional BC staging system prognosis is not satisfying. Recently, the study of identifying gene-based methylation signature prognostic model for BC has attracted much attention, and several papers have reported the feasibility of this method (Bao et al, 2019;Chen et al, 2019;Du et al, 2019;Qi et al, 2019). In the present study, integrated analysis on patients in the BRCA project of TCGA was carried out by MethylMix, identifying 879 methylation-driven genes with different methylation patterns in tumor and normal tissues.…”

Biological and clinical significance of flap endonuclease‑1 in triple‑negative breast cancer: Support of metastasis and a poor prognosis

“…A recent study identified FEN1 as one of the hub upregulated-hypomethylated genes in breast cancer ( 39 ). Results of the COSMIC analysis revealed that the marked elevation of FEN1 expression was a common variant status in patients with breast cancer, indicating that FEN1 may be involved in tumorigenesis or tumor progression.…”

Potential mechanism of RRM2 for promoting Cervical Cancer based on weighted gene co-expression network analysis

“…Research found that RRM2 was a novel downstream target activated by HPV E7, and promoted angiogenesis by producing ROS, activating the ERK1/2 signaling pathway and inducing expression of HIF-1a and VEGF, leading to cervical angiogenesis and carcinogenesis 6 . At present, evidence of the relationship between RRM2 and CDKN3 in cervical cancer is limited, but their relationship can be found in other cancers, such as hepatocellular carcinoma, breast cancer, renal carcinoma and lung cancer 51 - 54 . Qi et al have found RRM2 and CDKN3 may become biomarkers for diagnosis and poor prognosis of breast cancer 51 .…”

“…At present, evidence of the relationship between RRM2 and CDKN3 in cervical cancer is limited, but their relationship can be found in other cancers, such as hepatocellular carcinoma, breast cancer, renal carcinoma and lung cancer 51 - 54 . Qi et al have found RRM2 and CDKN3 may become biomarkers for diagnosis and poor prognosis of breast cancer 51 . Zhou et al have also found there is a correlation between RRM2 and CDKN3 in hepatocellular carcinoma 52 .…”