Exploring the Molecular Mechanism of the Drug-Treated Breast Cancer Based on Gene Expression Microarray

Breast cancer (BRCA) remains the leading cause of cancer morbidity and mortality worldwide. In the present study, we identified novel biomarkers expressed during estradiol and tamoxifen treatment of BRCA. The microarray dataset of E-MTAB-4975 from Array Express database was downloaded, and the differential expressed genes (DEGs) between estradiol-treated BRCA sample and tamoxifen-treated BRCA sample were identified by limma package. The pathway and gene ontology (GO) enrichment analysis, construction of protein-protein interaction (PPI) network, module analysis, construction of target genes—miRNA interaction network and target genes-transcription factor (TF) interaction network were performed using bioinformatics tools. The expression, prognostic values, and mutation of hub genes were validated by SurvExpress database, cBioPortal, and human protein atlas (HPA) database. A total of 856 genes (421 up-regulated genes and 435 down-regulated genes) were identified in T47D (overexpressing Split Ends (SPEN) + estradiol) samples compared to T47D (overexpressing Split Ends (SPEN) + tamoxifen) samples. Pathway and GO enrichment analysis revealed that the DEGs were mainly enriched in response to lysine degradation II (pipecolate pathway), cholesterol biosynthesis pathway, cell cycle pathway, and response to cytokine pathway. DEGs (MCM2, TCF4, OLR1, HSPA5, MAP1LC3B, SQSTM1, NEU1, HIST1H1B, RAD51, RFC3, MCM10, ISG15, TNFRSF10B, GBP2, IGFBP5, SOD2, DHF and MT1H), which were significantly up- and down-regulated in estradiol and tamoxifen-treated BRCA samples, were selected as hub genes according to the results of protein-protein interaction (PPI) network, module analysis, target genes—miRNA interaction network and target genes-TF interaction network analysis. The SurvExpress database, cBioPortal, and Human Protein Atlas (HPA) database further confirmed that patients with higher expression levels of these hub genes experienced a shorter overall survival. A comprehensive bioinformatics analysis was performed, and potential therapeutic applications of estradiol and tamoxifen were predicted in BRCA samples. The data may unravel the future molecular mechanisms of BRCA.


Introduction
Breast cancer (BRCA) is the most common type of gynecological cancer in women [1]. BRCA accounts for 2,088,849 (11.6%)of new cancer cases [2] and 626,679 (6.6%) deaths in women worldwide, as per 2018 cancer statistics [3].Surgical resection is an effective treatment to advance patient expression and low gene expression were compared by Kaplan-Meier survival plot, the log-rank p-value, and hazard ratio (HR, 95% confidence intervals). p < 0.05 is considered statistically significant.

Validation of Hub Genes
The mRNA expression of the DEGs was analyzed in 2 low-risk and 1 high-risk groups with the assistance of SurvExpress [53], which is an online tool to deliver customizable functionalities based on The Cancer Genome Atlas, and the translational levels of the hub genes were validated using the Human ProteinAtlas (HPA) database [54].

Mutation Analysis of Hub Genes
The cBio Cancer Genomics Portal [55] is a web tool, which provides mutation analysis, visualization, and downloads of cancer genomics datasets of various cancers. Complex cancer genomics profiles are accessible from the cBioPortal tool, thus enabling us to compare the genetic modifications of the selected ten hub genes in BRCA. The flowchart of the methodology is depicted below (Figure 1).

Figure 1.
The workflow representing the methodology and the major outcome of the study. BRCA-breast cancer, GO-gene ontology, miRNA-MicroRNA, TF-transcription factor, DEGs-differential expressed genes.

Gene Ontology (GO) Enrichment Analysis
The DEGs were uploaded to the online web tool ToppGene to pinpoint overrepresented GO categories. GO analysis results showed that up-regulated genes were significantly enriched in all GO terms, which include: cell cycle, DNA replication, chromosome, chromosomal part, chromosome, centromeric region, and DNA helicase activity (Table S4), while down-regulated genes were significantly enriched in all GO terms, which include: response to cytokine, cellular response to cytokine, endoplasmic reticulum, nuclear outer membrane-endoplasmic reticulum membrane network, cytokine activity, and cytokine receptor binding (Table S5).

Survival Analysis of Hub Genes
To evaluate if the identified prognostic markers are valuable in predicting patient survival, we focused on the hub genes (up-and down-regulated genes). We utilized SurvExpress [54], an online tool developed for conveniently exploring survival correlations with gene expression data from 502 cancer studies performed by The Cancer Genome Atlas (TCGA). Genes, such as BRCA1, FLNA, FLNB, HSPA5, MAP1LC3B, NDRG1, PCNA, and TUBB2B, which are overexpressed in BRCA, showed a positive correlation with patient survival. Patients with higher expression of these genes had favorable overall survival (p-value < 0.05) ( Figure 17). Genes, such as HIST1H3B and MAPK6, which are overexpressed in BRCA, showed a negative correlation with patient survival. Patients with higher expression of these genes had worse overall survival (p-value < 0.05) ( Figure 18).

Validation of Hub Genes
The expression level of hub genes was assessed in 2 low-risk and1 high-risk groups. The data showed that the hub gene expression of BRCA1, HIST1H3B, MAPK6, NDRG1, and PCNA were increased ( Figure 19), while that of FLNA, FLNB, HSPA5, MAP1LC3B, and TUBB2B were reduced ( Figure 20) in the high-risk group compared with those in the low-risk group. The outcome of the validation of the hub genes on a translational level through the HPA database are displayed in Figure 21.

Discussion
Breast cancer is one of the most common cancer to affect women. BRCA is a heterogeneous disease presenting distinct subtypes (Triple Negative, Luminal A, Luminal B, human epidermal growth factor receptor (HER2+)). Increased estradiol level is associated with breast cancer development through regulation of the progesterone receptor [56,57]. Estradiol antagonist tamoxifen has been the first line treatment for all stages of estrogen-receptor-positive BRCA [55]. In most cases, somatic mutations in breast cells acquired during a person's lifetime lead to breast cancer [58]. BRCA occurs due to the accumulation of different genetic mutations, thus, a high level of molecular heterogeneity in BRCA demands thorough investigation of the molecular markers and signaling pathways associated with pathogenesis of BRCA; this may be of benefit for the examination of targeted molecular therapy to assist early diagnosis and prognosis, and may also afford a molecular basis for treatment. In the current study, the integrated analysis was performed on the gene expression profiles in estradioland tamoxifen-treated BRCA cell lines. Using the microarray platforms, we identified 856 DEGs (421 up-regulated and 435 down-regulated). BRCA arises from the accumulation of different gene modifications, and it is important to characterize the genetic changes during the advancement of BRCA [59]. Methylation inactivation of tumor suppressor KCNB1 is responsible for the development of gliomas [60], but this gene may be identified with the development of BRCA. COL12A1 is diagnosed with the pathogenesis of gastric cancer [61], but this gene may be associated with the pathogenesis of BRCA. DIAPH3 is important for metastasis of hepatocellular carcinoma cells through stimulation of the beta-catenin/TCF signaling pathway [62], but this gene may be linked with metastasis of BRCA. SFXN2 is important for the invasion of oral squamous cell carcinoma [63], but this gene may be responsible for the invasion of BRCA cells. GLDC is involved in the pathogenesis of non-small cell lung cancer cell proliferation through pyrimidine metabolism [64], but this gene may be linked with changes in amino acid and nucleic acid metabolism in BRCA. DDIT4 is liable for the proliferation of gastric cancer cell through activation of p53 and MAPK pathways [65], but this gene may be associated with the proliferation of BRCA cells. Loss of genes, such as INSIG1 and ACSS2, is responsible for the advancement of gastric cancer [66,67], but inactivation of these genes may be linked with the development of BRCA. IFIT3 is responsible for inflammatory stimulus in pancreatic cancer [68], but this gene may be associated with inflammation in BRCA. Methylation inactivation of tumor suppressor genes, such as FLCN [69] and DDIT3 [70], is important for the development of many cancer, such as renal cancer and gastric cancer, but inactivation of these genes may be responsible for the advancement of BRCA. PRSS8 is liable for the development of ovarian cancer [71], but this gene may identify with the pathogenesis of BRCA. Genes, such as KLF8 [72], TCF4 [73], H19 [74], NEU1 [75], CXCL1 [76], TRIB3 [77], FTL [78], and UBE2L6 [79], are responsible for the pathogenesis of BRCA.
In target genes-miRNA network, target genes (up-regulated), such as IGFBP5, RAD51, DSN1, RRM2, and ZWINT, are identified with a high degree. Expression of IGFBP5 is responsible for the development of BRCA [266]. Meanwhile, target genes (down-regulated), such as SOD2, DNAJC10, PEG10, LDLR, and RORA, are identified with a high degree. Genes, such as SOD2 [267], and PEG10 [268], are associated with the pathogenesis of BRCA. LDLR is responsible for the advancement of prostate cancer cells [269], but this gene may be associated with the development of BRCA.
In target genes-TF network (up-regulated), target genes, such as DHFR, TBXAS1, MCEE, ETNK2, and CENPM, are identified with a high degree. TBXAS1 is responsible for the development of BRCA [270]. MCEE and ETNK2 are identified as novel molecular markers for the pathogenesis of BRCA. Meanwhile, target genes (down-regulated), such as MT1H, KRTAP5-4, RETN, HSD17B14, and SEPHS2, are identified with a high degree. KRTAP5-4 and HSD17B14 are identified as novel molecular markers for the pathogenesis of BRCA.

Conclusions
In this study, key genes were identified for the first time in estradiol and tamoxifen drug-treated BRCA by integrated bioinformatics analysis. By analyzing the pathway and GO enrichment analysis, we found that DEGs were mainly enriched in the lysine degradation II (pipecolate pathway), cholesterol biosynthesis, cell cycle, and response to cytokine, which provide a theoretical basis for studying the biological processes of BRCA. We successfully constructed a PPI network, miRNA-target gene regulatory network, and TF-target gene regulatory network of DEGs in BRCA and screened several key genes encoding proteins in the networks that are associated in the process of BRCA in the form of molecular populations. These findings promote our understanding of the molecular pathogenesis of BRCA during estradiol and tamoxifen drug treatment and may provide an enhanced perceptive of the molecular mechanisms that underlie breast cancer. However, further molecular biological experiments are required to confirm the action of the diagnosed genes that are linked with BRCA during estradiol and tamoxifen drug treatment.
Supplementary Materials: The following are available online at http://www.mdpi.com/2218-273X/9/7/282/s1, Table S1: The statistical metrics for key differentially expressed genes (DEGs), Table S2: The enriched pathway terms of the up-regulated differentially expressed genes, Table S3: The enriched pathway terms of the down-regulated differentially expressed genes, Table S4: The enriched GO terms of the up-regulated differentially expressed genes, Table S5: The enriched GO terms of the down-regulated differentially expressed genes, Table S6: Topology  table for up-and down-regulated genes, Table S7: miRNA-target gene interaction table, Table S8: TF-target gene interaction table.