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Exploring the molecular mechanism associated with breast cancer bone metastasis using bioinformatic analysis and microarray genetic interaction network.

ABSTRACT: BACKGROUND:Bone metastases are common in advanced breast cancer patients and frequently leading to skeletal-related morbidity and deterioration in the quality of life. Although chemotherapy and hormone therapy are able to control the symptoms caused by bone destruction, the underlying molecular mechanisms for the affinity of breast cancer cells towards skeletal bones are still not completely understood. METHODS:In this study, bioinformatic analysis was performed on patients' microarray gene expression data to explore the molecular mechanism associated with breast cancer bone metastasis. Microarray gene expression profile regarding patients with breast cancer and disseminated tumor cells was downloaded from Gene Expression Omnibus (GEO) database (NCBI, NIH). Raw data were normalized and differently expressed genes were identified by using Significance Analysis of Microarrays (SAM) methods. Protein interaction networks were expanded using String. Moreover, molecular functions, biological processes and signaling pathway enrichment analysis were performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). RESULTS:We identified 66 differentially expressed genes. After submitting the set of genes to String, genetic interaction network was expanded, which consisted of 110 nodes and 869 edges. Pathway enrichment analysis suggested that adhesion kinase, ECM-receptor interaction, calcium signaling, Wnt pathways, and PI3K/AKT signaling pathway are highly associated with breast cancer bone metastasis. CONCLUSION:In this study, we established a microarray genetic interaction network associated with breast cancer bone metastasis. This information provides some potential molecular therapeutic targets for breast cancer initiation and progression.

SUBMITTER: Chen X

PROVIDER: S-EPMC6156059 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Exploring the molecular mechanism associated with breast cancer bone metastasis using bioinformatic analysis and microarray genetic interaction network.

Chen Xinhua X Pei Zhe Z Peng Hao H Zheng Zhihong Z

Medicine 20180901 37

<h4>Background</h4>Bone metastases are common in advanced breast cancer patients and frequently leading to skeletal-related morbidity and deterioration in the quality of life. Although chemotherapy and hormone therapy are able to control the symptoms caused by bone destruction, the underlying molecular mechanisms for the affinity of breast cancer cells towards skeletal bones are still not completely understood.<h4>Methods</h4>In this study, bioinformatic analysis was performed on patients' micro ...[more]

PMID: 30212931

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Project description:: 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.

Dataset Information

Exploring the molecular mechanism associated with breast cancer bone metastasis using bioinformatic analysis and microarray genetic interaction network.

Publications

Exploring the molecular mechanism associated with breast cancer bone metastasis using bioinformatic analysis and microarray genetic interaction network.

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