Microarray based analysis of gene regulation by mesenchymal stem cells in breast cancer

Abstract

Abstract. Breast cancer is one of the most common malignant tumors with a high case-fatality rate among women. The present study aimed to investigate the effects of mesenchymal stem cells (MSCs) on breast cancer by exploring the potential underlying molecular mechanisms. The expression profile of GSE43306, which refers to MDA-MB-231 cells with or without a 1:1 ratio of MSCs, was downloaded from Gene Expression Omnibus database for differentially expressed gene (DEG) screening. The Database for Annotation, Visualization and Integrated Discovery was used for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for DEGs. The protein-protein interactional (PPI) network of DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins. The data was subsequently analyzed using molecular complex detection for sub-network mining of modules. Finally, DEGs in modules were analyzed using GO and KEGG pathway enrichment analyses. A total of 291 DEGs including 193 upregulated and 98 downregulated DEGs were obtained. Upregulated DEGs were primarily enriched in pathways including response to wounding (P=5.92x10 -7 ), inflammatory response (P=5.92x10 ). The PPI network, which contained 156 nodes and 289 edges, was constructed, and Fos was the hub node with the degree of 29. A total of 3 modules were mined from the PPI network. In total, 14 DEGs in module A were primarily enriched in GO terms, including response to wounding (P=4.77x10 -6 ), wounding healing (P=6.25x10 -7 ) and coagulation (P=1.13 x10 -7 ), and these DEGs were also enriched in 1 KEGG pathway (complement and coagulation cascades; P=0.0036). Therefore, MSCs were demonstrated to exhibit potentially beneficial effects for breast cancer therapy. In addition, the screened DEGs, particularly in PPI network modules, including FN1, CD44, NGF, SERPINE1 and CCNA2, may be the potential target genes of MSC therapy for breast cancer.

Molecular prognosticators in clinically and pathologically distinct cohorts of head and neck squamous cell carcinoma—A meta-analysis approach

“…Site-specific meta-analysis of publicly available data identified a subset of genes that were common across the three major sites of HNSCC (tongue, laryngopharynx, oropharynx); the pathways that were primarily enriched included focal adhesion and proteoglycans in cancer, and cell cycle, mitotic pathway, which are well known in various cancers [29][30][31][32][33][34][35][36][37]. Differential expression profiling of the tongue cancer cohort triaged based on the stage, pathology identified multiple candidate markers; JAM2, SMURF1, LY6E, MFN1 and SUPT16H.…”

Fibronectin 1: A Potential Biomarker for Ovarian Cancer

“…FN1 could also potentially be applied as an indicator of ovarian cancer progression or metastasis. OVCAR3 and A2780 are the cell lines that are most commonly used in ovarian cancer studies [18][19][20][21]. In our laboratory, we found that these two different cell lines exhibit strongly different cell migration and invasion abilities.…”

Integrated bioinformatics and statistical approaches to explore molecular biomarkers for breast cancer diagnosis, prognosis and therapies

“…Germline Genetic Variants in ANGPT1 , ANGPT2 , TEK , MMP9 , VEGFA and FGF2 are involved with Pathologic complete reaction to Bevacizumab in BC Patients [ 66 ]. Several studies have suggested that the gene FN1 is highly associated with BC [ 9 , 67 – 72 ]. They suggested that genetic variants of the ATF6B gene were associated with modified relationships between reproductive factors and BC [ 73 ].…”