Selection hub MicroRNAs as biomarkers in breast cancer stem cells in extracellular matrix using bioinformatics analyses

• Published in: Egyptian Journal of Medical Human Genetics Vol. 23; no. 1; pp. 1 - 11
• Main Authors: Shirinsokhan, Armaghan, Azarmehr, Zahra, Jalili, Arsalan, Sadrabadi, Amin Ebrahimi, Partan, Arman Saadati, Tutunchi, Sara, Bereimipour, Ahmad
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2022; Springer; Springer Nature B.V; SpringerOpen
• Subjects: Adjuvant treatment; Aging; Analysis; Apoptosis; Bioinformatics; Bioinformatics analyses; Biological markers; Biomarkers; Biosynthesis; Breast cancer; Cancer; Cancer stem cells; Cell cycle; Chromosome 5; Communication; Communications networks; Computational biology; Diseases; Extracellular matrix; Gene expression; Genes; Kinases; Medicine; Medicine & Public Health; MicroRNA; MicroRNAs; miRNA; Oncology, Experimental; Ontology; Osteonectin; Proteins; Relapse; RNA sequencing; Secretions; Stem cell research; Stem cells; Transplantation; Tumors; Iran; Biomarkers; Extracellular matrix; Breast cancer; Cancer stem cells; Bioinformatics analyses; MicroRNAs
• ISSN: 1110-8630; 2090-2441
• DOI: 10.1186/s43042-022-00359-w

Background Breast cancer is one of the most common cancers in women, and many people get it every year. The cancer stem cells are maybe crucial role to exacerbates and relapse the breast cancer. Therefore, finding biomarkers in human secretions can be an suitable solution for early detection and neo adjuvant therapy. This study aimed to investigate the molecular events related to the cancer stem cells in breast cancer, after which we nominated a suitable MicroRNAs participates in breast cancer pathogenesis. Methods In this study, we investigated the relationship between molecular pathways using a bioinformatics approach. First, we selected the appropriate RNA-Seq datasets from the GEO database. We used Enrichr, KEGG, and Shiny GO databases to evaluate the signal pathways and gene ontology after isolating the gene expression profiles. In the next step, we used the STRING database to assess the protein network, and we used the Targetscan database to nominate the MicroRNA. Results 510 high-expression genes and 460 low-expression genes were associated with breast cancer and the cancer stem cells. Highly expressed genes were involved in the cell cycle and cellular aging pathways. On the other hand, low-expression genes were involved in the RNA transports, spliceosome, and apoptosis pathways. After evaluating the ontology of genes and the relationship between proteins, high-expression SPARC, INHBA, FN1, and GBA proteins were nominated. In the next section, the MicroRNAs related to these genes were hsa miR-9.5p, hsa miR-203.3p, and hsa miR-429. Conclusion In general, we examined more closely and more the relationship between the cancer stem cells pathway and breast cancer using a regular and accurate bioinformatics framework. Finally, we nominated suitable MicroRNAs that were involved in breast cancer stem cells. Highlights Breast cancer stem cells play a significant role in the recurrence of the disease or even the development of secondary tumors. SPARC, INHBA, FN1, and GBA genes play a significant role in breast cancer stem cells. hsa miR-9.5p, hsa miR-203.3p, and hsa miR-429. associated with breast cancer stem cells can be detected in human secretions.