Researchers pinpointed 3 key diagnosed genes of breast cancer, which impact breast cancer cells by modulating immune-infiltrating cells. The analysis was reported in Medical Science Monitor.
In this study, data were collated from the National Center for Biotechnology Information Gene Expression Omnibus database and divided into a treatment group (consisting of breast cancer issue) and a control arm (comprised of normal breast issue). In total, researchers screened from 32 differentially expressed genes (DEGs) between the 2 groups (27 downregulated genes and 5 upregulated genes), using gene ontology and gene set enrichment analysis to discern key pathways. The researchers also sought to elucidate the relationship between key genes and immune-infiltrating cells.
According to the results, a machine learning model showed that SYNM, TGFBR (both downregulated genes), and COL10A1 (upregulate gene) were key genes associated with breast cancer diagnosis. The researchers observed that the 2 downregulated genes were positively linked CD8 T cells and monocytes but negatively correlated with gamma delta T cells and M1 macrophages. The upregulated gene showed a positive association with gamma delta T cells and M1 macrophages but a negative link with CD8 T cells, monocytes, and follicular helper-T cells.
Overall, the researchers concluded that these genes affect breast cancers via modulation of immune cells.
Reference: Bao S, He G. Identification of key genes and key pathways in breast cancer based on machine learning. Med Sci Monit. 2022;28:e935515. doi:10.12659/MSM.935515
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