The following is a summary of “Identification of key genes and immune infiltration in multiple myeloma by bioinformatics analysis,” published in the October 2023 issue of Hematology by Xu et al.
Multiple myeloma (MM) is a blood cancer with unknown molecular causes. Using bioinformatics analysis, researchers started a retrospective study to identify key genes, pathways, and immune cell infiltration patterns in MM.
Using the ‘limma’ R package, they filtered differentially expressed genes (DEGs) from the GSE6477 and GSE16558 datasets. The functions of these genes were explored through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Key genes were selected from a Protein-Protein Interaction network and a logistic regression model. Key gene correlation with MM survival was assessed using ‘survival’ and ‘survminer’ packages. Immune filtration analysis was carried out with CIBERSORT tools.
The results showed 118 DEGs (92 up-regulated and 26 down-regulated) were identified from 2 GSE datasets. These genes were linked to B cell receptor signaling and Epstein-Barr virus infection. Logistic regression identified CD24 and PTPRC as hub genes in the PPI network. Notably, CD24 and PTPRC expression exhibited a significant correlation with the survival time of MM patients. MM was associated with varying compositions of infiltrating immune cells, including increased infiltrations of B cells memory, Plasma cells, T cells CD4 memory resting, T cells follicular helper, Tregs, NK cells resting, Macrophages(M0/M1), Dendritic cells resting and Mast cells activating, along with decreased proportion of B- cells naive, T cells CD4 naïve, Macrophages M2 and Neutrophils.
They concluded that targeting CD24 and PTPRC molecular markers of MM and immune cell infiltration may improve MM therapy.