Researchers developed a bioinformatic approach to possible risk stratification of patients with multiple myeloma (MM) based on results of expression analyses of immune-related genes (IRGs). They described their approach in a report published in the journal Fronters in Genetics.
Tumor immunotherapy shows potential to provide benefits for patients with MM. For this reason, the researchers had an aim of determining whether IRGs have prognostic utility in patients with MM, with potential to aid in personalized immunotherapy.
The researchers used gene expression profiling and clinical data available in the Gene Expression Omnibus database to find possible IRGs and transcription factors (TFs) that may be linked to disease progression. They then developed and verified an immune-related prognostic model through a series of statistical approaches. The researchers also performed in vitro assays in MM cell lines to determine whether increased expression of certain potential IRGs was associated with tumor cell proliferation.
Gene expression profiles were examined from pretreatment, whole bone marrow samples of 354 patients, of whom 214 patients were included in a training dataset used for model development, while 120 patients were included in a dataset used for internal validation.
The researchers examined possibly relevant TFs and IRGs from these profiles and compared them with genes known to be associated with International Staging System characteristics. Overall, the researchers found 14 TFs and 88 IRGs that they considered potentially associated with MM disease progression.
A set of 10 of potentially survival-related IRGs was found through regression analysis and used in development of the prognostic model. These 10 IRGs were BDNF, CETP, LMBR, LTBP1, NENF, NR1D1, NR1H2, PTK2B, and SEMA4. Patients were stratified into low-risk and high-risk categories using this model. Receiver operating characteristic curve analyses of the training dataset indicated this model had area-under-the-curve (AUC) values of 0.681 for 1-year survival, 0.676 for 3-year survival, and 0.724 for 5-year survival. For the internal validation dataset, the 1-, 3-, and 5-year survival AUCs were 0.550, 0.609, and 0.600, respectively.
An analysis of possible interaction networks at the protein level revealed additional genes, including IRF7 and SHC1 genes, which appeared to have potential prognostic value in MM. In vitro analysis in MM cell lines suggested that overexpression of IRF7 and SHC1 genes was linked to tumor cell proliferation.
“In conclusion, our study identified a risk model associated with MM prognosis through a series of bioinformatics analyses, and this risk score may have important implications for MM progression,” the study investigators wrote in their report.
Wang QS, Shi QQ, Meng Y, Chen MP, Hou J. Identification of immune-related genes for risk stratification in multiple myeloma based on whole bone marrow gene expression profiling. Front Genet. 2022;13:897886. doi:10.3389/fgene.2022.897886