Construction of immune-related gene pairs signature to predict the overall survival of multiple myeloma patients based on whole bone marrow gene expression profiling

Abstract

Multiple myeloma (MM) is a plasma cell dyscrasia that is characterized by the uncontrolled proliferation of malignant PCs in the bone marrow. Due to immunotherapy, attention has returned to the immune system in MM, and it appears necessary to identify biomarkers in this area. In this study, we created a prognostic model for MM using immune-related gene pairs (IRGPs), with the advantage that it is not affected by technical bias. After retrieving microarray data of MM patients, bioinformatics analyses like COX regression and least absolute shrinkage and selection operator (LASSO) were used to construct the signature. Then its prognostic value is assessed via time-dependent receiver operating characteristic (ROC) and the Kaplan–Meier (KM) analysis. We also used XCELL to examine the status of immune cell infiltration among MM patients. 6-IRGP signatures were developed and proved to predict MM prognosis with a P-value of 0.001 in the KM analysis. Moreover, the risk score was significantly associated with clinicopathological characteristics and was an independent prognostic factor. Of note, the combination of age and β2-microglobulin with risk score could improve the accuracy of determining patients’ prognosis with the values of the area under the curve (AUC) of 0.73 in 5 years ROC curves. Our model was also associated with the distribution of immune cells. This novel signature, either alone or in combination with age and β2-microglobulin, showed a good prognostic predictive value and might be used to guide the management of MM patients in clinical practice.