Frontiers in Immunology (Nov 2021)
Gene Expression Analysis of the Bone Marrow Microenvironment Reveals Distinct Immunotypes in Smoldering Multiple Myeloma Associated to Progression to Symptomatic Disease
Abstract
BackgroundWe previously reported algorithms based on clinical parameters and plasma cell characteristics to identify patients with smoldering multiple myeloma (SMM) with higher risk of progressing who could benefit from early treatment. In this work, we analyzed differences in the immune bone marrow (BM) microenvironment in SMM to better understand the role of immune surveillance in disease progression and to identify immune biomarkers associated to higher risk of progression.MethodsGene expression analysis of BM cells from 28 patients with SMM, 22 patients with monoclonal gammopathy of undetermined significance (MGUS) and 22 patients with symptomatic MM was performed by using Nanostring Technology.ResultsBM cells in SMM compared to both MGUS and symptomatic MM showed upregulation of genes encoding for key molecules in cytotoxicity. However, some of these cytotoxic molecules positively correlated with inhibitory immune checkpoints, which may impair the effector function of BM cytotoxic cells. Analysis of 28 patients with SMM revealed 4 distinct clusters based on immune composition and activation markers. Patients in cluster 2 showed a significant increase in expression of cytotoxic molecules but also inhibitory immune checkpoints compared to cluster 3, suggesting the presence of cytotoxic cells with an exhausted phenotype. Accordingly, patients in cluster 3 had a significantly longer progression free survival. Finally, individual gene expression analysis showed that higher expression of TNF superfamily members (TNF, TNFAIP3, TNFRSF14) was associated with shorter progression free survival.ConclusionsOur results suggest that exhausted cytotoxic cells are associated to high-risk patients with SMM. Biomarkers overexpressed in patients with this immune gene profile in combination with clinical parameters and PC characterization may be useful to identify SMM patients with higher risk of progression.
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