Abstract
Overview: The emergence of effective immune therapies for multiple myeloma has highlighted the importance of understanding the roles of less abundant components within the tumor microenvironment. Single-cell analyses provide snapshots of the functional relationships of individual cells at precise moments in time, as well as insight into the overall cellular composition. By integrating single-cell datasets from multiple studies, we improve our ability to identify trends within rare cell populations, such as macrophages, and explore their clinical implications. We investigate human data here because our prior research of murine models indicated that macrophages expressing C1q, particularly those co-expressing Fcgr4, tend to correlate positively with increased tumor burden.
Methods: We combined 56 human bone marrow samples – primarily collected at baseline, post-induction, or post-ASCT – with three publicly available data sets: GSE210079 (post CAR-T bone marrow microenvironment); GSE223060 (single-cell analysis of the MMRF cohort); and GSE271107 (disease progression from healthy donors and MGUS to SMM and NDMM). These data sets were integrated using Seurat to generate robust cellular clusters from over 300,000 cells across 117 samples. We validated our single-cell findings with bulk Affymetrix, whole bone marrow gene expression data (collected at baseline and post-baseline) from the Total Therapy clinical trials (GSE136324).
Results: A distinct cluster of C1QA/B/C-expressing macrophages was consistently identified in all single-cell cohorts. These cells co-express FCER1G, CSF1R, and CD68 (markers also expressed in murine C1Q macrophages) and typically cluster adjacent to FCGR3A-expressing monocytes. Within the disease progression cohort, C1Q macrophages were found in all phases of progression: healthy donors, MGUS, SMM, and NDMM. However, C1Q macrophages in progressive disease (SMM and NDMM) have distinct expression features including lower levels of MRC1 and higher levels of APOBEC3A and ISG15 – genes linked to inflammatory responses. Among 11 post-induction samples submitted to lenalidomide maintenance, five with shorter responses displayed elevated expression of APOBEC3A and ISG15 in C1Q-expressing macrophages compared to six samples with longer responses. In a cohort of 22 samples 100 days post-ASCT, seven poor responders showed both an increased frequency of C1Q macrophages and elevated APOBEC3A expression compared to good responders. The MMRF cohort indicated that higher baseline frequencies of C1Q macrophages often preceded rapid disease progression (e.g. MMRF_1720, MMRF_1641). Anecdotal evidence from the CAR-T therapy cohort suggests that expansion of C1Q macrophages could serve as an early warning for tumor recurrence; sample 16 showed retention and expansion of C1Q macrophages 28 days post-CAR-T, that was subsequently followed by increased tumor cell counts at 3 months post-therapy.
Analysis of bulk, whole bone marrow gene expression revealed that elevated levels of C1Q genes correlated with poorer outcomes, particularly in post-baseline samples. Multivariate Cox survival analysis revealed that high C1Q expression independently predicted inferior overall survival in post-baseline samples after adjusting for age, ISS stage, high levels of tumor-associated markers (SDC1, JCHAIN, DERL3), and high-risk UAMS7 subtypes (MF, MS, PR). Moreover, post-baseline GEP70 risk scores (from matched bone marrow aspirates) positively correlated with elevated C1Q expression in whole bone marrow samples.
Conclusion: Both single-cell and bulk analyses indicate that the persistence of immunosuppressive C1Q macrophages following therapy is associated with inferior clinical outcomes. Although the precise mechanisms are yet to be fully understood, the close proximity of similar macrophages to tumor cells–as observed in other cancers–likely also occurs in myeloma and reflects the crucial relationship between tumor cells and macrophages within the bone marrow. While C1Q macrophages are typically rare in individual samples, analysis of combined cohorts is building evidence of their crucial role in immune cross-talk and therapeutic resistance mechanisms.
