Dual role of signaling pathways in myeloma requires cell-type specific targeting of ligand-receptor interactions.

Although most patients with multiple myeloma respond to treatment initially, therapy resistance develops almost invariably and only a subset of patients show durable responses to immunomodulatory (IMiD) therapies. While the immune microenvironment has been extensively studied in myeloma patients, its composition is currently not used as prognostic markers in clinical routine. We hypothesized that the outcome of immune signaling pathway engagement can be highly variable, depending on which two cellular populations participate in this interaction. This would have important prognostic and therapeutic implications, suggesting that it is crucial for immune pathways to be targeted in a specific cellular context. To test this hypothesis, we investigated a cohort of 25 patients with newly diagnosed multiple myeloma. We examined the complex regulatory networks within the immune compartment and their impact on disease progression. Analysis of immune cell composition and expression profiles revealed significant differences in the B cell compartment associated with treatment response. Transcriptional states in patients with short time to progression demonstrated an enrichment of pathways promoting B cell differentiation and inflammatory responses, which may indicate immune dysfunction. Importantly, the analysis of molecular interactions within the immune microenvironment highlights the dual role of signaling pathways, which can either be associated with good or poor prognosis depending on the cell types involved. Our findings therefore argue that therapeutic strategies targeting ligand-receptor interactions should take into consideration the composition of the microenvironment and the specific cell types involved in molecular interactions. Cryopreserved CD138- bone marrow samples from 25 treatment-naïve newly-diagnosed myeloma (NDMM) patients were analyzed in this study. Low-input RNA-Sequencing libraries were prepared using the SmartSeq2 protocol from 100 cell pools sorted for different immune cell populations. Pooled libraries were paired-end sequenced using a 75 cycle kit on a NextSeq 500 (Illumina) with an average sequencing depth of 1 million reads per sample. ------------------------------- Authors state "As these are primary human samples, I am only submitting the processed data (counts matrix) rather than the raw fast files."