Immunological regimens are an important area of research for treating multiple myeloma (MM). Plasma cells play a crucial role in immunotherapy. Patients and Methods: In our study, we used both single-cell RNA sequencing (scRNA-seq) and bulk sequencing techniques to analyze MM patients. We analyzed each sample using gene set variation analysis (GSVA) based on immune-related gene sets. We also conducted further analyses to compare immune infiltration, clinical characteristics, and expression of immune checkpoint molecules between the H-S100A9 and L-S100A9 groups of MM patients. Results: We identified eight subpopulations of plasma cells, with S100A9 plasma cells being more abundant in patients with 1q21 gain and 1q21 diploid. CellChat analysis revealed that GAS and HGF signaling pathways were prominent in intercellular communication of S100A9 plasma cells. We identified 14 immune-related genes in the S100A9 plasma cell population, which allowed us to classify patients into the H-S100A9 group or the L-S100A9 group. The H-S100A9 group showed higher ESTIMATE, immune and stroma scores, lower tumor purity, and greater immune checkpoint expression. Patients with 1q21 gain and four or more copies had the lowest ESTIMATE score, immune score, stroma score, and highest tumor purity. Drug sensitivity analysis indicated that the H-S100A9 group had lower IC50 values and greater drug sensitivity compared to the L-S100A9 group. Quantitative reverse transcription (RT-q) PCR showed significantly elevated expression of RNASE6, LYZ, S100A8, S100A9, and S100A12 in MM patients compared to the healthy control group.
Conclusion:Our study has identified a correlation between molecular subtypes of S100A9 plasma cells and the response to immunotherapy in MM patients. These findings improve our understanding of tumor immunology and provide guidance for developing effective immunotherapy strategies for this patient population.