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December 8, 2025Blood

Multi-omics reveals immune features in immune and non-immune cells, an IFN-γ/IFN-α-B2M positive feedback loop, and targeted metabolic therapy in multiple myeloma

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Authors

CLChen LiYCYan Chen

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Overview

Multi-omics reveals immune cell features and an IFN-γ/IFN-α feedback loop, suggesting new metabolic therapies for multiple myeloma.

Key Points

  • To elucidate the immune and non-immune cell dynamics along with therapeutic avenues in multiple myeloma.
  • Analyzed scRNA-seq data from 113 individuals alongside bulk RNA-seq.
  • Performed cell clustering, annotation, and pathway enrichment in R.
  • Validated key subpopulations via multiplex immunofluorescence.
  • Identified 23 plasma cell clusters correlating with disease progression.
  • Uncovered an IFN-γ/IFN-α-B2M positive feedback loop influencing immune evasion.
  • CB-839 and EGCG combination showed strong synergy in inhibiting MM cell proliferation.

Cite This Study

Li et al. (2025) studied this question.

synapsesocial.com/papers/69362f514fa91c937236d916https://doi.org/10.1182/blood-2025-7450
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Multi-omics reveals immune features in immune and non-immune cells, an IFN-γ/IFN-α-B2M positive feedback loop, and targeted metabolic therapy in multiple myeloma2025
  2. 2Longitudinal profiling of tumor and immune compartments uncovers patterns of dysregulation and associations with response in multiple myeloma2025
  3. 3Single-cell profiling reveals MIF-mediated immune evasion and CD8 + T cell exhaustion in relapsed multiple myeloma2026 · 2 citations
  4. 4Integrated transcriptomics reveals a TNFRSF-metabolism axis and a context-dependent BCMA signaling state in myeloma progression2026
  5. 5IL-6-driven metabolic reprogramming of the multiple myeloma microenvironment2026