Chawla, Yogesh

Cytotoxic T cells produce the cytokine interferon-γ (IFN-γ). We sought to determine whether IFN-γ directly kills target cells and found that T cells used IFN-γ to kill murine melanoma cells lacking the kinases TBK1 and IKKε. In the absence of both kinases, IFN-γ induced the production of TNF receptor 1 (TNFR1) and the sensor Z-DNA binding protein 1 (ZBP1) in the tumor cells to stimulate receptor-interacting protein kinase 1 (RIPK1)–dependent apoptosis in a cell-autonomous manner. IFN-γ also enhanced the activation of nuclear factor κB (NF-κB) signaling in a TNFR1-dependent manner in cells deficient in both TBK1 and IKKε. Because IFN-γ–induced apoptosis occurred in a transcription-dependent manner with slow kinetics, STAT1 and NF-κB cooperated to activate the expression of inflammatory genes in the dying cells. Thus, IFN-γ–induced cell death was accompanied by an inflammatory signature in the absence of TBK1 and IKKε. TBK1 and IKKε not only mediated the induction of type I IFN but also inhibited RIPK1-dependent death and NF-κB–dependent inflammation. Therefore, we propose that these kinases may have gained these intertwined functions so that cells infected by pathogens that produce antagonists of TBK1 and IKKε are eliminated by IFN-γ–secreting T cells in an inflammatory manner to compensate for the inhibition of type I IFN production.

Abstract Progression from monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM) is driven by coordinated metabolic reprogramming within clonal plasma cells and the bone marrow microenvironment. We applied high-resolution MALDI–FT-ICR mass spectrometry imaging (MSI) to archived FFPE bone-marrow biopsies, integrated with matched bone marrow plasma metabolomics, to map spatial and systemic metabolic alterations. Spatial clustering delineated plasma-cell–rich niches, while Hill-based diversity and β-diversity metrics quantified intra- and inter-compartment heterogeneity. MM niches exhibited elevated 3-hydroxykynurenine, rewired tryptophan–kynurenine flux, and increased nucleotide and bioactive lipid metabolism associated with proliferation. Notably, some MGUS-like samples displayed MM-like metabolic niches undetectable in bone marrow plasma alone, underscoring spatial heterogeneity. Cross-compartment integration revealed conserved metabolic signatures and systemic redistribution of key metabolites, consistent with ecological reorganization and niche divergence during progression. These findings establish spatial metabolomics of biopsies as a framework to dissect intramedullary metabolic heterogeneity and enable metabolite-based risk stratification in plasma-cell disorders.

AbstractBackgroundPrecursor plasma cell disorders such as monoclonal gammopathy of undetermined significance (MGUS) always precede the development of active malignancies such as multiple myeloma (MM). There is a need for novel biomarkers to identify those patients with such precursor plasma cell disorders who rapidly progress to MM. Plasma‐derived extracellular vesicles (EVs) may serve as a reservoir of potential biomarkers that can shed light on the pathogenesis and disease biology of MM.MethodsThis study isolated small EVs (SEVs) and large EVs (LEVs) from the platelet‐poor peripheral blood plasma of MGUS (n = 9) and MM (n = 12) patients using the size exclusion chromatography‐based method and evaluated their proteome using a label‐free proteomics workflow.ResultsIn total, 2055 proteins were identified in SEVs, while 2794 proteins were identified in LEVs. The transferrin receptor (or CD71) protein was upregulated in both populations of EVs derived from MM patients compared to MGUS patients and was of prognostic significance. Similarly, three isoforms of serum amyloid A (SAA) protein, SAA1, SAA2, and SAA4, were also highly upregulated in SEVs within MM patients relative to MGUS patients. Finally, CD40 expression was also higher in the LEVs derived from MM patients than in MGUS patients.ConclusionsThis study demonstrates the feasibility of successfully isolating both SEVs and LEVs from the peripheral blood of patients with plasma cell disorders and quantifying protein biomarkers within these EVs that could be of prognostic and diagnostic interest.