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Genomic, single-cell, and functional profiling of the CD48-CD244 axis and NK cell dysfunction in multiple myeloma
Bonell Patiño-Escobar, Torsten Steinbrunn, Lucy Perez-Lugo, Sham Rampersaud, Daniel D. Waller, Daniela Ordoñez, Huimin Geng, Fernando Salangsang, Paul Phojanakong, Juan Antonio Camara Serrano, Yan Zeng, Veronica Steri, Oscar A. Aguilar, Constantine S. Mitsiades, Arun P. Wiita
Bonell Patiño-Escobar, Torsten Steinbrunn, Lucy Perez-Lugo, Sham Rampersaud, Daniel D. Waller, Daniela Ordoñez, Huimin Geng, Fernando Salangsang, Paul Phojanakong, Juan Antonio Camara Serrano, Yan Zeng, Veronica Steri, Oscar A. Aguilar, Constantine S. Mitsiades, Arun P. Wiita
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Research Article Cell biology Hematology Immunology

Genomic, single-cell, and functional profiling of the CD48-CD244 axis and NK cell dysfunction in multiple myeloma

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Abstract

Multiple myeloma (MM) orchestrates immune evasion by subverting natural killer (NK) cell function. CD48, one of the most abundant NK ligands on MM cells, paradoxically enhances NK cell activation yet is associated with high-risk cytogenetics and poor patient survival. We integrated multiomics (bulk and single-cell RNA-seq, assay for transposase-accessible chromatin using sequencing [ATAC-seq], chromatin immunoprecipitation sequencing [ChIP-seq]), genome-wide CRISPR knockout/activation screens, and machine learning to dissect CD48 regulation and function. In human MM and Vκ*MYC mouse scRNA-seq datasets, NK cells exhibit stepwise increases in inflammatory and exhaustion signatures and loss of cytotoxic potential as disease progresses. In vitro coculture assays show that CD48 overexpression on MM enhances NK cell cytokine secretion, whereas chronic exposure leads to ex vivo NK dysfunction. In vivo, CD48-overexpressing Vκ*MYC tumors progress more slowly and extend host survival, while NK cell depletion accelerates disease. These findings support a context-dependent role for CD48, potentiating acute NK responses while coexisting with chronic NK exhaustion, and suggest strategies to modulate CD48 for therapeutic benefit.

Authors

Bonell Patiño-Escobar, Torsten Steinbrunn, Lucy Perez-Lugo, Sham Rampersaud, Daniel D. Waller, Daniela Ordoñez, Huimin Geng, Fernando Salangsang, Paul Phojanakong, Juan Antonio Camara Serrano, Yan Zeng, Veronica Steri, Oscar A. Aguilar, Constantine S. Mitsiades, Arun P. Wiita

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Figure 2

Combined chromatin profiling, machine learning, and functional screens reveal novel CD48 regulators in myeloma.

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Combined chromatin profiling, machine learning, and functional screens r...
(A) ATAC-seq tracks at the CD48 locus from normal memory B cells, plasmablasts, plasma cells, and primary MM samples. Two regions of enriched accessibility near the CD48 transcription start site are highlighted. (B) XGBoost model of observed versus predicted CD48 expression in CoMMpass samples (80% training, 20% test; R2 = 0.40). TMP, transcripts per million. (C) SHAP summary plot ranking transcription factors by their contribution to predicted CD48 expression; each dot represents one patient. (D and E) Correlation of CD48 expression with IRF4 and MEF2B in CoMMpass calculated using Pearson method. (F) Heatmap of average log2 fold change of sgRNAs in CRISPR-KO and CRISPRa screens comparing CD48-high and CD48-low populations across INA6, AMO1, and MM.1S cells. (G) STRING protein-protein interaction network of 52 overlapping CRISPR-KO/a hits, grouped by functional category. (H) Flow cytometric validation of surface CD48 after CRISPR/Cas9 knockout of ESRRA, MEF2B, TFAP2A, RELA, and CD48 in AMO1 cells. Bar graphs show surface CD48 mean fluorescence intensity (MFI) fold change (FC) relative to non-targeting scramble sgRNA control (dashed red line) following knockout of the indicated genes (n = 3 technical replicates; mean ± SEM). Pairwise comparisons with scramble control were performed using 2-sided Welch’s t test. ** P < 0.01; *** P < 0.001; absence of asterisks indicates no significant difference.

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