Identification of CD84 as a potent survival factor in acute myeloid leukemia
Yinghui Zhu, … , John C. Williams, Flavia Pichiorri
Yinghui Zhu, … , John C. Williams, Flavia Pichiorri
Published April 8, 2025
Citation Information: J Clin Invest. 2025;135(11):e176818. https://doi.org/10.1172/JCI176818.
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Research Article Cell biology Hematology Oncology

Identification of CD84 as a potent survival factor in acute myeloid leukemia

Abstract

Acute myeloid leukemia (AML) is an aggressive and often deadly malignancy associated with proliferative immature myeloid blasts. Here, we identified CD84 as a critical survival regulator in AML. High levels of CD84 expression provided a survival advantage to leukemia cells, whereas CD84 downregulation disrupted their proliferation, clonogenicity, and engraftment capabilities in both human cell lines and patient-derived xenograft cells. Critically, loss of CD84 also markedly blocked leukemia engraftment and clonogenicity in MLL-AF9 and inv(16) AML mouse models, highlighting its pivotal role as a survival factor across species. Mechanistically, CD84 regulated leukemia cells’ energy metabolism and mitochondrial dynamics. Depletion of CD84 altered mitochondrial ultrastructure and function of leukemia cells, and it caused downmodulation of both oxidative phosphorylation and fatty acid oxidation pathways. CD84 knockdown induced a block of Akt phosphorylation and downmodulation of nuclear factor erythroid 2-related factor 2 (NRF2), impairing AML antioxidant defense. Conversely, CD84 overexpression stabilized NRF2 and promoted its transcriptional activation, thereby supporting redox homeostasis and mitochondrial function in AML. Collectively, our findings indicate that AML cells depend on CD84 to support antioxidant prosurvival pathways, highlighting a therapeutic vulnerability of leukemia cells.

Authors

Yinghui Zhu, Mariam Murtadha, Miaomiao Liu, Enrico Caserta, Ottavio Napolitano, Le Xuan Truong Nguyen, Huafeng Wang, Milad Moloudizargari, Lokesh Nigam, Theophilus Tandoh, Xuemei Wang, Alex Pozhitkov, Rui Su, Xiangjie Lin, Marc Denisse Estepa, Raju Pillai, Joo Song, James F. Sanchez, Yu-Hsuan Fu, Lianjun Zhang, Man Li, Bin Zhang, Ling Li, Ya-Huei Kuo, Steven Rosen, Guido Marcucci, John C. Williams, Flavia Pichiorri

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Figure 6

CD84 knockdown deactivated energy metabolism and induced mitochondrial stress in AML.

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CD84 knockdown deactivated energy metabolism and induced mitochondrial s...
(A and B) Scattergrams of CD84-related gene sets based on enrichment analyses of DEGs in HEL cells (shCD84 vs shCtrl) (A) and THP1 cells (shCD84 vs shCtrl) (B). The color indicates the false discovery rate q values; NES, normalized enrichment score. (C) Venn diagram showing the overlapped DEGs between HEL (shCD84 versus shCtrl) and THP1 (shCD84 versus shCtrl) groups. (D) Heatmap showing gene expression of the overlapped differential genes between THP1 cells and HEL cells expressing shCD84 or shCtrl, based on a fold change >2 or <0.5 and P < 0.05. (E) Bar chart showing GO enrichment analysis of common DEGs (n = 188) in 2 AML cell lines. (F) Connecting lines showing the effects of CD84 deletion on levels of OCR and ECAR in THP1 cells. Cells were transfected with lentivirus expressing shCD84 or shCtrl, and puromycin selected for 2 days. The cells were harvested to measure levels of OCR and ECAR using the Seahorse XF Cell Energy Phenotype Test Kit. Data are represented as mean ± SEM and are representative of 3 biological replicates. Statistical significance was assessed with 2-way ANOVA (mixed model). (G) Box chart showing the effects of CD84 knockdown on FAO levels in THP1 cells. The cells were harvested as described in F, and FAO assay results are presented as fold change, compared with control. Data are represented as mean ± SEM and are representative of 3 independent experiments. Statistical significance was assessed by 2-tailed unpaired t test. (H) Connecting lines showing the effects of CD84 deletion on levels of OCR and ECAR in primary AML cells obtained from n = 3 different donors. Cells were transduced with lentivirus expressing shCD84 or shCtrl for 48 hours. The cells were harvested to measure levels of OCR and ECAR using the Seahorse XF Cell Energy Phenotype Test Kit. Data are represented as mean ± SEM and are representative of 3 independent experiments. Statistical significance was assessed with 2-way ANOVA (mixed model).