Fig 1: D2HGDH expression influences mitochondrial IDH activity and the cellular redox state.(a) Left panel: HEK-293 cells stably expressing WT D2HGDH displayed a significantly higher Vmax for IDH than those expressing mutant D2HGDH or an empty vector (P<0.0001, ANOVA). Middle panels: subcellular fractionation demonstrates that D2HGDH increases the Vmax for IDH in the mitochondria, but not in the cytosol; western blots at the right confirm the efficacy of the subcellular separation. (b) Left panel: knockdown of D2HGDH significantly decreased the Vmax for IDH (P<0.0001, ANOVA). Middle panels: subcellular fractionation demonstrates that D2HGDH levels influences exclusively the Vmax for mitochondrial IDH. Western blots at the right confirm the purity of the subcellular fractions. The data are shown as a nonlinear regression (curve fit) and each panel represents mean±s.d. of an assay performed in triplicate. Together with the data shown in Supplementary Fig. 9, the effects of D2HGDH on IDH activity were confirmed in three independent models of D2HGDH KD and two models of D2HGDH ectopic expression. The enzyme kinetics was calculated with the Michaelis–Menten equation. (c) Left: expression of WT D2HGDH significantly lowered NADP/NADPH ratio in comparison with isogenic cells expressing mutant D2HGDH or an empty vector (P=0.017, ANOVA), data shown are mean±s.d. from two biological replicates. Middle: transient expression of WT D2HGDH significantly lowered the NADP/NADPH ratio (P<0.0001, ANOVA); data shown are mean±s.d. of an assay performed in triplicate. Right panels: Stable (HEK-293) or transient (OCI-Ly8 and Ramos) knockdown of D2HGDH significantly increased NADP/NADPH ratio (P=0.01 and P=0.003, ANOVA, for HEK-293 or OCI-Ly8 and Ramos, respectively). Data shown are mean±s.d. of three biological replicates. (d) Left: cells expressing WT D2HGDH displayed significantly lower ROS levels than the isogenic models of mutant D2HGDH or empty-MSCV (P=0.0002, ANOVA); data shown are mean±s.d. from two biological replicates. Stable (middle) or transient (right) KD of D2HGDH in three distinct cell models significantly increased ROS levels (P=0.007, ANOVA, for all comparisons). Data shown at the middle are from two biological replicates; data on the right are from a single assay. In all instances, the Bonferroni's multiple comparison post hoc test yielded a P<0.05).
Fig 2: IDH mutations activate CEBPα-VDR-RXRα axis through 2HG production. (A) RT-qPCR showing gene expressions of VDR and RARA in HL60 IDH1WT (clone 2: ○; clone 7: ☐) versus HL60 IDH1R132H (clone 5: ◇; clone 11: △). (B) Western blot showing protein levels of VDR, RXRα and RARα in HL60 IDH1WT (clones 2 and 7) versus HL60 IDH1R132H (clones 5, 11 and 3) (left) and in HL60 IDH2WT versus HL60 IDH2R172K (right). (C) RT-qPCR showing gene expressions of VDR and RARA in 2HG-treated HL60 (200 µM, 1 week). (D) Western blot showing protein levels of VDR RXRα and RARα in 2HG-treated HL60 IDH1WT (clones 2 and 7) (200 µM, 1 week). (E) RT-qPCR showing gene expression of and VDR and RARA in HL60 IDH1WT (clone 2: ○, clone 7: ☐) and IDH1R132H (clone 5: ◇, clone 11: △) after CEBPA-KD by shRNA (F) Western blot showing protein levels of CEBPα, VDR, RARα and VDR in HL60 IDH1WT (clones 2 and 7) and IDH1R132H (clone 5 and 11) after CEBPA-KD by shRNA. (G) Western blot showing protein levels of VDR in 2HG-treated HL60 IDH1WT (clone 2 and 7) with CEBPA-KD by shRNA (200 µM, 1 week). The uncropped western blot figures are presented in Figure S6. * p < 0.05; ** p < 0.01.
Fig 3: Vitamin D receptor-related gene signatures are enriched in transcriptomes of IDH mutant AML cells. (A) Gene signature of pharmacological substances were compared with gene signatures associated with IDH1MUT HL60 cells, IDH1WT HL60 cells+2HG and IDHMUT patient cells from TCGA and GSE14468 transcriptomes using Genomatix software. VENN diagram represents common pharmacological substances associated with these four gene signatures. (B) VENN diagram of common genes from ATRA- and VD-responsive genes (Pharmacological substances, Genomatix) enriched in IDHMUT-AML and HL60 IDH1WT+2HG. (C) Gene set enrichment analysis (GSEA) of late VD/VDR activation pathway signature in HL60 IDH1R132H, HL60 IDH1WT treated with 2HG and in IDHMUT patients from GSE14468. (D) Correlation between late VD/VDR activation pathway gene signature and up-regulated genes in IDH1MUT signatures (left, GSE14468; right, TCGA) in scRNA-seq of AML cells from the PDX IDH1R132H. (E) GSEA of late VD/VDR activation pathway gene signature in IDHMUT patients relapsing after IDH inhibitor treatment compared to those patients before treatment (GSE153349).
Fig 4: IDH2-R172M and IDH2-R140Q affect tumor growthSoft-agar tumor colony formation of U87MG+IDH2 cell panel assessed at 28 days (A). Subcutaneous tumor xenografts of U87MG cells expressing IDH2-WT, IDH2-R172K, IDH2-R172M, or IDH2-R140Q in SCID mice (n = 3). Tumor volumes were measured over the course of 50 days (B). Orthotopic U87MG tumors in Rag1−/− mice (n = 3). Brains were collected after 28 days and tumor volumes determined by using 5 μM serial tissue sections (C). Shown are representative images taken at 4X magnification. *p ≤ 0.05.
Fig 5: High IDH2 expressed patients follow poor prognosis Representative immunostaining of IDH2, CAIX (surrogate marker of Hif‐1α), TIGAR, TKT, and CTPS1 in surgical specimens from upper tract urothelial carcinoma (UTUC) patients. The upper panel represents the immunostaining of metabolic enzymes of early‐stage UTUC tumors, whereas the lower panel represents the images of invasive UTUC tumors. The power field scale bar = 100 μm.Comparison of histoscores (H‐scores) for each metabolic enzyme divided by early‐ or advanced‐stage tumors. The H‐score was calculated by applying the following formula: mean percentage × intensity (range, 0–300). Violin plots were divided by pTa‐2: 116 UC patients and pT3‐4: 98 UC patients. Data were analyzed by Student's t‐test.Heat map describing the IHC score in UTUC patients treated with GEM and CDDP (GC) adjuvant chemotherapy (n = 74). The heat map of metabolic enzymes in patients was classified by chemo‐sensitivity with information for age, sex, pT stage, grade, and death.Kaplan–Meier curves showing the cancer‐specific survival (CSS) of 74 UTUC patients treated with GC adjuvant chemotherapy. Metabolic enzymes were classified according to the results of receiver operating curve (ROC) analysis. Data were compared with the log‐rank test.Representative immunostaining of IDH2, CAIX, TIGAR, TKT, and CTPS1 in surgical specimens from muscle invasive urothelial carcinoma (MIBC) patients with neoadjuvant GC chemotherapy. Case 1 was a transurethral resection of bladder tumor (TURBT) specimen that induced a pathological complete response (pT0) in a radical cystectomy (RC) specimen. Case 2 was indicated as residual pT3 after neoadjuvant GC therapy. The power field scale bars = 200 and 50 μm.Heat map describing the IHC score in MIBC patients treated with GC chemotherapy (n = 32). The heat map of metabolic enzymes in patients classified by IDH2 expression with information for age, sex, pT stage, grade, and death.Details of high and low expression of CAIX, TIGAR, TKT, and CTPS1 classified with IDH2 expression.Kaplan–Meier method showing the CSS of 32 MIBC patients treated with GC chemotherapy. The cutoffs for metabolic enzyme levels were determined according to the results of ROC analysis. Data were compared with the log‐rank test.
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