Restoring mitochondrial quantity and quality to reverse the Warburg effect and drive neuroblastoma differentiation

Abstract

Reduced mitochondrial quality and quantity in tumors is associated with dedifferentiation and increased malignancy. However, it remains unclear how to restore mitochondrial quantity and quality in tumors and whether mitochondrial restoration can drive tumor differentiation. Our study shows that restoring mitochondrial function using retinoic acid (RA) to boost mitochondrial biogenesis and a mitochondrial uncoupler to enhance respiration synergistically drives neuroblastoma differentiation and inhibits proliferation. U-¹³C-glucose/glutamine isotope tracing revealed a metabolic shift from the pentose phosphate pathway to oxidative phosphorylation, accelerating the tricarboxylic acid cycle and switching substrate preference from glutamine to glucose. These effects were abolished by electron transport chain (ETC) inhibitors or in ρ⁰ cells lacking mitochondrial DNA, emphasizing the necessity of mitochondrial function for differentiation. Dietary RA and uncoupler treatment promoted tumor differentiation in an orthotopic neuroblastoma xenograft model, evidenced by neuropil production and Schwann cell recruitment. Single-cell RNA sequencing of xenografts revealed that this strategy effectively eliminated the stem cell population, promoted differentiation, and increased mitochondrial gene signatures along the differentiation trajectory, potentially improving patient outcomes. Collectively, our findings establish a mitochondria-centric therapeutic strategy for inducing tumor differentiation, suggesting that maintaining/driving differentiation in tumor requires not only ATP production but also continuous ATP consumption and sustained ETC activity.

Keywords: differentiation; mitochondria; neuroblastoma; retinoic acid; uncoupler.

Fig. 1.

RA increased mitochondrial quantity without activating mitochondrial respiration. SK-N-BE(2) and CHP134 cells were treated with DMSO or 1 µM RA for 72 h. (A) Mitochondrial 3XHA-OMP25-GFP (green) intensity was normalized to Hoechst-stained nuclei (blue) (n = 5). (B) mtDNA copy number was quantified by qPCR using ND1 and TL1 normalized to ACTB (n = 4). (C) Mitochondrial function in SK-N-BE(2) cells was assessed by Seahorse assay, measuring basal, spare, and maximal oxygenconsumption rate (OCR) (n = 6). (D) Glucose labeling fractions in the pentose phosphate pathway and TCA cycle metabolites were measured by LC–MS (Liquid Chromatography-Mass Spectrometry) in SK-N-BE(2) cells (n = 3).

Fig. 2.

Mitochondrial uncoupler synergizes with RA to activate mitochondrial respiration and shift metabolism from anabolism to catabolism. (A, Top) Schematic illustrating the metabolic balance between ATP demand and biosynthetic needs in differentiated versus dedifferentiated/cancer cells. High ATP demand supports active mitochondria and proenergetic metabolism; low ATP demand favors building block accumulation and proproliferative metabolism. (Bottom) Diagram of the ETC showing how mitochondrial uncouplers dissipate the proton gradient to stimulate respiration. (B–E) SK-N-BE(2) and CHP134 cells were treated for 72 h with vehicle, 1 µM RA, 1 µM NEN, or RA+NEN. (B) Basal OCR was measured using the Seahorse analyzer (n = 9). (C) ATP/ADP and NAD⁺/NADH ratios were quantified by LC–MS (n = 3). (D and E) U-¹³C₆-glucose and U-¹³C₅-glutamine tracing by LC–MS revealed changes in labeling fractions in the PPP and TCA cycle metabolites in SK-N-BE(2) cells (n = 3).

Fig. 3.

RA and mitochondrial uncoupler synergize to induce neuronal differentiation in neuroblastoma cells. (A) Phase-contrast images of SK-N-BE(2), CHP134, SY-SH5Y, and LAN-5 cells treated with DMSO, 1 µM RA, 1 µM NEN, or RA+NEN for 72 h. Neurite outgrowth was quantified by average neurite length per cell. (Scale bar: 25 µm.) (B) Immunofluorescence of β-Tubulin-III (red) and DAPI (blue) in CHP134 and SK-N-BE(2) cells, showing neurite formation. (C and D) RNA-seq analysis showing differentially expressed genes related to RA signaling, neuronal differentiation, and chromatin remodeling (C), and GSEA revealing pathway enrichment in RA, NEN, and RA+NEN-treated cells (D). (E) Chou-Talalay analysis of RA and NEN synergy in SK-N-BE(2) and CHP134 proliferation (n = 6) using CompuSyn. (F, Left) Timeline of proliferation assays with pretreatment followed by cell counts every 2 d. (Right) Growth curves for SK-N-BE(2) and CHP134 under each condition (n = 6). Groups with different letters differ significantly (P < 0.05).

Fig. 4.

Mitochondrial respiration is essential for neuroblastoma differentiation. (A) Schematic of three mitochondrial inactivation methods: pharmacological (Rotenone, a complex I inhibitor) and genetic (low-dose ethidium bromide [EtBr] and TFAM knockout, both depleting mtDNA). (B) Phase-contrast images of indicated cells treated with DMSO, RA (1 μM), NEN (1 μM), or RA+NEN, with or without rotenone (0.05 μM). (C) Heatmap of differentiation gene expression in treated cells (RT-qPCR). (D) Schematic of ρ⁰ cell generation via EtBr treatment. (E, Left) Confocal images of mitochondrial morphology in WT and ρ⁰ cells. (Right) Linear/circular mitochondria ratio (n = 3). (F) mtDNA quantification in WT and ρ⁰ cells (n = 4). (G) Energy map of mitochondrial respiration in WT and ρ⁰ cells. (H) Phase-contrast images of WT and ρ⁰ cells treated with DMSO, RA, NEN, or RA+NEN. (I) CRISPR/Cas9-mediated TFAM knockout in CHP-134 cells validated by Western blot.(J) mtDNA quantification (n = 4) and energy map (n = 8) in CHP134 sgCTRL and sgTFAM cells. (K) Phase-contrast images of CHP134 sgCTRL and sgTFAM cells treated with DMSO, RA, NEN, or RA+NEN.

Fig. 5.

Effects of RA and NEN treatment on tumor differentiation in an orthotopic neuroblastoma model and potential beneficial impact on patient survival. (A) Schematic representation of the experimental design showing ultrasound monitoring, dietary interventions (CTRL, RA, NEN, and RA+NEN), and tumor size measurements until euthanasia (Animal Welfare Act Regulations). (B and C) Tumor growth curves (B) and body weight measurements (C) showing the effects of different diets on tumor progression and treatment tolerance (n = 8). (D) Representative H&E (Hematoxylin and Eosin) and IHC (immunohistochemistry) staining for S100β, TrkA, and N-Myc across treatment groups, along with quantification of cell and nuclear diameters (n = 15). (E) Quantification of S100β, TrkA, and N-Myc expression levels (n = 3). (F) Kaplan–Meier survival curves for patients with low or high RA, NEN, and RA+NEN treatments gene signatures. Solid: survival; dotted: 95% CI.

Fig. 6.

Single-cell RNA sequencing reveals differentiation dynamics induced by RA and uncoupler treatments. (A) RNA velocity analysis illustrates directional differentiation from Cycling Neuroblasts to Neuron-like cells. (B) Heatmap of stage-specific markers shows key gene expression across clusters—Cycling Neuroblast markers: ASCL1, GATA3, PHOX2B, RET, ALK, MKI67; Neuron markers: HAND2, TUBB3, NEFM, DCX, GAP43, TH, MAP2, PHOX2A. (C) Diffusion analysis highlights differentiation potential across cell clusters. (D) Prognostic analysis based on binary gene signatures from Neuron-like and Cycling Neuroblast markers. Solid: survival; dotted: 95% CI. (E) Bar graph showing Neuron-like/Cycling Neuroblast cell ratio across treatments. (F–I) Heatmaps showing expression of proliferation and stemness markers by cluster, and genes related to OXPHOS, mitochondrial ribosome, and ribosome function along the differentiation trajectory.