The tumor suppressor TP53 is frequently inactivated in cancers in a mutation-independent manner and is reactivated by inhibiting its negative regulators. We here co-target MDM2 with the nuclear exporter XPO1 to maximize transcriptional activity of p53. MDM2/XPO1 inhibition accumulated nuclear p53 and elicited a 25- to 60-fold increase of its transcriptional targets. TP53 regulates MYC, and MDM2/XPO1 inhibition disrupted the c-MYC-regulated transcriptome, resulting in synergistic induction of apoptosis in acute myeloid leukemia (AML). Surprisingly, venetoclax-resistant AMLs express high levels of c-MYC and are vulnerable to MDM2/XPO1 inhibition in vivo. However, AML cells persisting after MDM2/XPO1 inhibition exhibit a quiescence- and stress response-associated phenotype. Venetoclax overcomes that resistance, as shown by single-cell mass cytometry. The triple inhibition of MDM2, XPO1, and BCL2 was highly effective against venetoclax-resistant AML in vivo. Our results propose a novel, highly translatable therapeutic approach leveraging p53 reactivation to overcome non-genetic, stress-adapted venetoclax resistance.

AML cell lines OCI-AML3, MOLM-13 TP53 wild-type and MOLM-13 TP53 p.R248Q cells were treated with milademetan, selinexor, and the combination of milademetan and selinexor for 12 hours. RNA samples were collected from those cells and subjected to RNA sequencing.

RNA sequencing

OCI-AML3, MOLM-13 TP53 wild-type, and R248Q mutant cells were treated with DMSO, milademetan, selinexor, or the combination of Mil + Sel for 12 hours. Cells were harvested and total RNA was extracted using QIAGEN RNeasy extraction kit from each sample (N = 3 for each treatment, N = 12 in total) according to the manufacturer’s protocol.

Barcoded, Illumina-compatible, strand-specific total RNA libraries were prepared using the TruSeq Stranded Total RNA Sample Preparation Kit (Illumina, San Diego, CA). Briefly, 1mg of DNase I treated total RNA was depleted of cytoplasmic and mitochondrial ribosomal RNA (rRNA) using Ribo-Zero Gold (Illumina). After purification, the RNA was fragmented using divalent cations and double-stranded cDNA was synthesized using random primers. The ends of the resulting double-stranded cDNA fragments were repaired, 50-phosphorylated, 3’-A tailed and Illumina-specific indexed adapters were ligated. The products were purified and enriched by 11 cycles of PCR to create the final cDNA library. The libraries were quantified using the Qubit dsDNA HS Assay Kit (ThermoFisher, Waltham, MA) and assessed for size distribution using the Fragment Analyzer (Advanced Analytical, Ankeny, IA), then multiplexed 4 libraries per pool.

Library pools were quantified by qPCR and sequenced, one pool per lane, on the Illumina NovaSeq6000 sequencer using the 150 bp paired-end format. 

Differential gene expression profiling and pathway analyses

Gene expression was quantified using the Kallisto/sleuth pipeline. Read quantification was performed with Kallisto (v. 0.44.0), a pseudo-alignment-based method to quantify RNA abundance at the transcript level in transcripts per million (TPM) counts. Kallisto quant was utilized with the number of bootstraps set to 100 using ENSEMBL cDNA transcripts (Human assembly hg19, release GRC38.14) for indexing. Hierarchical clustering and principal component analysis (PCA) of the samples were performed. Sleuth v0.30.0 was used to measure the abundance of the transcripts as transcripts per million (TPM) with covariates for treatment conditions and downstream differential gene expression (DGE) to leverage the bootstrap estimates of Kallisto and to output model-based, gene-level normalized TPM matrix. The abundance of the genes was calculated as the sum of the TPMs mapped to a given gene. When using the sleuth preparation, gene isoforms were aggregated with a target map file derived from the Refseq hg19 transcriptome. For each gene, both the likelihood ratio test and Wald test were performed on the condition parameter to obtain their respective FDR-corrected p-values. Significantly altered genes were those passing the two tests at a cutoff of false discovery rate (FDR) < 0.1. The plot_transcript_heatmap function in the Sleuth package was utilized to visualize the cluster analysis. Enhanced Volcano R package was used to generate the volcano plots (Blighe, K.; Rana, S.; Lewis, M. EnhancedVolcano: Publication-Ready Volcano Plots with Enhanced Colouring and Labeling. 2018. R Package Version 1.3.5. Available online: https://github.com/kevinblighe/EnhancedVolcano), which is a visual tool for displaying differentially expressed genes (DEGs) among overall gene expression levels. Beta score (log2) of -1 and 1 (0.5 fold and 2 folds), and q value of 0.05 were used as threshold lines for the magnitude of change in gene expression and significance, respectively. HALLMARK gene sets were used for pathway enrichment and functional classification of differentially expressed genes.