Integrative methylome-transcriptome analysis unravels cancer cell vulnerabilities in infant MLL-rearranged B cell acute lymphoblastic leukemia
Juan Ramón Tejedor, … , Agustín F. Fernández, Pablo Menéndez
Juan Ramón Tejedor, … , Agustín F. Fernández, Pablo Menéndez
Published May 13, 2021
Citation Information: J Clin Invest. 2021;131(13):e138833. https://doi.org/10.1172/JCI138833.
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Research Article Genetics Oncology

Integrative methylome-transcriptome analysis unravels cancer cell vulnerabilities in infant MLL-rearranged B cell acute lymphoblastic leukemia

Abstract

B cell acute lymphoblastic leukemia (B-ALL) is the most common childhood cancer. As predicted by its prenatal origin, infant B-ALL (iB-ALL) shows an exceptionally silent DNA mutational landscape, suggesting that alternative epigenetic mechanisms may substantially contribute to its leukemogenesis. Here, we have integrated genome-wide DNA methylome and transcriptome data from 69 patients with de novo MLL-rearranged leukemia (MLLr) and non-MLLr iB-ALL leukemia uniformly treated according to the Interfant-99/06 protocol. iB-ALL methylome signatures display a plethora of common and specific alterations associated with chromatin states related to enhancer and transcriptional control in normal hematopoietic cells. DNA methylation, gene expression, and gene coexpression network analyses segregated MLLr away from non-MLLr iB-ALL and identified a coordinated and enriched expression of the AP-1 complex members FOS and JUN and RUNX factors in MLLr iB-ALL, consistent with the significant enrichment of hypomethylated CpGs in these genes. Integrative methylome-transcriptome analysis identified consistent cancer cell vulnerabilities, revealed a robust iB-ALL–specific gene expression–correlating dmCpG signature, and confirmed an epigenetic control of AP-1 and RUNX members in reshaping the molecular network of MLLr iB-ALL. Finally, pharmacological inhibition or functional ablation of AP-1 dramatically impaired MLLr-leukemic growth in vitro and in vivo using MLLr-iB-ALL patient–derived xenografts, providing rationale for new therapeutic avenues in MLLr-iB-ALL.

Authors

Juan Ramón Tejedor, Clara Bueno, Meritxell Vinyoles, Paolo Petazzi, Antonio Agraz-Doblas, Isabel Cobo, Raúl Torres-Ruiz, Gustavo F. Bayón, Raúl F. Pérez, Sara López-Tamargo, Francisco Gutierrez-Agüera, Pablo Santamarina-Ojeda, Manuel Ramírez-Orellana, Michela Bardini, Giovanni Cazzaniga, Paola Ballerini, Pauline Schneider, Ronald W. Stam, Ignacio Varela, Mario F. Fraga, Agustín F. Fernández, Pablo Menéndez

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Figure 5

Gene coexpression network analysis reveals the AP-1 complex members JUN and FOS as potential pathogenic contributors in MLLr iB-ALL.

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Gene coexpression network analysis reveals the AP-1 complex members JUN ...
(A) Schematic depicting the number of samples analyzed by RNA-Seq. (B) PCA generated from the gene expression matrix (log2 fragments per kilobase of transcript per million mapped reads [FPKM] values) across all samples analyzed by RNA-Seq. (C) Tanglegram representation of the cluster relationship between paired DNA methylation and gene expression data (entanglement = 0.31, cophenetic correlation score = 0.4). (D) Barplot indicating the number of common (black) and specific (colored) significantly up- or downregulated genes observed for each comparison versus healthy BCPs. Inner graph indicates the total number of DEGs under each condition. Venn diagram represents the number of overlapping DEGs between naive B cells and iB-ALL compared with healthy BCPs. P < 0.001, 1-tailed hypergeometric test. (E) Violin plots showing the coefficient of variation of the gene expression (log2 fold change) of the DEGs for each condition compared with healthy BCPs. P < 0.001 for all comparisons, 2-sided Wilcoxon’s rank sum test. (F) Scatter plot depicting the normalized enrichment score (NES) and the contribution (represented by dot size) of particular gene modules in each group.