Loss of Pax5 exploits sca1-BCR-ABLp190 susceptibility to confer the metabolic shift essential for pB-ALL

Preleukemic clones carrying BCR-ABLp190 oncogenic lesions are found in neonatal cord blood, where the majority of preleukemic carriers do not convert into precursor B-cell acute lymphoblastic leukemia (pB-ALL). However, the critical question of how these preleukemic cells transform into pB-ALL remains undefined. Here, we model a BCR-ABLp190 preleukemic state and show that limiting BCR-ABLp190 expression to hematopoietic stem/progenitor cells (HS/PC) in mice (Sca1-BCR-ABLp190) causes pB-ALL at low penetrance, which resembles the human disease. pB-ALL blast cells were BCR-ABL–negative and transcriptionally similar to pro-B/pre-B cells, suggesting disease onset upon reduced Pax5 functionality. Consistent with this, double Sca1-BCR-ABLp190+Pax5+/− mice developed pB-ALL with shorter latencies, 90% incidence, and accumulation of genomic alterations in the remaining wild-type Pax5 allele. Mechanistically, the Pax5-deficient leukemic pro-B cells exhibited a metabolic switch toward increased glucose utilization and energy metabolism. Transcriptome analysis revealed that metabolic genes (IDH1, G6PC3, GAPDH, PGK1, MYC, ENO1, ACO1) were upregulated in Pax5-deficient leukemic cells, and a similar metabolic signature could be observed in human leukemia. Our studies unveil the first in vivo evidence that the combination between Sca1-BCR-ABLp190 and metabolic reprogramming imposed by reduced Pax5 expression is sufficient for pB-ALL development. These findings might help to prevent conversion of BCR-ABLp190 preleukemic cells.J. Hauer has been supported by the German Cancer Aid (Project 110997 and Translational Oncology Program 70112951), the German Jose Carreras Foundation (DJCLS 02R/2016), the Kinderkrebsstiftung (2016/17), and the "Elterninitiative Kinderkrebstiftung e.V." S. Ginzel has been supported by a scholarship of the Hochschule Bonn-Rhein-Sieg. M. Muschen is an HHMI Faculty Scholar (HHMI- € 55108547) and supported by NIH/NCI through an Outstanding Investigator Award (R35CA197628, R01CA137060, R01CA157644, R01CA172558, R01CA213138) to M. Muschen, a Wellcome Trust Senior Investigator Award, € the Leukemia and Lymphoma Society, the Norman and Sadie Lee Foundation (for Pediatric Cancer, to M. Muschen), and the Dr. Ralph and Marian € Falk Medical Research Trust (to M. Muschen), Cancer Research Institute € through a Clinic and Laboratory Integration Program grant (to M. Muschen) € and the California Institute for Regenerative Medicine (CIRM) through DISC2-10061. A. Borkhardt has been supported by the German Children's Cancer Foundation and the Federal Ministry of Education and Research, Bonn, Germany. Research in I. Sanchez-García's group is partially supported by FEDER and by MINECO (SAF2012-32810, SAF2015-64420-R, and Red de Excelencia Consolider OncoBIO SAF2014-57791-REDC), Instituto de Salud Carlos III (PIE14/00066), ISCIII- Plan de Ayudas IBSAL 2015 Proyectos Integrados (IBY15/00003), by Junta de Castilla y Leon (BIO/SA51/15, CSI001U14, UIC-017, and CSI001U16), Fundacion Inocente Inocente and by the ARIMMORA project [European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 282891]. I. Sanchez-García's lab is a member of the EuroSyStem and the DECIDE Network funded by the European Union under the FP7 program. A. Borkhardt and I. Sanchez-García have been supported by the German Carreras Foundation (DJCLS R13/26). Research in C. Vicente-Duenas's ~ group is partially supported by FEDER, Ministerio de Economía y Competitividad ("Miguel Servet" Grant - CP14/00082 - AES 2013-2016) and (PI17/00167) from the Instituto de Salud Carlos III. A. Martín-Lorenzo and G. Rodríguez-Hernandez were supported by FSE-Conserjería de Educacion de la Junta de Castilla y Leon (CSI001-13 and CSI001-15, respectively). F. Auer was supported by a Deutsche Forschungsgemeinschaft (DFG) fellowship (AU 525/1-1)

Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression data

<p>Abstract</p> <p>Background</p> <p>Visualization of DNA microarray data in two or three dimensional spaces is an important exploratory analysis step in order to detect quality issues or to generate new hypotheses. Principal Component Analysis (PCA) is a widely used linear method to define the mapping between the high-dimensional data and its low-dimensional representation. During the last decade, many new nonlinear methods for dimension reduction have been proposed, but it is still unclear how well these methods capture the underlying structure of microarray gene expression data. In this study, we assessed the performance of the PCA approach and of six nonlinear dimension reduction methods, namely Kernel PCA, Locally Linear Embedding, Isomap, Diffusion Maps, Laplacian Eigenmaps and Maximum Variance Unfolding, in terms of visualization of microarray data.</p> <p>Results</p> <p>A systematic benchmark, consisting of Support Vector Machine classification, cluster validation and noise evaluations was applied to ten microarray and several simulated datasets. Significant differences between PCA and most of the nonlinear methods were observed in two and three dimensional target spaces. With an increasing number of dimensions and an increasing number of differentially expressed genes, all methods showed similar performance. PCA and Diffusion Maps responded less sensitive to noise than the other nonlinear methods.</p> <p>Conclusions</p> <p>Locally Linear Embedding and Isomap showed a superior performance on all datasets. In very low-dimensional representations and with few differentially expressed genes, these two methods preserve more of the underlying structure of the data than PCA, and thus are favorable alternatives for the visualization of microarray data.</p

RRM2 enhances MYCN-driven neuroblastoma formation and acts as a synergistic target with CHK1 inhibition

High-risk neuroblastoma, a pediatric tumor originating from the sympathetic nervous system, has a low mutation load but highly recurrent somatic DNA copy number variants. Previously, segmental gains and/or amplifications allowed identification of drivers for neuroblastoma development. Using this approach, combined with gene dosage impact on expression and survival, we identified ribonucleotide reductase subunit M2 (RRM2) as a candidate dependency factor further supported by growth inhibition upon in vitro knockdown and accelerated tumor formation in a neuroblastoma zebrafish model coexpressing human RRM2 with MYCN. Forced RRM2 induction alleviates excessive replicative stress induced by CHK1 inhibition, while high RRM2 expression in human neuroblastomas correlates with high CHK1 activity. MYCN-driven zebrafish tumors with RRM2 co-overexpression exhibit differentially expressed DNA repair genes in keeping with enhanced ATR-CHK1 signaling activity. In vitro, RRM2 inhibition enhances intrinsic replication stress checkpoint addiction. Last, combinatorial RRM2-CHK1 inhibition acts synergistic in high-risk neuroblastoma cell lines and patient-derived xenograft models, illustrating the therapeutic potential