Abstract A27: European Network NGS-PTL preliminary data: Whole exome sequencing identifies mutations of ALDH2, RETSAT, HSPG2, CHPF and other metabolic genes as a novel functional category in acute myeloid leukemia
Authors: Simonetti Giorgia , Padella Antonella , Iacobucci Ilaria , Valle Italo Do , Fontanarosa Gabriele , Zago Elisa , Griggio Francesca , Garonzi Marianna , Bernardi Simona , Papayannidis Cristina , Abbenante Maria Chiara , Marconi Giovanni , Melloni Giorgio , Riva Laura , Guadagnuolo Viviana , Fontana Mariachiara , Bruno Samantha , Zuffa Elisa , Franchini Eugenia , Astolfi Annalisa , Baldazzi Carmen , Dan Elisa , Sinigaglia Barbara , Cavo Michele , Testoni Nicoletta , Ottaviani Emanuela , Pelicci Pier Giuseppe , Sazzini Marco , Ferrarini Alberto , Delledonne Massimo , Remondini Daniel , Martinelli Giovanni 
Published: May 2016

Abstract
Next Generation Sequencing (NGS) studies identified 9 functional categories of mutations in acute myeloid leukemia (AML), with &gt;99% of cases having at least one of those mutations (Ley et al. NEJM 2013). However, multiple genetic hits participate to AML pathogenesis, and metabolic dysregulations, as the one induced by IDH1/2 mutations, play oncogenic functions (Ward et al. Cancer Cell 2010).
Aim of the study was to define novel functional categories of AML mutations affecting relevant and druggable biological processes, with focus on genetic determinants of metabolic plasticity.
Out of 455 whole exome sequencing (WES) cases from onco-hematological patients collected in the NGS-PTL project, we analyzed 37 AML cases, belonging to our cohort of 239 FLT3-WT samples (886 AML total). We performed 100 bp paired-end WES (HiSeq2000, Illumina) and mapped the sequenced reads with Burrows-Wheeler Aligner. Variants where called with MuTect or GATK for single nucleotide variant (SNV) and indels detection, respectively (&gt;90% confidence). Gene expression profiling was performed using HTA2.0 microarray (Affymetrix) on 56 bone marrow samples, including AML (≥80% blasts) and healthy controls.
By WES analysis, we detected an average of 26 somatic variants per patient (range, 7 to 65). Gene ontology annotation identified 8 novel relevant functional categories of mutated genes: transcription, translation and post-translational modifications, protein degradation, cytoskeleton, cell cycle, DNA damage, cell survival and metabolism. Since metabolic pathways are promising targets for tailored therapies (e.g. IDH1/2 and glutaminase inhibitors), we focused our analysis on them. We identified 82 variants (74 SNVs, 2 frameshift and 4 nonframeshift deletions, 2 stopgains) targeting 70 genes involved in metabolism, with 78% of patients carrying at least one mutation in a metabolic gene and 35 variants rated as damaging by CONDEL algorithm. Among mutations in metabolic genes, the most represented pathways according to Recon X database were amino acids, lipids, CoA and nucleotides metabolism, transport and bioenergetics pathways. Notably, IMPDH2, a mediator of MYC-induced proliferation involved in nucleotide interconversion, was mutated and overexpressed in our AML cohort (p=0.01), suggesting a potential oncogenic function. Moreover, ALDH2, a regulator of hematopoietic stem cell functions which is involved in multiple metabolic pathways and associates with metabolic remodeling, was mutated and 2-fold downregulated in AML blasts. Seven genes were mutated in 5-8% of samples: RETSAT, HSPG2, CHPF, ABCA2, ND1, APOBR, NAAA. Among them, RETSAT, HSPG2, CHPF mutations were also predicted as “drivers” by DOTS-Finder tool. Bioenergetics pathways were affected by mutations in glycolysis and gluconeogenesis (GPI, ITPA), oxidative phosphorylation (ND1, ND4, ND5, CYTB), pentose phosphate pathway (H6PD, PGLS). Patients carrying mutations in the bioenergetics pathway showed a strong trend towards reduced overall survival, which did not associate with unfavorable molecular mutations.
In conclusion, metabolism is the most represented class of mutated genes (8.6% of variants) in our FLT3-WT AML cohort after signaling, leading us to propose a novel functional category. Our data suggest that, along with mutations in established oncogenes and tumor suppressors involved in metabolic control (KRAS, TP53, MYC pathway), a number of genetic determinants participate to leukemia metabolic plasticity and oncogenic mutations of metabolic enzymes may drive leukemogenesis, impact on patient's survival and become novel targets for personalized therapies.
Acknowledgements: ELN, AIL, AIRC, progetto Regione-Università 2010-12 (L. Bolondi), FP7 NGS-PTL project.
GS and AP equally contributed to this work.
Citation Format: Giorgia Simonetti, Antonella Padella, Ilaria Iacobucci, Italo Do Valle, Gabriele Fontanarosa, Elisa Zago, Francesca Griggio, Marianna Garonzi, Simona Bernardi, Cristina Papayannidis, Maria Chiara Abbenante, Giovanni Marconi, Giorgio Melloni, Laura Riva, Viviana Guadagnuolo, Mariachiara Fontana, Samantha Bruno, Elisa Zuffa, Eugenia Franchini, Annalisa Astolfi, Carmen Baldazzi, Elisa Dan, Barbara Sinigaglia, Michele Cavo, Nicoletta Testoni, Emanuela Ottaviani, Pier Giuseppe Pelicci, Marco Sazzini, Alberto Ferrarini, Massimo Delledonne, Daniel Remondini, Giovanni Martinelli. European Network NGS-PTL preliminary data: Whole exome sequencing identifies mutations of ALDH2, RETSAT, HSPG2, CHPF and other metabolic genes as a novel functional category in acute myeloid leukemia. [abstract]. In: Proceedings of the AACR Special Conference: Metabolism and Cancer; Jun 7-10, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(1_Suppl):Abstract nr A27.