Cis-Acting Splicing-Associated Variants Can Redefine the Molecular Signature of Genes Commonly Mutated in Acute Myeloid Leukemia

Introduction: Acute Myeloid Leukemia (AML) is a blood malignancy that occurs as a result of genomic alterations acquired in hematopoietic stem cells (HSCs). Several studies have recognized the importance of these alterations, including chromosomal rearrangements and single nucleotide variations (SNV...

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Veröffentlicht in:Blood 2023-11, Vol.142 (Supplement 1), p.2936-2936
Hauptverfasser: Morote-Faubel, Mireya, Guaita-Céspedes, Maria, Fernández-Blanco, Beatriz, Martínez-Valiente, Cristina, García-Ruiz, Cristian, Santiago, Marta, Diaz-Gonzalez, Alvaro, Sanjuan-Pla, Alejandra, Ibáñez, Mariam, Barragan, Eva, Such, Esperanza, Faubel, Mireya Morote, Montesinos, Pau, De La Rubia, Javier, Liquori, Alessandro, Cervera, Jose
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Sprache:eng
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Zusammenfassung:Introduction: Acute Myeloid Leukemia (AML) is a blood malignancy that occurs as a result of genomic alterations acquired in hematopoietic stem cells (HSCs). Several studies have recognized the importance of these alterations, including chromosomal rearrangements and single nucleotide variations (SNVs), for the classification and risk stratification of patients. However, none of these studies have thoroughly explored the functional impact of these lesions, potentially leading to the oversight or misinterpretation of certain driver mutations. In this study, we focused on the splicing process, as we aim to comprehensively characterize cis-acting splicing-associated variants (SAVs) in a large cohort of AML patients. Methods: We obtained recurrent driver gene variants (n= 3,847) from Table S5 reported by Papaemmanuil et al. and selected unique SNVs (n= 915) for our analysis. Among them, 628 (69%) were missense variants, 232 (25%) were nonsense variants, and 55 (6%) were located within splice sites. To assess their potential impact on splicing, we employed three splicing predictor tools (MaxEntScan, regSNP-splicing, and SpliceAI) and considered variants with two favorable predictions for further functional studies. Firstly, we attempted to locate the SNVs within the exomes of the TCGA-LAML (n= 149) and the BeatAML (n=342) datasets available in the Genomic Data Commons repository. If an SNV was identified, we obtained the RNA sequencing bam file from the corresponding patient's sample and utilized the rest of the cohort as a control for statistical analysis (pG and IDH1 c.394C>A, novel donor splice sites were created at distances of one (p=0.04522) and 34 nucleotides from the mutations (p=0.01878), respectively. Whereas, the TP53 c.395A>G change was found to activate a cryptic acceptor splice site located XX nucleotides away (p=0). Among private AML variants, minigene assays showed that eight v
ISSN:0006-4971
1528-0020
DOI:10.1182/blood-2023-177571