Allelic Imbalance of Recurrently Mutated Genes in Acute Myeloid Leukaemia

Batcha, Aarif M. N.; Bamopoulos, Stefanos A.; Kerbs, Paul; Kumar, Ashwini; Jurinovic, Vindi; Rothenberg-Thurley, Maja; Ksienzyk, Bianka; Philippou-Massier, Julia; Krebs, Stefan; Blum, Helmut; Schneider, Stephanie; Konstandin, Nikola; Bohlander, Stefan K.; Heckman, Caroline; Kontro, Mika; Hiddemann, Wolfgang; Spiekermann, Karsten; Braess, Jan; Metzeler, Klaus H.; Greif, Philipp A.; Mansmann, Ulrich und Herold, Tobias (2019): Allelic Imbalance of Recurrently Mutated Genes in Acute Myeloid Leukaemia. In: Scientific Reports, Bd. 9, Nr. 11796

Abstract

The patho-mechanism of somatic driver mutations in cancer usually involves transcription, but the proportion of mutations and wild-type alleles transcribed from DNA to RNA is largely unknown. We systematically compared the variant allele frequencies of recurrently mutated genes in DNA and RNA sequencing data of 246 acute myeloid leukaemia (AML) patients. We observed that 95% of all detected variants were transcribed while the rest were not detectable in RNA sequencing with a minimum read-depth cut-off (10x). Our analysis focusing on 11 genes harbouring recurring mutations demonstrated allelic imbalance (AI) in most patients. GATA2, RUNX1, TET2, SRSF2, IDH2, PTPN11, WT1, NPM1 and CEBPA showed significant AIs. While the effect size was small in general, GATA2 exhibited the largest allelic imbalance. By pooling heterogeneous data from three independent AML cohorts with paired DNA and RNA sequencing (N = 253), we could validate the preferential transcription of GATA2-mutated alleles. Differential expression analysis of the genes with significant AI showed no significant differential gene and isoform expression for the mutated genes, between mutated and wild-type patients. In conclusion, our analyses identified AI in nine out of eleven recurrently mutated genes. AI might be a common phenomenon in AML which potentially contributes to leukaemogenesis.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Medizin > Institut für Medizinische Informationsverarbeitung, Biometrie und Epidemiologie
• Themengebiete: 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit
• ISSN: 2045-2322
• Sprache: Englisch