The genomic basis of childhood T-lineage acute lymphoblastic leukaemia.
Petri PolonenDanika Di GiacomoAnna Eames SeffernickAbdelrahman ElsayedShunsuke KimuraFrancesca BeniniLindsey E MontefioriBrent L WoodJason XuChangya ChenZhongshan ChengHaley NewmanJason R MyersIlaria IacobucciElizabeth LiJonathan H SussmanDale HedgesYawei HuiCaroline DiorioLahari UppuluriDavid FrankYiping FanYunchao ChangSoheil MeshinchiRhonda E RiesRawan ShraimAlexander LiKathrin Maria BerntMeenakshi DevidasStuart S WinterKimberly P DunsmoreHiroto InabaWilliam L CarrollNilsa C RamirezAaron H PhillipsRichard W KriwackiJun J YangTiffaney L VincentYaqi ZhaoPankaj S GhateJian WangColleen ReillyXin ZhouMathijs A SandersJunko TakitaMotohiro KatoNao TakasugiBill H ChangRichard D PressMignon L LohEvadnie RampersaudElizabeth RaetzStephen P HungerKai TanTi-Cheng ChangGang WuStanley B PoundsCharles G MullighanDavid Trent TeacheyPublished in: Nature (2024)
T-lineage acute lymphoblastic leukaemia (T-ALL) is a high-risk tumour 1 that has eluded comprehensive genomic characterization, which is partly due to the high frequency of noncoding genomic alterations that result in oncogene deregulation 2,3 . Here we report an integrated analysis of genome and transcriptome sequencing of tumour and remission samples from more than 1,300 uniformly treated children with T-ALL, coupled with epigenomic and single-cell analyses of malignant and normal T cell precursors. This approach identified 15 subtypes with distinct genomic drivers, gene expression patterns, developmental states and outcomes. Analyses of chromatin topology revealed multiple mechanisms of enhancer deregulation that involve enhancers and genes in a subtype-specific manner, thereby demonstrating widespread involvement of the noncoding genome. We show that the immunophenotypically described, high-risk entity of early T cell precursor ALL is superseded by a broader category of 'early T cell precursor-like' leukaemia. This category has a variable immunophenotype and diverse genomic alterations of a core set of genes that encode regulators of hematopoietic stem cell development. Using multivariable outcome models, we show that genetic subtypes, driver and concomitant genetic alterations independently predict treatment failure and survival. These findings provide a roadmap for the classification, risk stratification and mechanistic understanding of this disease.
Keyphrases
- genome wide
- single cell
- copy number
- gene expression
- high frequency
- dna methylation
- rna seq
- liver failure
- transcription factor
- high throughput
- machine learning
- hematopoietic stem cell
- drug induced
- rheumatoid arthritis
- systemic lupus erythematosus
- metabolic syndrome
- adipose tissue
- genome wide identification
- disease activity
- mechanical ventilation
- intensive care unit
- combination therapy
- early life