Impact of Genetic Ancestry on T-cell Acute Lymphoblastic Leukemia Outcomes.
David Trent TeacheyHaley NewmanShawn LeePetri PolonenRawan ShraimYimei LiHongyan LiuRichard AplencShovik BandyopadhyayChangya ChenZhiguo ChenMeenakshi DevidasCaroline DiorioKimberly DunsmoreOmar ElghawyAmira ElhachimiTori FullerSumit GuptaJunior HallAndrew HughesStephen HungerMignon L LohZachary MartinezMichael McCoyCassidy MullenStanley B PoundsElizabeth RaetzTheresa RyanAnna SeffernickGongping ShiJonathan H SussmanKai TanLahari UppuluriTiffaney L VincentRuth Wang'onduLena WinestoneStuart WinterBrent WoodGang WuJason XuWenjian YangCharles G MullighanJun J YangKira BonaPublished in: Research square (2024)
The influence of genetic ancestry on biology, survival outcomes, and risk stratification in T-cell Acute Lymphoblastic Leukemia (T-ALL) has not been explored. Genetic ancestry was genomically-derived from DNA-based single nucleotide polymorphisms in children and young adults with T-ALL treated on Children's Oncology Group trial AALL0434. We determined associations of genetic ancestry, leukemia genomics and survival outcomes; co-primary outcomes were genomic subtype, pathway alteration, overall survival (OS), and event-free survival (EFS). Among 1309 patients, T-ALL molecular subtypes varied significantly by genetic ancestry, including increased frequency of genomically defined ETP-like, MLLT10, and BCL11B-activated subtypes in patients of African ancestry. In multivariable Cox models adjusting for high-risk subtype and pathways, patients of Admixed American ancestry had superior 5-year EFS/OS compared with European; EFS/OS for patients of African and European ancestry were similar. The prognostic value of five commonly altered T-ALL genes varied by ancestry - including NOTCH1 , which was associated with superior OS for patients of European and Admixed American ancestry but non-prognostic among patients of African ancestry. Furthermore, a published five-gene risk classifier accurately risk stratified patients of European ancestry, but misclassified patients of African ancestry. We developed a penalized Cox model which successfully risk stratified patients across ancestries. Overall, 80% of patients had a genomic alteration in at least one gene with differential prognostic impact by genetic ancestry. T-ALL genomics and prognostic associations of genomic alterations vary by genetic ancestry. These data demonstrate the importance of incorporating genetic ancestry into analyses of tumor biology for risk classification algorithms.
Keyphrases
- end stage renal disease
- ejection fraction
- chronic kidney disease
- acute lymphoblastic leukemia
- newly diagnosed
- copy number
- genome wide
- prognostic factors
- type diabetes
- randomized controlled trial
- peritoneal dialysis
- systematic review
- young adults
- transcription factor
- dna methylation
- deep learning
- single cell
- gene expression
- palliative care
- acute myeloid leukemia
- study protocol
- data analysis
- placebo controlled