bioRxivCancer BiologyPreprint
Single-Cell Sequencing Reveals Extensive Genetic Diversity Underlying Pediatric ALL Treatment Complexity
Yakun PangiD, Tamara PrietoiD, Veronica Gonzalez-PenaiD, Athena Aragon, Yuntao XiaiD, Sheng Kao, Srinivas RajagopalaniD, John ZinnoiD, Jean Quentin, Julien Laval, Dennis J. YuaniD, Nathaniel D. OmansiD, Catherine Potenski, David KleiniD, Matthew J. MacKayiD, Iwijn De VlaminckiD, John B. EastoniD, William Edward EvansiD, Dan Avi LandauiD, Charles GawadiD
- Citations
- 3
Abstract
Approximately 15-20% of children with acute lymphoblastic leukemia (pALL) are not cured despite years of treatment with more than ten chemotherapeutic agents, yet bulk sequencing reveals minimal somatic variation that could explain genetic treatment resistance. Using error-corrected bulk sequencing, and primary template-directed amplification (PTA)-enabled single-cell exome and whole-genome sequencing, we discovered much more genetic diversity in pALL. Individual leukemic cells harbor 3.7-fold more mutations (mean 3,553) than detected in bulk samples (mean 965). Many ETV6-RUNX1 patients harbor multiple independent ras-mutated clones, and we also identified convergent evolution of JAK2 mutations as well as copy number alterations. PTA-based phylogenetic analysis of over 150 single-cell genomes linked heritable phenotypes to specific genetic alterations and identified low-frequency clones harboring mutations in treatment resistance-associated genes (ITGA9, NTRK3, SULF2) that increased in frequency during treatment. These findings reveal extensive hidden genetic diversity in pALL while providing a framework for the early detection of high-risk leukemic populations.
- organism: human
- assay: scRNA-seq
- assay: whole-exome sequencing
- assay: whole-genome sequencing
- research focus: clustering
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: deep learning
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