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Error-corrected Sequencing Strategies Enable Comprehensive Detection of Leukemic Mutations Relevant for Diagnosis and Minimal Residual Disease Monitoring

Overview
Publisher Biomed Central
Specialty Genetics
Date 2020 Mar 6
PMID 32131829
Citations 10
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Abstract

Background: Pediatric leukemias have a diverse genomic landscape associated with complex structural variants, including gene fusions, insertions and deletions, and single nucleotide variants. Routine karyotype and fluorescence in situ hybridization (FISH) techniques lack sensitivity for smaller genomic alternations. Next-generation sequencing (NGS) assays are being increasingly utilized for assessment of these various lesions. However, standard NGS lacks quantitative sensitivity for minimal residual disease (MRD) surveillance due to an inherently high error rate.

Methods: Primary bone marrow samples from pediatric leukemia (n = 32) and adult leukemia subjects (n = 5), cell line MV4-11, and an umbilical cord sample were utilized for this study. Samples were sequenced using molecular barcoding with targeted DNA and RNA library enrichment techniques based on anchored multiplexed PCR (AMP®) technology, amplicon based error-corrected sequencing (ECS) or a human cancer transcriptome assay. Computational analyses were performed to quantitatively assess limit of detection (LOD) for various DNA and RNA lesions, which could be systematically used for MRD assays.

Results: Matched leukemia patient samples were analyzed at three time points; diagnosis, end of induction (EOI), and relapse. Similar to flow cytometry for ALL MRD, the LOD for point mutations by these sequencing strategies was ≥0.001. For DNA structural variants, FLT3 internal tandem duplication (ITD) positive cell line and patient samples showed a LOD of ≥0.001 in addition to previously unknown copy number losses in leukemia genes. ECS in RNA identified multiple novel gene fusions, including a SPANT-ABL gene fusion in an ALL patient, which could have been used to alter therapy. Collectively, ECS for RNA demonstrated a quantitative and complex landscape of RNA molecules with 12% of the molecules representing gene fusions, 12% exon duplications, 8% exon deletions, and 68% with retained introns. Droplet digital PCR validation of ECS-RNA confirmed results to single mRNA molecule quantities.

Conclusions: Collectively, these assays enable a highly sensitive, comprehensive, and simultaneous analysis of various clonal leukemic mutations, which can be tracked across disease states (diagnosis, EOI, and relapse) with a high degree of sensitivity. The approaches and results presented here highlight the ability to use NGS for MRD tracking.

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References
1.
Heinaniemi M, Vuorenmaa T, Teppo S, Kaikkonen M, Bouvy-Liivrand M, Mehtonen J . Transcription-coupled genetic instability marks acute lymphoblastic leukemia structural variation hotspots. Elife. 2016; 5. PMC: 4951197. DOI: 10.7554/eLife.13087. View

2.
Young A, Wong T, Hughes A, Heath S, Ley T, Link D . Quantifying ultra-rare pre-leukemic clones via targeted error-corrected sequencing. Leukemia. 2015; 29(7):1608-11. PMC: 4497921. DOI: 10.1038/leu.2015.17. View

3.
Jongen-Lavrencic M, Grob T, Hanekamp D, Kavelaars F, Al Hinai A, Zeilemaker A . Molecular Minimal Residual Disease in Acute Myeloid Leukemia. N Engl J Med. 2018; 378(13):1189-1199. DOI: 10.1056/NEJMoa1716863. View

4.
Young A, Challen G, Birmann B, Druley T . Clonal haematopoiesis harbouring AML-associated mutations is ubiquitous in healthy adults. Nat Commun. 2016; 7:12484. PMC: 4996934. DOI: 10.1038/ncomms12484. View

5.
Churpek J, Pyrtel K, Kanchi K, Shao J, Koboldt D, Miller C . Genomic analysis of germ line and somatic variants in familial myelodysplasia/acute myeloid leukemia. Blood. 2015; 126(22):2484-90. PMC: 4661171. DOI: 10.1182/blood-2015-04-641100. View