NGS-Based Copy Number Analysis in 1,185 Patients with Myeloid Neoplasms

Background

Copy number alteration (CNA) is a hallmark of cancer genomes and has been implicated in the development of human cancers, including myeloid neoplasms. We developed a novel, next-generation sequencing-based platform for highly sensitive detection of CNAs with a single exon resolution, which was applied to sequencing data from 1,185 patients to delineate a comprehensive landscape of CNAs in myeloid neoplasms.

Materials and Methods

We enrolled 1,185 patients with different myeloid neoplasms including myelodysplastic syndromes (n = 607), myelodysplastic/myeloproliferative neoplasms (n = 80), de novo acute myeloid leukemia (AML) (n = 136), secondary AML (sAML) (n = 226), and unknown myeloid malignancies (n = 136). Whole-exome sequencing (WES) was performed on samples from 260 patients, while samples from 925 patients including pre-transplantation peripheral blood samples provided by Japan Marrow Donor Program were subjected to targeted deep sequencing. Eight cases were serially evaluated before and after progression tosAML. RNA baits for targeted deep sequencing were designed to cover 69 driver genes in myeloid neoplasms and 1,158 single-nucleotide polymorphisms (SNPs)for assessment of allelic imbalance. In WES, allelic imbalance was examined using allele frequencies of SNPs within coding regions. Focal CNAs were defined as CNAs whose lengths relative to the chromosomal arms were below 10%.

Results

To obtain a landscape of CNAs in coding regions, a comprehensive copy number analysis was performed on 260 patients including 136 with de novo AML and 124 with myeloid neoplasms with myelodysplasia, all of whom were studied by WES. A total of 755 CNAs (502 deletions and 253 amplifications) were identified, where 52% of the patients harbored at least one alteration. Using GISTIC 2.0 algorism, we identified 21 significantly altered regions involving known or putative driver genes (Figure 1): losses of 7q22.1 (CUX1), 12p13.2 (ETV6), 13q14 (RB1),17p13.1(TP53), and 17q11.2 (NF1), and gains of 3q26-27 (EVI1), 8q24.21 (MYC), 11q13.5-14.1(PAK1), 11q23.3 (MLL),11q24-25 (ETS1), 13q12.2 (FLT3),21q22.2 (ETS2 and ERG). We next compared the frequencies of CNAs between de novo AML and myeloid neoplasms with myelodysplasia. While chromosomes 7, 12, and 17 were commonly affected, deletions of 13q14 were significantly enriched in myeloid neoplasms with myelodysplasia (Odds ratio [OR]: 5.07, P = 0.040), and amplifications of 11q24-25 (OR: 5.54, P = 0.028), and 21q22.2 (OR: 6.10, P = 0.020) in de novo AML, suggesting a specific role of these events in each disease entity. In addition, serial sampling revealed trisomy8, deletions of 7q and 12p were recurrently acquired during leukemic transformation in patients withmyelodysplasia. Taken together, many driver genes in myeloid neoplasms were frequently targeted by CNAs includingmicrodeletions.

Based on these finding, we sought to obtain a more detailed landscape of CNAs in a larger cohort. We combined copy number profiles of patients studied by targeted deep sequencing and those by WES. Of total, 1,691 CNAs (1,096 deletions and 595 amplifications) were detected, where 39% of the cases harbored at least one alteration. Microdeletionsor focal amplifications were frequently found in the significantly altered regions revealed by WES: microdeletionsof ETV6 (n = 10), NF1 (n = 8), CUX1 (n = 5), TP53 (n = 5), and amplifications of FLT3 (n = 7), ETS1 (n = 3), ETS2 (n = 3), and ERG (n = 3), validating the result obtained from a cohort studied by WES. We also identified known driver genes in myeloid neoplasms were recurrently affected with focal CNAs: microdeletions of RUNX1, BCOR, ASXL2, DNMT3A, and ZRSR2, and amplifications of GNAS, RIT1, CSF3R, and BCL11A. Among them, DNMT3A and ASXL2, located within 500 kb in chromosome 2, tended to be co-deleted (3 out of 4 cases). Focal deletions of TP53 were often affected with homozygous deletions or were accompanied by gene mutations, implying bi-allelic inactivation. High amplifications were also observed in regions including ETS1, MLL, FLT3, MYC, and PAK1, which suggest a critical role in the pathogenesis of myeloid malignancy.

Conclusion

We obtained the landscape of CNAs in myeloid neoplasms based on the sequencing data of 1,185 patients. Collectively, our results indicated that CNAs targeted a specific set genes including well-known drivers of myeloid malignancies, indicating a critical role inleukemogenesis.

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