Introduction

Molecular mutation analyses are performed in myeloid malignancies either in a stepwise procedure, i.e. one target gene after each other or are not performed at all, e.g. in low-risk MDS. A comprehensive pan-myeloid panel to simultaneously target mutations in 26 genes allows a comprehensive analysis with the perspective to detect disease defining mutations in the majority of patients.

Aims

To test the utility of a pan-myeloid panel in routine diagnostics.

Methods

We developed sensitive next-generation deep-sequencing (NGS) assays comprising in total 26 genes: ASXL1, BCOR, BRAF, CBL, DNMT3A, ETV6, EZH2, FLT3 (TKD), GATA1, GATA2, IDH1, IDH2, JAK2, KIT, KRAS, MPL, NPM1, NRAS, PHF6, RUNX1, SF3B1, SRSF2, TET2, TP53, U2AF1, and WT1. With the exception of RUNX1, which was sequenced on the 454 Life Sciences NGS platform (Branford, CT), all remainder genes were studied using a combination of a microdroplet-based assay (RainDance, Lexington, MA) and the MiSeq sequencing instrument (Illumina, San Diego, CA). The assay's turn-around time was less than 6 days, loading up to eight patients per sequencing run. In summary, 389 amplicons were designed with a median length of 206 bp (range 150-240 bp), representing a total target sequence of 78.15 kb. The sequencing library was constructed starting off 2.2 μg genomic DNA per patient, purified from isolated mononuclear cells. Using the 500 cycles sequencing-by-synthesis chemistry in median 7.644 millions of paired-end reads were generated per run. This resulted in a median coverage per gene of 7,626 reads (range 174-12,256). The lower limit of detection was set at a cut-off of 3%.

Results

Thus far, 191 prospectively collected cases have been analyzed during routine operations. In all cases the assay was successfully performed. Mutations (range 0-7) have been found in 119/191 (62.3%) cases. The major disease categories were as follows: MDS (n=76), suspected MDS (n=28), MDS/MPN (n=10), reactive bone marrow conditions (n=46), AML (n=8), CML (n=3), other conditions (n=20).

We first were interested to address the utility of the panel in MDS when the analysis was restricted to the five prognostically relevant predictors of poor overall survival according to Bejar et al. (N Engl J Med. 2011;364:2496-506), i.e. ASXL1, ETV6, EZH2, RUNX1, and TP53. In detail, 69 cases with MDS were studied and in 42.0% (29/69) of cases mutations had been detected in these five genes while 40 patients showed no mutation. Interestingly, upon extending the analysis to the remainder 21 genes, at least one more mutation was discovered in 72.5% (29/40) of these cases, thereby extending the number of cases with at least one mutation to 84.1% (58/69) of patients. Of note, in 65.5% (19/29) of these latter cases, spliceosome mutations occurred in a mutually exclusive manner (SRSF2, SF3B1, U2AF1), thus also detecting mutations conferring a favorable clinical outcome, i.e. SF3B1 alterations.

We next studied in more detail 28 cases with suspected MDS according to cytomorphology, i.e. cases with dysplastic features not sufficient to diagnose MDS. When again in a first step the five predictors of poor overall survival according to Bejar et al. were analyzed, mutations in ASXL1, ETV6, EZH2, RUNX1, and TP53 were observed in 25.0% of cases (7/28). In the group of 75.0% (21/28) of samples with no mutations according to Bejar et al., 28.6% (6/21) of cases harbored a mutation in the group of the 21 remainder genes analyzed simultaneously in the gene panel assay. Thus, in total the number of cases with at least one mutation increased to 46.4% (13/28) of patients. Of note, 6 of the 13 suspected MDS cases with mutations had a normal karyotype. In summary, with respect to correlations between these two cohorts, we observed that morphologically confirmed MDS cases (n=69) showed a higher number of mutated genes compared to “suspected MDS” cases (n=28) (1.88 vs 0.71; p<0.001).

Conclusion

A pan-myeloid screening assay using NGS allows to address 26 relevant gene mutations in myeloid malignancies with diagnostic or prognostic impact. This approach is scalable and adoptable to accommodate the inclusion of novel gene targets according to the latest evidence from the literature. Importantly, given the broad spectrum of mutations in myeloid diseases covered by such a panel, mutations can be identified in the majority of patients and enable to support a more comprehensive classification in these complex diseases.

Disclosures:

Kohlmann:MLL Munich Leukemia Laboratory: Employment. Kuznia:MLL Munich Leukemia Laboratory: Employment. Nadarajah:MLL Munich Leukemia Laboratory: Employment. Alpermann:MLL Munich Leukemia Laboratory: Employment. Weissmann:MLL Munich Leukemia Laboratory: Employment. Roller:MLL Munich Leukemia Laboratory: Employment. Albuquerque:MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Schnittger:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

Author notes

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Asterisk with author names denotes non-ASH members.

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