Whole Genome Sequencing Identifies Microdeletions Affecting TET2 and RUNX1 with Clinical Impact in Myeloid Malignancies

Background:

The current routine genetic work-up in hematological malignancies includes chromosome banding analysis (CBA) to detect complete or partial chromosomal deletions and fusions, and the identification of point mutations and small deletions or insertions by sequencing panels (max. length ~50 bp). Deletions of individual genes (e.g. IKZF1 in ALL) are only detected by specifically designed molecular tools. Therefore, those microdeletions might be overlooked by the current gold standard despite their clinical relevance. We established a bioinformatic pipeline to screen for microdeletions in whole genome sequencing (WGS) data of myeloid malignancies.

Aim:

(1) Screen for recurrent microdeletions in myeloid malignancies with a normal karyotype, and (2) characterize a patient specific profile of microdeletions in genes with known clinical and/or prognostic relevance.

Patients and Methods:

We analyzed 1356 cases (M/F: 778/578) of myeloid malignancies with a normal karyotype according to CBA (aCML: n=47; AML: n=251; CMML: n=165, mastocytosis: n=90; MDS: n=415, MDS/MPN-RS-T: n=69; MDS/MPN-U: n=42; MPN: n=250; PNH: n=27) using WGS. Median age was 71 [20-94] years. Amplification-free WGS was performed on the NovaSeq or HiSeq system with a median coverage of 103x (Illumina, San Diego, CA). Reads were aligned to the human reference genome (GRCh37, Ensembl annotation, Isaac aligner) and somatic copy number variant (CNV) discovery was performed with GATK (v 4.0.2.1), following best practice guidelines. Only gene overlapping CNV calls were considered for analysis (gene coordinates biomaRt (v 2.42.1), GRCh37 Ensembl).

Results:

On average, 38 genes per patient were partially or completely deleted and the size of the deletions ranged from 0.9 kb to 32 Mb (median 399 kb). The microdeletions affected a broad list of genes, but no gene was present in >5% of myeloid malignancies. As technical validation, we used 36 B-ALL samples (normal karyotype) and identified the known deletions of IKZF1 (42%); PAX5 (25%) and CDKN2A/CDKN2B (22%) with expected incidences.

We focused on a patient-by-patient analysis of genes (n=47) with known clinical relevance in myeloid malignancies. We identified deleted genes in 46 out of 1356 patients (3.4%). In aCML 13% of patients had one of the above-mentioned genes deleted (6/47), in mastocytosis only 1% (1/90). The most frequently deleted genes were TET2 (20/1356, 1.5%) and RUNX1 (9/1356, 0.7%). Other deletions also affected transcription factors (e.g. GATA2) or epigenetic regulators (e.g. DNMT3A, figure 1). No deletion of splicing factors, RAS genes or cohesion complex regulators was observed. We found only two deletions of kinases, which are predominantly affected by activating mutations (both FLT3). Instead, the deletions in 41 patients involved genes with a known loss-of-function mutation profile in myeloid malignancies. This corresponds to 89% (41/46) of patients with microdeletions or 3% (41/1356) of all analyzed patients with myeloid malignancies. Microdeletions are thus another genetic element that can lead to loss of gene activity.

Deletions and mutations are either alternative genetic mechanisms or co-operate as double hits to affect the same gene. We found additional mutations present in 18 of the 46 patients with microdeletions (39%, figure 1). The majority of these (n=14) involved TET2. TET2 mutations had a median variant allele frequency of 82% [9-100%] indicative of a mutation on the non-deleted allele. For the remaining genes (incl. RUNX1), deletions are predominantly an alternative genetic mechanism to mutations.

For validation of WGS results we applied interphase FISH and identified 6/9 RUNX1 deletions. The remaining three microdeletions were only detectable by WGS and too small to be identified by FISH.

Conclusions:

(1) WGS data unrevealed a plethora of microdeletions, which can be an alternative genetic mechanism to mutations, but are not detected with today's standard diagnostic tools.

(2) In the light of increasingly personalized therapy and diagnostics, all genetic mechanisms should be considered, which impact the function of clinically relevant genes.

(3) Bioinformatic pipelines for WGS as a potential diagnostic tool in the near future should address microdeletions in genes with relevance for patients' diagnosis, prognosis and hopefully targeted treatment.

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