Introduction: Germline mutations in CEBPA, ETV6, RUNX1, and GATA2 have been reported to be associated with predisposition to hematologic malignancies. Next Generation Sequencing (NGS), used to identify somatic mutations to aid in targeted therapies, may incidentally uncover inherited germline mutations. Recognizing familial predisposition is important as it may impact management and surveillance. We assessed the prevalence of potentially clinically significant germline mutations detected incidentally by NGS in samples from patients investigated for myeloid disorders.

Methods: NGS was performed to identify somatic mutations in 54 genes, on 6100 consecutive bone marrow aspirates or peripheral blood specimens between January 2014 and mid-2017. The average depth of sequencing was 10,000x. DNA was extracted using the QIAamp DNA Mini Kit and subjected to the TruSight Myeloid panel (Illumina, San Diego, CA). Most (92%) of the common dbSNP variants (>10% allele frequency in dbSNP) were found between 45-55% variant allele frequency (VAF) or 98-100% VAF for hetero- and homozygous states. This suggests that common SNPs are mostly found between those frequencies; hence, alleles with these frequencies were defined as candidate germline variants. However, to further enrich for germline variants, we only analyzed those cases with at least one other somatic variant with VAF of 5-40%; the rational being that it is unlikely that a sample would have two true independent somatic mutation events in different subclones. Following this enrichment process, 2951 specimens were eligible for further analysis for potential germline mutations. The ClinVar and dbSNP databases were used to assess allele frequencies and clinical significance.

Results: In 2951 of 6100 specimens, we reported at least one somatic mutation with a variant allele frequency in the range of 5-40%. A total of 5322 variants were identified in this subset of specimens. Among the candidate germline mutations in 4 genes implicated in myeloid neoplasm predisposition, we identified 93 unique putative loss of function variants that met our germline criteria. Nine of these mutations were identified in more than 3 cases and more than half of these were represented in ClinVar as germline loss of function variants. One of them, RUNX1 : p.Arg201Gln, identified in 5 patients, is described as a germline pathogenic variant. In contrast, the other 84 variants identified in the 4 genes were rare (observed in 1 or 2 cases) and few (7/84) had been characterized in dbSNP. Most loss of function germline variants are unique and rare with few hotspots, which is consistent with our data.

Analysis of germline mutations in genes, which have not yet been implicated in predisposition to myeloid neoplasm, revealed 4858 candidate mutations in 23 genes: 15.4% (750/4858) were unique, 13.6% (102/750) were more common (> 3 cases), while most (86.4%; 648/750) were found in only 1 or 2 cases. Some of the more common variants were identified in ClinVar as pathogenic germline variants, including IDH2 (p.Arg140Gln; MIM: 613657), identified in 84 cases, and a TP53 loss of function mutation (p.Pro72Arg) identified in 424 cases.

Conclusion: Germline mutations, GATA2, RUNX1, CEBPA, and ETV6, known to predispose to myeloid malignancies, may be identified incidentally during testing for somatic mutations in myeloid malignancies.

In addition, if the NGS panel includes genes other than those known to predispose towards myeloid malignancies, pathogenic variants of wide ranging clinical implication may be uncovered, as observed in the cases with mutation in IDH2 or TP53 . Although the specific mutation observed in IDH2 has been identified most often as a somatic mutation, it has been reported to be inherited in one instance. Inheriting this allele can confer D-2-hydroxyglutaric aciduria-2 (D2HGA2). The TP53 mutation observed is known to be involved in other hereditary cancers (e.g. Li-Fraumeni syndrome) and could affect the recommended therapy of antineoplastic agents.

Rare incidentally identified potential germline mutations remain a challenge as their clinical significance may be unknown. These mutations require additional investigation to determine if they could contribute to clinical management.


Funari: NeoGenomics: Employment. Thangavelu: NeoGenomics: Employment. Ma: NeoGenomics: Employment. De Dios: NeoGenomics: Employment. Agersborg: NeoGenomics: Employment. Blocker: NeoGenomics: Employment. Albitar: NeoGenomics: Employment.

Author notes


Asterisk with author names denotes non-ASH members.

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