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Utility of Targeted Gene Sequencing to Differentiate Myeloid Malignancies from other Cytopenic Conditions

2023 Mar 22

Journal Article

DeZern, A.E.; Goll, J.B.; Lindsley, C.; Bejar, R.; Wilson, S.H.; Hebert, D.; Deeg, J.; Zhang, L.; Gore, S.D.; Baghdadi, T.Al; Maciejewski, J.P.; Liu, J.Jijun; Padron, E.; Komrokji, R.S.; Saber, W.; Abel, G.A.; Kroft, S.H.; Harrington, A.M.; Grimes, T.; Reed, H.H.Vaughn; Fulton, R.S.; Difronzo, N.L.; Gillis, N.; Sekeres, M.A.; Walter, M.J.

Blood Adv




bone marrow conditions; classifier-predicted diagnosis; cytopenia; malignancy; myelodysplastic syndromes (MDS); NHLBI

The National Heart, Lung, and Blood Institute National MDS Natural History Study (NCT02775383) is a prospective cohort study enrolling cytopenic patients with suspected myelodysplastic syndromes (MDS) to evaluate factors associated with disease. Here, we sequenced 53 genes in bone marrow samples harvested from 1,298 patients diagnosed with myeloid malignancy, including MDS and non-MDS myeloid malignancy, or alternative marrow conditions with cytopenia based on concordance between independent histopathologic reviews (local, centralized, and tertiary to adjudicate disagreements when needed). We developed a novel two-stage diagnostic classifier based on mutational profiles in 18 of 53 sequenced genes that were sufficient to best (1) predict a diagnosis of myeloid malignancy and (2) within those with a predicted myeloid malignancy, predict whether they had MDS. The classifier achieved a PPV of 0.84 and NPV of 0.8 with an AUROC of 0.85 when classifying patients as myeloid vs. no myeloid malignancy based on VAFs in 17 genes and a PPV of 0.71 and NPV of 0.64 with an AUROC of 0.73 when classifying patients as MDS vs. non-MDS malignancy based on VAFs in 10 genes. We next assessed how this approach could complement histopathology to improve diagnostic accuracy. For 99 of 139 (71%) patients (PPV of 0.83 and NPV of 0.65) with local and centralized histopathologic disagreement in myeloid vs. no myeloid malignancy, the classifier-predicted diagnosis agreed with the tertiary pathology review (considered the internal gold standard). An online version of the classifier that can be used with either VAFs or binary mutation profiles is available at

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