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. 2014 Feb;28(2):241-7.
doi: 10.1038/leu.2013.336. Epub 2013 Nov 13.

Landscape of genetic lesions in 944 patients with myelodysplastic syndromes

T Haferlach  1 , Y Nagata  2 , V Grossmann  1 , Y Okuno  3 , U Bacher  1 , G Nagae  4 , S Schnittger  1 , M Sanada  2 , A Kon  2 , T Alpermann  1 , K Yoshida  2 , A Roller  1 , N Nadarajah  1 , Y Shiraishi  5 , Y Shiozawa  2 , K Chiba  5 , H Tanaka  6 , H P Koeffler  7 , H-U Klein  8 , M Dugas  8 , H Aburatani  4 , A Kohlmann  1 , S Miyano  9 , C Haferlach  1 , W Kern  1 , S Ogawa  2
Affiliations
Free PMC article

Landscape of genetic lesions in 944 patients with myelodysplastic syndromes

T Haferlach et al. Leukemia. 2014 Feb.
Free PMC article

Abstract

High-throughput DNA sequencing significantly contributed to diagnosis and prognostication in patients with myelodysplastic syndromes (MDS). We determined the biological and prognostic significance of genetic aberrations in MDS. In total, 944 patients with various MDS subtypes were screened for known/putative mutations/deletions in 104 genes using targeted deep sequencing and array-based genomic hybridization. In total, 845/944 patients (89.5%) harbored at least one mutation (median, 3 per patient; range, 0-12). Forty-seven genes were significantly mutated with TET2, SF3B1, ASXL1, SRSF2, DNMT3A, and RUNX1 mutated in >10% of cases. Many mutations were associated with higher risk groups and/or blast elevation. Survival was investigated in 875 patients. By univariate analysis, 25/48 genes (resulting from 47 genes tested significantly plus PRPF8) affected survival (P<0.05). The status of 14 genes combined with conventional factors revealed a novel prognostic model ('Model-1') separating patients into four risk groups ('low', 'intermediate', 'high', 'very high risk') with 3-year survival of 95.2, 69.3, 32.8, and 5.3% (P<0.001). Subsequently, a 'gene-only model' ('Model-2') was constructed based on 14 genes also yielding four significant risk groups (P<0.001). Both models were reproducible in the validation cohort (n=175 patients; P<0.001 each). Thus, large-scale genetic and molecular profiling of multiple target genes is invaluable for subclassification and prognostication in MDS patients.

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Figures

Figure 1
Figure 1
Significantly mutated genes in MDS. (a) Frequency of mutations in 47 significantly mutated genes in 944 cases with different WHO subtypes, which are shown in indicated colors. (b) Frequency of gene mutations involved in common functional pathways, which are defined in Supplementary Table S3. (c) Number of gene mutations detected in different MDS subtypes. (d) Distribution of mutations/deletions of significantly mutated genes in 944 MDS cases.
Figure 2
Figure 2
Comparison of mutation loads between major gene targets in MDS. (a) Correlations between major genetic lesions, where the correlation coefficients are indicated by a color gradient and show diagonal plots of variant allele frequencies (VAFs) between ASXL1 and U2AF1 mutations (b) and between mutations in RAS pathway genes (CBL, KRAS, NF1, NRAS and PTPN11) and DNA methylation-related genes (TET2, IDH1/2 and DNMT3A) (c), in which copy number-adjusted VAF values between indicated mutations or mutations of indicated functional pathways were compared using paired T-tests. Comparison was made exhaustively between all possible combinations of commonly mutated genes (>2.5% of mutation rates) (d) or gene pathways (e) with adjustment for multiple testing. Significance (q-values) and difference (relative difference in VAFs) is indicated by the size of circles and color gradient, as indicated, respectively.
Figure 3
Figure 3
Illustration of hazard ratios for Model-1 and Model-2. Hazard ratios (HRs, given in numbers) as well as logHR and their 95% confidential intervals (given as chart) for parameters used for Model-1 including clinical and genetic variables (a) and for Model-2 including only genetic variables (referring to the training cohort) (b) are plotted. For a, baseline level for the analysis was the respective IPSS-R risk category with the least risk score (hemoglobin: ⩾10 g/dl, platelets score: ⩾100 × 109/l, blast score: ⩽2%, cytogenetic score very good).
Figure 4
Figure 4
Development of a novel prognostic risk classification. (a) Kaplan–Meier estimates of OS in months (m) for four groups according to Model-1 in the training cohort. Three-year OS for low, intermediate, high and very high-risk groups amounts to 95.2, 69.3, 32.8 and 5.3%, respectively. (b) Kaplan–Meier estimates of OS for four groups according to Model-2 in the training cohort. Three-year OS for low, intermediate, high and very high-risk groups amounts to 83.3, 66.4, 39.7 and 9.5%, respectively. (c) Kaplan–Meier estimates of OS for five groups according to IPSS-R in the training cohort. Three-year OS for very low, low, intermediate, high and very high-risk groups amounts to 88.2, 73.9, 51.9, 45.3 and 19.6%, respectively. (d) Kaplan–Meier estimates of OS for four groups according to Model-1 in the validation cohort. Three-year OS for low, intermediate, high and very high-risk groups amounts to 88.3, 84.4, 55.7 and 22.8%, respectively. (e) Kaplan–Meier estimates of OS for four groups according to Model-2 in the validation cohort. Three-year OS for low, intermediate, high and very high-risk groups amounts to 83.3, 77.0, 64.1 and 33.3%, respectively. (f) Kaplan–Meier estimates of OS for five groups according to IPSS-R in the validation cohort. Three-year OS was 83.3, 93.7, 59.3 and 57.1% for the very low, low, intermediate and high-risk groups. For the very high-risk group, the median OS was 9.2 months, as 3-year OS was not applicable.
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