ALBERT

Description: Key Points The majority of mutations are found in genes that have low or no detectable biological expression. Mutated genes often show differential allelic expression in multiple myeloma patient samples.

Description: Multiple Myeloma (MM) is a heterogeneous disease but the hallmark genetic changes involve large numbers of genomic rearrangements. Recent studies have focused on attempts to identify individual driver mutations that might provide both prognostic information and unique therapeutic targets. Whole genome and exome sequencing of increasingly large numbers of patient samples have identified a number of commonly mutated genes in MM patients. However, none of these mutations are found in more than one quarter of patients and most are found in less than 10% of samples sequenced. We recently reported a large cohort of MM exome sequences involving 84 samples from 67 patients (Nat Commun. 2014;5:2997). We defined a diverse set of gene mutations with significant heterogeneity across our cohort with a median of 52 (range 21-488) mutations identified per sample. Although computational approaches can be used to prioritize mutations that are expected to alter protein structure and function, it is more challenging to determine which mutations are likely to be clinically meaningful. As a first step towards that understanding, here we report the frequency of expression of mutant alleles in Multiple Myeloma. In this study we report RNA-seq (100 million paired end reads on Illumina HiSeq) data on 14 samples from 10 MM patients for which we have previously performed exome sequencing and correlate allele-specific expression to the DNA mutant allele frequency. We find that a minority, average 27% (range 11-48%), of previously identified DNA mutations are expressed at detectable levels in MM patients. We also compared the allele frequency found in the RNA-seq to that from our exome sequencing to identify genes that demonstrate differential allelic expression and show that this is a common phenomenon in MM patients. We identified 42 such mutations in our analysis supported by at least 10 RNA-seq reads that showed a significant difference as determined by Bayesian hypothesis testing. For instance, the CCND1 mutant allele is expressed at a higher level than would be predicted based on exome-seq frequencies. Another gene showing a similar pattern of increased expression of the mutant allele in one patient was PARP4 (87% in RNA-seq vs 49% in exome-seq). Conversely, the mutant allele frequency of EIF1AX was lower than would be expected suggesting that the mutant allele may be suppressed in our patient (15% in RNA-seq vs 67% in exome-seq). Moreover, among a subset of genes previously identified as recurrently mutated within our patient samples we see that 8/11 (73%) express the mutant allele, providing further evidence that these genes may in fact be important in disease pathogenesis. Therefore, while a large number of mutations have been described in MM, only a small fraction of the mutant alleles have detectable expression and are likely to be biologically relevant. Unbalanced allelic expression of mutant alleles appears to be a relatively common occurrence in MM patients and may help explain why patients with the same identified mutation do not always behave in a similar fashion. This analysis for the first time highlights the important issue that DNA-based reporting of mutations may have significant limitations. It will be important in the future to study expression of mutant alleles in order to understand the biology, generate prognostic models and develop targeted therapies. Disclosures No relevant conflicts of interest to declare.

Description: Oncogenic mutations confer on cells the ability to propagate indefinitely, but whether oncogenes alter the cell fate of these cells is unknown. Here, we show that the transcriptional regulator PRDM16s causes oncogenic fate conversion by transforming cells fated to form platelets and erythrocytes into myeloid leukemia stem cells (LSCs). Prdm16s expression in megakaryocyte-erythroid progenitors (MEPs), which normally lack the potential to generate granulomonocytic cells, caused AML by converting MEPs into LSCs. Prdm16s blocked megakaryocytic/erythroid potential by interacting with super enhancers and activating myeloid master regulators, including PU.1. A CRISPR dropout screen confirmed that PU.1 is required for Prdm16s-induced leukemia. Ablating PU.1 attenuated leukemogenesis and reinstated the megakaryocytic/erythroid potential of leukemic MEPs in mouse models and human AML with PRDM16 rearrangement. Thus, oncogenic PRDM16s expression gives MEPs an LSC fate by activating myeloid gene regulatory networks.

Description: Introduction Increased complexity of sub-clonal architecture has been associated with poor outcome in AML (Papaemmanuil et al. NEJM 2016). Currently, assessment of intra-tumor genetic heterogeneity is performed with next-generation sequencing (NGS) using bulk tumor samples and relies on the variance of variant allele frequency among the individual mutations. However, this analysis is inherently confounded by the tumor purity and zygosity of the mutations. To overcome these limitations, we recently developed a high-throughput single-cell DNA sequencing platform using droplet microfluidics (Mission Bio Inc.) and showed the feasibility of genotyping primary AML samples at single-cell resolution (Pellegrino et al. Genome Research 2018). Here we used this novel platform in a large cohort of AML samples to characterize the clonal heterogeneity of AML and its evolution at relapse. Methods In total, 76 bone marrow (BM) samples from 68 AML patients (pts) were single-cell genotyped using the Mission Bio platform. In order to avoid allelic imbalance, most of the samples (66/76, 87%) were obtained from normal karyotype (NK) AML pts. The platform covered 40 amplicons in 19 recurrently mutated AML genes (median 31x coverage/amplicon/cell [IQR 22-41]). Fastq files were processed using the proprietary pipeline for adapter trimming, sequence alignment, barcode demultiplexing, and genotype and variant calling. Loom files were loaded to Tapestri Insights software for variant filtering. As a reference, all samples were concurrently sequenced by the conventional bulk NGS using targeted capture sequencing (N=64) or whole exome sequencing (N=12). An average allele drop-out (ADO) rate was inferred by the genotype of known single nucleotide polymorphisms that were incorporated into the platform. Results In total, 333,731 cells were genotyped from 76 AML samples (median 4,423 cells/sample [IQR 2,801-5,844]). The single-cell DNA sequencing detected 208 driver mutations in 76 samples with median 3 mutations per sample (IQR: 2-3). Most commonly detected mutations were NPM1 (N = 28, 13%), followed by DNMT3A (N = 24, 12%), SRSF2 (N = 24, 12%), FLT3 (N = 22, 11%), and IDH2 (N = 21, 10%), which is in accordance with the genetic landscape for NK AML. All mutations detected by the single-cell sequencing were also confirmed by the bulk NGS. The median ADO rate was 8.5% (IQR 6.8-10.4). We detected median 5 [IQR 4-8] sub-clones per sample by the single-cell sequencing. The platform unambiguously detected co-occurrence and mutual exclusivity among the driver mutations at a single-cell level. For instance, the single-cell sequencing of the samples carrying NRAS/KRAS, double NRAS, double RUNX1, IDH1/IDH2, FLT3-ITD/FLT3-TKD, or NRAS/PTPN11 mutations showed that these two mutations in the same molecular pathway were in different cellular population. In contrast, the platform also detected co-occurrence of multiple mutations in a single-cell. For example, we detected a single cell population with a clear co-occurrence of DNMT3A,FLT3-ITD, and NPM1, the most commonly co-occurring mutations in AML. Computational analysis of the single-cell genotype data by the stochastic search algorithm generated phylogenetic trees of the driver mutations in AML. DNMT3A, IDH1, IDH2, and U2AF1 were frequently detected as a trunk mutation, while mutations in FLT3, NRAS, and NPM1 were frequently detected as branch mutations. Analysis of 14 baseline and relapse paired samples revealed the remodeling of clonal architecture at relapse in 7 pts. Relapsed samples tended to have simpler clonal architecture with less sub-clones compared to the baseline (7 vs. 4, P = 0.169), suggesting the clonal selection process during the therapy. In 54 pts who were previously untreated and had single-cell genotype information on baseline BM, the pts with ≥ 10 sub-clones had significantly worse overall survival than pts with 〈 10 sub-clones (2-year survival 17% vs. 43%, P = 0.0468). Conclusion The high-throughput single-cell DNA sequencing of 76 AML samples generated an atlas of driver mutations in 333,731 AML cells. The platform uncovered detailed evolutionary history of driver mutations in AML and unambiguously visualized co-occurrence and mutual exclusivity of driver mutations at a single-cell level, features that are not observable with conventional bulk NGS. Our data also suggest the prognostic implication of intra-tumor heterogeneity in AML. Disclosures Durruthy-Durruthy: Mission Bio, Inc.: Employment, Equity Ownership. Parikh:Mission Bio, Inc.: Employment. DiNardo:Agios: Consultancy; Bayer: Honoraria; Karyopharm: Honoraria; Medimmune: Honoraria; Celgene: Honoraria; Abbvie: Honoraria. Ravandi:Bristol-Myers Squibb: Research Funding; Jazz: Honoraria; Astellas Pharmaceuticals: Consultancy, Honoraria; Sunesis: Honoraria; Xencor: Research Funding; Sunesis: Honoraria; Seattle Genetics: Research Funding; Abbvie: Research Funding; Abbvie: Research Funding; Xencor: Research Funding; Astellas Pharmaceuticals: Consultancy, Honoraria; Seattle Genetics: Research Funding; Jazz: Honoraria; Amgen: Honoraria, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Research Funding; Orsenix: Honoraria; Orsenix: Honoraria; Amgen: Honoraria, Research Funding, Speakers Bureau; Macrogenix: Honoraria, Research Funding; Macrogenix: Honoraria, Research Funding. Jabbour:Abbvie: Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Research Funding; Takeda: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding. Andreeff:United Therapeutics: Patents & Royalties: GD2 inhibition in breast cancer ; SentiBio: Equity Ownership; Oncoceutics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; SentiBio: Equity Ownership; Reata: Equity Ownership; Amgen: Consultancy, Research Funding; Daiichi-Sankyo: Consultancy, Patents & Royalties: MDM2 inhibitor activity patent, Research Funding; Reata: Equity Ownership; Jazz Pharma: Consultancy; Eutropics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Jazz Pharma: Consultancy; Eutropics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy; Oncolyze: Equity Ownership; Oncoceutics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; United Therapeutics: Patents & Royalties: GD2 inhibition in breast cancer ; Daiichi-Sankyo: Consultancy, Patents & Royalties: MDM2 inhibitor activity patent, Research Funding; Astra Zeneca: Research Funding; Amgen: Consultancy, Research Funding; Oncolyze: Equity Ownership; Celgene: Consultancy; Aptose: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Aptose: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Research Funding. Cortes:Astellas Pharma: Consultancy, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Arog: Research Funding; Pfizer: Consultancy, Research Funding. Konopleva:Stemline Therapeutics: Research Funding. Eastburn:Mission Bio, Inc.: Employment, Equity Ownership.

Description: Background Clinical outcomes of patients with Philadelphia chromosome-positive B-cell acute lymphoblastic leukemia (Ph+ B-ALL) have improved with combination of tyrosine kinase inhibitors (TKIs) with intensive chemotherapies. However, patients with IKZF1 deletion (del) has been shown to manifest poor prognosis when treated with imatinib-based regimens (Martinelli et al. J Clin Oncol. 2009, Veer et al. Blood 2014). Prognostic significance of IKZF1 del in the context of more potent TKIs, such as dasatinib or ponatinib, is not known. Methods We studied 62 patients with previously untreated Ph+ B-ALL who were part of the phase II clinical trials of Hyper-CVAD alternating with high-dose methotrexate and cytarabine (Hyper-CVAD/MA) plus dasatinib (N = 27) or Hyper-CVAD/MA plus ponatinib (N = 35). Details of the treatment protocols have been previously published elsewhere (Ravandi et al. Blood 2010 and Jabbour et al. Lancet Haematol 2018). DNA from diagnostic bone marrow samples were analyzed by genome-wide SNP arrays using Infinium Omni2.5 array (Illumina, N = 39), Infinium CytoSNP-850K array (Illumina, N = 20), or by whole exome sequencing (N= 3) for copy number analyses. Somatic point mutations were also detected by Agilent's SureSelect Custom 295 gene panel with median 500x depth. Results The baseline clinical characteristics of the 62 Ph+ B-ALL patients are described in Table 1. There were no significant differences in major clinical features between dasatinib- and ponatinib-treated groups. Overall, IKZF1 del, CDKN2A del, and PAX5 del were detected in 30 (48.3%), 16 (25.8%), and 9 (14.5%) patients, respectively. Frequency of IKZF1 and CDKN2A deletions were comparable between dasatinib- and ponatinib-treated groups, but PAX5 deletions were more frequently detected in dasatinib-treated group (dasatinib vs. ponatinib, 25.9% vs. 5.7%, P = 0.034) (Table 1). Somatic point mutations were rare in Ph+ B-ALL and 20 (32.3%) of the patients were found to have at least one point mutations. DNMT3A (N = 4) was most frequently detected among the cohort followed by CHEK2 (N = 2), EP300 (N = 2), SETD2 (N = 2), and TET2 (N = 2). Irrespective of the treatment regimen, 100% of the patients attained complete remission (CR) after 1 cycle of therapy. 29 (48.3%) and 41 (68.3%) patients attained CR with negative minimal residual disease (MRD) with RT-PCR at 1 month and 3 months, respectively. Patients with IKZF1 del had significantly lower chance of attaining CR with negative MRD compared to IKZF1 wild type (WT) patients at 1 month (IKZF1 del vs. WT, 26.7% vs. 70.0% , P = 0.002). However, at 3 months, no difference of complete molecular response (CMR) was observed (IKZF1 del vs. WT, 71.0% vs. 65.5%, P = 0.783). Other deletions or point mutations did not affect MRD negative status. With the median follow up duration of 59 months (95% confidence interval [CI]: 54-67), the median overall survival (OS) of the entire cohort was 80 months (95% CI: 76-not reached) and the 5-year OS rate of the entire cohort was 70.3% (95% CI: 57.1-80.2). In the entire cohort, patients with IKZF1 del had a strong trend of poor OS compared to IKZF1 WT patients (IKZF1 del vs. WT, median survival: 76 months vs. not reached, 5-year OS: 57.8% vs. 81.2%, P = 0.082), while PAX5 and CDKN2A deletion status did not affect OS. Among the dasatinib-treated subgroup, IKZF1, PAX5, and CDKN2A del status did not affect OS. Among the patients with IKZF1 del, ponatinib-treated subgroup had better prognosis than dasatinib-treated subgroup (dasatinib vs. ponatinib, median survival: not reached vs. 80 months, 5-year OS: 40.0% vs. 77.2%, P = 0.0337) [Table 2]. In ponatinib-treated subgroup, CDKN2A del was associated with significantly worse OS (CDKN2A del vs. WT, median survival: both not reached, 5-year OS: 66.7% vs. 96.0%, P = 0.0259), while IKZF1 del was associated with a trend of worse OS (IKZF1 del vs. WT, median survival: both not reached, 5-year OS: 77.0% vs. 95.0%, P = 0.161). One of limitations of this study is the number of cases is small. Discussion In the patients with Ph+ B-ALL treated with Hyper-CVAD/MA plus dasatinib or ponatinib, IKZF1 del did not affect CMR at 3 months while it was associated with a trend toward worse OS. In the patients harboring IKZF1 del, ponatinib-treated subgroup had better prognosis than dasatinib-treated subgroup. Further investigation is needed to determine the prognostic significance of IKZF1 del in individual treatment subgroup. Disclosures Short: AstraZeneca: Consultancy; Amgen: Honoraria; Takeda Oncology: Consultancy, Research Funding. Kantarjian:Novartis: Research Funding; Pfizer: Honoraria, Research Funding; Jazz Pharma: Research Funding; AbbVie: Honoraria, Research Funding; Daiichi-Sankyo: Research Funding; Amgen: Honoraria, Research Funding; Cyclacel: Research Funding; BMS: Research Funding; Astex: Research Funding; Takeda: Honoraria; Ariad: Research Funding; Immunogen: Research Funding; Agios: Honoraria, Research Funding; Actinium: Honoraria, Membership on an entity's Board of Directors or advisory committees. Jain:Pfizer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZeneca: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; ADC Therapeutics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen Pharmaceuticals, Inc.: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics, an AbbVie company: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Cellectis: Research Funding; Servier: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Incyte: Research Funding; Verastem: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Precision Biosciences: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnologies: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Research Funding. Sasaki:Pfizer: Consultancy; Otsuka: Honoraria. Ravandi:Xencor: Consultancy, Research Funding; Macrogenix: Consultancy, Research Funding; Cyclacel LTD: Research Funding; Selvita: Research Funding; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Menarini Ricerche: Research Funding. Konopleva:Genentech: Honoraria, Research Funding; F. Hoffman La-Roche: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria; Calithera: Research Funding; Kisoji: Consultancy, Honoraria; Ascentage: Research Funding; Astra Zeneca: Research Funding; Agios: Research Funding; Cellectis: Research Funding; AbbVie: Consultancy, Honoraria, Research Funding; Eli Lilly: Research Funding; Forty-Seven: Consultancy, Honoraria; Stemline Therapeutics: Consultancy, Honoraria, Research Funding; Ablynx: Research Funding; Reata Pharmaceuticals: Equity Ownership, Patents & Royalties. Garcia-Manero:Onconova: Research Funding; H3 Biomedicine: Research Funding; Merck: Research Funding; Helsinn: Research Funding; Amphivena: Consultancy, Research Funding; Novartis: Research Funding; AbbVie: Research Funding; Celgene: Consultancy, Research Funding; Astex: Consultancy, Research Funding. Takahashi:Symbio Pharmaceuticals: Consultancy. Jabbour:Cyclacel LTD: Research Funding; Pfizer: Consultancy, Research Funding; AbbVie: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Adaptive: Consultancy, Research Funding.

Description: Abstract 3 Myelodysplastic syndromes (MDS) are myeloid neoplasms characterized by dysplasia in one or more cell lines, ineffective hematopoiesis, and variable risk of progression to acute myeloid leukemia (AML). As any other neoplasm, MDS is expected to be driven by mutation, and its clonal evolution is likely a multistep process in which several genetic events occur. Somatic mutations of TET2 have been found in about 25% of MDS patients, while additional mutant genes (including ASXL1, ETV6, EZH2, IDH1, IDH2, RUNX1, and TP53) have been detected in smaller proportions of patients, particularly in those with poor prognosis. Refractory anemia with ring sideroblasts (RARS) is a phenotypically well-defined subtype of MDS, characterized by 15% or more ring sideroblasts (RS, erythroblasts with perinuclear iron-loaded mitochondria) in the bone marrow. We reasoned that the identification of recurrently mutated genes in RARS could provide novel insights into molecular pathogenesis of MDS, and used massively parallel sequencing technology to identify somatically acquired point mutations across all protein-coding exons in the genome in 8 patients with RARS. We identified 62 point mutations across the 8 patients, and the mutation spectrum showed a predominance of transitions, especially C〉T/G〉A mutations. Within 5/8 patients studied, the observed proportion of reads reporting a mutant allele showed significantly greater variability than expected by chance, indicating that the population of malignant cells was genetically heterogeneous. In 6/8 RARS patients, we identified recurrent somatic mutations (found in granulocytes but not in T-lymphocytes) in a gene that encodes a core component of the RNA splicing machinery, SF3B1. Based on the proportion of reads reporting the mutant allele, the mutations all appeared to be heterozygous and present in the dominant clone of cells. To characterize the spectrum and frequency of SF3B1 mutations in greater detail, both in myeloid malignancies and other cancers, we undertook targeted resequencing of the gene. In particular, we studied patients with MDS, myelodysplastic/myeloproliferative neoplasm (MDS/MPN) or AML evolving from MDS. Somatic mutations of SF3B1 were found in 150/533 (28.1%) patients with MDS, 16/83 (19.3%) patients with MDS/MPN, and 2/38 (5.3%) patients with AML. The gene was also mutated in 1–5% of diverse other tumor types. All mutations appeared to be heterozygous substitutions, and we observed no frameshift indels, splice site mutations or nonsense substitutions. The mutations clustered in exons 12–15 of the gene, and K700E accounted for 97/168 (57.7%) of the variants observed. SF3B1 mutations were less deleterious than expected by chance, implying that the mutated protein retains structural integrity with altered function. Gene expression profiling revealed SF3B1 mutations are associated with down-regulation of key gene networks, including core mitochondrial pathways. Close relationships were found between mutant SF3B1 and presence of RS (P

Description: Introduction: Outcomes of adverse risk acute myeloid leukemia (AML) remain dismal. Despite some morphologic remission following therapy, the majority of patients relapse and succumb to their disease. Induction chemotherapy leads to a significant reduction in tumor burden, however, resistant leukemia cells persist as minimal residual disease (MRD), the reservoir for relapse. This is likely due to the capacity of these persistent cells to hijack properties from normal hematopoietic stem cells such as self-renewal, quiescence, and recapitulation of the malignant progeny. Thus leukemia cells are functionally heterogeneous, with the majority of cells at diagnosis susceptible to chemotherapy, and a minority of resistant cells that persist despite treatment. Deeper understanding of all leukemia sub-populations is necessary in order to understand mechanisms of resistance. We hypothesized that sub-populations such as leukemia-stem cells (LSCs), and post-therapy residual cells possess identifiable, targetable characteristics that drive resistance. We performed RNA-sequencing and compared differences in gene expression between these sub-populations. Methods: We collected 47 bone marrow samples from 27 patients who met criteria for adverse risk AML by ELN 2017 risk stratification. We performed RNA-sequencing on paired pre- and post-treatment sorted samples. Mononuclear cells were flow-sorted for bulk (CD45dim) and LSCs (Lin-CD34+CD38-CD123+) from diagnostic samples. Post-treatment samples were sorted for bulk mononuclear cells and MRD, determined based on patient-specific aberrant phenotype using multi-color flow cytometry analysis (Xu J et al., Clinics in laboratory medicine 2017). Sixteen patients (59%) had mutations in TP53, 9 (33%) had mutations in FLT3, and 3 (11%) had no mutations in these genes but had other adverse risk features. RNA was isolated using low-input methodology, and RNA-sequencing was performed using Illumina HiSeq 2000. Samples with low-expression of housekeeping genes were excluded from the analysis. Differential expression was analyzed using DESeq2 and Gene Set Enrichment Analysis (GSEA) was performed using the HALLMARK gene set. Results: The median age of patients included in this cohort was 67 years (range: 35-81). Baseline characteristics, including adverse risk features, commonly mutated genes, treatments and responses are described in Figure 1A. Differentially expressed genes were compared between sub-populations. Figure 1B includes pathways with statistically significant changes (changes with q

Description: In a previous study, we identified somatic mutations of SF3B1, a gene encoding a core component of RNA splicing machinery, in patients with myelodysplastic syndrome (MDS). Here, we define the clinical significance of these mutations in MDS and myelodysplastic/myeloproliferative neoplasms (MDS/MPN). The coding exons of SF3B1 were screened using massively parallel pyrosequencing in patients with MDS, MDS/MPN, or acute myeloid leukemia (AML) evolving from MDS. Somatic mutations of SF3B1 were found in 150 of 533 (28.1%) patients with MDS, 16 of 83 (19.3%) with MDS/MPN, and 2 of 38 (5.3%) with AML. There was a significant association of SF3B1 mutations with the presence of ring sideroblasts (P 〈 .001) and of mutant allele burden with their proportion (P = .002). The mutant gene had a positive predictive value for ring sideroblasts of 97.7% (95% confidence interval, 93.5%-99.5%). In multivariate analysis including established risk factors, SF3B1 mutations were found to be independently associated with better overall survival (hazard ratio = 0.15, P = .025) and lower risk of evolution into AML (hazard ratio = 0.33, P = .049). The close association between SF3B1 mutations and disease phenotype with ring sideroblasts across MDS and MDS/MPN is consistent with a causal relationship. Furthermore, SF3B1 mutations are independent predictors of favorable clinical outcome, and their incorporation into stratification systems might improve risk assessment in MDS.

Description: Key Points Cancer gene mutations affect treatment response and survival in patients with CLL treated with lenalidomide. The assessment of cancer gene mutations may be useful in the risk stratification of CLL patients.