Loghavi, Sanam

Introduction: Somatic mutations in RAS pathway genes are present in ~30% of patients with chronic myelomonocytic leukemia (CMML) and are usually associated with myeloproliferative features. Whether mutations in distinct RAS pathway genes share similar genomic context and have similar implications remains unknown. Such an understanding might inform future studies evaluating genotype-specific therapies (RAS-codon specific and pan-RAS inhibitors) or cooperative leukemogenic mechanisms. This multicenter study examines the landscape of RAS pathway mutations (RASMT) in CMML. Methods: Newly diagnosed CMML patients evaluated at MD Anderson Cancer Center (n=449, 54%) and Mayo Clinic (n=383, n=46%) were included after IRB approval. Clonal relationships were tested using Pearson goodness-of-fit. Clones with the highest variant allele frequency (VAF), or with VAF close to 40% were defined as dominant, and those present at VAF <20% in the presence of another dominant clone were defined as subclonal. RASMT genes included NRAS, KRAS, BRAF, CBL, CBLC, PTPN11 and NF1. Standard statistical measures were applied. Results: Among 832 CMML patients (median age 71 years, 68% male) 387 (47%) had myeloproliferative (MP) and 445 (53%) had myelodysplastic (MD) CMML. A total of 350 (42%) patients had RASMT with higher prevalence among MP-CMML compared to MD-CMML (55% vs 31%, p<0.001). Among patients with RASMT, 262 (32%), 59 (7%), 20 (2%), 6 (<1%) and 3 (<1%) had 1, 2, 3, 4 or 5 distinct RASMT, respectively. Importantly, 17 patients harbored a RASmt as the only detectable somatic mutation, with KRASMT being the most frequent (n=10, 59%), including 3 (18%) patients with >1 RASMT. Among RASMT patients, a trend for higher hemoglobin (12.7 vs 10.8 g/dL, p=0.054) was observed in NF1MT CMML and lower WBC (14.4 vs 27.9 x109/L, p=0.067) values in CBLMT CMML. In total, 479 somatic mutations in RAS pathway genes were identified the most frequent involving NRAS (n=169, 35%) followed by CBL (n=120, 25%), KRAS (n=102, 21%), PTPN11 (n=38, 8%), NF1 (n=34, 7%), BRAF (n=11, 2%) and CBLC (n=5, 1%). Most frequently involved codons for each RAS pathway gene were as follows: G594 (n=3) for BRAF, R420 (n=22) and C404 (n=15) for CBL, G12 (n=41; G12D: 13, G12C: 3) and A146 (n=16) for KRAS, G12 (n=116; G12D: 74, G12C: 5) for NRAS and A72 (n=8) for PTPN11. CBLMT CMML had higher ASXL1 (58% vs 44%, p=0.011), BRAF (8% vs 4%, p=0.017), IDH2 (10% vs 4%, p=0.024), KIT (5% vs 1%, p=0.038), SRSF2 (54% vs 40%, p=0.004), TET2 (59% vs 47%, p=0.019) and ZRSR2 (10% vs 4%, p=0.014) co-mutation frequency. Of note, DNMT3A mutations were mutually exclusive of CBLMT CMML (0% vs 7%, p=0.007), and multihit TET2 was more common among TET2MT/CBLMT vs TET2MT/CBLWT CMML (82% vs 67%, p =0.039). CMML with NF1 mutations had higher BCORL1 (8% vs 0%, p=0.005), PTPN11 (15% vs 3%, p=0.014) and SETBP1 (23% vs 8%, p=0.022) mutational cooccurrences. NRASMT CMML was enriched for ASXL1 (53% vs 43%, p=0.042), ETNK1 (5% vs 1%, p=0.004), GATA2 (4% vs 1%, p=0.034) and STAG2 (4% vs 1 %, p=0.023) mutations but had lower JAK2 (1% vs 6%, p=0.036) and TP53 (1% vs 5%, p=0.022) mutational frequency. PTPN11 mutations were associated with higher NF1 (29% vs 7%, p=0.014), SETBP1 (27% vs 9%, p=0.01) and WT1 (6% vs <1%, p=0.014) mutational cooccurrences and lower SRSF2 (23% vs 42%, p=0.05) frequency. We evaluated RAS mutant clonal dominance in 253 (72%) RASMT patients. NRAS (63% vs 38%), KRAS (63% vs 38%) and CBL (65% vs 35%) mutations were more frequently observed as dominant clones while PTPN11 (44% vs 56%), BRAF (25% vs 75%) and NF1 (35% vs 65%) mutations were more frequently subclonal events, particularly of TET2, ASXL1 or SRSF2 mutant clones. Presence of a RAS pathway mutation was associated with shorter LFS (36 vs 53 months, HR 1.5, 95% CI 1.1-2.2, p=0.020), with presence of multiple RAS mutations shortening LFS further (53, 43, 27 months for 0, 1 and >1, p=0.017). PTPN11 mutations predicted for shorter OS (18 vs 39 months, HR 1.7, 95% CI 1.0-2.8, p=0.035) and LFS (14 vs 36 months, HR 1.9, 95% CI 1.2-2.9, p=0.008). Presence of >1 RAS pathway mutation was associated with shorter OS in ASXL1MT/TET2MT CMML compared to those with no RAS mutations (24 vs 53 months, HR 4.2, 95% CI 1.6-10.8, p=0.004). Conclusions: RAS mutations exhibit distinct genomic features and clonal hierarchy in CMML and cooperate with other somatic mutations to drive clinical outcomes. This study forms the foundation for assessment of novel RAS pathway inhibitors in CMML.

Introduction Somatic mutations in TET2 are present in ~60% of chronic myelomonocytic leukemia (CMML) patients and are associated with improved median overall (mOS) and acute leukemia free survival (mLFS). Multiple TET2 mutations are detected in ~50% of such cases and are thought to confer additional benefit. Whether these benefits apply to the molecularly distinct myelodysplastic (MD) and myeloproliferative (MP) CMML subtypes is unknown. This study assesses the impact of the number and type of TET2 mutations across the MD and MP-CMML subtypes. Methods CMML patients seen at Mayo Clinic (n = 400, 47%) and MD Anderson Cancer Center (n = 449, 53%) were included with IRB approval. Analyses considered the clinical and molecular data at diagnosis or first referral. Truncating (frameshift or nonsense) mutations in TET2 were further annotated by location in either the proximal genome targeting domain (aa 1 - 1128) or distal catalytic domain (aa 1129 - 1936) as described (Coltro, 2020). Categorical variables were compared by Pearson Chi squared and continuous by Mann-Whitney U or Kruskal-Wallis tests. Univariate and multivariate analyses utilized Cox proportional hazards models with continuous variables binarized by receiver operator curves. Kaplan-Meier analyses were censored at hematopoietic cell transplantation (HCT). P < 0.05 was considered significant. Calculations used BlueSky (v10.3.1) or Prism (v10.2.3). Results In a cohort of 849 CMML patients (median age 71 years, 32% female, 90% white), 454 (54%) were classified as MD-CMML and 394 (46%) as MP-CMML. Cumulatively, 664 somatic TET2 mutations were identified across the MD (n = 415, 63%) and MP-CMML (n = 249, 38%) subgroups, with ≥1 TET2 mutation in 57% vs 44% (p < 0.001) and ≥2 TET2mutations in 33% vs 20% (p = 0.001) , respectively. The median (range) number of TET2 mutations in MD vs MP-CMML was 1 (0 - 4) vs 0 (0 - 3; p < 0.001). Truncating frameshift or nonsense mutations comprised 86% vs 78% of mutations in each group with hypomorphic missense mutations comprising 13% vs 20% (p = 0.03). Proximal (48% vs 43%) and distal (38% vs 35%) truncations were evenly distributed between MD and MP-CMML (p = 0.91). In both the MD and MP subgroups as well as the overall cohort (p < 0.01 each), increasing number of TET2 mutations (0 vs 1 vs ≥2) was associated with higher median hemoglobin (10.3 vs 11.4 vs 12.0 g/dL), fewer mean peripheral blasts (1.3% vs 0.5% vs 0.3%), and a higher proportion of normal karyotypes (60% vs 76% vs 79%). Likewise, co-mutations were increasingly frequent in SRSF2 (36% vs 45% vs 53%) and less frequent in IDH2 (9% vs 1% vs 1%) and SETBP1 (14% vs 4% vs 0%) throughout the cohort. TET2 mutations were mutually exclusive with ETV6, GATA2, IDH1, and WT1 mutations. Uniquely, MD-CMML cases with TET2 mutations (0 vs 1 vs ≥2) were enriched for co-mutations in ZRSR2 (5% vs 13% vs 9%) and had fewer co-mutations in both ASXL1 (47% vs 34% vs 28%) and U2AF1 (11% vs 6% vs 3%). In MP-CMML, co-mutations in CBL (11% vs 20% vs 27%) were increased while co-mutations in BCOR (6% vs 1% vs 0%) were decreased. Accordingly, the favorable ASXL1WT/TET2MT genotype was more common in MD (39% vs 22%), while the adverse ASXL1MT/TET2WT genotype was more common in MP-CMML (20% vs 33%; p < 0.001). In multivariate analyses, the presence of ≥2 TET2 mutations was favorably associated with OS and LFS in both MD and MP-CMML (hazard ratios 0.53 - 0.67, p < 0.04) independent of several clinical and genetic features including ASXL1 mutations and abnormal karyotype. Beyond the number of TET2 mutations, however, neither the mutation class (truncating vs hypomorphic) nor location (proximal vs distal) further affected OS or LFS. Likewise, although the median variant allele fraction (VAF) was lower in MD vs MP-CMML (42% vs 46%, p < 0.001), VAF did not impact survival. Accordingly, the mOS for patients with 0, 1, or ≥2 TET2 mutations was 29, 58, and 75 months in MD-CMML and 19, 26, and 39 months in MP-CMML, respectively (p < 0.001 each). The mLFS was similarly improved to 26, 52, and 67 months in MD-CMML (p < 0.001) and 16, 22, and 31 months in MP-CMML (p = 0.003). CONCLUSIONS This multicenter study demonstrates that the favorable impact of multiple TET2 mutations in CMML extends to both the MD and MP subtypes. In MD-CMML, multiple TET2 mutations segregate against adverse ASXL1 mutations while, in MP-CMML, they appear to offset the impact of adverse RAS pathway mutations. Thus, multiple TET2 mutations may identify a lower-risk subgroup of MP-CMML patients.

Introduction Oligomonocytic chronic myelomonocytic leukemia (OM-CMML) is defined by relative monocytosis ≥ 10% and an absolute monocyte count (AMC) between ≥ 0.5 and < 1.0 x109/L. The 5th ed WHO and International Consensus Classifications lowered the AMC threshold to ≥ 0.5 x10/9L for CMML diagnosis, thereby incorporating OM-CMML (Khoury, 2022; Arber, 2022). However, prior reports differ as to whether OM-CMML is a distinct CMML subtype. This multi-center study compares the clinical, molecular, and survival features of OM-CMML with myelodysplastic (MD, WBC < 13.0 x109/L) and myeloproliferative (MP, WBC ≥ 13.0 x109/L) CMML with an AMC ≥1.0. Methods After IRB approval, patients with CMML from Mayo Clinic (n = 400, 47%) and MD Anderson Cancer Center (n = 449, 53%) were identified retrospectively. Analyses considered clinical, laboratory, and next generation sequencing parameters at diagnosis or first referral (in chronic phase). Categorical variables were compared by Fisher exact or Pearson χ2 tests and continuous variables by Mann-Whitney U or ANOVA tests. Survival was assessed via the Kaplan-Meier method with outcomes censored at allogeneic stem cell transplantation (alloSCT). P < 0.05 was considered significant. Calculations used BlueSky Statistics (v10.3.1). Results A molecularly annotated cohort of 849 patients with CMML (median age 71 years, 32% female, 90% white, median follow up 31 months [mo]) was categorized as OM-CMML (n = 57, 7%), MD-CMML (n = 394, 46%), and MP-CMML (n = 391, 46%). There were no differences in age or sex across subtypes. No clinical differences were observed between OM-CMML and MD-CMML, with similar hematologic parameters, karyotype distributions, Mayo-Molecular (Patnaik, 2014) or CPSS-Molecular (Elena, 2016) risk stratifications, and rates of leukemic transformation (12% vs 12%, p = 0.98) and death (35% vs 43%, p = 0.27). Cases of OM-CMML had lower WBC counts (median 4.4 vs 24.7 x109/L, p < 0.0001), fewer circulating immature myeloid cells (23% vs 57%, p < 0.0001) and fewer marrow blasts (median 3% vs 4%, p = 0.0065) than MP-CMML. Comparatively, OM-CMML cases were overrepresented in the lower-risk groups of the CPSS-Molecular and Mayo-Molecular models (p < 0.0001). Leukemic transformation (12% vs 20%, p = 0.015) and death (35% vs 52%, p = 0.034) rates were higher in the MP-CMML cohort. Molecular profiles were similar between OM-CMML and MD-CMML, including median number of genes mutated (3 vs 3, p = 0.88). Frequencies of ASXL1 (39% vs 38%, p = 0.91), SRSF2 (48% vs 43%, p = 0.49), DNMT3A (7% vs 5%, p = 0.60), and SF3B1 (4% vs 7%, p = 0.48) mutations were also similar. TET2 mutation frequency was higher in OM-CMML (70% vs 55%, p = 0.031) and occurred in isolation more frequently (12% vs 6%, p = 0.048) compared to MD-CMML. Neither median number of TET2 mutations (1 vs 2, p = 0.87), nor TET2 variant allele fractions (41% vs 44%, p = 0.19) were different between the two groups. Compared to OM-CMML, patients with MP-CMML were more likely to have mutations in ASXL1 (39% vs 56%, p = 0.017), EZH2 (0% vs 9%, p = 0.019), JAK2 (0% vs 9%, p = 0.019), NRAS (7% vs 25%, p = 0.0024), and SETBP1 (2% vs 13%, p = 0.021). RAS family (CBL, BRAF, KRAS, NRAS, PTPN11; 25% vs 54%, p < 0.0001) and signaling pathway (CSF3R, FLT3, JAK2, SH2B3; 2% vs 14%, p = 0.0078) mutations were also more frequent whereas spliceosome mutations (SF3B1, SRSF2, U2AF1, ZRSR2; 61% vs 46%, p = 0.033) were less frequent in MP-CMML. The median (95% CI) overall survival (OS) of OM-CMML patients was 44 (38 - not reached) mo compared to 45 (34 - 60) mo in MD-CMML (p = 0.76) and 23 (20 - 29) mo in MP-CMML (p < 0.0032). Similar results were obtained when comparing the acute leukemia-free survival (LFS) of the OM-CMML (41 mo), MD-CMML (39 mo), and MP-CMML (19 mo) groups. At last follow up (medians 42 and 62 mo, respectively), 33% of evaluable OM-CMML patients had progressed to MD-CMML and 28% of MD-CMML patients had progressed to MP-CMML. No patient with OM-CMML progressed directly to MP-CMML. Conclusions These data show that OM-CMML and MD-CMML are a relatively homogenous subset of patients with similar clinicomolecular profiles and survival outcomes. Although OM-CMML patients are more likely to have TET2 mutations in comparison to other CMML subtypes, they have similar rates of disease progression as MD-CMML. This validates recent modifications to CMML classification criteria, in which OM-CMML cases are included as bona fide CMML.

Background: The addition of midostaurin (M), an oral multi-kinase inhibitor, to intensive chemotherapy (IC) prolongs survival in newly diagnosed (ND) FLT3 mutated (m) AML. It is not known if there is a benefit to more potent and selective FLT3 inhibitors. Among these is Gilteritinib (G), now approved as a single agent in relapsed/refractory FLT3m AML. Combined with IC, G also leads to high measurable residual disease (MRD)negative (-) composite complete remission (CRc) in FLT3 Internal Tandem Duplication (ITD)m AML. The aim of the PrECOG 0905 study was to compare FLT3m clearance and CRc rates of G vs M with IC in adults with ND FLT3m AML. Methods: We conducted a randomized, open-label, phase 2 trial comparing G to M in combination with IC during induction and consolidation in ND AML pts with centrally PCR detected FLT3 ITD or TKD mutations. Pts age 18-70 with non M3 AML and no known core binding factor rearrangement were eligible. Pts were stratified by mutation type (TKD only vs. ITD (+/- TKD)), NPM1 mutation status, and FLT3-ITD allelic ratio. Induction consisted of cytarabine 100 mg/m2 by continuous infusion daily, on day (d) 1-7 and daunorubicin 90 mg/m2 IV on d 1-3. G 120 mg daily or M 50 mg twice daily was given orally on d8-21. Consolidation (up to 4 cycles) began within 60 d of induction with Cytarabine (1.5-3 g/m2 IV) X 6 doses and G or M (as per randomization) on d8-21. Pts could proceed to transplant (HCT) at any time. Maintenance was not included. The primary outcome was FLT3m MRD (-) CRc after induction. MRD for TKD mutations was tested by PCR (sensitivity 10-2); ITD MRD was tested by amplicon-based NGS (sensitivity 10-4). Safety and efficacy were analyzed in all eligible pts who received treatment. Secondary endpoints included comparison of CRc, MRD by flow cytometry (sensitivity 10-3), and survival. Results: From 11/2019 to 11/2022, 722 pts were screened at 37 centers, 180 pts randomized, and 177 pts (58% female, 77% white, 8.5% black, 8.5% hispanic) treated on the G (n=90) or M (n=87) arm. Median age was 54, with 27.7% > age 60. FLT3-ITD was present in 80% in the G arm and 78.2% in the M arm. Of those with FLT3-ITD, NPM1 was detected in 56.9% pts in G arm and 58.8% in M arm. 24.4% G and 20.7% M pts had co-occuring FLT3-ITD, NPM1 and DNMT3A mutations. Adverse karyotype was seen in 3.4% G and 9.3% M while 10% G and 13.8% M were ELN 2022 adverse risk. For pts on G arm, 85.6% achieved CRc compared to 72.4% for M (p=0.042). 5 (5.6%) pts on G arm and 6 (6.9%) on M arm received 2 cycles in induction. Post induction, the FLT3m- CRc rate was 40% for G vs 47.1% for M (p=0.366). FLT3-TKD only mutated pts achieved CRc in 88.9 % with G and 63.2% with M and FLT3m- CRc in 72.2% and 63.2% respectively. FLT3-ITDm (+/- TKDm) pts achieved CRc/FLT3m- CRc in 84.7%/31.9% with G and 75%/42.6% with M, respectively. In pts with FLT3-ITD, NPM1 and DNMT3A mutations, 95.5% G and 72.2% M achieved CRc and 50% G vs 33.3% on M achieved FLT3m- CRc. Flow cytometry MRD negative CRc was documented in 64.4% on G arm and 59.8% on M arm after induction (p=0.539). On G arm 67 (74%) patients received at least one cycle of consolidation compared to 53 (61%) pts on M arm. On exploratory analysis, 54 (66%) G and 40 (46%) M were reported to proceed to HCT in first remission. FLT3m testing was done post consolidation cycle 1 in 27 pts in FLT3m+ CRc after induction and 15/18 (83%) on G and 4/9 (44.4%) on M converted to FLT3m-. On multivariate logistic regression analysis for FLT3m-CRc post-induction, FLT3-ITD allelic ratio, NPM1m, WBC and hemoglobin at baseline were significant at the 0.10 two-sided level, while treatment arm, and 2017 ELN risk were not. There were no deaths from treatment-related (TR) adverse events (TRAEs) while grade >=3 TRAE was reported in 73%G vs 70% M during induction and 79%G vs 73%M pts during consolidation. Conclusion: Induction therapy with daunorubicin 90 mg/m2 X 3 days, cytarabine 100 mg/m2 and gilteritinib results in an excellent CRc rate with no TR deaths in pts with ND FLT3m AML up to age 70. Compared to M, G increased the CRc but not the FLT3m- CRc rate after induction. More post induction FLT3m+CRc pts who received G became FLT3m- after consolidation cycle 1 and more G pts succeeded in proceeding to HCT. Future survival data will help evaluate the clinical impact of G and MRD assessments in ND FLT3mAML. Larger studies will be needed to establish most predictive timing of MRD and for definitive comparisons of these drugs in patients with specific mutation profiles ( ie TKD, ITD/NPM1/DNMT3).

Background. The inclusion of gene mutations and chromosomal abnormalities in the 2022 WHO and ICC Classifications of MDS has enhanced diagnostic precision and is expected to improve clinical decision-making process. Although these two systems share similarities, clinically relevant discrepancies still exist and potentially cause inconsistency in their adoption in a clinical setting. In this study on behalf of the International Consortium for MDS (icMDS), we adopted a data-driven approach to provide a harmonization roadmap between the 2022 WHO and ICC classification for MDS. A modified Delphi Process consensus approach is currently ongoing among icMDS experts to finalize a harmonized MDS classification scheme. Methods. We analyzed retrospective international cohorts of patients with a diagnosis of MDS (n=7017) and AML (n=1002) according to WHO 2016 criteria. Hierarchical Dirichlet Processes were applied to define clusters capturing broad dependencies among all gene mutations and cytogenetic abnormalities. To investigate the features of importance and their impact on the clustering process, we employed the SHapley Additive exPlanations approach (SHAP). This allowed to define harmonized labels for each clinical entity. The clinical relevance of the unsupervised clustering was assessed through the analysis of phenotypic features and outcomes among each group. ( Blood 2022;140: 9828-9830) Results. Patients' characteristics are summarized in Table 1. We identified 9 clusters, defined by specific genomic features. The cluster of highest hierarchical importance was characterized by biallelic inactivation of TP53 (biTP53). According to SHAP analysis, bi TP53 was defined as 2 or more TP53 mutations, or 1 mutation with copy number loss or cnLOH. Most patients assigned to bi TP53 cluster had TP53 VAF>10% (77.9%) and complex karyotype (70.1%). Assignment to bi TP53 cluster was irrespective of blast count. Patients with monoallelic TP53 mutation segregated into other clusters. Hierarchically, the second cluster included patients with del(5q). SHAP analysis highlighted 5q deletion alone, or with one other chromosomal abnormality other than -7, and absence of bi TP53, as the most relevant features. Most of these patients had blast counts <5% (88.1%). The third distinct cluster included patients with SF3B1 mutations (in the absence of concurrent del(7q), abn3q26.2, complex karyotype or RUNX1 mutation). Most patients with MDS and SF3B1 mutation had <5% blasts (94.2%). Common co-mutated variants in the SF3B1 cluster included mutant DNMT3A (25.2%) and TET2 (38.3%). Morphologically defined MDS cases (i.e., not meeting criteria for bi TP53, del(5q) or SF3B1) were preferentially assigned to the following additional clusters: SF3B1 and concurrent higher-risk mutations (e.g., RUNX1 and ASXL1); SRSF2 and concomitant TET2 mutations; U2AF1 mutations with del(20q), del(7q) or -7; SRSF2 with TET2 mutations and co-mutational patterns including RUNX1 and ASXL1; and AML-like genomic signatures. Our analyses suggest that morphologically defined MDS is characterized by a large heterogeneity in terms of mutation profiles, not entirely captured by the presence of unilineage versus multilineage dysplasia, percentage of bone marrow blasts, and presence of hypocellularity and fibrosis. To better investigate the continuum between high risk MDS (i.e., patients with ≥10% blasts) and AML, an exploratory comparison was made using a cohort of AML (defined according to WHO 2016) patients analyzed using the same statistical methods. Only a partial overlap in genetic signatures was observed between MDS with ≥10% blasts and AML. However, similarities were observed between the AML-like MDS clusters (characterized by mutant NPM1, bZIP CEBPA, and Core Binding Factor abnormalities) and AML clusters defined by the same genetic signature, thus supporting the classification of these entities as AML, irrespective of blast count. Conclusion. Our study demonstrated the utility of a data-driven approach based on advanced statistical methods to generate a harmonized classification for MDS. Table 2 shows a provisional, hierarchical classification algorithm. Further refinement of entity labels and classification criteria is the subject of the ongoing modified Delphi Process consensus approach among icMDS experts.

Abstract Myeloid neoplasms and acute leukemias derive from the clonal expansion of hematopoietic cells driven by somatic gene mutations. Although assessment of morphology plays a crucial role in the diagnostic evaluation of patients with these malignancies, genomic characterization has become increasingly important for accurate diagnosis, risk assessment, and therapeutic decision making. Conventional cytogenetics, a comprehensive and unbiased method for assessing chromosomal abnormalities, has been the mainstay of genomic testing over the past several decades and remains relevant today. However, more recent advances in sequencing technology have increased our ability to detect somatic mutations through the use of targeted gene panels, whole-exome sequencing, whole-genome sequencing, and whole-transcriptome sequencing or RNA sequencing. In patients with myeloid neoplasms, whole-genome sequencing represents a potential replacement for both conventional cytogenetic and sequencing approaches, providing rapid and accurate comprehensive genomic profiling. DNA sequencing methods are used not only for detecting somatically acquired gene mutations but also for identifying germline gene mutations associated with inherited predisposition to hematologic neoplasms. The 2022 International Consensus Classification of myeloid neoplasms and acute leukemias makes extensive use of genomic data. The aim of this report is to help physicians and laboratorians implement genomic testing for diagnosis, risk stratification, and clinical decision making and illustrates the potential of genomic profiling for enabling personalized medicine in patients with hematologic neoplasms.

AimsRearrangement of the platelet‐derived growth factor receptor B (PDGFRB) gene defines a unique group of myeloid/lymphoid neoplasms with frequent eosinophilia and high sensitivity to tyrosine kinase inhibitors. This genetic abnormality is also rarely reported in Philadelphia‐like B‐cell acute lymphoblastic leukaemia/lymphoma (B‐ALL). PDGFRB rearrangement was initially thought to only occur in cases with 5q31–33 rearrangement as determined with conventional cytogenetics; however, there are reported cases with cryptic rearrangements. We aim to develop a broader strategy for screening of PDGFRB rearrangements of patients with myeloid/lymphoid neoplasms.Methods and resultsWe performed fluorescence in‐situ hybridisation (FISH) for PDGFRB rearrangement in 197 patients, including 70 with B‐ALL, 10 with myeloid neoplasms with 5q31–33 rearrangements, and 117 with eosinophilia (≥0.5 × 109/l in peripheral blood or ≥5% in bone marrow), and identified PDGFRB rearrangement in four of 197 (2.0%) cases. In an attempt to identify clinicopathological and genetic features that may have a stronger association with PDGFRB rearrangement, we analysed 13 patients with confirmed PDGFRB rearrangements, including 10 with myeloid neoplasms and three with B‐ALL. Among the 10 patients with myeloid neoplasms, eosinophilia was present in eight, monocytosis in two, 5q31–33 rearrangement in seven, and abnormal bone marrow morphology in all. All patients with myeloid neoplasms showed an excellent response to imatinib, including a patient in blast crisis. The three B‐ALL patients presented de novo, showed no eosinophilia, had a complex karyotype including 5q31–33 rearrangement, and had clinically aggressive courses with ultimate patient demise.ConclusionsThese findings suggest that a higher yield for the identification of PDGFRB rearrangement may result from an index of suspicion in patients with eosinophilia, monocytosis, bone marrow features of a myeloid neoplasm, and 5q31–33 rearrangement, and patients with Philadelphia‐like B‐ALL.

Background: The use of midostaurin in combination with standard induction chemotherapy has been shown to improve the outcomes in patients with newly diagnosed FLT3 mutated (FLT3m) AML (Stone et al) and allogeneic transplant is often recommended in first remission. While likely to achieve remission with standard induction, the majority of these patients will relapse and die of their disease. Gilteritinib, a potent FLT3 inhibitor, has been approved for use in patients with relapsed or refractory FLT3 mutated AML. In Phase I/II studies, when used as part of induction therapy, gilteritinib has shown promising CR rates. We have designed a trial comparing the outcomes of induction therapy with gilteritinib to those with midostaurin. The hypothesis is that gilteritinib, when added to induction chemotherapy, will produce more FLT3m negative composite complete remission (CRc). The Ratify trial combined midostaurin with daunorubicin 60 mg/m2/d X 3 days and cytarabine X 7 days Daunorubicin 90 mg/m2/d has however been shown to be superior during induction in patients with newly diagnosed FLT3 ITD mutated AML (Luskin et al, Burnett et al) While improved survival is the ultimate goal of any leukemia regimen, it is known that AML patients who proceed to allogeneic transplant with measurable residual disease (MRD) positive disease fare worse than those with MRD negative disease. As such, our goal is to increase the likelihood of an MRD negative state after induction. Study Design This is a randomized, open-label, multicenter phase II study comparing gilteritinib to midostaurin in combination with cytarabine 100 mg/m2 and daunorubicin 90 mg/m2 in newly diagnosed FLT3 mutated AML patients ages 18-65. Central confirmation of FLT3 mutation and other pretreatment studies are required. In order to identify patients without delay, all patients with suspected AML will be able to be prescreened without enrollment to the randomized treatment trial. Patients will be stratified according to TKD vs. ITD FLT3 mutation. Patients with FLT3-ITD mutation will undergo further stratification with NPM1 mutation status (positive vs. negative) and FLT3 ITD to FLT3 wild type signal ratio (high [≥ 0.5] vs. low [<0.5]). Patients will be randomized to receive standard induction treatment (cytarabine and daunorubicin) with either gilteritinib or midostaurin. Mandatory bone marrow samples are required after Induction and Consolidation. Patients who achieve CR or complete remission with incomplete hematologic recovery (CRi) will be assessed for MRD and be eligible at count recovery to go on to receive standard consolidation treatment of high-dose cytarabine with the study drug received during induction (gilteritinib or midostaurin). Patients may proceed to allogeneic transplant after induction or after 0-4 cycles of chemotherapy consolidation and may participate in BMT CTN 1506. Key Eligibility: Newly diagnosed FLT3m AML Primary Objective To evaluate the FLT3m negative (evaluated by polymerase chain reaction [PCR] and capillary electrophoresis) composite complete response (CRc) (includes CR or CRi)rate of patients with FLT3 mutated AML who receive gilteritinib compared to those who receive midostaurin in addition to standard therapy with cytarabine and daunorubicin during induction. Sample Size and Statistical design The accrual goal of this study will be 179 patients. Patients who achieve remission will be followed for survival and relapse. With an allocation ratio of 1:1 to the two arms, the study will have 80% power to detect an improvement of 20% in the FLT3 mutation negative CRc rate in the gilteritinib arm (i.e. from 40% to 60%) at the one-sided significance level of 0.05 based on Fisher's exact test. This study is conducted through PrECOG and is funded by Astellas Pharma. The study is slated to open in the summer of 2019 at 30 US sites. References: Stone R.M., Mandrekar S.J., Sanford B.L., et al. N Engl J Med 2017; 377:454-464 Luskin MR, Lee JW, Fernandez HF et al. Blood 2016 :blood-2015-07-657403; doi: https://doi.org/10.1182/blood-2015-07-657403 Burnett AK, Russell NH, Hills RK et al. Blood 2016; Blood 2016 128:449-452; doi: https://doi.org/10.1182/blood-2016-04-712091 Figure Disclosures Luger: Genetech: Research Funding; Jazz: Honoraria; Celgene: Research Funding; Pfizer: Honoraria; Kura: Research Funding; Onconova: Research Funding; Agios: Honoraria; Ariad: Research Funding; Biosight: Research Funding; Seattle Genetics: Research Funding; Cyslacel: Research Funding; Daichi Sankyo: Honoraria. Loghavi:MDACC: Employment; GLG Consultants: Consultancy; AlphaSights: Consultancy. Lazarus:Genentech: Speakers Bureau; Pluristem Therapeutics, Inc: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Adaptive Biotechnologies: Consultancy, Honoraria; CSL Behring: Consultancy; Jazz Pharmaceuticals: Consultancy, Honoraria, Speakers Bureau; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AstraZeneca: Honoraria, Speakers Bureau; Actinium Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Honoraria, Speakers Bureau; Seattle Genetics: Consultancy, Honoraria, Speakers Bureau; Biosight: Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Speakers Bureau; Teva Pharmaceuticals: Speakers Bureau. Rowe:BioSight: Consultancy. Tallman:Jazz Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Rigel: Consultancy, Membership on an entity's Board of Directors or advisory committees; Biosight: Research Funding; ADC Therapeutics: Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; KAHR: Consultancy, Membership on an entity's Board of Directors or advisory committees; Nohla: Consultancy, Membership on an entity's Board of Directors or advisory committees; Oncolyze: Consultancy, Membership on an entity's Board of Directors or advisory committees; BioLineRx: Consultancy, Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Consultancy, Membership on an entity's Board of Directors or advisory committees; Delta Fly Pharma: Consultancy, Membership on an entity's Board of Directors or advisory committees; Orsenix: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Cellerant: Research Funding; Tetraphase: Consultancy, Membership on an entity's Board of Directors or advisory committees; UpToDate: Patents & Royalties. Pratz:Astellas Pharma: Consultancy, Research Funding; AbbVie: Consultancy, Research Funding; Agios: Consultancy, Research Funding; Millenium/Takeda: Research Funding; Boston Biomedical: Consultancy. OffLabel Disclosure: In this study gilteritinib is being studies in newly diagnosed AML.