Hammond, Danielle

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.

Introduction Chronic myelomonocytic leukemia (CMML) can be classified into dysplastic (dCMML) and proliferative (pCMML) subtypes based on a white blood cell count (WBC) ≥ 13 x 10 9/L for pCMML. Though this cutoff may seem arbitrary, there is evidence that pCMML is a unique biological entity with a distinct molecular profile and worse outcomes (Carr RM, et al. Nat Commun. 2021). We hypothesized that contemporary CMML prognostic scoring systems - such as the Mayo Molecular Model (MMM; Patnaik MM, et al. Leukemia. 2014) and the CPSS-Molecular Model (CMM; Elena C, et al. Blood. 2016) - would not adequately risk-stratify pCMML patients. Moreover, while truncating ASXL1 mutations are considered a high-risk feature in CMML, their prognostic relevance in pCMML is unknown. Methods After IRB approval, we compiled a large (n = 888), molecularly-annotated database of CMML patients seen at two US medical centers (Mayo Clinic and MD Anderson) via retrospective chart review. All statistical analyses considered the clinical and laboratory parameters obtained at the time of presentation. The cohort was divided into dCMML and pCMML subgroups, which were analyzed independently alongside the entire cohort. Categorical variables were compared by Fisher exact or Pearson χ 2 tests and continuous variables by Mann-Whitney U tests. Univariate and multivariate analyses were performed using Cox proportional hazards regression models. Survival was assessed via the Kaplan-Meier method. P-values < 0.05 were considered significant. Calculations were performed using the BlueSky Statistics (v10.3.1) interface for R. Results We identified 474 (54%) dCMML cases and 410 (46%) pCMML cases with median age 71 years and 67% males. Patients with pCMML were more likely to have higher AMC (5.1 vs 1.5 x 10 9/L, p < 0.0001), circulating immature myeloid cells (IMC; 65% vs 36%, p < 0.0001) and abnormal karyotypes (37% vs 30%, p = 0.0187). They were also overrepresented in higher-risk categories of the MMM and CMM compared to dCMML (p < 0.0001 for each model). The number of somatic mutations was higher in pCMML than dCMML (mean 3.0 vs 2.6, p = 0.0050). Mutations in ASXL1 (53% vs 39%), NRAS (21% vs 11%), CBL (18% vs 12%), SETBP1 (14% vs 7%), JAK2 (10% vs 3%), CEBPA (5% vs 2%), GATA2 (3% vs 0%), and FLT3 (3% vs 1%) were more frequent while mutations in TET2 (38% vs 48%), SF3B1 (2% vs 8%), ZRSR2 (2% vs 8%), and NPM1 (1% vs 3%) were less frequent in pCMML compared to dCMML, respectively (p < 0.05 for all). Though the MMM and CMM effectively stratified the dCMML group, they did not provide meaningful risk stratification in the pCMML group (MMM p < 0.05 overall but could not distinguish between low and intermediate-1/2 or intermediate-1 and high risks; CMM p > 0.05). Likewise, there was no difference in the median overall survival (OS) or leukemia free survival (LFS) when pCMML patients were stratified by truncating ASXL1 mutations( Figure 1A). We then sought to better risk stratify pCMML. Univariate analysis identified increasing age, male gender, abnormal karyotype, and elevated WBC, ANC, and AMC as adverse predictors for OS. In addition, the presence of IMC and peripheral blood (PB) blast % were adverse factors for LFS, while age was not significant for LFS. None of the aforementioned mutations were significant in the univariate model for OS, whereas GATA2 and NPM1 mutations were significant for LFS. In multivariate analysis for OS, only male gender and AMC ≥ 10 x 10 9/L retained significance. In multivariate analysis for LFS, male gender, AMC ≥ 10 x 10 9/L, and peripheral blasts ≥ 5% remained significant; GATA2 and NPM1 mutations were not significant. These variables risk-stratified pCMML patients based on the presence of 0, 1, or ≥ 2 risk factors ( Figure 1B). In comparison, OS was 40.7 months (95% CI 35.2 - 50.1 mo.) for dCMML patients, 20.1 months (95% CI 18.2 - 22.7 mo.) for pCMML patients, and 31.8 months (95% CI 28.4 - 33.5 mo.) for the entire cohort. At last follow up, 586 deaths (66%) and 168 AML transformations (19%) were recorded in the cohort. Deaths in dCMML vs pCMML were 294 (62%) vs 291 (71%; p = 0.0067), with AML transformations in 83 (18%) vs 84 (21%; p = 0.2055) patients, respectively. Conclusions Truncating ASXL1 mutations, along with ASXL1-mutation weighted CMML prognostic models failed to effectively risk stratify pCMML patients. In pCMML, male gender and AMC ≥ 10 x 10 9/L, effectively risk stratified for OS, while these factors along with PB blasts ≥ 5% effectively risk stratified for LFS.

Introduction HMAs are the only approved therapy for CMML. In order to improve response rates and survival, the addition of VEN has been utilized in both CMML and after blast transformation (CMML-BT) with conflicting results in small single center studies. To clarify the role of upfront HMA+VEN in CMML and CMML-BT, we performed a large multicenter analysis. Methods We included patients with HMA-naïve CMML and CMML-BT treated with combination HMA and VEN from 4 academic centers. The primary outcome was overall survival (OS) with secondary outcomes including overall response rate (ORR) by 2015 MDS/MPN IWG criteria for CMML and 2022 ELN criteria for CMML-BT. To better appreciate the benefit of adding VEN to HMA treatment, we also performed 1:1 propensity score matched (PSM) analysis of patients treated with HMA alone as upfront therapy for CMML or CMML-BT. Matching was based on age, sex, ECOG performance status, CPSS-Mol, blood counts, peripheral and bone marrow blasts. Results Eighty-nine patients were treated with frontline HMA+VEN, 51 CMML and 38 CMML-BT (5 had received HMA alone for prior CMML). The median age was 71 years, 70% were male, and 83% had ECOG 0-1. Among CMML patients, 55% had MP-CMML subtype, 65% had CMML-2 and 12%, 30%, 58% were CPSS-mol intermediate-1, intermediate-2 and high risk, respectively. In the entire cohort, ASXL1 (63%), TET2 (47%), SRSF2 (39%) and RUNX1 (27%) were the most commonly mutated genes and 55% of patients harbored a RAS mutation ( KRAS [20%], NRAS [18%], CBL [13%], NF1 [11%], PTPN11 [9%]). For HMA combination partner, 46 (52%) were treated with azacitidine, 35 (39%) with decitabine, and 8 (9%) with both during their VEN course. During a median follow-up time of 15.8 months (mos) 52 patients (58%) died: 23 (45%) with CMML and 29 (76%) with CMML-BT. Among CMML patients, the ORR was 90%, including complete remission (CR) in 22%, complete cytogenic remission (CCR) in 4%, optimal marrow response (CMR) in 50%, and partial marrow response (PMR) in 6%. The OS of CMML patients was 25.1 mo (95% CI 15.7 - NR). A PSM population of HMA patients matched to HMA+VEN treated patients showing similar baseline characteristics. ORR was significantly higher with HMA+VEN (95%) as compared those treated with HMA alone (46%), p < 0.001. However, there was no significant OS difference between HMA+VEN vs HMA alone (19.1 mos vs 19.1 mos, p = 0.85, Figure 1). For CMML-BT patients, the ORR of HMA+VEN was 81% including CR in 17%, CR with partial hematologic recover (CRh) in 3%, CR with incomplete hematologic recovery (CRi) in 28%, morphologic leukemia-free state (MLFS) in 22% and partial response (PR) in 11%. The OS of CMML-BT patients was 8 mos (95% CI 4.6 - 26.2). A PSM population of CMML-BT patients treated with HMA alone showed a significantly increased ORR with HMA+VEN (82% vs 40%, p = 0.039). However, there was no difference in OS (7.49 mos vs 9.26 mos, p = 0.83, Figure 2). Among HMA-VEN treated patients, achievement of a CR was associated with an improved OS in the CMML (HR 0.31, 95% CI 0.13 - 0.75) and CMML-BT (HR 0.37, 95% CI 0.19 - 0.74). No predictors of response were identified, including the presence of a RAS mutation. In terms of safety, 7 patients (7.9%) had a grade 3/4 (G3/4) neutropenic infection and 2 patients (2.2%) had a G3/4 hemorrhagic event while being treated with HMA+VEN. A total of 29 patients went on to receive allogeneic transplant (alloSCT): 22 (43%) with CMML and 7 (18%) with CMML-BT. CMML patients who underwent alloSCT after HMA+VEN were younger as compared to non-transplanted patients (64 vs 74 years, p < 0.0001), but had otherwise similar baseline characteristics including stage, CPSS-mol category and prevalence of RAS mutations. Similarly, CMML-BT patients bridged to alloSCT were younger (66 vs 74 years, p < 0.002) and had a better ECOG performance status (p = 0.047). Of patients who received alloSCT, 10 patients (34%) died, 5 with CMML and 5 with CMML-BT. The median OS after alloSCT was 26.7 mo. Conclusions Although the use of VEN with HMA in the upfront treatment of CMML and AML secondary to CMML results in higher response rates compared to HMA alone, this combination does not improve survival based on this multi-center PSM analysis. The current sample size of CMML-BT may limit detection of OS differences between treatment groups. The role of VEN to reduce blasts and serve as a bridge to alloSCT, particularly after HMA failure, requires further investigation in larger studies in both the CMML and CMML-BT populations.

Introduction Truncating ASXL1 mutations in chronic myelomonocytic leukemia (CMML) are associated with inferior overall survival (OS) and leukemia free survival (LFS). Conversely, loss-of-function mutations in TET2 are associated with better outcomes, with the ASXL1wt/ TET2mut genotype being associated with the best OS and LFS-rates (Coltro G, et al. Leukemia. 2020). Contemporary CMML prognostic scoring systems - such as the Mayo Molecular Model (MMM; Patnaik MM, et al. Leukemia. 2014) and the CPSS-Molecular Model (CMM; Elena C, et al. Blood. 2016) - do not consider concomitant ASXL1/ TET2 mutational status or mutational VAF. We hypothesized that the ASXL1/ TET2 genotype would better risk stratify patients in comparison to ASXL1 mutations alone, and that this effect would be proportional to the underlying mutational VAF. Methods After IRB approval, we compiled a large (n = 888), molecularly annotated database of CMML patients seen at two US medical centers (Mayo Clinic and MD Anderson) via retrospective chart review. All statistical analyses considered the clinical and laboratory parameters obtained at the time of presentation to the respective institution. Categorical variables were compared by Fisher exact or Pearson χ 2 tests and continuous variables by Mann-Whitney U tests. Univariate and multivariate analyses were performed using Cox proportional hazards regression models. Survival was assessed via the Kaplan-Meier method. P-values < 0.05 were considered significant. All statistical calculations were performed using the BlueSky Statistics (v10.3.1) interface for R. Results The median age of the cohort was 71 years (range 20 - 94), 67% were male, 46% had proliferative CMML (pCMML), and 19% had CMML-2. The distribution of low, intermediate-1, intermediate-2, and high-risk patients was 15%, 11%, 32%, and 42% by the MMM and 9%, 23%, 40%, and 28% by the CMM, respectively. The most frequently mutated genes were ASXL1 (45%), TET2 (43%), SRSF2 (41%), and RUNX1 (17%), while 40% harbored at least one RAS pathway mutation ( NRAS 16%, CBL 15%, KRAS 8%, PTPN11 4%, FLT3 2%). The median OS and LFS of the entire cohort were 31.8 months (95% CI 28.4 - 33.5 months) and 28.4 months (95% CI 24.6 - 32.1 months), respectively. Patients were stratified into ASXL1wt/ TET2wt (28%), ASXL1mut/ TET2wt (29%), ASXL1wt/ TET2mut (26%), and ASXL1mut/ TET2mut (17%) genotypes. Those with isolated TET2 mutations had the longest median OS (53.6 months; p < 0.02 for all comparisons) whereas those with isolated ASXL1 mutations had the shortest median OS (20.9 months; p < 0.04 for all comparisons); mutations in neither or both genes performed similarly (p = 0.9224; Figure 1A). The same trend was seen for LFS. We further hypothesized that the ASXL1 or TET2 mutation VAF would be more predictive of outcomes than a binary metric. The respective median VAFs were 37% (quartiles 28% - 45%) and 45% (quartiles 40% - 49%). When treated as a continuous variable, however, there was no correlation between either VAF and OS or LFS by both Pearson linear regression and Cox proportional hazard modeling. Unlike the overall cohort, the ASXL1/ TET2 genotypes did not further stratify patients with pCMML, CMML-2, or those considered high risk by the CMM in Kaplan-Meier analyses, suggesting that the high-risk features inherent in these subgroups outweigh the benefits of the TET2 mutation. In contrast, patients considered high-risk by the MMM were further stratified by the ASXL1/ TET2 genotypes. Incorporating TET2 mutations into the MMM as a protective factor (worth -1.5 points) improved detection of low- (≤ 1 point) and high-risk (≥ 4 points) patients, while intermediate-1 and intermediate-2 coalesced into a single intermediate risk category ( Figure 1B). A similar phenomenon was observed when TET2 was incorporated into the CMM (worth -1 point, yielding low- (0 points), intermediate- (1-2 points), and high-risk (≥ 3 points) groups with median OS of 83 months (95% CI 66.2 - 104.2), 34.3 months (95% CI 31.6 - 38.7), and 17.7 months (95% CI 15.7 - 20.2), respectively. Conclusions Truncating and hypomorphic TET2 mutations are associated with better outcomes in CMML, with the ASXL1mut/ TET2wt genotype being associated with improved risk stratification in comparison to ASXL1 mutational status alone. Counterintuitively, in our data set, this stratification was not impacted by mutational VAF, supporting binary mutational assessments in prognostic models.