Kewan, Tariq Zuheir

ABSTRACT Background IDH mutations are found in 15%–20% of acute myeloid leukemia (AML). Recent evidence suggests that IDH mutation subtypes may respond differently to intensive chemotherapy. We evaluated blast clearance patterns, remission outcomes, and overall survival (OS) in AML patients with IDH2 R140, IDH2 R172, and IDH1 R132 mutations to assess differences in treatment response. Methods We retrospectively reviewed AML patients diagnosed at Mayo Clinic, Rochester (2016–2023) with NGS data and treated with intensive chemotherapy (7+3 or CPX‐351). Bone marrow blasts were assessed at diagnosis, mid‐induction, and end‐of‐cycle; blast clearance was defined as < 5%. Composite remission (CRc) included CR/CRi per ELN 2022. IDH2 responders were classified as early (after Cycle 1) or late (≥ 2 cycles). Blast reduction was calculated as log 10 (diagnosis blasts/end‐induction blasts) and normalized per day. OS was measured from diagnosis. Results Among 381 patients, 31 had IDH2 mutations (23 R140, 8 R172) and eight had IDH1 R132. Baseline blasts were similar. Mid‐cycle blasts were lower in R140 versus R172 (4% vs. 10%), with higher clearance (68% vs. 38%). End‐induction blasts were lower in R140 versus R172 (2% vs. 4%) with higher clearance (100% vs. 75%). IDH1 and IDH2 showed similar clearance patterns. Log 10 analyses showed deeper and faster blast reduction in R140 versus R172, with comparable kinetics between IDH1 and IDH2 . OS did not differ across subtypes. Early CRc in IDH2 ‐mutated patients was associated with numerically longer OS. Conclusion IDH2 R140 demonstrated faster blast clearance than R172, while remission and survival were similar across IDH subtypes. Trial Registration : The authors have confirmed clinical trial registration is not needed for this submission.

Abstract Introduction The European Leukemia Net (ELN) 2022 stratified acute myeloid leukemia (AML) patients (pts) treated with intensive chemotherapy (IC) into three groups based on genetic features. ELN 2024 (Döhner et al, Blood) and Beat AML 2024 (Hoff et al, Blood Advances) proposed revised systems to better capture the impact of genetic features in pts receiving less-intensive therapy (LIT). Real-world validation across treatment settings, including allogeneic hematopoietic stem cell transplantation (allo-HCT), is warranted. Methods We evaluated the performance of ELN 2022, ELN 2024, and Beat AML 2024 among AML pts treated at Mayo Clinic from 2016 to 2025. Only treated pts with available molecular data included. Response was assessed according to the ELN 2022 criteria. Overall survival (OS) was calculated from diagnosis. Multivariable Cox proportional hazard (CPH) models were used to adjust for covariates. Model performances were assessed using Harrell's c-index. Results 426 AML pts (median age 68 years; 60% male) were included; 195 (46%) received IC and 231 (54%) received LIT, while Allo-HCT was performed in 133 (31%) pts. Complex karyotype was present in 126 (30%) and normal cytogenetics in 143 (34%) pts. Molecular mutations included TP53 (20%), TET2 (18%), DNMT3A (16%), SRSF2 (16%), RUNX1 (16%), ASXL1 (16%), and NPM1 (15%). Among evaluable pts (83%), complete remission (CR) after first-line therapy was achieved in 47%. Risk group assignments varied: ELN 2022 vs. ELN 2024 classified pts as favorable (20% vs. 55%), intermediate (20% vs. 24%), and adverse (60% vs. 20%); Beat AML 2024 categorized pts as favorable (41%), intermediate (21%), and adverse (38%). ELN 2024 reclassified 229 (54%) pts of whom 5% upstaged and 49% downstaged, primarily affecting ELN 2022 adverse (67%) and intermediate (46%) groups. Among LIT-treated, CR rates did not differ across groups in any classification. Per ELN 2024, CR was achieved in 43% (favorable), 67% (intermediate), and 29% (adverse) of the LIT-treated pts. However, among IC-treated pts, CR was higher in favorable/intermediate vs. adverse groups across all models (p&lt;0.0001). Allo-HCT was most common in ELN 2024 intermediate (41%) and favorable (32%) vs. adverse (16%) groups. Median OS (months; 95% CI) for the entire cohort was 15.7 (12.5–20.9) with median follow-up time of 49.8 (40.9-55). By ELN 2022, OS of the entire cohort was 49.4 (30.7–NA) for favorable, 50.0 (29.2–NA) for intermediate, and 8.8 (7.7–11.2) for adverse (p&lt;0.0001). Per ELN 2024, OS of the entire cohort was 25.4 (18.5–37.3), 20.3 (13.4–39.8), and 5.7 (3.4–8.2), respectively (p&lt;0.0001). Beat AML 2024 stratified OS of the entire cohort as 42.5 (30.7–NA), 11.4 (9.3–16.7), and 5.6 (3.5–8.0) for favorable, intermediate, and adverse groups (p&lt;0.0001). ELN 2024 stratified the OS of the pts treated with LIT as 15.7 (10.1-24.9), 8.0 (4.9-13.9), and 6.8 (3.4-10.2) for favorable, intermediate and adverse risk groups, (p &lt;0.0001). Among ELN 2022 adverse-risk pts, those reclassified as favorable per ELN 2024 had superior OS (15.0, 9.8–22.7) compared to intermediate (7.8, 5.0–9.3) or adverse (5.4, 3.3–8.0) risk groups, p&lt;0.0001. C-index (95% CI) for OS in the entire cohort was highest for Beat AML 2024 (0.658, 0.629–0.688), followed by ELN 2022 (0.627, 0.599–0.655), and ELN 2024 (0.600, 0.568–0.631). In LIT-treated pts, ELN 2024 (0.597, 0.558–0.637) and Beat AML 2024 (0.586, 0.545–0.627) outperformed ELN 2022 (0.559, 0.521–0.596). Among allo-HCT pts, regardless of treatment type, ELN 2022 (0.610, 0.539–0.681) performed better than ELN 2024 (0.568, 0.487–0.648). In multivariable CPH models adjusted for age, bone marrow blasts, treatment intensity, and complex karyotype, ELN 2022 and ELN 2024 adverse-risk groups had higher hazard of death (HR 2.4, 1.6–3.5 and HR 1.7, 1.1–2.5, respectively, vs. favorable). No significant difference was observed between intermediate and favorable risk for ELN 2022 (HR 1.4, 0.9–2.2) or ELN 2024 (HR 1.4, 0.9–1.9). Allo-HCT was associated with a lower hazard of death (HR 0.4, 0.3–0.5). Conclusions In this real-world AML cohort, ELN 2024 and Beat AML 2024 improved OS prediction in LIT-treated pts compared to ELN 2022. This advantage was not observed in allo-HCT pts. Multivariable analysis confirmed the adverse-risk group as having the worst prognosis across all models. These findings highlight the importance of aligning molecular risk stratification with treatment modalities to enhance prognostication in AML.

Abstract Myeloid neoplasia encompasses a heterogeneous and complex molecular landscape whereby the distinct combinatorial patterns associated with clinical phenotypes are difficult to delineate. Given that genetic heterogeneity can be a consequence of the topology of the fitness landscape (peaked/non-peaked=high vs low fitness), we investigated co-mutational patterns in TP53 context as an example of hallmark genomic heterogeneity. Indeed, TP53 gene is characterized by hypomorphic/loss-of-function lesions, truncating mutations (frameshifts, stop codons), missense mutations often having a dominant-negative effect and loss of heterozygosity by chromosome 17p deletion driving clonal expansion. Clinical phenotypes of TP53 mutants are also heterogeneous. Here, we stratify TP53 mutations based on our previous published data1 whereby patients with single-hit TP53 and variant allelic frequency (VAF) &gt;50% were classified as obligatory biallelic, patients with VAF between 23-50% as probable biallelic and &lt;23% as probable monoallelic. A threshold of VAF 23% was optimal to separate monoallelic vs biallelic and was based on all-cause mortality. A tree-based model (RandomForestSRC) was used to build a survival model with VAF as a single covariate and minimum node size set to 15 to optimize the cut-off. Using this cut-off, we delineate the epistatic landscape and potential interactions among different TP53 mutational spectra and its fitness. We curated a cohort of 800 patients with TP53 mutations from our institution. In total 36% of the cases carried single hits while 64% had double hits genomic configuration. About 70% of the mutations were missense and were detected at canonical sites (R175H, Y220C, M237I, R273H, R282W, R248Q). We took into consideration 35 features and clustered our cohort of TP53 mutants using factor analysis. When we stratified the cohort based on our predetermined VAF threshold, we found that majority of the variants with high VAF, to be deemed as obligatory biallelic, co-occurred with complex karyotype. These cases were very homogeneous hence had on average a low number of additional variants, likely due to TP53 clones having reduced fitness in the presence of additional mutations. Conversely, patients without complex karyotype were mostly assigned to the monoallelic group due to low to median VAFs. Consequently, these samples had on average a higher number of additional hits, hence a heterogeneous molecular landscape. To substantiate this finding, we noticed that among monoallelic patients two characteristic pairs were observed (TP53-TET2 and TP53-SF3B1) and showed different patterns according to karyotypic associations. Indeed, both pairs in normal karyotype (TP53-TET2, 65%; TP53-SF3B1, 23%) had the highest number of additional mutations on average compared to other monoallelic hits in complex karyotype suggesting that clones resulting by these pairs were advantageous and produced higher fitness driving heterogeneity when together with other mutations. As a preliminary analysis to characterize the fitness landscape of canonical missense TP53 mutations, we investigated whether distinct TP53 mutations conferred differential clonal fitness by implementing a previously published model of stochastic hematopoietic stem cell growth based on the distribution of allelic frequencies across different age groups. Given a fixed stem cell population pool and a constant mutation rate, the distribution of allelic frequencies in the population of corresponding mutations across age can inform the fitness/selection coefficient. The model predicts that high fit mutations will expand more in the population (high VAF) depending on the time the mutation is allowed to expand (age). Based on the literature, we set the stem cell pool to 100,000 and the mutation rate to 1.4E-8.2We limited our analysis to mutations found in at least 10 individual in our cohort and to single hits due to potential epistatic interactions across multiple mutations in the same gene. Given this criterion two mutations R273H and R248Q were analyzed. Interestingly, we observed a 15% increase in fitness gain for R273H compared to R248Q. In summary, mutational heterogeneity and clonal fitness might provide clues to the diversity of TP53 mutational configurations. Our model will be further optimized for the upcoming ASH meeting by incorporating temporal sampling and increasing sample size to define differences in fitness according to mutation site.

Abstract Introduction: HMA monotherapy (HMAm) continues to be the standard of care for HR-MDS. While the addition of VEN to azacitidine (AZA) improved overall survival (OS) and complete remission (CR) rates among older pts with acute myeloid leukemia (AML) over AZA monotherapy, the recently completed phase III VERONA trial of AZA+/-VEN in HR-MDS failed to show an OS benefit for AZA/VEN over AZA monotherapy. Using the icMDS VALIDATE database, we compared outcomes of pts with HR-MDS treated with HMA or HMA/VEN as frontline therapy. Methods: The icMDS VALIDATE database includes over 4000 adult MDS pts who received HMA-based therapy from 32 international centers in 9 countries. For this analysis, we included pts with HR-MDS defined by International Prognostic Scoring System [IPSS] ≥1.5 or IPSS-revised [IPSS-R] ≥4 (at diagnosis or HMA initiation) and treated with HMAm or HMA/VEN as frontline therapy for HR-MDS. We assessed responses based on IWG 2023 criteria (Zeidan A et al, Blood 2023). Composite complete remission (cCR) was defined as CR+CRbi+CRuni+CRh+CRequivalent. We calculated OS from time of HMA initiation to date of death from any cause. Pts lost to follow-up were censored at the date they were last known to be alive. We used Kaplan-Meier methods to calculate OS and compared OS between different groups using the log-rank test. We used Cox and logistic regression models to adjust for baseline prognostic variables as appropriate. The study was funded by an independent grant from Abbvie. Results: A total of 1907 pts met eligibility and were included (1552 AZA, 221 decitabine, 134 HMA+VEN). 479 pts subsequently underwent allogeneic stem cell transplant (allo-SCT; 430 after HMAm [32.6%]; 49 after HMA/VEN [37.1%]). Our cohort was enriched for pts with adverse disease characteristics including complex karyotype (33.6%) and TP53 mutations (28.7%). Compared to pts treated with HMA/VEN, pts treated with HMAm were more likely to be male (p=0.012), have lower baseline platelet counts (p=0.037), peripheral blood (PB) blasts (p=0.004), or bone marrow blasts (p&lt;0.001), and were less likely to have very high risk IPSS-M (p&lt;0.001), TP53 mutations (p&lt;0.001), or complex karyotype (p=0.020). In unadjusted analyses, the rate of cCR was significantly lower in HMAm treated pts compared to HMA/VEN treated pts (27.7% vs. 48.8%, p&lt;0.001). However, CR rate was not significantly different (11.7% vs. 17.1% for HMAm and HMA/VEN, respectively, p=0.22). After adjusting for age, sex, and IPSS-M, pts treated with HMA/VEN were more likely to achieve cCR compared to HMAm with an odds ratio (OR) of 2.49 (95% CI: 1.56-3.96, p&lt;0.001). When separated by TP53 mutation status, the OR for cCR for HMA/VEN vs HMAm was 4.17 (95%CI: 2.14-8.31; p&lt;0.001) and 1.27 (95%CI: 0.54-2.86; p=0.57) for TP53 wild-type and TP53-mutant pts, respectively. In unadjusted analyses, median OS was 17.4 months for HMAm and 19.6 months for HMA+VEN, and OS did not differ significantly by treatment type (p=0.33). For HMAm treated pts, the OS rates at year 1, 2, 3 were 0.65 (95%CI: 0.63-0.67), 0.38 (95%CI: 0.36-0.40), and 0.27 (95%CI: 0.25-0.29), respectively. For HMA/VEN treated pts, the OS rates at year 1, 2, 3 were 0.64 (95%CI: 0.56-0.73), 0.45 (95%CI: 0.36-0.56), and 0.37 (95%CI: 0.27-0.51), respectively. In a multivariate analysis adjusting for age, sex, PB blast, IPSS-M and allo-SCT as a time-varying covariate, treatment with HMA/VEN vs HMAm did not significantly influence OS (hazard ratio (HR) of OS for HMA/VEN vs HMAm: 0.89, 95%CI: 0.69-1.13, p=0.33). When stratified by TP53 mutation status, HR of HMA/VEN vs. HMAm was favorable for TP53 wild-type (HR: 0.47; 95%CI: 0.29-0.74) but not TP53-mutant pts (HR=0.96; 95%CI: 0.66-1.41). Adjusting for other variables in the model, HR for pts who underwent vs. those who did not undergo allo-SCT were 0.65 (95% CI: 0.49-0.85) and 0.36 (95%CI: 0.24-0.53) in TP53 wild-type and mutant patients, respectively. Conclusion: In this large, international retrospective analysis from the icMDS VALIDATE database, HMA/VEN was associated with higher cCR rates—but not CR rates—compared to HMAm among pts with HR-MDS, though we observed no significant differences in OS. In our analysis, clinical benefit from the addition of VEN was most clear in TP53 wild-type pts, and allo-SCT was associated with improved OS regardless of baseline TP53 status. Our analysis was limited by the relatively small number of HMA/VEN-treated pts and heterogeneous real-world treatment patterns.

Abstract Background: Higher-risk myelodysplastic syndromes/neoplasms (HR-MDS) and secondary acute myeloid leukemia (sAML) share overlapping molecular features but both remain clinically diverse with poor prognosis. Machine learning (ML)-based genomic clustering offers an opportunity to redefine disease subgroups beyond traditional clinical prognostic schemes or pathologic classifications. Prognostic scoring systems emphasize outcomes while pathologic classifications morphology resulting in inclusion of patients (pts) with different genetic background into same outcome or morphologic subgroup. We compared our ML-unsupervised clustering (UC) model named molecular nosology1 with the taxonomy model2 to evaluate differences in cluster architecture and clinical relevance in HR-MDS and sAML. Methods We analyzed HR-MDS (≥10% blasts) and sAML pts with available molecular data at diagnosis from a well-annotated cohort. Our molecular nosology model used UC via a binary latent-factor model to generate molecular clusters (MCs). The taxonomy model assigned pts to predefined genomic classes. We compared MC size, genomic enrichment, and overall survival (OS) across diagnostic categories. Concordance was assessed using Adjusted Rand Index (ARI) and Normalized Mutual Information (NMI). Purity and entropy were calculated to assess how concentrated (purity) or dispersed (entropy) each taxonomy group was across MCs. Results Among 898 pts, 367 (41%) had HR-MDS and 531 (59%) had sAML. Median age was 71 (IQR 65–77) years. Compared to sAML, HR-MDS pts had similar age (71 vs. 72, p=0.556) but higher hemoglobin (9.9 vs. 9.3, p&lt;0.001) and platelet counts (91 vs. 50, p&lt;0.001). Normal karyotype was more common in HR-MDS (55% vs. 42%, p&lt;0.001). TET2 (24%), ASXL1 (24%), RUNX1 (23%), and SRSF2 (22%) were the most frequently mutated genes. Using our nosology model, we identified 14 MCs.1 The most frequent were MC2 (normal karyotype) at 22% and MC13 (TP53-complex) at 17%, followed by MC1 (+8/ASXL1/TET2/RUNX1, 12%), MC6 (SRSF2/RAS-pathway, 9%), and MC9 and MC14 (each 8%). Less common clusters included MC12 (5%) and MC3–MC5 (2–3%). For comparison, the taxonomy model included 18 genomic groups: TP53-complex (20%), mNOS (13%), bi-TET2, IDH-STAG2, and no event (each 10%), CCUS-like, SETBP1/-7, and AML-like (each 6%), SRSF2 (4%), del(5q), BCOR/L1, EZH2-ASXL1, and SF3B1 (each 3%), and five rare subgroups (DDX41, der(1;7), U2AF1157, U2AF134, ZRSR2; all &lt;1%). Our MCs aligned closely with several taxonomy groups: 82% of TP53-complex cases were assigned to MC13, 99% of no event cases mapped to MC2, and 97% of del(5q) cases mapped to MC8. Bi-TET2 cases were distributed across MC6 and MC12 (both TET2-enriched); SETBP1/-7 to MC11; and EZH2-ASXL1 cases to MC1 and MC12. In contrast, mNOS, AML-like, and CCUS-like groups were genomically heterogeneous and spanned multiple MCs. ARI and NMI values were 0.391 and 0.458, indicating moderate concordance. Purity was highest in no event (0.989), del(5q) (0.967), and TP53-complex (0.823), and lowest in IDH-STAG2 (0.247), CCUS-like (0.241), and AML-like (0.347), all with high entropy (&gt;2.5), reflecting genomic diversity not captured by taxonomy groups alone. Median OS for the entire cohort was 17 mo (95%CI: 14–20). HR-MDS pts had longer OS vs. sAML (26 vs. 12 mo, p&lt;0.001). OS did not differ significantly between HR-MDS and sAML within most taxonomy groups or MCs, except for MC3 (NA vs. 11 mo, p=0.014), MC6 (111 vs. 15 mo, p&lt;0.001), and MC9 (18 vs. 9 mo, p=0.027) for the nosology model and SF3B1 (129 vs. 23 mo, p=0.033), del(5q) (33 vs. 6 mo, p=0.022), bi-TET2 (25 vs. 8 mo, p=0.019), mNOS (34 vs. 9 mo, p&lt;0.001) for taxonomy. Conclusions Some molecular taxonomy groups showed strong concordance with our nosology-defined clusters, which served as the gold standard for genomically distinct subsets (e.g., TP53-complex, del(5q), and no event), irrespective of diagnosis or blast percentage which may present the stage of the disease. In contrast, taxonomy-defined categories such as CCUS-like, AML-like, and mNOS were more genetically diverse and less aligned with specific clusters in the nosology model. Median OS within most clusters was not significantly influenced by blast count, underscoring the potential of molecular-driven clustering to reveal underlying disease biology not captured by morphology and to refine classification in MDS/AML and sAML with few exceptions (SF3B1 or biTET2). Ref 1.Kewan, Durmaz et al.Nat Commun 2023 2.Bernard, et al.Blood 2024

Abstract Background & aim: Myelodysplastic syndromes with isolated deletion of chromosome 5q (MDS-del(5q)) are associated with low-risk features and favorable prognosis. In contrast, TP53 multihit alterations, typically reflecting biallelic inactivation, are associated with high-risk features and adverse outcomes across MDS subtypes. Although current classification systems exclude MDS-del(5q) cases with TP53 multihit from low-risk categories, the prognostic significance of these alterations in this specific context remains unclear. Methods: We conducted an international, multicenter, retrospective study comparing MDS-del(5q) per 2017 WHO criteria with TP53 multihit alterations (MDS-del(5q) TP53 multihit) from 21 international institutions, to MDS with low blast counts with TP53 multihit alterations without isolated del(5q) (MDS-LB TP53 multihit) from the public data from the study of Bernard et al., Nat Med 2020. Clinical and biological data were collected at diagnosis. Genetic profiling included G-banding and NGS of myeloid genes. TP53 multihit was defined as &gt;1 TP53 mutation or a single mutation with 17p deletion, copy-neutral loss of heterozygosity (LOH), or variant allele frequency (VAF) ≥50%. Patients were stratified as lower- or higher-risk based on IPSS-R and IPSS-M scores. Lower-risk included those with IPSS-R ≤3.5 points or very-low, low, or moderate-low IPSS-M, while higher-risk included those with IPSS-R &gt;3.5 points or moderate-high, high, or very-high IPSS-M. Clinical, molecular features, overall survival (OS), and AML progression were compared between MDS-del(5q) TP53 multihit and MDS-LB TP53 multihit groups. Finally, outcomes between patients with likely biallelic TP53 multihit status, defined as harboring a single TP53 mutation accompanied by a co-occurring deletion/LOH of 17p or a TP53 VAF ≥50%, versus those considered less likely to be biallelic, thus still classified as multihit, defined as having &gt;1 TP53 mutation but a combined VAF &lt;50%, were compared in both MDS-del(5q) and MDS-LB groups. Statistical analysis was performed using R (version 4.2.2). Results: We included 113 patients with a median follow-up of 81.1 months (95% CI 74.9–NR). A total of 45 (39.8%) were MDS-del(5q) TP53 multihit, and 68 (60.2%) MDS-LB TP53 multihit. Compared to MDS-LB TP53 multihit, patients with MDS-del(5q) TP53 multihit had significantly higher platelet counts (209 ×10⁹/L vs. 77 ×10⁹/L) and were more frequently classified as lower-risk by both IPSS-R (75.4% vs. 9.8%) and IPSS-M (90.2% vs. 24.6%). The median number of mutations per patient, excluding TP53, was 1 in both groups, and only SF3B1 mutations were significantly more frequent in the MDS-del(5q) TP53 multihit group compared to MDS-LB TP53 multihit (20.5% vs. 2.9%; p&lt;0.01). Regarding survival, MDS-del(5q) TP53 multihit patients showed an improved OS compared to MDS-LB TP53 multihit (median OS of 57.0 months (95%CI, 43.0–112.0) vs 14.0 months (95%CI, 8.6–19.0); p&lt;0.01). Moreover, while the risk of progression to AML at 48 months were comparable between groups (34.9% for MDS-del(5q) TP53 multihit and 33.0% for MDS-LB TP53 multihit; p=0.8), a significant difference was observed in the timing of AML progression: median time to AML evolution of 31.7 months (IQR 23.4–55.3) in the MDS-del(5q) TP53 multihit group and 7.2 months (IQR 4.1–12.9) in the MDS-LB TP53 multihit group (p&lt;0.01). Notably, no significant differences in outcomes were found between TP53 multihit and most likely biallelic cases in both MDS-del(5q) and MDS-LB cohorts. The impact of complex karyotype (CK) in MDS-LB TP53 multihit was also explored. MDS-LB TP53 multihitwith CK showed a significantly worse OS compared to MDS-LB TP53 multihitwithout CK (median OS of 10.0 months (95% CI 7.5–17.0) vs 40.0 months (95% CI 14.0–NA); respectively; p&lt;0.001. However, the incidence of AML and median time to AML evolution were comparable between both groups. Finally, OS between MDS-LB TP53 multihit patients without CK and the MDS-del(5q) TP53 multihit cohort was compared. Median OS was significantly shorter in the former group (median of 40 months) compared to the latter (median of 61 months) (p &lt;0.01) Conclusions: These findings underscore that, in contrast to other TP53-multihit MDS subtypes, MDS-del(5q) with TP53 multihit alterations constitute a clinically distinct entity with better outcomes, thereby warranting reconsideration of its place in current classification systems.

Abstract Outgrowth of a founder mutant clone is an initial event in leukemogenesis. The corresponding somatic hit likely conveys a fitness advantage over a polyclonal background. Several factors may modulate the competitiveness of hematopoietic stem or progenitor cells, including aging, genotoxic stress, repeated cycles of stress hematopoiesis, and inherited genetic fitness deficiency. The nature of these conditions provides a particularly fertile environment in which only certain mutant clones thrive. For instance, chemotherapy facilitates expansion of PPMD1MT or TP53MT clones, aging-related loss of fitness predisposes to outgrowth of TET2MT clones, while many inherited bone marrow failure (BMF) syndromes are associated with specific clonal acquisitions due to somatic gene rescue. Identification of factors enabling the expansion of clones with specific mutations may help to develop targeted preventive, screening, or therapeutic strategies. Recently, high levels of erythropoietin (EPO) induced by frequent blood donation were shown to favor the emergence of DNMT3AR882 clones due to their increased EPO sensitivity1. We theorized that this may be a more general phenomenon operating in other diseases characterized by high EPO levels. Thus, we selected 644 patients in whom endogenous serum EPO levels had been assessed and who underwent mutational NGS analysis. Given that this cohort consisted of patients with hematologic neoplasms, EPO levels were broad with the majority falling outside the normal clinical reference range. For this study we used EPO levels ≥100mU/mL as the threshold to define high and low EPO groups. This threshold laid above the 75th percentile for our cohort (M=31.1; IQR=109.7) to capture outliers more likely to reflect biologically significant erythropoietic stress. DNMT3AMT were present in 14% of high EPO and in 12% of low EPO groups (p=0.5). However, in the high EPO group, R882 constituted 32% of DNMT3AMT while in the low EPO group R882 was found in only 11% of DNMT3AMT cases (p=.02). In a reverse fashion, the mean level of EPO in DNMT3AR882 was 441.7mU/mL while it was 215.3mU/mL in other DNMT3AMT carriers (p=0.03) and 186.2mU/mL in DNMT3AWT cases (p&lt;0.001). To assess whether the effect on DNMT3A was dependent on EPO levels rather than anemia, we determined mean hemoglobin levels in R882 (µ=10.2g/dL), other DNMT3AMT (µ=10.4g/dL), and wild type cases (µ=10.9g/dL) and found no significant differences (p=0.33). To assess whether R882-EPO sensitivity was related to EPO-R expression levels, we compared EPO-R expression in R882 (µ=2.7), non-R882 (µ=2.6) mutations, and WT cases (µ=2.8) and found no significant difference. To assess whether the impact of high EPO states was specific to DNMT3AMT we next analyzed the distribution of other mutations. We observed that frameshift mutations in BCOR (p = 0.013) and BCORL1 (p=0.036) were significantly more frequent in high EPO patients. BCORMT was also overall more prevalent in the high EPO group (p=.001), while BCORL1 frequency was similar across EPO strata (p=0.77) showing a similar trend to DNMT3AMT. Beyond these genes, other patterns emerged, particularly within CH-associated genes. Individuals with U2AF1MT had elevated EPO (p=.0087), with variant-specific enrichment: p.S34F was more common in high EPO (p=.038) whereas p.Q157P predominated in low EPO patients (p=0.038). No significant EPO associations were observed for other CH-related genes such as ASXL1, CBL, and TET2. The limitations of this study notwithstanding, these findings support a biologically meaningful relationship between elevated EPO levels and the acquisition or enrichment of specific CH-associated mutations in patients with hematologic malignancies. The association of high EPO with DNMT3AR882, frameshift mutations in BCOR/L1, and variant-specific enrichment in U2AF1 suggests that EPO-driven stress may contribute to clonal selection or expansion. Our study of high EPO levels and DNMT3AMT analysis illustrates that external conditions may influence selection pressure for specific mutations. However, selection pressure may be a complex combination of factors. Non-malignant conditions with high EPO, such as hypoxia or intrinsic BMF, may also create conditions facilitating the acquisition of specific somatic hits. Recognition of evolutionary pressures and their associations with specific mutations may improve our understanding of CH pathogenesis, and conceptualization of therapeutic or preventative measures.

Abstract Introduction: Standardized reporting of clinical trials results for MDS is essential to improve clinical interpretation and cross-study comparison. However, reporting of patient characteristics, response criteria, and endpoints in publications is often inconsistent; there is no systemic analysis of MDS trial reporting available. We conducted a systematic review of published MDS trial manuscripts on behalf of the international consortium for MDS (icMDS) to assess variability in reporting practices. Methods We searched ClinicalTrials.gov to identify all clinical trials registered for adults (≥18 years) with MDS that reported results between 2015-2024. Clinical trials that included acute myeloid leukemia (AML) or MDS/myeloproliferative neoplasms (MPN) were included if they enrolled ≥5 MDS patients. We excluded trials without an MDS cohort; non-therapeutic trials; trials focused on transplant interventions; or those which enrolled solid malignancies or other hematologic malignancies (chronic myeloid leukemia or lymphoid diseases). Finally, trials were required to have a manuscript available on Larvol, PubMed, or Google Scholar. Trials were categorized by disease risk (lower-risk [LR] vs. higher-risk [HR]) and trial phase (early phase [EP] vs. late phase [LP]). Results We identified 502 MDS trials on ClinicalTrials.gov, of which 351 did not meet inclusion criteria and 79 lacked a manuscript. A total of 72 trials (32 EP, 40 LP) with 80 publications (34 EP, 46 LP) were analyzed. Frequently reported baseline characteristics included age (100% EP, 100% LP), disease risk (74% EP, 74% LP), Eastern Cooperative Oncology Group performance status (85% EP, 72% LP), prior treatments (71% EP, 67% LP), and RBC transfusion dependency (32% EP, 70% LP). Less frequently reported characteristics included blood counts (hemoglobin [Hb; 38% EP, 54% LP], platelet count [38% EP, 54% LP], neutrophil count [24% EP and LP]) and bone marrow blasts (29% EP, 43% LP). Although disease risk was widely reported, definitions varied: IPSS and IPSS-R were each reported in 54% of manuscripts, while IPSS-M appeared in only 3%. Cytogenetic risk was separately reported in 39% of manuscripts (38% EP, 39% LP), and mutational data in 45% (47% EP, 43% LP). Responses per IWG 2006 criteria were reported in 84% of manuscripts. The primary endpoint involved safety/tolerability in 85% of EP manuscripts, though definitions were variable; recommended phase 2 dose was the most common (26% of EP manuscripts). In LP trials, primary endpoints were risk-specific: transfusion independence (TI) in 77% of LR, overall response rate (ORR) in 28% of HR, and complete remission (CR) or overall survival (OS) in 22% of HR. In HR manuscripts, CR was reported in 100%, ORR in 73%, hematologic improvement (HI) in 48%, RBC-TI in 23%, and OS in 80%. However, seven different definitions were used for ORR: CR + marrow CR + partial remission + HI per IWG 2006 was most common (35%). Event-free survival was reported in 25%; progression-free survival and relapse-free survival in 13%; and leukemia-free survival in 5%. Early mortality rate was reported in 35% (18% EP, 56% LP) and transplant rate in 58% (50% EP, 67% LP). Only 47% of HR and 90% of LR manuscripts identified HI-eligible patients. In LR-MDS, RBC-TI was reported in 72% of manuscripts but used six definitions. The most common were RBC-TI ≥8 weeks at any time during treatment (24%), ≥8 weeks within 28 weeks of treatment (13%), ≥8 weeks with Hb increase ≥1.0 (4%), ≥12 weeks with Hb increase ≥1.5 (4%), and ≥16 weeks within 24 weeks of treatment (12%). The remainder did not report RBC-TI, did not define it, or used a custom definition not used in another trial. HI was reported in 80% of LR papers with most of those reporting HI using IWG 2006 criteria (90%). Conclusion Reporting of baseline characteristics, response criteria, and outcomes is inconsistent in MDS clinical trials, with wide variability in response definitions, including ORR and TI. This heterogeneity limits interpretability, hampers historical comparisons and may obscure efficacy signals. Our findings highlight the need for standardized reporting guidelines to ensure clarity and consistency in MDS trial publications. As a next phase of this effort, we will conduct a formal Delphi process among icMDS experts to establish consensus recommendations for minimal and optimal MDS clinical trial reporting in manuscripts by disease risk (LR/HR) and trial phase (EP/LP).

Abstract Introduction TP53MT are associated with poor outcomes in MDS, especially in the context of biallelic MT. We have previously reported on outcomes of pts with HR-MDS with TP53MT who received HMA in the VALIDATE dataset (Kewan T et al, ASH 2023). Here we provide expanded analyses focusing on outcomes post allo-HCT, and we explore the prognostic significance of different classification methods for biallelic TP53MT. Methods The VALIDATE database includes 4,732 pts with MDS who received HMA-based frontline therapy from 32 international centers in 9 countries. For this study, only pts with HR-MDS with molecular data at time of diagnosis were included. Biallelic TP53MT status was assessed using three classification schemes: WHO 2022, ICC 2022, and a VAF-based Cleveland Clinic Foundation (CCF) method.1TP53 copy neutral loss of heterozygosity (CN-LOH) was evaluable in 386 pts (118 had TP53MT). Treatment responses were evaluated using IWG 2023 criteria (Zeidan A et al, Blood 2023). Composite complete remission (cCR) was defined as CR+CRbi+CRuni+CRh+CRequivalent. We calculated OS from time of HMA initiation to date of death or last follow up. Unsupervised clustering (MOSAIC framework) was applied to identify molecular subgroups within the TP53MT cohort. The study was funded by an independent grant from Abbvie. Results A total of 1,485 pts were included. Median age was 69 years (IQR: 62–76), with 66% male pts. Median bone marrow blast was 7%, and 28% had a complex karyotype. Treatment regimens included azacitidine (68%), decitabine (15%), HMA/Venetoclax (8%), and other HMA combinations (9%); 34% underwent allo-HCT. Overall, 392 (26%) had TP53MT with 430 TP53 mutations (missense: 316; truncating: 89). Biallelic TP53MT % varied by classification: 72% (WHO), 84% (ICC), and 85% (CCF). Compared to TP53 wild-type (TP53WT) pts, pts with TP53MT had worse OS (median: 11.5 vs. 23.9 months [mo], p&lt; 0.001), were younger (68 vs. 70 years, p=0.039), and had lower counts at diagnosis. Complex karyotype (81% vs. 14%) and chromosomal abnormalities were more frequent in TP53MT pts. Pts with TP53MT also had fewer co-mutations in other genes. Response to HMA was evaluable in 1,094 pts: cCR and CR were 32% and 13%, respectively. TP53MT pts had higher cCR (39% vs. 29%, p=0.001) than TP53WT, but similar CR rates (16% vs. 12%, p=0.093). According to WHO 2022, biallelic TP53MT had higher CR rates than monoallelic TP53MT (18% vs. 8%, p=0.03), but similar cCR. ICC and CCF classifications did not differentiate response rates. Median OS did not differ by TP53MT allelic status using WHO or ICC definitions. However, using the CCF method, pts with biallelic TP53MT had shorter OS than monoallelic TP53MT (10.4 vs. 17.2 mo, p=0.038). In multivariable models adjusted for age, gender, and allo-HCT, only the CCF-defined biallelic TP53MT group had significantly worse OS (HR: 1.6; 95% CI: 1.1–2.4). TP53MT pts undergoing allo-HCT had improved OS regardless of allelic status. Median OS for TP53MT pts with allo-HCT was 18.9 vs. 9.2 mo without all-HCT. This benefit was observed across WHO, ICC, and CCF classifications. However, a TP53MT VAF ≥19% predicted worse OS even post allo-HCT (14.6 vs. 47.1 mo, p&lt;0.001). At 1 year, the survival rate was 78% (95%CI: 69-89%) in TP53MT pts who underwent allo-HCT and had cCR vs. 68% (95%CI: 55-84%) in pts who did not have cCR. However, 1 year survival rate was significantly higher for pts with TP53MT who did not have allo-HCT and achieved cCR (60%, 95%CI: 48-76%) vs. no cCR (26%, 95%CI: 20-35%). Unsupervised clustering of 335 TP53MT pts identified 9 molecular clusters (MCs). MC2, characterized by low TP53MT VAF (median 17%), fewer co-mutations, and frequent del17p, was associated with significantly improved OS (17.9 mo) and predicted favorable outcome (HR for death: 0.6; 95% CI: 0.4–0.8). Other clusters were enriched for adverse features (e.g., high VAF, multi-hit TP53MT).Conclusions The CCF method appears to best classify biallelic TP53MT pts with worse survival in the absence of accurate assessment of LOH status. Treatment response per IWG 2023 for TP53MT pts was associated with OS only in non-transplanted pts. Allo-HCT improved survival across TP53MT subsets, but TP53 VAF ≥19% at diagnosis remained a strong negative prognostic factor. Integrative clustering revealed a less aggresive molecular subset among TP53MT pts, suggesting refined risk stratification may guide therapy in this high-risk population. Ref: 1.Bahaj et al. J Hematol Oncol 2023.

Abstract Introduction: Marrow complete remission (mCR) in 2006 IWG criteria for MDS (Cheson B et al, Blood 2006) reflects achieving bone marrow (BM) blast percentage below 5% but is frequently not associated with meaningful count recovery. While mCR + hematologic improvement (HI) does reflect wide ranges of count improvement or transfusion reductions, HI is difficult to measure accurately in routine clinical practice. The 2023 International Working Group (IWG) response criteria (Zeidan A et al, Blood 2023) eliminated the mCR category without meaningful count recovery and reclassified mCR associated with meaningful count recovery into specific “less-than-CR” categories. Still, many clinical trials continue to use mCR as a secondary efficacy endpoint or as a part of overall response rate (ORR). Within the icMDS VALIDATE database, we assessed the association of mCR with OS in hypomethylating agent (HMA)-treated higher risk (HR)-MDS patients among both (1) transplanted and (2) non-transplanted patients. Methods We included patients with HR-MDS (defined as IPSS ≥1.5 and/or IPSS-R &gt;3.5) who received HMA-based therapies from the international icMDS VALIDATE dataset. We evaluated the best response by IWG 2006 criteria into CR, mCR, or no CR/mCR. We then reclassified patients with mCR per IWG 2023 criteria into either (A) having achieved a composite CR (cCR) defined as CR + CR equivalent (CRequ) + CR with bilineage count recovery (CRbi) + CR with unilineage count recovery (CRuni) + CR with partial hematologic recovery (CRh) or (B) not having achieved cCR (no cCR). OS was calculated from time of HMA initiation to date of death or last follow-up by using 6-month landmark analyses. We used Kaplan-Meier methods to estimate OS, and the Log-rank test to compare OS. VALIDATE is supported by an independent grant from AbbVie. Results A total of1049 patients met eligibility.Median age of patients was 69 (range 21-95), 64% were men. While 61% received azacitidine, 17% received decitabine, and 22% received HMA-based combination therapy. In total, 37% underwent subsequent allogenic stem cell transplantation (allo-HCT). Based on IWG 2006 criteria, 17%, 33%, and 50% achieved CR, mCR, and no CR/mCR as their best response, respectively. Patients achieving CR had superior median OS (25 months, 95% CI: 21-34 months) compared to those with mCR (16 months, 95% CI: 13-18 months; p=0.038) and no CR/mCR (15 months, 95% CI: 12-17 months; p=0.001). In patients who received a subsequent allo-HCT, the median OS for patients with mCR (30 months, 95% CI: 21-54 months; 1 year OS: 71%, 2 year OS: 55%) did not significantly differ compared to patients with CR (59 months, 95% CI: 25 months-not reached, p=0.80; 1 year OS: 73%, 2 year OS 62%) and patients with no CR/mCR (32 months, 95% CI: 21-45 months, p=0.46; 1 year OS: 69%, 2 year OS 54%). In contrast, in patients treated with HMA therapy alone without subsequent allo-HCT, median OS for patients with mCR (11 months, 95% CI: 9-15 months; 1 year OS: 46%, 2 year OS: 23%) did not significantly differ compared to patients with no CR/mCR (11 months, 95% CI: 9-14 months, p=0.85; 1 year OS: 47%, 2 year OS: 22%) but was significantly shorter compared to patients with CR (20 months, 95% CI: 17-28 months, p&lt;0.001; 1 year OS: 69%, 2 year OS: 46%). Patients with mCR by IWG 2006 (N=347) were reclassified per IWG 2023 into having either achieved a cCR (N=219, 63%) or no cCR (N=128, 37%). Specifically, patients with mCR were reclassified per IWG 2023 into CR (4.9%), CRequ (0.6%), CRbi (26.8%), CRuni (29.4%), CRh (1.4%), PR (0%), HI (10%), no response (21.9%) and PD (4.9%). Patients with mCR who were reclassified into cCR had an improved median OS (16 months, 95% CI: 15-26 months; 1 year OS: 62%; 2 year OS: 43%) compared to patients reclassified into no cCR per IWG 2023 (13 months, 95% CI: 11-17 months, p=0.023; 1 year OS: 52%; 2 year OS: 31%). Conclusions Using the large icMDS VALIDATE dataset, we found that achievement of mCR by 2006 IWG criteria was not associated with improved OS compared to patients who did not achieve CR/mCR. Reclassification of mCR using IWG 2023 highlights the heterogeneity within the mCR group and suggests that IWG 2023 criteria stratifies outcomes in patients previously labeled as mCR by IWG 2006. IWG 2023 should be the standard used for ORR assessment in all future clinical trials involving patients with HR-MDS.