Onyee Chan

From the 2026 National Summit on Hematologic Cancers

Myelodysplastic syndromes (MDS) with isolated deletion of chromosome 5q [MDS-del(5q)] constitute a distinct biological entity traditionally associated with favorable outcomes, although up to one-quarter of patients progress to acute myeloid leukemia (AML). Existing prognostic models, developed in heterogeneous MDS populations, may not adequately capture risk within this subgroup. We assembled an international cohort of 682 patients with MDS-del(5q) to evaluate the performance of the Revised International Prognostic Scoring System (IPSS-R) and its molecular version (IPSS-M), identify prognostic variables, and develop a disease-specific prognostic tool, the IPSS-del(5q). Most patients were classified as lower risk by IPSS-R (94.4%) and IPSS-M (85.5%), yet both systems showed limited discriminatory ability (concordance indices [C-indices] ≈0.5). Independent adverse prognostic factors included age of ≥70 years, male sex, anemia (hemoglobin ≤10 g/dL), thrombocytopenia (platelet count ≤100 × 109/L), the presence of 1 additional chromosomal abnormality, ≥2 gene mutations, SF3B1 mutations, and high-risk TP53 status. Six variables were included in the IPSS-del(5q), stratifying patients into standard-risk (74.3%) and high-risk (25.7%) groups with significantly different leukemia-free survival (69.2 months vs 32.0 months, respectively; P< .01). Moreover, this model reclassified 19.1% of patients in lower-risk IPSS-R group and 14.6% of those in lower-risk IPSS-M group into the high-risk IPSS-del(5q) group. However, its discriminative power remained modest, with a C-index of 0.60. Overall, to our knowledge, this study provides the most comprehensive prognostic evaluation of MDS-del(5q) to date, demonstrates the limited discriminatory capacity of existing MDS scores in this entity, and underscores the need to develop refined disease-specific prognostic approaches for this MDS subtype.

Acute myeloid leukemia (AML) is a biologically heterogeneous hematologic malignancy, and racial disparities in outcomes remain incompletely characterized. This retrospective study analyzed 677 patients diagnosed with AML at Moffitt Cancer Center (2014-2024) to evaluate the impact of race on genomic profiles and clinical outcomes. The cohort comprised 18.6% Black, 19.1% Hispanic, and 62.3% White patients. While ELN 2022 risk groups and most driver mutations were similarly distributed, Black patients exhibited a higher frequency of KRAS mutations (p < 0.05). With a median follow-up of 3.3 years, median overall survival (OS) was 2.2 years for White, 1.5 years for Black, and 2.4 years for Hispanic patients (p = 0.045). Notably, no survival differences existed within favorable or adverse ELN risk categories; however, Black patients with intermediate-risk disease experienced significantly inferior OS compared to White (p = 0.02) and Hispanic patients (p = 0.003). Among those receiving intensive induction, Black patients had significantly worse OS (p ≤ 0.001), while Hispanic patients treated with lower-intensity regimens demonstrated inferior OS compared to White patients (p = 0.01). In multivariable analysis, race was not an independent predictor of OS. Survival was independently driven by prior myeloid malignancy, ELN risk, allogeneic HCT, and mutations in TP53 and IDH2. Regarding race-specific molecular drivers, TP53 and IDH2 mutations were associated with OS in White patients, TP53 in Black patients, and IDH1 in Hispanic patients. These findings suggest that while racial disparities exist in specific clinical subgroups, they are primarily driven by distinct molecular profiles, cytogenetic heterogeneity, and patient-specific clinical factors rather than race alone.

Figure S5. Changes in signaling in BM of trisomy 8+ TN-MF patient and MYC MF mice. Figure S6. Effects of silencing S100a9 in MYC-driven MF or overexpression of S100a9. Figure S7. Effects of inhibition of S100a9 or MYC in MYC-driven MF. Figure S8. Synthesis and Characterization of Tasquinimod. Figure S9. Synthesis and Characterization of MYCi975.

Supplementary Table 7. Targeted Next Generation Sequencing (NGS) panels used for the Moffitt Cancer Center, Nice University Hospital, and University of Maryland Cohorts.

Supplementary Table 2. Predictors of complete response with (CR) or without (CRi) count recovery.

Supplementary Figure 10. Nested Bootstrap Analysis.

Supplementary Figure 1. Study Flow and Model Development Pipeline.

Supplementary Figure 12. Comparison of Risk Group Classifications Between the Moffitt Model vs. Other Prognostic Models.