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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<0.001) and platelet counts (91 vs. 50, p<0.001). Normal karyotype was more common in HR-MDS (55% vs. 42%, p<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 <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 (>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<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<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<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 Introduction: Iptacopan, the first oral complement inhibitor, offers an attractive alternative to parenteral complement blockers in paroxysmal nocturnal hemoglobinuria (PNH). While clinical trials have confirmed its efficacy vs terminal C5 inhibition, real-world data on breakthrough hemolysis (BTH), complement-activating conditions (CACs), and switching patients with satisfactory response to prior therapy (hemoglobin [Hgb] ≥10 g/dL) are limited. We studied a large multi-institutional PNH cohort treated with iptacopan. Methods: We performed a retrospective analysis of 62 patients with PNH who received iptacopan for ≥3 months between FDA approval in December 2023 and April 2025 (mean exposure, 1.01 years; 62 patient-years). Patients from the Cleveland Clinic network and Mayo Clinic were analyzed. Demographics, prior therapies, reasons for transition, Hgb, lactate dehydrogenase (LDH), platelet counts, thrombotic events, CACs, BTH, and adverse events were extracted. Efficacy was assessed separately for treatment-naive patients and treatment-experienced patients (sub-optimal responders [Hgb <10 g/dL] and optimal responders to prior therapy). Results: Overall, 12 of 62 patients were treatment naive and 50 switched from prior therapy (of whom 21 had sub-optimal responses and 29 had optimal responses). In the 50 patients who switched, 60% transitioned from ravulizumab, 30% from pegcetacoplan, 8% from eculizumab, and 2% from ravulizumab and danicopan. The primary reasons for switching were the convenience of oral medications (n=17), extravascular hemolysis or BTH (n=10), prior medication side effects (n=5), desire to further improve Hgb (n=6), and not documented (n=12). A total of 4 patients discontinued iptacopan (2 pregnancies, 1 insurance reversal, 1 intolerable gastrointestinal toxicity). Three patients reported headaches, and 1 reported abdominal pain; all resolved within 1 week from treatment start. Across the 62 patient-years, no thrombotic events occurred, 18 CAC episodes were managed with iptacopan 200 mg BID (10 infections, 1 heart-failure exacerbation, 2 minor surgeries, 1 traumatic brain injury, 2 pancreatitis, 2 pregnancies), and none triggered BTH. Overall, 3 clinically significant BTH events (in 3 patients; 4.8% annualized) were recorded: 2 infection-related (managed outpatient) and 1 alcoholic pancreatitis; all resolved with a 1- to 2-day increase to iptacopan 400 mg BID ± single-dose eculizumab. Two hemolytic events secondary to non-adherence were reported (4 days after stopping iptacopan). These resolved after resuming iptacopan 200 mg BID without need for hospitalization. In treatment-naive patients, mean Hgb increased significantly by 1.87 g/dL from iptacopan initiation (baseline) to 3 months (9.9±1.9 to 11.8±1.3 g/dL; P=.005), sustained until last follow-up at 12 months. LDH decreased by 369 U/L at 3 months (P=.058), sustained through 12 months. No significant change was seen in platelets, absolute neutrophil count (ANC), or white blood cell (WBC) count. In treatment-experienced sub-optimal responders, mean Hgb increased significantly by 2.16 g/dL from baseline to 3 months (8.6±.89 to 10.8±2.1; P<0.001). At 12 months, 85% of patients had increased Hgb compared with baseline (median increase: 3.31±1.62 g/dL). LDH decreased significantly from baseline to 3 months by 229 U/L (P=.03), with no significant changes noted in LDH from 3 to 12 months or in platelets, ANC, or WBC counts. In previously treated complement inhibitor responders, mean Hgb increased significantly by 0.75 g/dL from baseline to 3 months (12.0±1.3 to 12.8±1.7 g/dL; P=.004), with 79% showing improvements from baseline at 12-month follow-up (median increase: 1.16±0.82 g/dL). LDH decreased significantly by 45 U/L from baseline to 3 months (P=.03), with no further significant changes from 3 to 12 months. Conclusions: In this real-world cohort, iptacopan provided substantial and durable hemoglobin improvement across naive and previously treated patients with PNH, with meaningful reduction in hemolytic parameters, absence of thrombosis, and low BTH rate predominantly linked to infection. Patients with previous satisfactory responses also showed improved Hgb levels. The favorable safety profile and high treatment persistence underscore iptacopan's role as an effective first-line or switch therapy and support its incorporation into evidence-based sequencing algorithms in the evolving PNH treatment landscape.

Abstract Introduction: The therapeutic landscape for paroxysmal nocturnal hemoglobinuria (PNH) has rapidly evolved with multiple proximal complement inhibitors now available, including pegcetacoplan (C3 inhibitor) and iptacopan (oral factor B inhibitor). While clinical trials have established individual drug efficacy compared with terminal complement inhibitors, real-world evidence regarding therapeutic transitions between proximal complement inhibitors remains extremely limited. As patients and clinicians increasingly seek to optimize treatment through sequential therapy approaches, understanding the outcomes of transitioning from pegcetacoplan to iptacopan becomes critical for evidence-based treatment sequencing in this rare hematologic disorder. Methods: We conducted a retrospective multicenter analysis across 3 academic medical centers (Cleveland Clinic, Mayo Clinic, Levine Cancer Institute) that evaluated 15 consecutive patients with PNH who were considered for transition from pegcetacoplan to iptacopan. Patients had confirmed PNH by flow cytometry and ≥3 months pegcetacoplan exposure. After switching to iptacopan, we assessed treatment acceptance rates, demographic characteristics, clinical outcomes including hemoglobin and lactate dehydrogenase (LDH) levels, and safety parameters. Responses to iptacopan were classified as optimal (hemoglobin >10.5 g/dL with clinical improvement) or suboptimal. Statistical analysis used paired t tests for continuous variables. Results: Of the 15 patients evaluated (median age [range]: 53 [22-81] years; 73% female), 14 patients (93.3%) elected to transition to iptacopan, demonstrating high treatment acceptance. Disease subtypes included classic PNH (36%) and PNH (64%) in the setting of another bone marrow disorder (n=7), multiple myeloma (n=1), and myelofibrosis (n=1). Median (range) duration of pegcetacoplan treatment pre-switch was 3 months (2-7 months), and median (range) duration of iptacopan treatment was 24 months (6-36 months). Among patients who transitioned, 79% (11/14) achieved hemoglobin improvement, with a mean increase from 9.2±1.8 to 10.8±2.1 g/dL (P=.028). Overall, optimal response was achieved in 64% (9/14) of patients. Response rates varied significantly by disease subtype: 80% in patients with classic PNH vs 56% in patients with PNH and aplastic anemia, with particularly poor outcomes in patients with concurrent hematologic malignancies (0%). LDH levels improved in 86% of patients, decreasing from 400±152 to 310±95 U/L (P=.015). PNH clone sizes remained stable throughout transition (erythrocyte: 75.1%±9.2% vs 75.4%±9.4%, P=.62; granulocyte: 95.0%±3.9% versus 95.2%±4.0%, P=.45). Treatment was well tolerated with no serious adverse events, breakthrough hemolysis, thrombosis, or discontinuations required. Two patients experienced mild self-limited gastrointestinal symptoms. Conclusions: This first multicenter real-world analysis demonstrates that the pegcetacoplan-to-iptacopan transition provides clinical benefit in the majority of this initial set of patients with PNH, with significant improvements in hemoglobin and an excellent safety profile while maintaining clone stability. The high acceptance rate suggests that patients prefer oral therapy over subcutaneous administration. These findings address a critical knowledge gap in proximal complement inhibitor sequencing, suggesting that iptacopan is an effective therapeutic option for patients with inadequate pegcetacoplan response and supporting the development of evidence-based treatment algorithms for optimal PNH care in the era of multiple complement inhibitor options.