Session: 618. Acute Myeloid Leukemias: Biomarkers and Molecular Markers in Diagnosis and Prognosis: Poster III
Hematology Disease Topics & Pathways:
Research, Acute Myeloid Malignancies, AML, Translational Research, Clinical Practice (Health Services and Quality), Diseases, Myeloid Malignancies
Objective: To explore the prognostic impact of monocytic differentiation accounting for mPRS in a single-center cohort of AML pts treated with Ven-Azacytidine (Aza).
Methods & Results: We included 86 newly diagnosed AML pts sequentially accrued to our registry (NCT05326919) who underwent morphologic, cytogenetic, genomic, and multiparameter flow cytometry (MFC)-based phenotypic assessments, and who received Ven-Aza as frontline therapy between Jan 2017 and Jan 2024. Median age was 73 IQR [69, 77] years and 26 (30%) had a morphological diagnosis of monocytic AML (FAB 4/5). Most pts (75, 87%) were classified as ELN 2022 adverse risk, while mPRS classified 36 (42%), 24 (28%) and 26 (30%) pts as higher, intermediate and lower benefit respectively.
Monocytic blasts (mono-blasts) were defined as SSClow-int/CD45low/+ blasts expressing ≥2 monocytic markers among CD4, CD36 and CD64. Additional markers (CD11b, CD14) were available in 42 (49%) and used in a confirmatory subanalysis. Expectedly, the proportion of mono-blasts among CD45+ cells (referred as mono-blasts/CD45+) was higher in FAB M4/5 AMLs than in non-M4/5 AMLs (17% IQR [11-28] vs 3% IQR [1-8], p<0.001).
We analyzed the correlations between mono-blasts/CD45+ as a continuous variable and baseline demographic, clinical and genetic variables. Higher white blood cell count (WBC, p=0.001), presence of TET2 (p=0.003), N/KRAS (p=0.026), and ASXL1 mutations (p=0.035) significantly correlated with increasing proportion of mono-blasts, while this fraction was similar across ELN22 (p=0.27) or mPRS (p=0.19) categories.
Higher mono-blasts/CD45+ significantly and negatively influenced the odds of achieving complete remission (CR) in both univariable (OR 0.99 95%CI [0.98-1.00], p=0.013) and multivariable models (OR 0.83 95%CI [0.72-0.93], p=0.006) accounting for Log10(WBC) (OR 0.21 95%CI [0.05-0.70], p=0.019), age (p=0.2), and mPRS classifier (p=0.05). Substituting mPRS for ELN2022 led to similar results, while FAB M4/5 status did not influence response (p=0.3).
With a median follow-up of 60.0 months, median overall survival (OS) in the cohort was 20.2 IQR [9.1-68.1] months. As a continuous variable, a higher proportion of mono-blasts/CD45+ adversely impacted OS in univariable (HR 1.03 95%CI [1.01-1.05], p=0.005) and in multivariable (HR 1.02 95%CI [1.01-1.04], p=0.02) analysis encompassing age (p=0.04), Log10(WBC) (p=0.07) and mPRS (p=0.12).
Maximally selected rank statistics identified 10% as the optimal cutoff to dichotomize mono-blasts/CD45+ in our cohort, with 34 (40%) mono-blastshigh and 52 (60%) mono-blastslow pts. There were no significant differences in ELN 2022 or mPRS genetic risk between these groups. Twelve (20%) of 60 non-FAB-M4/5 pts were reclassified as mono-blastshigh. Mono-blastshigh pts displayed lower rates of CR (4/28 vs 19/43, p=0.01). The mono-blastshigh status was associated with poorer OS (median 10.3 IQR [8.2-37.4] vs. 27.6 IQR [13.0-NR] months, p=0.007), and remained an independent predictor (HR 2.1, 95%CI [1.2-3.55], p=0.045) from WBC (p=0.060) and mPRS (p=0.11) in multivariate analysis.
Conclusion: In a single-center cohort of AML pts treated with frontline Ven-Aza, the presence ≥10% of mono-blasts in CD45+ cells by MFC predicted poorer CR rate and OS independently of genetics. MFC outperformed FAB classification to identify this independent prognostic contribution of monocytic differentiation. Our findings require independent validation but may guide the identification of high-risk pts and instruct the design of trials investigating alternative frontline strategies.
Disclosures: Fenaux: Jazz Pharmaceuticals: Honoraria, Research Funding; BMS: Honoraria, Research Funding; Astex: Research Funding; AbbVie: Honoraria, Research Funding; Novartis: Research Funding; Servier: Research Funding; Janssen: Research Funding; Agios: Research Funding. Ades: BMS: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Takeda: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding. Itzykson: Abbvie: Research Funding; Advesya: Research Funding.