Introduction: Myelodysplastic syndrome (MDS) is characterized by differentiation blockade, cytopenias with commontransfusion dependency and immune defects. Upon progression the myeloblasts accumulate and the patients become vulnerable to severe infection complications. Based on the Prague Charles University General Hospital registry (N=164, median age 73), the AZA therapy in higher-risk MDS patients results in median OS 13.8 Mo with ORR 48.5%. We also noted from our retrospective data that AZA-treated patients with higher G-CSF consumption had significantly reduced occurrence of Grade 4 neutropenias and longer OS (19 vs 16 Mo, p value 0.039).
Rationale: To improve poor clinical outcomes we initiated a randomized open labeled academic trial that compares standard AZA therapy (A) with novel AZA-based therapy combination involving use of G-CSF added prior AZA (GA). Both AZA and also decitabine were preclinically shown to induce myeloid differentiation upon G-CSF preincubation. G-CSF binds its receptor in granulocytic precursors and neutrophils to stimulate their survival, proliferation, and differentiation via myeloid master regulator transcription factor and leukemia-suppressor PU.1. We also have previously shown that AZA increases PU.1. expression.
Study design & Methods: GA/MDS-2013 (EudraCT No 2013-001639-38). Expected for enrollment are 134 patients, currently enrolled 53 patients (GA arm N=29, A arm N=24) with median age 74 years, M:F ratio 32:21 (GA 16:16, A 13:8),median IPSS-R 6, median follow up 11.2 Mo, median cycles of therapy 6. Diagnosis included:MDS (EB1, EB 2) with IPSS int-2/high (75%), MDS/AML<30% MB (22.5%), and CMML II (2.5%). Transplant candidates were excluded. Randomization is 2:1 for GA vs A arm. Primary endpoints: OS, PFS, time to AML transformation, ORR, infections & QoL. Secondary endpoints: biomarkers. Therapy schedule: 75mg/m2 of AZA 5-2-2, in GA: G-CSF s.c. injected 48 hrs before dose 1 and dose 6. G-CSF is measured in patient sera (prior therapy), myeloid surface markers are determined by flow cytometry (day -2, day 1, and day 9 of cycle 1). Genomic libraries from whole bone marrow are prepared by NEBNext Direct Kit involving 33 gene panel, sequencing runs are performed on Illumina platform. Statistics involved longitudinal multivariate data analysis including the joint models for the OS and response.
Results: The presented data include 2.5 years since the beginning of the trial. Median survival for GA arm was 11 vs 6 Mo in the A arm. ORR (CR, CRm, PR, HI) was 56% in GA arm vs 33% in the A arm. Transformation to AML for both arms was comparable. The stratified longitudinal Cox proportional hazards model containing time-varying covariates together with the ordinal multilevel logistic mixed model were utilized. From this joint fitted model, a negative coefficient for the G-AZA treatment (significant p-value 0.0442) can be noticed in the case of the Cox Proportional Hazard part of the model. This means that G-AZA treatment improves patient survival. The estimated odds for the GA arm that responded to the therapy with remission rather than progression is 12.4x higher than for the A arm, controlling for the remaining patients' characteristics (p-value 0.0016).Both the GA and A arms are comparably tolerated. Data on serious infections and neutropenia gr4 were not yet available. The levels of G-CSF in sera prior the study in both arms (GA vs A) were comparable. Flow cytometry revealed G-CSF mediated upregulation of FCgRI (CD64) in the GA but not in the A arm. Multivariate analysis indicates the following: mutated genes: DNMT3A (p-value 0.0157), EZH2 (p-value 0.0091), TP53 (borderline p-value 0.0510), & CSF3R (p-value 0.0057) shorten the overall survival. The significant negative effects on response was noted for mutated EZH2 (p-value 0.0208) and CSF3R (p-value 0.0424) genes.
Conclusions: The current results supported by different methods and statistics indicates a beneficial effect of G-CSF pre-treatment to standard AZA therapy in higher risk MDS patients. G-CSF pre-treatment to AZA increases OS and ORR. In addition, we identified biomarkers that are negatively associated with patient survival and response including EZH2, DNMT3A, TP53, & CSF3R.
Grant Support: Ministry of Health, #16-27790A. Institutional resources: Progres Q49 & Q26, UNCE/MED/016, LQ1604, SVV 260374/2017, RVO-64165.
Disclosures
No relevant conflicts of interest to declare.
Submerged microfiltration membrane and activated carbon processes for recalcitrant compounds removal in Oil refinery effluent as electrodialysis pre-treatment