Correlation Between Outcome and Genetic Abnormalities Identified by High-Density Single Nucleotide Polymorphism Array Analysis In Patients with Myelodysplastic Syndromes or Acute Myeloid Leukemia with Multi-Lineage Dysplasia Treated with Azacitidine
Authors: Cluzeau Thomas , Moreilhon Chimène , Mounier Nicolas , Karsenti Jean-Michel , Mannone Lionel , Vinti Henri , Legros Laurence , Thyss Antoine , Garnier Georges , Gutnecht Jean , Re Daniel , Auberger Patrick , Cassuto Jill-Patrice , Raynaud S. Dominique 
Published: October 2019

Abstract 2929

Background:

Azacitidine (AZA) has changed the outcome of patients (pts) with myelodysplastic syndromes (MDS) or acute myeloid leukemia with multi-lineage dysplasia (AML-MLD) unfit for intensive chemotherapy. AZA is a hypomethylating agent providing about 50% of responses in MDS and AML with low blast count (Fenaux et al., Lancet Oncol 2009, JCO 2010). To date, no consensus genetic predictor of response has been reported.

Methods:

In MDS (including RAEB-t) and AML-MLD (>30% blasts) patients treated by AZA in 5 centers, we performed genomewide single nucleotide polymorphism (SNP) analysis using SNP 6.0 arrays (Affymetrix, High Wycombe, U.K.) on bone marrow (BM) samples. Patients having received ≥ 1 cycle of AZA and who had bone marrow evaluation after ≥ 4 cycles, or who died or progressed before completion of 4 cycles were considered evaluable (the last 2 groups were considered as treatment failures). Responses were scored according to IWG 2006 criteria for MDS and to Cheson et al. (JCO 2003) for AML. DNA were prepared for hybridization according to the manufacturers' recommendations. Affymetrix CEL files for each sample were analyzed using the Genotyping Console software (v3.0.2). Genotyping was performed using Birdseed V2 algorithm. Unpaired Copy Number and LOH analysis was performed with Regional GC correction. Copy number and UPD were also analyzed using the Copy Number Analyzer for GeneChip (CNAG version 3.3.0.1) algorithm (http://www.genome.umin.jp/CNAGtop2.html).

Results:

The study population included 92 pts: F/M: 41/51; median age 72 (range 35–88). Diagnosis at AZA onset was MDS in 54 (RAEB-1 n=6, RAEB-2 n=37, RAEB-t=11, IPSS int-1 in 7, int-2 in 15, high in 32, undetermined in 2) and AML-MLD in 38 pts. Cytogenetic according to IPSS was favorable in 33, intermediate in 19, unfavorable in 28, unknown in 11. Median number of cycles was 6 (range 1–41). All pts received the approved (75 mg/m2 for 7 days every 4 weeks) or a reduced AZA schedule (75 mg/m2 for 5 days every 4 weeks). Median overall survival (OS) of our cohort was 22 months.

DNA samples from 52 patients were available for SNP analysis. There were no significant differences between the SNP and no SNP subgroups in term of median age, sex ratio, disease status at AZA onset, cytogenetic according to IPSS, median number of cycles, responses and OS.

We listed aneuploidies (CNA) and uniparental disomies (UPD) detected by SNP analysis in the samples, and focused on 18 chromosomal bands (1p13.2, 2q34, 3p14.2, 3q26, 4q24, 5q33.1, 5q35, 6p21.3, 7q36.1, 9p21.3, 11p13, 11q23.3, 13q12.2, 15q21, 15q26.2, 20q11.21, 21q22.1) containing genes implicated in MDS or AML. Preliminary results show correlations between some CNA/UPD and response to AZA and OS, such as 1/a UPD at 9p21 (6% of patients) associated to a better hematologic improvement (X2, p=0.037), 2/an amplification at 20q11.21 (8% of patients) correlated with a poorer response (X2, p=0.048) and a trend toward poorer OS (Log-Rank, p=0.091), and 3/deletion and UPD at 15q21 (6% of patients) strongly correlated to poorer OS (Log-Rank, p=0.001). Several additional CNA and UPD of potential interest are presently under investigation.

Conclusion:

SNP analysis using SNP 6.0 is a powerful tool to decipher genome complexity in BM samples of MDS and AML patients treated with AZA. Our data suggest that this approach could allow characterizing profiles of responder versus non responder pts. Our study must be extended to a larger cohort and relevant anomalies must be confirmed by more sensitive techniques such as high-scale sequencing.

Disclosures:

Cluzeau: Celgene: Consultancy. Raynaud:Celgene: Consultancy.