AML-443 Clonal Evolution Analysis Using Next Generation Sequencing (NGS) Panel in a Cohort of 3,025 Patients With Acute Myeloid Leukemia (AML)

• Published in: Clinical lymphoma, myeloma and leukemia Vol. 23; p. S301
• Main Authors: Colmenares, Rafael, Sargas, Claudia, Álvarez, Noemí, Chillón, María Carmen, Carrillo-Cruz, Estrella, Bilbao-Sieyro, Cristina, de la Torre, Esther Prados, Martínez-Cuadrón, David, Rodríguez-Veiga, Rebeca, Boluda, Blanca, Gil, Cristina, Bernal, Teresa, Bergua, Juan Miguel, Algarra, Lorenzo, Tormo, Mar, Martínez-Sánchez, Pilar, Soria, Elena, Serrano, Josefina, Alonso-Domínguez, Juan Manuel, García-Boyero, Raimundo, Amigo, María Luz, Herrera-Puente, Pilar, Sayas, María José, Lavilla-Rubira, Esperanza, Calasanz, María José, García-Sanz, Ramón, Pérez-Simón, José Antonio, Gómez-Casares, María Teresa, Sánchez-García, Joaquín, Barragán, Eva, Martínez-López, Joaquín, Montesinos, Pau
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.09.2023
• Subjects: AML; clonal evolution; molecular biology; AML; molecular biology; clonal evolution
• ISSN: 2152-2650; 2152-2669
• DOI: 10.1016/S2152-2650(23)01061-3

AML is a neoplasm diagnosed mainly in older patients, and the study of the mutational profile at diagnosis is important for prognostic and therapeutic purposes. To analyze the differences in molecular alterations between diagnosis, refractoriness, and relapse in patients with AML. Laboratory data from the PETHEMA (Spanish Hematology Treatment Program) AML group were used. Patients diagnosed between 2017 and 2022 were included in the study; diagnostic, relapse, and primary refractory samples were analyzed, using a NGS panel with 26 common genes. Variant allele frequency (VAF) changes were analyzed too. A total of 3,603 samples were registered during the study period: 3,025 diagnostic samples, 307 relapse samples, and 197 primary refractoriness samples; 74 samples correspond to other times of the disease (e.g., end of treatment). First, unpaired data were analyzed. The most frequent mutation at diagnosis and, primary refractory and relapsed patients was DNMT3A (23.8%, 23.9% and 32.6%). Comparing diagnosis and primary refractoriness, there were differences in NPM1 (23.5% vs 11.7%, P<0.01), RUNX1 (17.9% vs 23.9%, P=0.04), SRSF2 (15.8% vs 21.3%, P=0.04), IDH1 (9.9% vs 15.2%, P=0.02), WT1 (5.1% vs 8.6%, P=0.03). Comparing diagnosis and relapse, there were differences in DNMT3A (23.8% vs 32.6%, P<0.01), RUNX1 (17.9% vs 23.1%, P=0.02), TP53 (17.5% vs 10. 4%, P<0.01), NRAS (15.8% vs 7.5%, P<0.01), IDH1 (9.9% vs 15.0%, P<0.01), KRAS (7.9% vs 2.9%, P<0.01), JAK2 (5.6% vs 2.9%, P=0.04), and WT1 (5.1% vs 11.1%, P<0.01). In a preliminary analysis, paired diagnosis-primary refractoriness (57 patients) and diagnosis-relapse samples (97 patients) were studied. DNMT3A was the most frequent mutation in all the groups. In diagnosis-relapse samples, there was a difference in NRAS mutation (15.7% vs 4.7%, P<0.01). Comparing the mean VAF at diagnosis, relapse and refractoriness, the differences are significant with VAF decrease in KRAS and NPM1 and increase in WT1 and FLT3-ITD. Clonal evolution studies can help to better understand the biology of AML and identify therapeutic targets in the most refractory alterations to conventional chemotherapy. We will show the results of the prediction of the profile at relapse or refractoriness based on the data at diagnosis.