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. 2023 Jan 10;15(2):438.
doi: 10.3390/cancers15020438.

Molecular Landscape and Validation of New Genomic Classification in 2668 Adult AML Patients: Real Life Data from the PETHEMA Registry

Claudia Sargas  1 , Rosa Ayala  2 , María José Larráyoz  3 , María Carmen Chillón  4 , Estrella Carrillo-Cruz  5 , Cristina Bilbao-Sieyro  6 , Esther Prados de la Torre  7 , David Martínez-Cuadrón  8   9 , Rebeca Rodríguez-Veiga  8 , Blanca Boluda  8 , Cristina Gil  10 , Teresa Bernal  11 , Juan Miguel Bergua  12 , Lorenzo Algarra  13 , Mar Tormo  14 , Pilar Martínez-Sánchez  2 , Elena Soria  5 , Josefina Serrano  7 , Juan Manuel Alonso-Domínguez  15 , Raimundo García-Boyero  16 , María Luz Amigo  17 , Pilar Herrera-Puente  18 , María José Sayas  19 , Esperanza Lavilla-Rubira  20 , Joaquín Martínez-López  2 , María José Calasanz  3 , Ramón García-Sanz  4 , José Antonio Pérez-Simón  5 , María Teresa Gómez-Casares  6 , Joaquín Sánchez-García  7 , Eva Barragán  10   21 , Pau Montesinos  8   10 , On Behalf Of Pethema Group
Affiliations

Molecular Landscape and Validation of New Genomic Classification in 2668 Adult AML Patients: Real Life Data from the PETHEMA Registry

Claudia Sargas et al. Cancers (Basel). .

Abstract

Next-Generation Sequencing (NGS) implementation to perform accurate diagnosis in acute myeloid leukemia (AML) represents a major challenge for molecular laboratories in terms of specialization, standardization, costs and logistical support. In this context, the PETHEMA cooperative group has established the first nationwide diagnostic network of seven reference laboratories to provide standardized NGS studies for AML patients. Cross-validation (CV) rounds are regularly performed to ensure the quality of NGS studies and to keep updated clinically relevant genes recommended for NGS study. The molecular characterization of 2856 samples (1631 derived from the NGS-AML project; NCT03311815) with standardized NGS of consensus genes (ABL1, ASXL1, BRAF, CALR, CBL, CEBPA, CSF3R, DNMT3A, ETV6, EZH2, FLT3, GATA2, HRAS, IDH1, IDH2, JAK2, KIT, KRAS, MPL, NPM1, NRAS, PTPN11, RUNX1, SETBP1, SF3B1, SRSF2, TET2, TP53, U2AF1 and WT1) showed 97% of patients having at least one mutation. The mutational profile was highly variable according to moment of disease, age and sex, and several co-occurring and exclusion relations were detected. Molecular testing based on NGS allowed accurate diagnosis and reliable prognosis stratification of 954 AML patients according to new genomic classification proposed by Tazi et al. Novel molecular subgroups, such as mutated WT1 and mutations in at least two myelodysplasia-related genes, have been associated with an adverse prognosis in our cohort. In this way, the PETHEMA cooperative group efficiently provides an extensive molecular characterization for AML diagnosis and risk stratification, ensuring technical quality and equity in access to NGS studies.

Keywords: Next–Generation Sequencing; acute myeloid leukemia; clinical validation; cross–validations; genomic classification; mutational profile.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1
Figure 1
Co–occurrence and mutual exclusivity patterns among genes. Red: exclusive relationship; Green: co–occurring relationship. Higher color intensity indicates stronger association: * p < 0.05, ** p < 0.01, *** p < 0.001.
Figure 2
Figure 2
Heatmap of association and exclusivity patterns among functional categories. Red: exclusivity relationship; Green: co–occurring relationship. Higher color intensity indicates stronger association. * p < 0.05, ** p < 0.01, *** p < 0.001.
Figure 3
Figure 3
Mutational frequency according to disease stage. Blue bars: Diagnosis, green bars: Relapse and red bars: refractoriness. * p < 0.05, ** p < 0.01, *** p < 0.001. ITD: internal tandem duplication; TKD: tyrosine kinase domain.
Figure 4
Figure 4
Age–related mutational profile. Bar chart representing mutational frequencies according to age at diagnosis. Green; <65 years old, red; ≥65 years old. * p < 0.05, ** p < 0.01, *** p < 0.001. ITD: internal tandem duplication; TKD: tyrosine kinase domain.
Figure 5
Figure 5
Sex–related mutational profile. Bar chart representing mutational frequencies. Orange; female, blue; male. * p < 0.05, ** p < 0.01, *** p < 0.001. ITD: internal tandem duplication; TKD: tyrosine kinase domain.
Figure 6
Figure 6
Molecular classes’ distribution according to the Tazi et al., 2022 genomic classification. CK: Complex karytotype. mNOS: Not class defining mutations.
Figure 7
Figure 7
Hazard ratio for death according to (A) New molecular subgroups in the global cohort; and new genomic risk score for: (B) Global cohort, (C) Patients < 65 years and (D) Patients ≥65 years. * p < 0.05, *** p < 0.001.
Figure 8
Figure 8
Overall survival according to new genomic risk score: (A) Global cohort, (B) Patients < 65 years, (C) Patients ≥ 65 years.
Figure 9
Figure 9
Overall survival curves according to 2022 ELN risk classification and Tazi et al. [2] genomic AML classification: (A) Favorable, (B) Intermediate and (C) Adverse risk groups.
See this image and copyright information in PMC

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