Abstract

Cytogenetically normal acute myeloid leukemias (CN-AML) represent about 50% of total adult AML. Despite the well-known prognosis role of gene mutations such as NPM1 mutations or FLT3 internal tandem duplication (FLT3-ITD), clinical outcomes remain heterogeneous in this subset of AML. Given the role of genomic instability in leukemogenesis, expression analysis of DNA repair genes might be relevant to sharpen prognosis evaluation in CN-AML. Publicly available gene expression profile dataset from two independent cohorts of patients with CN-AML were analyzed (GSE12417). A list set of 175 genes involved in six major DNA repair pathways (base excision repair (BER), NER, mismatch repair (MMR), homologous recombination repair (HRR), non-homologous end joining (NHEJ) and FANC pathways) was defined using the REPAIRtoire database (http://repairtoire. genesilico.pl) and review of the literature. We investigated the prognostic value of these 175 genes involved in DNA repair. Among these genes, 23 were associated with a prognostic value, using the MaxStat R function. To further corroborate gene expression data on a functional level, CRISPR or RNAi screening publicly available data were used (Dependency Map data, Broad Institute, www.depmap.org). Among the 19 genes associated with a poor outcome, APEX (BER), RTEL1 (HRR) and COPS6 (NER) were identified as significant essential AML genes (p = 7.9e-05, 3.4e-04 and 2.8e-04 respectively). The prognostic information provided by these 23 genes was summed (sum of the beta coefficients of the Cox model for each prognostic gene, weighted by +1 or -1 according to the patient signal ≥ the probe set MaxStat value) in a DNA repair score to consider connection of DNA repair pathways. In the CN-AML training cohort (n=162), DNA repair score allowed to define a group of patients (n=87; 53,7%) with poor median overall survival (OS) of 233 days (95% CI: 184-260). These results were confirmed in the validation cohort (n=78) (median OS: 120 days; 95% CI: 36-303). In multivariate Cox analysis, the DNA repair score, NPM1and FLT3-ITD mutational status remained independent prognosis factors in CN-AML. Therefore, we investigated the interest of combining DNA repair score and NPM1/FLT3 mutational status to predict CN-AML outcome. Patients were classified according to prognosis value of DNA repair score (0 point for group I; 1 for group II; 2 for group III), and NPM1/FLT3 mutational status (0 point if NPM1 mutation without FLT3-ITD; 2 points if FLT3-ITD without NPM1 mutation; 1 point in other situations). The sum of the prognostic information was computed for all patients, allowing to separate patients in three new prognostic groups: group A including patients with 0 or 1 point, group B for patients with 2 points and group C for patients with 3 or 4 points. Combining these parameters allowed the identification of three risk groups with different clinical outcomes in both training and validation cohorts (Figure 1). In the training cohort, median OS was not reached (95% CI: NR-NR), 326 days (95% CI: 127-NR) and 236 days (95% CI: 190-263) respectively for patients in groups A, B and C. One-year OS was 90.3% (95% CI: 80.5-100) in group A, 49.3% (95% CI: 37.1-65.7) in group B, and 24.2% (95% CI: 16.2-36.2) in group C.These results were confirmed in the validation cohort where median OS was not reached (95% CI: 1278-NR), 516 days (95% CI: 308-NR) and 253 days (95% CI: 52-403) for patients respectively in groups A, B and C. One-year OS was 92.6% (95% CI: 83.2-100) in group A, 54.9% (95% CI: 39.8-75.7) in group B, and 26.5% (95% CI: 12.4-55.8) in group C. OS was statistically different between groups A, B and C in both training and validation cohorts. Combined with NPM1 and FLT3 mutational status, our GE-based DNA repair score might be used as a biomarker to predict outcomes for patients with CN-AML. DNA repair score has the potential to identify CN-AML patients whose tumor cells are dependent on specific DNA repair pathways to design new therapeutic avenues. Disclosures Cartron: Celgene: Consultancy, Honoraria; F. Hoffmann-La Roche: Consultancy, Honoraria; Sanofi: Honoraria; Gilead: Honoraria; Jansen: Honoraria; Abbvie: Honoraria. Moreaux:Diag2Tec: Consultancy.

Highlights

  • Acute myeloid leukemia (AML) is the most frequent type of adult leukemia

  • Considering the important role of DNA repair in drug resistance and adaptation to replication stress in cancer cells, we first aimed to identify the DNA repair genes associated with overall survival in cytogenetically normal AML” (CN-AML)

  • A list set of 175 genes involved in six major DNA repair pathways (base excision repair (BER), Nucleotide Excision Repair (NER), mismatch repair (MMR), homologous recombination repair (HRR), nonhomologous end joining (NHEJ) and Fanconi pathway (FANC) pathways) was defined using the REPAIRtoire database and review of the literature (Supplementary Table S1)

Read more

Summary

Introduction

Acute myeloid leukemia (AML) is the most frequent type of adult leukemia. When analyzed with conventional cytogenetics, about 40-50% of AML exhibit no chromosomal abnormalities, and are defined as “cytogenetically normal AML” (CN-AML)[1]. CN-AML were revealed by deep sequencing techniques, such as mutations of DNA modification, cohesin or tumor-suppressor genes, suggesting the wide heterogeneity of molecular mechanisms involved in leukemogenesis[4,5,6]. Even if the study of mutational landscape by new DNA sequencing technologies demonstrated a low mutation frequency in AML compared to others cancers[7], genomic instability remains a well-described leukemogenesis mechanism, illustrated by the high frequency of AML with non-random cytogenetics abnormalities or with complex karyotype[8, 9]. Recurrent AML fusion transcripts such as RUNX1-RUNX1T1 or PML-RARA has been demonstrated to downregulate the expression of genes implied in DDR[11,12,13,14]. Dysregulation in DDR contribute to increased resistance to conventional chemotherapy by several mechanisms, such as paradoxical increased expression of DDR or cell cycle check-point genes[17,18,19]

Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call