Molecular Characterisation and Outcomes of 363 Adolescent and Young Adults with AML in Saudi Arabia Risk Stratified By PCR and NGS-Based Testing
Authors: Alfaham Manar , Alotaibi Ahmad S. , Rasheed Walid , Alsuwaidan Abdullah , Mufti Ghulam , Shaheen Marwan , Alfayez Mansour , Alfares Ahmed , Alzayed Balqees , Bakshi Nasir , Khogeer Haitham A. , Alhossiny Midrar , Filimban Najlaa , Chaudhri Naeem A. , Almohareb Fahad , Hejab Amal , Alyamany Ruah , Alnughmush Ahmed , Alsharif Fahad , Hanbali Amr , Alfraih Feras Abdulaziz , Alhayli Saud , Alahmari Ali D , Alshaibani Alfadel , Albabtain Abdulwahab , Saad Ayman , Alamer Abdullah , Abdrabou Ahmed , Bin salman Ahmed , Haroon Alfadil , Hussain Taimoor , Mohammed Saleh Mostafa Faisal , Samarkandi Sarah , Nassani Momen , Bajuaifer Yazeed , Sharif Mohamed Isam , Madien Heba , Alasbali Reem , Nassar Marwa , Bahkali Fahad , Almarrzoq Deemah , Ramadan Sahar , Youniss Riad , Meyer Brian , Elfakih Riad , Alzahrani Hazza A , Aljurf Mahmoud , Ahmed Syed Osman 
Published: December 2023

Introduction
Acute Myeloid Leukaemia (AML) is characterised by cytogenetic (CGN) abnormalities and or mutations in one or more of a number of genes that allow risk stratification and guide treatment. The mutational landscape of patients from Saudi Arabia, which has a young population, has not been well characterised. One study indicates a higher rate of core binding factor and monosomies. Mutational analysis by Next generation sequencing (NGS) has not had widespread utilisation hampering the risk stratification of AML in the country. The more recent introduction of NGS panels has allowed more risk stratification. Here we analysed patients and characterised the CGN and molecular abnormalities.
Methods
Data were collected from 363 patients, and their cytogenetic and molecular results were reviewed. Patients were divided into 2 cohorts: Cohort A only had PCR-based testing diagnosed or treated at King Faisal Specialist Hospital and research centre - Riyadh. PCR testing included mutation analysis for FLT3, NPM1, CEBPA, c-KIT, IDH1, IDH2, WT1, DNMT3A, and JAK2; quantitative PCR for RUNX1-ETO in a subset of patients. Cohort B had PCR-based mutation testing in addition to the Next-Generation Sequencing (NGS) myeloid panel, which was Illumina-based or Ion Torrent. The panel comprises 23 hotspot genes, 17 entire genes, 29 fusion drivers, and five expression genes associated with haematological malignancies. We risk-stratified patients according to the most recent testing method available. Cohort A and Cohort B were risk-stratified, according to ELN risk classification 2017. Survival analysis for these patients was conducted.
Results
The median age for all patients was 39 years (13-89). PCR testing included mutation analysis for FLT3 (93.4%), NPM1 (90.4%), CEBPA (69.7%), c -KIT (54.3%), IDH1 (57%), IDH2 (57.9%), WT1 (61.2%), DNMT3A (54.5.5%), JAK2 (4.7%) and quantitative PCR for RUNX1- ETO fusion (13.2%). Cohort A comprised 262 (72.7%) patients who underwent PCR-based mutation testing only. Cohort B consisted of 101 (27.8%) patients who underwent PCR-based mutation testing in addition to NGS myeloid panel analysis. In the entire cohort of 363 patients, we found FLT3-ITD mutations in 85 patients (23.4%) and NPM1 mutations in 68 (18.7%). 36 patients (9.9%) harboured both FLT3-ITD and NPM1 mutations together. In Cohort A, FLT3-ITD detected 26.7% of patients, and 20.2% had NPM1 mutation, while 40% had no detectable mutations by conventional PCR. On the other hand, FLT3-ITD was detected in 14.9% of patients by both NGS and conventional PCR and in 14.9% of patients with NPM1. When comparing Cohort A and Cohort B, Cohort B had more mutations in genes that play an important role in myeloid malignancies, which might have better risk stratification and precision, including TP53 in 13.9% of patients and RUNX1 in 18.8% of patients and ASXL1 in 9.9% of patients. Moreover, NGS pick up more mutations in CEBPA, c-KIT, WT1, IDH1 and JAK2 genes compared to conventional PCR. Within cohort A, 9.2% of patients had normal cytogenetic testing results with no detectable mutations, whereas in cohort B, only 1% of patients had normal karyotype and molecular testing. Furthermore, six mutations were detected only by NGS but not PCR in FLT3-ITD, CEBPA, c-KIT, IDH2, WT1 and DNMT3A in 5.9% of patients. Cohorts A and B were also categorised into ELN risk groups using PCR, sequencing, and cytogenetics testing. It was found that patients at adverse risk had shorter overall survival compared to those at intermediate or favourable risk in both cohorts, with p-values of 0.030 and 0.0007, respectively (Figure 1). The use of NGS was found to be more effective than conventional testing in identifying patients with adverse risk, with a hazard ratio for death of 0.22 (95% CI, 0.08989-0.5732) compared to a hazard ratio of 0.66 (95% CI, 0.4352 -1.031) for conventional PCR testing.
Conclusion
In this study, we present the mutational profile of AML in young Saudi patients and identify certain frequent mutations in this population. The study presents the largest molecular profiling to our knowledge of this population. The study emphasises the need for integration of NGS to enhance risk stratification and precision, enable better characterisation of high-risk patients, and improve the potential for targeted treatments.