Contributions
Abstract: PB1612
Type: Publication Only
Background
Acute lymphoblastic leukemia (ALL) is the most common cancer in children, representing about 80% of acute leukemias, whereas it is less common in adults (20%). Identification of cytogenetic aberrations and a small number of molecular abnormalities are still the most important risk and therapy stratification methods in clinical practice today.
Aims
The aim of the present study was to assess mutational profile of both childhood (cALL) and adult acute lymphoblast leukemia (aALL) patients, by applying targeted next generation sequencing (NGS) on MiSeq System.
Methods
We analyzed DNA samples from 34 de novo ALL patients (17 cALL and 17 aALL) using TruSeq Amplicon – Cancer Panel (TSACP) that targets mutational hotspots in 48 cancer related genes (212 amplicons). The bioinformatics analyses was conducted using processing pipeline composed of both freely available open source bioinformatics tools as well as tools developed in-house. The average coverage of high-quality sequences was 2609 × per amplicon. Ten genes were discarded due to insufficient coverage, therefore we analyzed a total of 183 amplicons from 38 genes. Variants were identified in relation to the GRCh37 reference genome by applying a Bayesian approach and compared to public genetic variation databases and in-house databases.
Results
We identified a total of 331 (159 cALL, 172 aALL) variants in the coding regions (median per patient: 9, range: 6-12; median per cALL: 9, range: 6-12; median per aALL: 10, range: 7-12 ) and 429 (211 cALL, 218 aALL) variants in the non-coding regions (median per patient: 13 range: 10-15; median per cALL: 13, range: 10-14; median per aALL: 13, range: 10-15). Overall, a total of 98 variants (median per patient: 2.8, range: 1–6) were potentially protein-changing, including nonsense, frameshift, and missense (NFM) mutations. There were no significant differences in the number of NFM mutations between cALL (total 47, median per patient: 3, range: 1–5) and aALL patients (total 51, median per patient: 3, range: 1–5). Moreover, we identified 5 NFM mutations in STK11 gene, 3 in ABL1, RET, KRAS and 2 in HNF1A, NRAS, and NOTCH1. Observed in individual patients detected mutations predominantly disrupted Ras/RTK pathway (STK11, KIT, MET, NRAS, KRAS, PTEN). Additionally, we identified 5 patients with the same mutation in HNF1A gene coding for transcriptional factor, disrupting both Wnt and Notch signaling pathway. Notch pathway was disrupted in two patients in which detected variants affected NOTCH1 gene. HNF1A and NOTCH1 variants were mutually exclusive, while genes involved in Ras/RTK pathway exhibit a tendency of mutation accumulation.
Conclusion
Our targeted NGS study showed low number of recurrent mutations in both cALL and aALL patients. Detected mutations affect few key signaling pathways, primarily Ras/RTK and Notch pathways. This study contributes to knowledge of ALL mutational landscape, leading to better understanding of molecular basis of ALL and better stratification and treatment of ALL patients.
Session topic: 1. Acute lymphoblastic leukemia - Biology
Abstract: PB1612
Type: Publication Only
Background
Acute lymphoblastic leukemia (ALL) is the most common cancer in children, representing about 80% of acute leukemias, whereas it is less common in adults (20%). Identification of cytogenetic aberrations and a small number of molecular abnormalities are still the most important risk and therapy stratification methods in clinical practice today.
Aims
The aim of the present study was to assess mutational profile of both childhood (cALL) and adult acute lymphoblast leukemia (aALL) patients, by applying targeted next generation sequencing (NGS) on MiSeq System.
Methods
We analyzed DNA samples from 34 de novo ALL patients (17 cALL and 17 aALL) using TruSeq Amplicon – Cancer Panel (TSACP) that targets mutational hotspots in 48 cancer related genes (212 amplicons). The bioinformatics analyses was conducted using processing pipeline composed of both freely available open source bioinformatics tools as well as tools developed in-house. The average coverage of high-quality sequences was 2609 × per amplicon. Ten genes were discarded due to insufficient coverage, therefore we analyzed a total of 183 amplicons from 38 genes. Variants were identified in relation to the GRCh37 reference genome by applying a Bayesian approach and compared to public genetic variation databases and in-house databases.
Results
We identified a total of 331 (159 cALL, 172 aALL) variants in the coding regions (median per patient: 9, range: 6-12; median per cALL: 9, range: 6-12; median per aALL: 10, range: 7-12 ) and 429 (211 cALL, 218 aALL) variants in the non-coding regions (median per patient: 13 range: 10-15; median per cALL: 13, range: 10-14; median per aALL: 13, range: 10-15). Overall, a total of 98 variants (median per patient: 2.8, range: 1–6) were potentially protein-changing, including nonsense, frameshift, and missense (NFM) mutations. There were no significant differences in the number of NFM mutations between cALL (total 47, median per patient: 3, range: 1–5) and aALL patients (total 51, median per patient: 3, range: 1–5). Moreover, we identified 5 NFM mutations in STK11 gene, 3 in ABL1, RET, KRAS and 2 in HNF1A, NRAS, and NOTCH1. Observed in individual patients detected mutations predominantly disrupted Ras/RTK pathway (STK11, KIT, MET, NRAS, KRAS, PTEN). Additionally, we identified 5 patients with the same mutation in HNF1A gene coding for transcriptional factor, disrupting both Wnt and Notch signaling pathway. Notch pathway was disrupted in two patients in which detected variants affected NOTCH1 gene. HNF1A and NOTCH1 variants were mutually exclusive, while genes involved in Ras/RTK pathway exhibit a tendency of mutation accumulation.
Conclusion
Our targeted NGS study showed low number of recurrent mutations in both cALL and aALL patients. Detected mutations affect few key signaling pathways, primarily Ras/RTK and Notch pathways. This study contributes to knowledge of ALL mutational landscape, leading to better understanding of molecular basis of ALL and better stratification and treatment of ALL patients.
Session topic: 1. Acute lymphoblastic leukemia - Biology