Genetic Profiling of Pediatric Patients with B-Cell Precursor Acute Lymphoblastic Leukemia.
Dilara Fatma Akin-BaliBeyza Doğanay ErdoğanDeniz Aslar OnerAkkan MahmudSerpil TaşdelenAhmet Emin KürekçiM Nejat AkarHilal OzdagPublished in: Journal of pediatric genetics (2022)
B-cell precursor acute lymphoblastic leukemia (BCP-ALL) is a heterogeneous leukemia subgroup. It has multiple sub-types that are likely to be classified by prognostic factors. Following a systematic literature review, this study analyzed the genes correlated with BCP-ALL prognosis ( IKZF1, PAX5, EBF1, CREBBP, CRLF2, JAK2, ERG, CXCR4, ZAP70, VLA4, NF1, NR3C1, RB1, TSLP, ZNRF1, and FOXO3A) , specifically their nucleotide variations and expression profiles in pediatric BCP-ALL samples. The study included 45 pediatric BCP-ALL patients with no cytogenetic anomaly and a control group of 10 children. The selected genes' hot-spot regions were sequenced using next-generation sequencing, while Polymorphism Phenotyping v2 and Supplemental Nutrition Assistance Program were used to identify pathogenic mutations. The expression analysis was performed using quantitative real-time polymerase chain reaction. The mutation analysis detected 328 variants (28 insertions, 47 indels, 74 nucleotide variants, 75 duplications, and 104 deletions). The most and least frequently mutated genes were IKZF1 and CREBBP , respectively. There were statistically significant differences between patients and controls for mutation distribution in eight genes ( ERG, CRLF2, CREBBP, TSLP, JAK2, ZAP70, FOXO3A, and NR3C1 ). The expression analysis revealed that JAK and ERG were significantly overexpressed in patients compared with controls (respectively, p = 0.004 and p = 0.003). This study combined genes and pathways previously analyzed in pediatric BCP-ALL into one dataset for a comprehensive analysis from the same samples to unravel candidate prognostic biomarkers. Novel mutations were identified in all of the studied genes.
Keyphrases
- acute lymphoblastic leukemia
- prognostic factors
- genome wide
- genome wide identification
- end stage renal disease
- signaling pathway
- newly diagnosed
- bioinformatics analysis
- ejection fraction
- chronic kidney disease
- transcription factor
- dna methylation
- acute myeloid leukemia
- single cell
- young adults
- oxidative stress
- inflammatory response
- gene expression
- genome wide analysis
- high resolution
- high throughput
- quality improvement
- mass spectrometry
- patient reported outcomes