T-cell acute lymphoblastic leukaemia accounts for 10–15% of all acute lymphoblastic leukaemias in children. Despite advances in the treatment of the disease in
recent years, the T-cell immunophenotype, which is genetically very heterogeneous, poses a higher risk of treatment failure than B-cell immunophenotype. Patients with relapse have a very poor prognosis, as relapses are often resistant to treatment. Unlike B-cell acute lymphoblastic leukaemia, in which the immunophenotype-genotype association profile is well established as outcome predictors, T-cell acute lymphoblastic leukemia still needs further investigations.The aim of the study is a transcriptome analysis in T-cell acute lymphoblastic leukemia pediatric patients with differential gene expression analysis. We isolated RNA from bone marrow and peripheral blood of children diagnosed with T-cell acute lymphoblastic leukemia at the Pediatric clinic in Ljubljana between 2009 and 2023. Then RNA libraries were prepared and sequenced using the NovaSeq 6000, Illumina. Using the Snakepipes data pipeline, DESeq2 and edgeR, we identified differential gene expression in relapsed patients compared to patients in remission. We also identified differences in gene expression between immature and mature immunophenotype and compared differentially expressed genes in T- and B-cell acute lymphoblastic leukaemia patients. Sequencing data
from patients with B-cell acute lymphoblastic leukaemia patients were used for this part of the analysis. Eleven highly expressed genes were identified in relapsed and 41 genes in remission patients. In some cases, increased expression of oncogenes or decreased expression of tumour suppressor genes could indicate a poorer prognosis of relapsed patients, in other cases the association was unclear as gene expression has not yet been described in the literature. Analysis of gene expression in different immunophenotypes showed poor association between immunophenotype and genetic profile, which is also described in the literature. In differential analysis of gene expression between T- and B-cell acute lymphoblastic leukemia patients, we identified 8,848 differently expressed genes. We identified a pathway of immunoregulatory interactions between lymphoid and non-lymphoid cells using Enrichr enrichment analysis as one that could play a role in the poorer outcome of the disease compared to B-cell acute lymphoblastic leukemia. Further research is needed to determine gene expression that would have a significant prognostic value for patients.
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