Molecular Characterization of Pediatric Acute Lymphoblastic Leukemia via Integrative Transcriptomics: A Multicenter Study in Argentina
Ruiz, M. S.; Abbate, M. M.; Sosa, E.; Avendano, D.; Mercado, I. G.; Lacreu, M. L.; Riccheri, M. C.; Schuttenberg, V.; Aversa, L.; Vazquez, E.; Gueron, G.; Cotignola, J.
Show abstract
Acute lymphoblastic leukemia (ALL) is the most common childhood cancer worldwide, and exhibits high molecular heterogeneity. Molecular subtypes are characterized by specific chromosomal and molecular alterations, which are critical for guiding risk-adapted therapies. However, the increasing number of recognized prognostic molecular subtypes demands large resources, which are often limited in low/middle-income countries; thereby restricting the molecular characterization. This study aimed to perform an integrated molecular characterization of childhood B-ALL in Argentine patients. We performed RNA-seq on diagnostic bone marrow aspirates from Argentine patients enrolled in the ALLIC-GATLA-2010 protocol. We used different bioinformatic tools to identify and validate single nucleotide variants, fusion transcripts, gene expression profiles and molecular subtypes. We successfully determined transcriptome-based molecular subtype in 93.7% of patients; with high concordance to conventional karyotyping and RT-PCR (17/18 patients with available molecular data). Analysis of chimeric transcripts revealed 82 fusions, both intra- and inter-chromosomal, suggesting that leukemic cells may undergo chromosomal instability. Two of these fusions were novel: SCAF8::FER1L4 and DBF4B::EFTUD2. We also identified 21 different SNVs/InDels in 16 genes, including three novel variants (DUX4 p.I65N, CREBBP p.G1542V, and CSF3R p.G147R) and predicted to alter protein function. Overall, we observed that all patients who relapsed carried high-risk genetic alterations at diagnosis. Whole-transcriptome analysis of leukemic bone marrow enabled molecular subtyping and the identification of both known and novel molecular alterations associated with prognosis.
Matching journals
The top 9 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Mapping AML heterogeneity – multi-cohort transcriptomic analysis identifies novel clusters and divergent ex-vivo drug responses 95%
- Single-cell transcriptomics predicts relapse in MLL-rearranged acute lymphoblastic leukemia in infants 94%
- Combining LSD1 and JAK-STAT inhibition targets Down syndrome-associated myeloid leukemia at its core 94%
Similar papers in this journal
- Complex genotype-phenotype relationships shape the response to treatment of Down Syndrome Childhood Acute Lymphoblastic Leukaemia 95%
- Cas9-directed long-read sequencing to resolve optical genome mapping findings in leukemia diagnostics. 94%
- Refined detection and phasing of structural aberrations in pediatric acute lymphoblastic leukemia by linked-read whole genome sequencing 94%
Similar papers in this journal
- CAR-T cells targeting CCR9 and CD1a for the treatment of T cell acute lymphoblastic leukemia 91%
- First-in-human evaluation of memory-like NK cells with an IL-15 super-agonist and CTLA-4 blockade in advanced head and neck cancer 89%
- Stable colony stimulating factor 1 fusion protein treatment increases HSC pool and enhances their mobilisation in mice. 89%
Similar papers in this journal
- Resistance mechanism to Notch inhibition and combination therapy in human T cell acute lymphoblastic leukemia 95%
- Modeling IKZF1 lesions in B-ALL reveals distinct chemosensitivity patterns and potential therapeutic vulnerabilities 94%
- Molecular mechanisms promoting long-term cytopenia after BCMA CAR-T therapy in Multiple Myeloma 94%
Similar papers in this journal
- Acute myeloid leukemia expresses a specific group of olfactory receptors 96%
- Development of a Notch pathway assay and quantification of functional Notch pathway activity in T-cell acute lymphoblastic leukemia 96%
- ARPP19 promotes MYC expression and associates with patient relapse in acute myeloid leukemia 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.