Characterisation of cells markers associated with IKZF1plus in BCP-ALL

Blunck, Caroline Barbieri; Poubel, Caroline Pires; Lopes, Bruno A.; Barbosa, Thayana C.; Maciel, Ana Luiza Tardem; da Costa, Elaine Sobral; Figueiredo, Ariadne da Rocha; Land, Marcelo G.P.; Schramm, Márcia Trindade; Ikoma-Coltutato, Maura Rosane Valério; Gomes, Renan Garcia; Lins, Mecneide Mendes; Aguiar, Thais Ferraz; Mansur, Marcela Braga; Emerenciano, Mariana

doi:10.1016/j.tranon.2024.102127

Translational Oncology

2024

DOI: 10.1016/j.tranon.2024.102127

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Characterisation of cells markers associated with IKZF1plus in BCP-ALL

Caroline Barbieri Blunck,

Caroline Pires Poubel,

Bruno A. Lopes

et al.

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RanBALL: An Ensemble Random Projection Model for Identifying Subtypes of B-cell Acute Lymphoblastic Leukemia

Li,

Xiao,

et al. 2024

Preprint

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As the most common pediatric malignancy, B-cell acute lymphoblastic leukemia (B-ALL) has multiple distinct subtypes characterized by recurrent and sporadic somatic and germline genetic alterations. Identification of B-ALL subtypes can facilitate risk stratification and enable tailored therapeutic approaches. Existing methods for B-ALL subtyping primarily depend on immunophenotypic, cytogenetic and genomic analyses, which would be costly, complicated, and laborious in clinical practice applications. To overcome these challenges, we present RanBALL (an Ensemble Random Projection-Based Model for Identifying B-Cell Acute Lymphoblastic Leukemia Subtypes), an accurate and cost-effective model for B-ALL subtype identification based on transcriptomic profiling only. RanBALL leverages random projection (RP) to construct an ensemble of dimension-reduced multi-class support vector machine (SVM) classifiers for B-ALL subtyping. Results based on 10 times 5-fold cross validation tests for >1700 B-ALL patients demonstrated that the proposed model achieved an accuracy of 93.35%, indicating promising prediction capabilities of RanBALL for B-ALL subtyping. The high accuracies of RanBALL suggested that our model could effectively capture underlying patterns of transcriptomic profiling for accurate B-ALL subtype identification. We believe RanBALL will facilitate the discovery of B-ALL subtype-specific marker genes and therapeutic targets, and eventually have consequential positive impacts on downstream risk stratification and tailored treatment design.

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RanBALL: An Ensemble Random Projection Model for Identifying Subtypes of B-cell Acute Lymphoblastic Leukemia

Li,

Xiao,

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

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Characterisation of cells markers associated with IKZF1plus in BCP-ALL

Cited by 1 publication

References 21 publications

RanBALL: An Ensemble Random Projection Model for Identifying Subtypes of B-cell Acute Lymphoblastic Leukemia

RanBALL: An Ensemble Random Projection Model for Identifying Subtypes of B-cell Acute Lymphoblastic Leukemia

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