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. 2025 Jul 21;26(14):7003.
doi: 10.3390/ijms26147003.

Identification of Molecular Subtypes of B-Cell Acute Lymphoblastic Leukemia in Mexican Children by Whole-Transcriptome Analysis

Norberto Sánchez-Escobar  1   2 , María de Los Ángeles Romero-Tlalolini  1 , Haydeé Rosas-Vargas  2 , Elva Jiménez-Hernández  3 , Juan Carlos Núñez Enríquez  4 , Angélica Rangel-López  5 , José Manuel Sánchez López  2   6 , Daniela Rojo-Serrato  2   7 , América Mariana Jasso Mata  2 , Efraín Abimael Márquez Aguilar  2 , Janet Flores-Lujano  8 , Juan Carlos Bravata-Alcántara  9 , Jorge Alfonso Martín-Trejo  10 , Silvia Jiménez-Morales  11 , José Arellano-Galindo  5 , Aurora Medina Sanson  12 , Jose Gabriel Peñaloza Gonzalez  13 , Juan Manuel Mejía-Aranguré  14   15 , Minerva Mata-Rocha  2   16
Affiliations

Identification of Molecular Subtypes of B-Cell Acute Lymphoblastic Leukemia in Mexican Children by Whole-Transcriptome Analysis

Norberto Sánchez-Escobar et al. Int J Mol Sci. .

Abstract

B-lineage acute lymphoblastic leukemia (B-ALL) is classified into more than 20 molecular subtypes, and next-generation sequencing has facilitated the identification of these with high sensitivity. Bulk RNA-seq analysis of bone marrow was realized to identify molecular subtypes in Mexican pediatric patients with B-ALL. High hyperdiploidy (27.3%) was the most frequent molecular subtype, followed by DUX4 (13.6%), TCF3::PBX1 (9.1%), ETV6::RUNX1 (9.1%), Ph-like (9.1%), ETV6::RUNX1-like (9.1%), PAX5alt (4.5%), Ph (4.5%), KMT2A (4.5%), and ZNF384 (4.5%), with one patient presenting both the PAX5alt and low hypodiploidy subtypes (4.5%). The genes TYK2, SEMA6A, FLT3, NRAS, SETD2, JAK2, NT5C2, RAG1, and SPATS2L harbor deleterious missense variants across different B-ALL molecular subtypes. The Ph-like subtype exhibited mutations in STAT2, ADGRF1, TCF3, BCR, JAK2, and NRAS with overexpression of the CRLF2 gene. The DUX4 subtype showed mutually exclusive missense variants in the PDGRFA gene. Here, we have demonstrated the importance of using RNA-seq to facilitate the differential diagnosis of B-ALL with successful detection of gene fusions and mutations. This will aid both patient risk stratification and precision medicine.

Keywords: DUX4; NGS; RNA-seq; molecular subtypes of B-ALL; transcriptome.

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Conflict of interest statement

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
Oncoplot of distribution of clinical characteristics. The plot shows the frequency of the characteristics and outcome in each patient. Each column represents a patient with acute lymphoblastic leukemia (B-ALL) and each row represents a clinical characteristic corresponding to a patient; right bar represents the frequency of clinical characteristic.
Figure 2
Figure 2
Prediction and frequency of molecular subtypes in Mexican children with ALL. (A) The line represents each algorithm used for prediction of our cohort. The X axis shows the score prediction from 0 to 1 and the Y axis the patients and their respective molecular subtype predicted. (B) The pie chart shows the frequency of molecular subtype in our cohort. (C) The age distribution of molecular subtype classified in three age ranges (<1, 1–10 and >10 years).
Figure 3
Figure 3
Oncoplot of the most frequently observed genes with mutations. Distribution of recurring missense variants across key genes implicated in acute lymphoblastic leukemia (ALL), classified as tolerated (blue) or deleterious (red) based on Sift Prediction. The oncoplot shows each column represents a patient (ID), and each row corresponds to a gene; the bar chart on the right shows the percentage of patients harboring variants in each gene. The plot is divided into molecular subtypes that are indicated by the color-coded labels below each column.
See this image and copyright information in PMC

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