Design and Validation of a Custom Next-Generation Sequencing Panel in Pediatric Acute Lymphoblastic Leukemia.

The molecular landscape of acute lymphoblastic leukemia (ALL) is highly heterogeneous, and genetic lesions are clinically relevant for diagnosis, risk stratification, and treatment guidance. Next-generation sequencing (NGS) has become an essential tool for clinical laboratories, where disease-targeted panels are able to capture the most relevant alterations in a cost-effective and fast way. However, comprehensive ALL panels assessing all relevant alterations are scarce. Here, we design and validate an NGS panel including single-nucleotide variants (SNVs), insertion-deletions (indels), copy number variations (CNVs), fusions, and gene expression (ALLseq). ALLseq sequencing metrics were acceptable for clinical use and showed 100% sensitivity and specificity for virtually all types of alterations. The limit of detection was established at a 2% variant allele frequency for SNVs and indels, and at a 0.5 copy number ratio for CNVs. Overall, ALLseq is able to provide clinically relevant information to more than 83% of pediatric patients, making it an attractive tool for the molecular characterization of ALL in clinical settings.

Comprehensive detection of CRLF2 alterations in acute lymphoblastic leukemia: a rapid and accurate novel approach.

Introduction: Acute lymphoblastic leukemia (ALL) is a prevalent childhood cancer with high cure rate, but poses a significant medical challenge in adults and relapsed patients. Philadelphia-like acute lymphoblastic leukemia (Ph-like ALL) is a high-risk subtype, with approximately half of cases characterized by CRLF2 overexpression and frequent concomitant IKZF1 deletions. Methods: To address the need for efficient, rapid, and cost-effective detection of CRLF2 alterations, we developed a novel RT-qPCR technique combining SYBR Green and highresolution melting analysis on a single plate. Results: The method successfully identified CRLF2 expression, P2RY8::CRLF2 fusions, and CRLF2 and JAK2 variants, achieving a 100% sensitivity and specificity. Application of this method across 61 samples revealed that 24.59% exhibited CRLF2 overexpression, predominantly driven by IGH::CRLF2 (73.33%). High Resolution Melting analysis unveiled concurrent CRLF2 or JAK2 variants in 8.19% of samples, as well as a dynamic nature of CRLF2 alterations during disease progression. Discussion: Overall, this approach provides an accurate identification of CRLF2 alterations, enabling improved diagnostic and facilitating therapeutic decision-making.