ReviewIndian journal of hematology & blood transfusion : an official journal of Indian Society of Hematology and Blood Transfusion2025
Genetics of B-Cell Acute Lymphoblastic Leukemia (B-ALL): Recent Updates and Indian Perspective.
Review in Indian journal of hematology & blood transfusion : an official journal of Indian Society of Hematology and Blood Transfusion, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
B-cell acute lymphoblastic leukemia (B-ALL) is the most common hematological malignancy of childhood. The initial risk-stratification includes the genetic evaluation for common recurrent translocations and aneuploidies in B-ALL using karyotyping, fluorescence in-situ hybridization (FISH), reverse transcription polymerase chain reaction (RT-PCR), etc. However, many cases remain genetically unclassified and are labeled as B-other ALL. Recent advances in the high throughput genomics have provided new insights and many distinct genetic subtypes have been identified in B-ALL. These new subtypes have been incorporated in the latest World Health Organization (WHO)-HAEM5 classification of haematolymphoid tumors and the International Consensus Classification. Besides the driver mutations, there is also a role of secondary genetic events like copy number alterations (CNAs) in the pathogenesis of B-ALL as well as for better risk-stratification. New molecular genetic risk evaluation like Moorman's criteria, IKZF1plus and MRplus scores have been recently validated which can risk-stratify B-ALL patients at baseline based on the CNA profile. The new diagnostic armamentarium now also includes flow-based ploidy analysis, cytokine receptor like factor 2 (CRLF2/TSLPR) overexpression screening on flow cytometry, multiplex ligation dependent probe amplification (MLPA) for CNAs, targeted RNA sequencing and whole transcriptome sequencing for detection of known and novel fusions. The gene expression profiling data can also be assessed with the machine learning based genetic classifiers for prediction of the newly identified subtypes of B-ALL. This review attempts to provide updates about the latest developments in the field of B-ALL genetics with inputs of Indian data, wherever available.
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