The development of acute lymphoblastic leukemia in an existing myeloproliferative neoplasm is rare with historical cases unable to differentiate between concomitant malignancies or leukemic transformation. Molecular studies of coexisting JAK2 V617F-positive myeloproliferative neoplasms and mature B cell malignancies indicate distinct disease entities arising in myeloid and lymphoid committed hematopoietic progenitor cells, respectively. Mutations of CALR in essential thrombocythemia appear to be associated with a distinct phenotype and a lower risk of thrombosis yet their impact on disease progression is less well defined. The as yet undescribed scenario of pro-B cell acute lymphoblastic leukemia arising in CALR mutated essential thrombocythemia is presented. Intensive treatment for the leukemia allowed for expansion of the original CALR mutated clone. Whether CALR mutations in myeloproliferative neoplasms predispose to the acquisition of additional malignancies, particularly lymphoproliferative disorders, is not yet known.
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http://dx.doi.org/10.1155/2016/6545861 | DOI Listing |
G-quadruplexes (G4s) are four-stranded alternative secondary structures formed by guanine-rich nucleic acids and are prevalent across the human genome. G4s are enzymatically resolved using specialized helicases. Previous studies showed that DEAH-box Helicase 36 (DHX36/G4R1/RHAU), has the highest specificity and affinity for G4 structures.
View Article and Find Full Text PDFBiol Methods Protoc
December 2024
Division of Molecular Medicine, St John's Research Institute, St John's National Academy of Health Sciences (a Unit of CBCI Society for Medical Education), Bangalore 560034, Karnataka, India.
Real time-polymerase chain reaction (RT-PCR) is used routinely in clinical practice as a cost-effective method for molecular diagnostics. Research in pediatric B-cell Acute Lymphoblastic Leukemia (ped B-ALL) suggests that apart from cytogenetics and clinical features, there is a need to include Copy number variation (CNV) in select genes at diagnosis, for upfront stratification of patients. Using ped B-ALL as a model, we have developed a RT-PCR-based iterative probability scoring method for reporting CNVs, and relative gene-expression changes.
View Article and Find Full Text PDFCancer
January 2025
Division of Pediatric Hematology-Oncology, Department of Pediatrics, Charles-Bruneau Cancer Center, Centre Hospitalier Universitaire (CHU) de Sainte-Justine, Montreal, Quebec, Canada.
Background: Childhood obesity can result in adverse health outcomes. The objectives of this study were to describe the prevalence of obesity and determine the association between obesity at cancer diagnosis and event-free survival (EFS) and overall survival (OS) in children diagnosed with cancer in Canada.
Methods: The authors conducted a retrospective cohort study using the Cancer in Young People in Canada database, including all children with newly diagnosed cancer aged 2-18 years across Canada from 2001 to 2020.
Mol Cancer
January 2025
Molecular Epidemiology (MOLE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
VTRNA2-1 is a polymorphically imprinted locus. The proportion of individuals with a maternally imprinted VTRNA2-1 locus is consistently approximately 75% in populations of European origin, with the remaining circa 25% having a non-methylated VTRNA2-1 locus. Recently, VTRNA2-1 hypermethylation at birth was suggested to be a precursor of paediatric acute lymphoblastic leukaemia with biomarker potential.
View Article and Find Full Text PDFISA Trans
January 2025
Department of Electronics and Telecommunication, C. V. Raman Global University, Bhubaneswar 752054, Odisha, India. Electronic address:
Early and highly accurate detection of rapidly damaging deadly disease like Acute Lymphoblastic Leukemia (ALL) is essential for providing appropriate treatment to save valuable lives. Recent development in deep learning, particularly transfer learning, is gaining a preferred trend of research in medical image processing because of their admirable performance, even with small datasets. It inspires us to develop a novel deep learning-based leukemia detection system in which an efficient and lightweight MobileNetV2 is used in conjunction with ShuffleNet to boost discrimination ability and enhance the receptive field via convolution layer succession.
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