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Neurofibromatosis type 1 (NF1) is a hereditary disorder caused by mutations in the NF1 gene. Detecting mutation in NF1 is hindered by the gene's large size, the lack of mutation hotspots, and the presence of pseudogenes.Our goal was to establish a sensitive, feasible, and comparatively economical protocol to detect NF1 mutations using blood samples.We developed a method to screen patients for mutations. Thirty-two NF1 patients from 32 unrelated families and 120 unrelated population-match controls were investigated in this study. Specific primers were designed for NF1 to avoid pseudogenes. NF1 mutations were detected by sequencing at the deoxyribonucleic acid (DNA) and complementary DNA (cDNA) levels, and multiplex ligation-dependent probe amplification (MLPA) and familial segregation analyses were used.Forty-four specific primers designed according to the NF1 structure were successfully used for polymerase chain reaction (PCR) and DNA sequencing, which was more feasible and useful than cDNA sequencing. Thirty distinct NF1 mutations were identified in 32 patients. Thirteen mutations were novel and most were frameshift mutations (33.3%). Mutations were detected at a rate of 93.8%.Our study suggests that this sensitive, feasible, and comparatively economical protocol is effective for the detection of NF1 mutations.
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http://dx.doi.org/10.1097/MD.0000000000003043 | DOI Listing |
Cancer Genet
August 2025
Clinical Hematology and BMT Unit, Bahrain Oncology Center, Road 2835, Block 228, P.O. Box 24343, Busaiteen, Kingdom of Bahrain. Electronic address:
Complex chromosomal changes in Acute Myeloid Leukemia (AML) are highly heterogeneous, with disease progression shaped by both the number and nature of abnormalities. Rarely do, multiple unrelated clones with independent chromosomal changes coexist at diagnosis. Present study showcases a comprehensive characterization of two cytogenetically distinct complex clones in AML, driven by non-cyclic and chromoplexy mechanisms, highlighting their co-existence with key molecular alterations (TP53, NF1, DNMT3A, TET2) along with their potential contribution to clonal evolution.
View Article and Find Full Text PDFPediatr Dev Pathol
September 2025
The Hospital for Sick Children, Division of Pathology, Toronto, Canada.
Background: Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma of childhood. For stratification purposes, rhabdomyosarcoma is classified into fusion-positive RMS (alveolar rhabdomyosarcoma) and fusion-negative RMS (embryonal or spindle cell/sclerosing, FN-RMS) subtypes according to its fusion status. This study aims to highlight the pathologic and molecular characteristics of a cohort of FN-RMS using a targeted NGS RNA-Seq assay.
View Article and Find Full Text PDFCancer
September 2025
Department of Medical Oncology, Centre Léon Bérard, Lyon, France.
Background: Immune checkpoint inhibitors (ICIs) in unselected sarcomas yield limited response rates and tumor control. Long-term responders have however been reported, suggesting a critical challenge in refining patient selection, by identifying reliable predictive factors for response.
Methods: The authors conducted a multicenter, retrospective study of patients with advanced sarcomas treated with ICIs in six French reference sarcoma centers.
Int J Dev Neurosci
October 2025
Department of Neurology, Children's Hospital Affiliated to Shandong University, Jinan, Shandong, China.
Neurofibromatosis type 1 (NF1) is an autosomal dominant genetic disorder, with plexiform neurofibromas occurring in approximately 20%-50% of patients. A 12-year-old girl underwent surgery due to unbearable pain caused by diffuse neurofibromas. Postoperatively, the girl exhibited rapid growth and extremely extensive plexiform neurofibromas, with multiple plexiform neurofibromas that were inoperable.
View Article and Find Full Text PDFHum Genomics
August 2025
Laboratory of Translational Oncology, European Institute of Oncology IRCCS, Milan, Italy.
Identification of a pathogenic variant in NF1 is diagnostic for neurofibromatosis, but is often impossible at the moment of variant detection due to many factors including allelic heterogeneity, sequence homology, and the lack of functional assays. Computational tools may aid in interpretation but are not established for NF1. Here, we optimized our random forest-based predictor RENOVO for NF1 variant interpretation.
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