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Molecular analysis of Fanconi anemia: the experience of the Bone Marrow Failure Study Group of the Italian Association of Pediatric Onco-Hematology
Authors:Daniela De Rocco  Roberta Bottega  Enrico Cappelli  Simona Cavani  Maria Criscuolo  Elena Nicchia  Fabio Corsolini  Chiara Greco  Adriana Borriello  Johanna Svahn  Marta Pillon  Cristina Mecucci  Gabriella Casazza  Federico Verzegnassi  Chiara Cugno  Anna Locasciulli  Piero Farruggia  Daniela Longoni  Ugo Ramenghi  Walter Barberi  Fabio Tucci  Silverio Perrotta  Paola Grammatico  Helmut Hanenberg  Fulvio Della Ragione  Carlo Dufour  Anna Savoia
Abstract:Fanconi anemia is an inherited disease characterized by congenital malformations, pancytopenia, cancer predisposition, and sensitivity to cross-linking agents. The molecular diagnosis of Fanconi anemia is relatively complex for several aspects including genetic heterogeneity with mutations in at least 16 different genes. In this paper, we report the mutations identified in 100 unrelated probands enrolled into the National Network of the Italian Association of Pediatric Hematoly and Oncology. In approximately half of these cases, mutational screening was carried out after retroviral complementation analyses or protein analysis. In the other half, the analysis was performed on the most frequently mutated genes or using a next generation sequencing approach. We identified 108 distinct variants of the FANCA, FANCG, FANCC, FANCD2, and FANCB genes in 85, 9, 3, 2, and 1 families, respectively. Despite the relatively high number of private mutations, 45 of which are novel Fanconi anemia alleles, 26% of the FANCA alleles are due to 5 distinct mutations. Most of the mutations are large genomic deletions and nonsense or frameshift mutations, although we identified a series of missense mutations, whose pathogenetic role was not always certain. The molecular diagnosis of Fanconi anemia is still a tiered procedure that requires identifying candidate genes to avoid useless sequencing. Introduction of next generation sequencing strategies will greatly improve the diagnostic process, allowing a rapid analysis of all the genes.
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