BACKGROUND: Rhabdoid tumors are rare cancers of early childhood arising in the kidney, central nervous system and other organs. The majority are caused by somatic inactivating mutations or deletions affecting the tumor suppressor locus SMARCB1 [OMIM 601607]. Germ-line SMARCB1 inactivation has been reported in association with rhabdoid tumor, epitheloid sarcoma and familial schwannomatosis, underscoring the importance of accurate mutation screening to ascertain recurrence and transmission risks. We describe a rapid and sensitive diagnostic screening method, using high resolution melting (HRM), for detecting sequence variations in SMARCB1. METHODS: Amplicons, encompassing the nine coding exons of SMARCB1, flanking splice site sequences and the 5' and 3' UTR, were screened by both HRM and direct DNA sequencing to establish the reliability of HRM as a primary mutation screening tool. Reaction conditions were optimized with commercially available HRM mixes. RESULTS: The false negative rate for detecting sequence variants by HRM in our sample series was zero. Nine amplicons out of a total of 140 (6.4%) showed variant melt profiles that were subsequently shown to be false positive. Overall nine distinct pathogenic SMARCB1 mutations were identified in a total of 19 possible rhabdoid tumors. Two tumors had two distinct mutations and two harbored SMARCB1 deletion. Other mutations were nonsense or frame-shifts. The detection sensitivity of the HRM screening method was influenced by both sequence context and specific nucleotide change and varied from 1: 4 to 1:1000 (variant to wild-type DNA). A novel method involving digital HRM, followed by re-sequencing, was used to confirm mutations in tumor specimens containing associated normal tissue. CONCLUSIONS: This is the first report describing SMARCB1 mutation screening using HRM. HRM is a rapid, sensitive and inexpensive screening technology that is likely to be widely adopted in diagnostic laboratories to facilitate whole gene mutation screening.
BACKGROUND:Rhabdoid tumors are rare cancers of early childhood arising in the kidney, central nervous system and other organs. The majority are caused by somatic inactivating mutations or deletions affecting the tumor suppressor locus SMARCB1 [OMIM 601607]. Germ-line SMARCB1 inactivation has been reported in association with rhabdoid tumor, epitheloid sarcoma and familial schwannomatosis, underscoring the importance of accurate mutation screening to ascertain recurrence and transmission risks. We describe a rapid and sensitive diagnostic screening method, using high resolution melting (HRM), for detecting sequence variations in SMARCB1. METHODS: Amplicons, encompassing the nine coding exons of SMARCB1, flanking splice site sequences and the 5' and 3' UTR, were screened by both HRM and direct DNA sequencing to establish the reliability of HRM as a primary mutation screening tool. Reaction conditions were optimized with commercially available HRM mixes. RESULTS: The false negative rate for detecting sequence variants by HRM in our sample series was zero. Nine amplicons out of a total of 140 (6.4%) showed variant melt profiles that were subsequently shown to be false positive. Overall nine distinct pathogenic SMARCB1 mutations were identified in a total of 19 possible rhabdoid tumors. Two tumors had two distinct mutations and two harbored SMARCB1 deletion. Other mutations were nonsense or frame-shifts. The detection sensitivity of the HRM screening method was influenced by both sequence context and specific nucleotide change and varied from 1: 4 to 1:1000 (variant to wild-type DNA). A novel method involving digital HRM, followed by re-sequencing, was used to confirm mutations in tumor specimens containing associated normal tissue. CONCLUSIONS: This is the first report describing SMARCB1 mutation screening using HRM. HRM is a rapid, sensitive and inexpensive screening technology that is likely to be widely adopted in diagnostic laboratories to facilitate whole gene mutation screening.
Authors: Theo J M Hulsebos; Astrid S Plomp; Ruud A Wolterman; Els C Robanus-Maandag; Frank Baas; Pieter Wesseling Journal: Am J Hum Genet Date: 2007-02-16 Impact factor: 11.025
Authors: Piergiorgio Modena; Elena Lualdi; Federica Facchinetti; Lisa Galli; Manuel R Teixeira; Silvana Pilotti; Gabriella Sozzi Journal: Cancer Res Date: 2005-05-15 Impact factor: 12.701
Authors: Kristin Janson; Lucien A Nedzi; Odile David; Marshall Schorin; John W Walsh; Meena Bhattacharjee; Gabriella Pridjian; Lu Tan; Alexander R Judkins; Jaclyn A Biegel Journal: Pediatr Blood Cancer Date: 2006-09 Impact factor: 3.167
Authors: K D Hadfield; W G Newman; N L Bowers; A Wallace; C Bolger; A Colley; E McCann; D Trump; T Prescott; D G R Evans Journal: J Med Genet Date: 2008-02-19 Impact factor: 6.318
Authors: I Versteege; N Sévenet; J Lange; M F Rousseau-Merck; P Ambros; R Handgretinger; A Aurias; O Delattre Journal: Nature Date: 1998-07-09 Impact factor: 49.962
Authors: A C J Ammerlaan; A Ararou; M P W A Houben; F Baas; C C Tijssen; J L J M Teepen; P Wesseling; T J M Hulsebos Journal: Br J Cancer Date: 2007-12-18 Impact factor: 7.640
Authors: Stephanie I Fraley; Justin Hardick; Billie J Masek; Billie Jo Masek; Pornpat Athamanolap; Richard E Rothman; Charlotte A Gaydos; Karen C Carroll; Teresa Wakefield; Tza-Huei Wang; Samuel Yang Journal: Nucleic Acids Res Date: 2013-08-09 Impact factor: 16.971