2009 Vienna - European Society of Human Genetics

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Cancer genetics P06.116 Uptake of BRcA1/2 predictive testing and gender L. Denayer1 , A. Boogaerts1 , K. Philippe1 , E. Legius2 , G. Evers-Kiebooms1 ; 1 2 Psychosocial Genetics, Center for Human Genetics, Leuven, Belgium, Clinical Genetics, Center for Human Genetics, Leuven, Belgium. Data concerning male uptake of BRCA1/2 predictive testing and pretest characteristics in comparison to females are scarce. We investigated the cohorts of male and female applicants attending the Center of Human Genetics in Leuven during a 10-years period (1998-2007). Considering all unaffected siblings in the family of origin of the predictive test applicants, uptake of predictive testing for BRCA1/2 was 32% in males and 82% in females (p
Cancer genetics the past and it is probably positioned in a hot spot point for mutations. The two different haplotypes reflects diverse historical origins in the east and west Castilla-León region. P06.121 Detection and characterization of new large deletion of exon 3 in the BRCA gene among a French breast cancer family. D. Muller1 , E. Rouleau2 , I. Schultz1 , C. Andrieux2 , O. Caron3 , R. Lidereau2 , J. Abecassis1 , J. Fricker1 ; 1 2 CRLCC P. Strauss, Strasbourg, France, CRLCC R. Huguenin, Inserm U735, Saint Cloud, France, 3Hôpitaux Universitaires, Strasbourg, France. Germ-line mutations in two genes, BRCA1 and BRCA2 genes, are the major contributors to hereditary breast/ovarian cancer. Nowadays, large rearrangements have been described regularly in BRCA1 with approximately 10-15% of the mutations in this gene. In contrast, large genomic rearrangements in the BRCA2 gene have been rarely reported. During the comprehensive screening of breast/ovarian cancer families for germ-line mutation in these genes, we detected a deletion of exon 3 in BRCA2 in a breast cancer family, using the QMPSF (quantitative multiplex PCR of short fluorescent fragments) and confirmed by MLPA (multiplex ligation-dependent probe amplification) methods for detection of large genomic rearrangements. This mutation was characterized by high-resolution oligonucleotide array-CGH technology which estimated the size of the deleted region and helped to find the breakpoint. Precise determination of the size and identification of the breakpoint were obtained with a specific PCR and the deleted sequence was different from previous reports. Moreover, analysis of transcripts revealed the only skipping of exon 3. Since this deletion is in-frame, the deleterious impact is largely discussed in the literature. Despite a limited number of cases in this family, the segregation data seemed to be consistent with a causal effect of the mutation. In addition to conventional DNA diagnostic testing by sequencing, familial breast cancer patients can benefit from searching for large rearrangements in the BRCA2 gene. The in-frame deletion of exon 3 needs additional studies to investigate its contribution to hereditary breast/ovarian cancer. P06.122 BRCA1/2 screening results: Review of molecular data concerning Portuguese high-risk breast/ovarian cancer families P. M. Machado 1 , S. Santos 1 , S. Fragoso 1 , S. Bento 2 , P. Rodrigues 2 , A. Luís 2 , A. Opinião 2 , F. Vaz 1,2 ; 1 Molecular Biology Department - Portuguese Institute of Oncology, Lisbon, Portugal, 2 Breast Cancer Risk Evalution Clinic- Portuguese Institute of Oncology, Lisbon, Portugal. Introduction: Although BRCA1 and BRCA2 are the genes most frequently involved in familial aggregation of breast/ovarian cancer, mutations in other genes like TP53, PTEN, ATM, CHEK2 and PALB2 could also cause breast cancer risks. Taken together, the known susceptibility genes account for less than one third of breast cancer families undergoing genetic testing while other gene defects remain to be discovered [EMQN guidelines 2007]. Patients and methods: Review of all patients for whom BRCA1/2 screening is complete. All patients underwent pre and post-test counselling and are pre-screened for the BRCA2 Portuguese founder mutation [Machado et al, 2007]. Negative patients are further analysed by CSCE and samples with a different pattern are sequenced. Previous to the CSCE optimization, DNA samples were analysed by CSGE. Results: Two hundred and forty nine families were fully screened for BRCA1/2 mutations and 61 positive patients were detected (10 BRCA1 and 51 BRCA2 mutations, including 28 families with the founder mutation), which corresponds to a 25% detection rate. The range of mutations and sequence variants as well as their frequency in this set of patients were analysed, allowing for a better characterization of the breast/ovarian cancer high risk families from the Central and Southern regions of Portugal. Depending on pedigree reanalysis BRCA1/2 negative families are being screened for other gene mutations (p53 and PTEN). Conclusion: From 249 Portuguese high-risk families, 61 presented deleterious BRCA mutations. As expected, several neutral or unknown variants were also detected, posing a significant challenge for counselling. P06.123 Identification and characterization of large genomic rearrangements in BRCA , BRCA and CHEK genes J. Del Valle 1 , M. Nadal 1 , L. Feliubadaló 1 , R. Cuesta 1 , E. Tornero 1 , M. Menéndez 1 , J. Brunet 2 , À. Teulé 2 , G. Capellá 1 , I. Blanco 2 , C. Lázaro 1 ; 1 Programa de Diagnòstic Molecular de Càncer Hereditari, Laboratori de Recerca Translacional, Institut Català d’Oncologia-IDIBELL, Hospitalet de Llobregat, Barcelona, Spain, Hospitalet de Llobregat, Spain, 2 Programa de Consell Genètic en Càncer, Institut Català d’Oncologia, Hospitalet de Llobregat-IDIBELL (AT, IB) and Girona- IdIBGi (JB), Hospitalet de Llobregat, Spain. Large genomic rearrangements are estimated to account for about 5- 10% of all disease-causing mutations in BRCA1 and BRCA2 genes in patients with hereditary breast and ovarian cancer syndrome (HBOC). To screen for such rearrangements in patients with HBOC, and as a first step in our genetic testing workflow, we use MRC-Holland Multiplex Ligation-dependent Probe Amplification (MLPA). We have used this technique in a set of 310 independent patients and we have detected 9 different copy number alterations corresponding to 3% of the studied samples and about 15% of all identified mutations in BRCA1 and BRCA2 genes in our cohort. As commercial MLPA tests are not suitable to determine the specific breakpoints or to define the exact extension of the rearrangement, we have applied a set of different complementary techniques in order to better characterize these genetic alterations. We have used long-range PCR amplification, RNA analysis, SNP array chips, not commercial MLPA probes and FISH analysis to fully define the extent and mechanism of each of the identified alterations. Briefly, in BRCA1 we have characterized 6 rearrangements: deletion of E22, deletion of E9-E24, deletion of E16-E23, deletion of E1-E13, deletion of E1-E2, duplication of E1-E2. In BRCA2 we studied a deletion of E15-E16 and a deletion of E1-E24 and in CHEK2 we have identified a complete gene deletion. In addition, it is worth to mention that MLPA demonstrated to be useful to identify point mutations located within probe sequences. P06.124 cost-effectiveness analysis of prophylaxis programme in women with a family history of breast cancer and cHEK2*1100delc heterozygosity in the Polish health-care system E. Orlewska1 , J. Lubinski2 , C. Cybulski2 ; 1 2 Centre for Pharmacoeconomics, Warsaw, Poland, Pomeranian Medical University, Szczecin, Poland. Aim of the study: economic evaluation of prophylaxis programme starting at 25 years old women with a family history of breast cancer and CHEK2*1100delC heterozygosity versus no prophylaxis. Methods: Cost-effectiveness analysis was perfomed using modelling technique. Two cohorts were studied: without prophylaxis, and with prophylaxis. Data on life expectancy, breast cancer risk, efficacy of prophylaxis and medical costs were obtained from published literatures. The cohort simulation started with 25-year-old women and projected direct medical costs and outcomes over patients lifetimes. Effectiveness was measured as life years gained (LYG). Only direct medical costs (breast cancer prophylaxis and treatment of breast cancer I-IV stages) were included, assessed from health-care payer perspective and reported in PLN (1 EUR= 4.5 PLN in 2009). 5% and 3.5% discount rate was used for cost and effectiveness, respectively. Sensitivity analyses to treatment patterns, efficacy of prophylaxis and costs were performed. Results: The total lifetime costs/patient were estimated to be 4453 PLN (discounted: 1318 PLN) in no prophylaxis arm and 5380 PLN (discounted : 2135 PLN) in prophylaxis arm . The life expectancy generated with prophylaxis was 75.43 vs. 70.5 for no prophylaxis (without discounting) and 48.01 vs. 46.79 (discounted), respectively. This results in ICER for prophylaxis of 187.7 PLN/LYG (without discounting) and 672.7 PLN/LY (discounted). Results were robust to sensitivity analyses. Conclusion: Breast cancer prophylaxis programme for women with a family history of breast cancer and CHEK2*1100delC heterozygosity compared to no prophylaxis improves survival and is highly cost-effective in the Polish health-care system.
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Volume 17 Supplement 2 May 2009 www
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European Society of Human Genetics
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Table of Contents spoken Presentati
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Plenary Lectures PL2.2 massive para
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Concurrent Symposia s01.1 Genome va
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Concurrent Symposia Monogenic diabe
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Concurrent Symposia invariable in t
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Concurrent Symposia s11.2 clinical,
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Concurrent Symposia s13.2 A novel g
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Concurrent Sessions c01.1 mRNA-seq
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Concurrent Sessions velopmental del
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Concurrent Sessions development of
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Concurrent Sessions c04.6 Duplicati
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Concurrent Sessions genes to be rec
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Concurrent Sessions c07.5 Prenatal
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Concurrent Sessions with familial h
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Concurrent Sessions University of W
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Concurrent Sessions with this, we f
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Concurrent Sessions had immotile ci
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Concurrent Sessions abnormal glycos
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Concurrent Sessions showers’ and
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Concurrent Sessions partial gene de
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Concurrent Sessions leads to distre
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Genetic counseling Genetics educati
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Clinical genetics and Dysmorphology
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Cytogenetics P03. cytogenetics Recu
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Cytogenetics use of metaphase analy
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Cytogenetics 2: mother’s age < fa
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Cytogenetics P03.028 HLA B27 allele
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Cytogenetics karyotype revealed a p
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Cytogenetics drome is estimated at
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Cytogenetics P03.057 Pathological c
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Cytogenetics grandmother and 2 mate
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Cytogenetics method used to detect
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Cytogenetics P03.082 High-resolutio
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Cytogenetics All detected anomalies
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Cytogenetics somy for chromosome 2.
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Cytogenetics cially in chromosome 4
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Cytogenetics (59.390.122 to 62.021.
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Cytogenetics For further characteri
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Cytogenetics 9p duplication. This c
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Cytogenetics regions with mental /d
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Cytogenetics donation program of po
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Cytogenetics P03.165 interpretation
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Cytogenetics P03.174 Deletion of th
Page 145 and 146: Cytogenetics P03.183 An atypical 7q
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Page 149 and 150: Reproductive genetics and social fa
Page 151 and 152: Reproductive genetics mosomal chang
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Page 155 and 156: Reproductive genetics the 147 SC ch
Page 157 and 158: Prenatal and perinatal genetics P05
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Page 169 and 170: Prenatal and perinatal genetics P05
Page 171 and 172: Cancer genetics P06.005 tiling reso
Page 173 and 174: Cancer genetics tient group in whic
Page 175 and 176: Cancer genetics chronic inflammatio
Page 177 and 178: Cancer genetics licular thyroid can
Page 179 and 180: Cancer genetics also studied. In 31
Page 181 and 182: Cancer genetics tile polyposis. We
Page 183 and 184: Cancer genetics Upon recombinant ex
Page 185 and 186: Cancer genetics variant allele was
Page 187 and 188: Cancer genetics from patients with
Page 189 and 190: Cancer genetics tion (PAX5 and GATA
Page 191 and 192: Cancer genetics scribed underexpres
Page 193 and 194: Cancer genetics of the ZIC gene fam
Page 195: Cancer genetics Materials and metho
Page 199 and 200: Cancer genetics P06.130 spectrum an
Page 201 and 202: Cancer genetics P06.139 the role of
Page 203 and 204: Cancer genetics and MSH2 germline m
Page 205 and 206: Cancer genetics P06.155 New roles f
Page 207 and 208: Cancer genetics screening was perfo
Page 209 and 210: Cancer genetics val (DFI) than pati
Page 211 and 212: Cancer genetics is hTERC gene ampli
Page 213 and 214: Cancer genetics on chromosome regio
Page 215 and 216: Cancer genetics preferentially dupl
Page 217 and 218: Cancer cytogenetics mutations in co
Page 219 and 220: Cancer cytogenetics P07.08 molecula
Page 221 and 222: Statistical genetics, includes Mapp
Page 235 and 236: Complex traits and polygenic disord
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Complex traits and polygenic disord
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Evolutionary and population genetic
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Genomics, Genomic technology and Ep
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Molecular basis of Mendelian disord
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Metabolic disorders P12.167 Pattern
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Metabolic disorders PKU. BH4 challe
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Metabolic disorders catepe Universi
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Metabolic disorders respectively. G
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Metabolic disorders enzymaticaly co
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Metabolic disorders Normal Affected
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Therapy for genetic disorders in th
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Therapy for genetic disorders P14.0
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Therapy for genetic disorders of me
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Laboratory and quality management P
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Laboratory and quality management T
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Molecular and biochemical basis of
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Genetic analysis, linkage ans assoc
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Author Index Allanson, J.: P02.140
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Author Index 0 Barbacioru, C.: C01.
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Author Index 0 Bonneau, D.: C16.2,
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Author Index 0 Chakravarti, A.: C13
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Author Index 0 Dan, D.: P01.39, P14
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Author Index 0 Duskova, J.: P06.012
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Author Index Franke, A.: P09.056 Fr
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Author Index Grasso, R.: P02.025 Gr
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Author Index Holder-Espinasse, M.:
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Author Index Jurkiewicz, E.: C14.5
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Author Index Kooper, A. J. A.: P05.
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Author Index Li, K. J.: P11.086 Li,
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Author Index Martinet, D.: P03.095
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Author Index Moorman, A. F. M.: P16
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Author Index P10.57, P10.82 Oguzkan
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Author Index P09.054, P09.085, P09.
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Author Index P16.01 Renieri, A.: P0
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Author Index Santorelli, F.: P08.55
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Author Index Sinke, R. J.: P02.020
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Author Index Taheri, M.: P04.33, P0
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Author Index Valentino, P.: P02.064
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Author Index Wiemer-Kruel, A.: P14.
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Keyword Index 1 10q22 deletions: P0
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Keyword Index autosomal dominant re
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Keyword Index CLA: P06.073 CLCN1 ge
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Keyword Index DMD: P16.40, P16.41,
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Keyword Index gene networks: S12.2
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Keyword Index hydrocephaly: P05.11
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Keyword Index malignant hyperthermi
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Keyword Index NAT2: P12.118 natridi
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Keyword Index Polymalformations: P0
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Keyword Index Sardinia: C09.6 Sardi
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Keyword Index TNFalpha: P08.61, P09
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2009 Vienna - European Society of Human Genetics

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