Mutations of FBN1 and genotype-phenotype correlations in Marfan syndrome and related fibrillinopathies

The Marfan syndrome (MFS) is a pleiotropic, autosomal dominant disorder of connective tissue with highly variable clinical manifestations including aortic dilatation and dissection, ectopia lentis, and a series of skeletal anomalies. Mutations in the gene for fibrillin-1 (FBN1) cause MFS, and at least 337 mainly unique mutations have been published to date. FBN1 mutations have been found not only in MFS but also in a range of connective tissue disorders collectively termed fibrillinopathies ranging from mild phenotypes, such as isolated ectopia lentis, to severe disorders including neonatal MFS, which generally leads to death within the first two years of life. The present article intends to provide an overview of mutations found in MFS and related disorders and to discuss potential genotype-phenotype correlations in MFS

TGGE screening of the entire FBN1 coding sequence in 126 individuals with marfan syndrome and related fibrillinopathies

Mutations in the gene for fibrillin-1 (FBN1) cause Marfan syndrome (MFS), an autosomal dominant heritable disorder of connective tissue with prominent manifestations in the skeletal, ocular, and cardiovascular system. FBN1 mutations have also been identified in a series of related disorders of connective tissue collectively termed type-1 fibrillinopathies. We have developed temperature-gradient gel electrophoresis (TGGE) assays for all 65 FBN1 exons, screened 126 individuals with MFS, other type-1 fibrillinopathies, and other potentially related disorders of connective tissue for FBN1 mutations, and identified a total of 53 mutations, of which 33 are described here for the first time. Several mutations were identified in individuals with fibrillinopathies other than classic Marfan syndrome, including aneurysm of the ascending aorta with only minor skeletal anomalies, and several individuals with only skeletal and ocular involvement. The mutation detection rate in this study was 42% overall, but was only 12% in individuals not fulfilling the diagnostic criteria for MFS, suggesting that clinical overdiagnosis is one reason for the low detection rate observed for FBN1 mutation analysis. Hum Mutat 20:197-208, 2002. © 2002 Wiley-Liss, Inc

Decentral gene expression analysis for ER+/Her2- breast cancer: results of a proficiency testing program for the EndoPredict assay

Gene expression profiles provide important information about the biology of breast tumors and can be used to develop prognostic tests. However, the implementation of quantitative RNA-based testing in routine molecular pathology has not been accomplished, so far. The EndoPredict assay has recently been described as a quantitative RT-PCR-based multigene expression test to identify a subgroup of hormone-receptor-positive tumors that have an excellent prognosis with endocrine therapy only. To transfer this test from bench to bedside, it is essential to evaluate the test-performance in a multicenter setting in different molecular pathology laboratories. In this study, we have evaluated the EndoPredict (EP) assay in seven different molecular pathology laboratories in Germany, Austria, and Switzerland. A set of ten formalin-fixed paraffin-embedded tumors was tested in the different labs, and the variance and accuracy of the EndoPredict assays were determined using predefined reference values. Extraction of a sufficient amount of RNA and generation of a valid EP score was possible for all 70 study samples (100%). The EP scores measured by the individual participants showed an excellent correlation with the reference values, respectively, as reflected by Pearson correlation coefficients ranging from 0.987 to 0.999. The Pearson correlation coefficient of all values compared to the reference value was 0.994. All laboratories determined EP scores for all samples differing not more than 1.0 score units from the pre-defined references. All samples were assigned to the correct EP risk group, resulting in a sensitivity and specificity of 100%, a concordance of 100%, and a kappa of 1.0. Taken together, the EndoPredict test could be successfully implemented in all seven participating laboratories and is feasible for reliable decentralized assessment of gene expression in luminal breast cancer