The CYSMA web server: An example of integrative tool for in silico analysis of missense variants identified in Mendelian disorders.

Exome sequencing used for molecular diagnosis of Mendelian disorders considerably increases the number of missense variants of unclear significance, whose pathogenicity can be assessed by a variety of prediction tools. As the performance of algorithms may vary according to the datasets, complementary specific resources are needed to improve variant interpretation. As a model, we were interested in the cystic fibrosis transmembrane conductance regulator gene (CFTR) causing cystic fibrosis, in which at least 40% of missense variants are reported. Cystic fibrosis missense analysis (CYSMA) is a new web server designed for online estimation of the pathological relevance of CFTR missense variants. CYSMA generates a set of computationally derived data, ranging from evolutionary conservation to functional observations from three-dimensional structures, provides all available allelic frequencies, clinical observations, and references for functional studies. Compared to software classically used in analysis pipelines on a dataset of 141 well-characterized missense variants, CYSMA was the most efficient tool to discriminate benign missense variants, with a specificity of 85%, and very good sensitivity of 89%. These results suggest that such integrative tools could be adapted to numbers of genes involved in Mendelian disorders to improve the interpretation of missense variants identified in the context of diagnosis.

CFTR-France, a national relational patient database for sharing genetic and phenotypic data associated with rare CFTR variants.

Most of the 2,000 variants identified in the CFTR (cystic fibrosis transmembrane regulator) gene are rare or private. Their interpretation is hampered by the lack of available data and resources, making patient care and genetic counseling challenging. We developed a patient-based database dedicated to the annotations of rare CFTR variants in the context of their cis- and trans-allelic combinations. Based on almost 30 years of experience of CFTR testing, CFTR-France (https://cftr.iurc.montp.inserm.fr/cftr) currently compiles 16,819 variant records from 4,615 individuals with cystic fibrosis (CF) or CFTR-RD (related disorders), fetuses with ultrasound bowel anomalies, newborns awaiting clinical diagnosis, and asymptomatic compound heterozygotes. For each of the 736 different variants reported in the database, patient characteristics and genetic information (other variations in cis or in trans) have been thoroughly checked by a dedicated curator. Combining updated clinical, epidemiological, in silico, or in vitro functional data helps to the interpretation of unclassified and the reassessment of misclassified variants. This comprehensive CFTR database is now an invaluable tool for diagnostic laboratories gathering information on rare variants, especially in the context of genetic counseling, prenatal and preimplantation genetic diagnosis. CFTR-France is thus highly complementary to the international database CFTR2 focused so far on the most common CF-causing alleles.

Non-invasive prenatal diagnosis of monogenic disorders: an optimized protocol using MEMO qPCR with miniSTR as internal control.

BACKGROUND: Analysis of circulating cell-free fetal DNA (cffDNA) in maternal plasma is very promising for early diagnosis of monogenic diseases. However, this approach is not yet available for routine use and remains technically challenging because of the low concentration of cffDNA, which is swamped by the overwhelming maternal DNA. METHODS: To make clinical applications more readily accessible, we propose a new approach based on mutant enrichment with 3'-modified oligonucleotides (MEMO) PCR along with real-time PCR to selectively amplify from the maternal blood the paternally inherited fetal allele that is not present in the maternal genome. RESULTS: The first proof of concept of this strategy was displayed for cystic fibrosis by the accuracy of our detection of the p.Gly542* mutation used as the initial developmental model. Subsequently, a retrospective study of plasmas originating from two pregnant women carrying a fetus with private mutation confirmed the effectiveness of our method. We confirmed the presence of cffDNA in the studied samples by the identification of a tri-allelic DNA profile using a miniSTR kit. CONCLUSIONS: This new non-invasive prenatal diagnosis test offers numerous advantages over current methods: it is simple, cost effective, time efficient and does not require complex equipment or bioinformatics settings. Moreover, our assays for different private mutations demonstrate the viability of this approach in clinical settings for monogenic disorders.

A classification model relative to splicing for variants of unknown clinical significance: application to the CFTR gene.

Molecular diagnosis of cystic fibrosis and cystic fibrosis transmembrane regulator (CFTR)-related disorders led to the worldwide identification of nearly 1,900 sequence variations in the CFTR gene that consist mainly of private point mutations and small insertions/deletions. Establishing their effect on the function of the encoded protein and therefore their involvement in the disease is still challenging and directly impacts genetic counseling. In this context, we built a decision tree following the international guidelines for the classification of variants of unknown clinical significance (VUCS) in the CFTR gene specifically focused on their consequences on splicing. We applied general and specific criteria, including comprehensive review of literature and databases, familial genetics data, and thorough in silico studies. This model was tested on 15 intronic and exonic VUCS identified in our cohort. Six variants were classified as probably nonpathogenic considering their impact on splicing and eight as probably pathogenic, which include two apparent missense mutations. We assessed the validity of our method by performing minigenes studies and confirmed that 93% (14/15) were correctly classified. We provide in this study a high-performance method that can play a full role in interpreting the results of molecular diagnosis in emergency context, when functional studies are not achievable.

UMD-CFTR: a database dedicated to CF and CFTR-related disorders.

With the increasing knowledge of cystic fibrosis (CF) and CFTR-related diseases (CFTR-RD), the number of sequence variations in the CFTR gene is constantly raising. CF and particularly CFTR-RD provide a particular challenge because of many unclassified variants and identical genotypes associated with different phenotypes. Using the Universal Mutation Database (UMD) software we have constructed UMD-CFTR (freely available at the URL: http://www.umd.be/CFTR/), the first comprehensive relational CFTR database that allows an in-depth analysis and annotation of all variations identified in individuals whose CFTR genes have been analyzed extensively. The system has been tested on the molecular data from 757 patients (540 CF and 217 CBAVD) including disease-causing, unclassified, and nonpathogenic alterations (301 different sequence variations) representing 3,973 entries. Tools are provided to assess the pathogenicity of mutations. UMD-CFTR also offers a number of query tools and graphical views providing instant access to the list of mutations, their frequencies, positions and predicted consequences, or correlations between genotypes, haplotypes, and phenotypes. UMD-CFTR offers a way to compile not only disease-causing genotypes but also haplotypes. It will help the CFTR scientific and medical communities to improve sequence variation interpretation, evaluate the putative influence of haplotypes on mutations, and correlate molecular data with phenotypes.

Comprehensive and rapid genotyping of mutations and haplotypes in congenital bilateral absence of the vas deferens and other cystic fibrosis transmembrane conductance regulator-related disorders.

Available commercial kits only screen for the most common cystic fibrosis transmembrane conductance regulator (CFTR) mutations causing classic cystic fibrosis and for the Tn variant in IVS8. However, full scanning of CFTR is needed for the diagnosis of patients with cystic fibrosis or CFTR-related disorders (including congenital bilateral absence of the vas deferens) bearing rare mutations. Standard strategies for detecting point mutations rely on extensive scanning of the gene by denaturing gradient gel electrophoresis or denaturing high performance liquid chromatography, which are time-consuming. Moreover, the haplotyping of IVS8-(TG)m and Tn tracts is still challenging despite several recent improvements. We have optimized both the detection of mutations and the haplotyping of IVS8 polyvariants in developing two methods: i) a rapid and robust direct sequence analysis of all exons/flanking introns of the CFTR gene based on single condition touchdown amplification/sequencing in 96-well plates, and ii) a fluorescent assay that allows haplotyping of IVS8-(TG)mTn even without family linkage study. Combined with search for rare large rearrangements, this strategy detected 87.9% of CFTR defects in congenital bilateral absence of the vas deferens patients, a proportion considerably higher than those usually reported. These highly efficient tests, scanning each sample in a few days, greatly improve the genotyping of patients with CFTR-related symptoms and may be particularly important in emergency situations such as fetus with hyperechogenic bowel suggestive of cystic fibrosis.

Gene expression signature in advanced colorectal cancer patients select drugs and response for the use of leucovorin, fluorouracil, and irinotecan.

PURPOSE: In patients with advanced colorectal cancer, leucovorin, fluorouracil, and irinotecan (FOLFIRI) is considered as one of the reference first-line treatments. However, only about half of treated patients respond to this regimen, and there is no clinically useful marker that predicts response. A major clinical challenge is to identify the subset of patients who could benefit from this chemotherapy. We aimed to identify a gene expression profile in primary colon cancer tissue that could predict chemotherapy response. PATIENTS AND METHODS: Tumor colon samples from 21 patients with advanced colorectal cancer were analyzed for gene expression profiling using Human Genome GeneChip arrays U133. At the end of the first-line treatment, the best observed response, according to WHO criteria, was used to define the responders and nonresponders. Discriminatory genes were first selected by the significance analysis of microarrays algorithm and the area under the receiver operating characteristic curve. A predictor classifier was then constructed using support vector machines. Finally, leave-one-out cross validation was used to estimate the performance and the accuracy of the output class prediction rule. RESULTS: We determined a set of 14 predictor genes of response to FOLFIRI. Nine of nine responders (100% specificity) and 11 of 12 nonresponders (92% sensitivity) were classified correctly, for an overall accuracy of 95%. CONCLUSION: After validation in an independent cohort of patients, our gene signature could be used as a decision tool to assist oncologists in selecting colorectal cancer patients who could benefit from FOLFIRI chemotherapy, both in the adjuvant and the first-line metastatic setting.