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Rare diseases comprise a diverse group of conditions, most of which involve genetic causes. We describe the variable spectrum of findings and clinical impacts of exome sequencing (ES) in a cohort of 500 patients with rare diseases. In total, 164 primary findings were reported in 158 patients, representing an overall diagnostic yield of 31.6%. Most of the findings (61.6%) corresponded to autosomal dominant conditions, followed by autosomal recessive (25.6%) and X-linked (12.8%) conditions. These patients harbored 195 variants, among which 43.6% are novel in the literature. The rate of molecular diagnosis was considerably higher for prenatal samples (67%; 4/6), younger children (44%; 24/55), consanguinity (50%; 3/6), gastrointestinal/liver disease (44%; 16/36) and syndromic/malformative conditions (41%; 72/175). For 15.6% of the cohort patients, we observed a direct potential for the redirection of care with targeted therapy, tumor screening, medication adjustment and monitoring for disease-specific complications. Secondary findings were reported in 37 patients (7.4%). Based on cost-effectiveness studies in the literature, we speculate that the reports of secondary findings may influence an increase of 123.2 years in the life expectancy for our cohort, or 0.246 years/cohort patient. ES is a powerful method to identify the molecular bases of monogenic disorders and redirect clinical care.

Background Breast cancer is the most common among women worldwide, and ovarian cancer is the most difficult gynecological tumor to diagnose and with the lowest chance of cure. Mutations in BRCA1 and BRCA2 genes increase the risk of ovarian cancer by 60% and breast cancer by up to 80% in women. Molecular tests allow a better orientation for patients carrying these mutations, affecting prophylaxis, treatment, and genetic counseling. Results Here, we evaluated the performance of a panel for BRCA1 and BRCA2, using the Ion Torrent PGM (Life Technologies) platform in a customized workflow and multiplex ligation-dependent probe amplification for detection of mutations, insertions, and deletions in these genes. We validated the panel with 26 samples previously analyzed by Myriad Genetics Laboratory, and our workflow showed 95.6% sensitivity and 100% agreement with Myriad reports, with 85% sensitivity on the positive control sample from NIST. We also screened 68 clinical samples and found 22 distinct mutations. Conclusions The selection of a robust methodology for sample preparation and sequencing, together with bioinformatics tools optimized for the data analysis, enabled the development of a very sensitive test with high reproducibility. We also highlight the need to explore the limitations of the NGS technique and the strategies to overcome them in a clinically confident manner. Electronic supplementary material The online version of this article (doi:10.1186/s40246-017-0110-x) contains supplementary material, which is available to authorized users.

e13148 Background: Tumor mutation profiling has become a key component for orienteering the treatment of oncologic patients. A crucial step for this is the correct identification and classification of pathogenic and actionable variants. In the present work we aimed at the development and validation of a tumor mutation profiling panel, based on NGS, which uses artificial intelligence for variant annotation. Methods: We designed a hybrid capture panel, containing 366 genes to evaluate somatic SNVs, INDELs and CNVs, and to calculate TMB, using a customized bioinformatics pipeline. MSI status was determined by fragment analysis using capillary electrophoresis. Analytical performance was determined using reference cell lines. FFPE samples from 70 tumors were accessed and 53 were sequenced. Variant annotation was performed by IBM Watson for Genomics (WfG) platform. Assay performance on clinical samples was defined based on orthogonal assays using Agilent CGH+SNParray 400K (for CNVs only) and Foundation One test (Foundation Medicine) (F1). Results: Breast, colon and lung were the most common tumor origins. Fifty-three samples were successfully sequenced, while 41 of them could also be analyzed by F1 test. A summary of the assay performance is presented in Table 1. Our pipeline detected 1219 variants and 290 (23%) were classified as Pathogenic, Likely Pathogenic or Actionable, according to WfG. Thirty-five samples (66%) presented a variant that could drive the treatment, with 37.7% of samples being sensitive to targeted therapies, while 22.6% were resistant; additionally, 86% had an indication for a clinical trial. Conclusions: The developed assay presented a good overall sensitivity and allele frequency correlation, with TMB and MSI having the best rates. Comparisons with F1 had reduced values of concordance; however, SNVs and INDELs presented a similar frequency. Differences on CNVs identification may rely on distinct thresholds established by the different groups. The high percentage of samples that could benefit from mutational profiling highlights the importance of such approach in the clinical routine. Additionally, the high number of variants features the need for updated information for annotation. [Table: see text]

Congenital hypogonadotrophic hypogonadism (CHH) is a challenging inherited endocrine disorder characterised by absent or incomplete pubertal development and infertility as a result of the low action/secretion of the hypothalamic gonadotrophin-releasing hormone (GnRH). Given a growing list of gene mutations accounting for CHH, the application of massively parallel sequencing comprises an excellent molecular diagnostic approach because it enables the simultaneous evaluation of many genes. The present study proposes the use of whole exome sequencing (WES) to identify causative and modifying mutations based on a phenotype-genotype CHH analysis using an in-house exome pipeline. Based on 44 known genes related to CHH in humans, we were able to identify a novel homozygous gonadotrophin-releasing hormone receptor (GNRHR) p.Thr269Met mutant, which segregates with the CHH kindred and was predicted to be deleterious by in silico analysis. A functional study measuring intracellular inositol phosphate (IP) when stimulated with GnRH on COS-7 cells confirmed that the p.Thr269Met GnRHR mutant performed greatly diminished IP accumulation relative to the transfected wild-type GnRHR. Additionally, the proband carries three heterozygous variants in CCDC141 and one homozygous in SEMA3A gene, although their effects with respect to modifying the phenotype are uncertain. Because they do not segregate with reproductive phenotype in family members, we advocate they do not contribute to CHH oligogenicity. WES proved to be useful for CHH molecular diagnosis and reinforced its benefit with respect to identifying heterogeneous genetic disorders. Our findings expand the GnRHR mutation spectrum and phenotype-genotype correlation in CHH.