BackgroundApproximately 5 to 10% of all cancers are caused by inherited germline mutations, many of which are associated with different Hereditary Cancer Syndromes (HCS). In the context of the Program of Hereditary Cancer of the Valencia Community, individuals belonging to specific HCS and their families receive genetic counselling and genetic testing according to internationally established guidelines. The current diagnostic approach is based on sequencing a few high-risk genes related to each HCS; however, this method is time-consuming, expensive and does not achieve a confirmatory genetic diagnosis in many cases. This study aims to test the level of improvement offered by a Next Generation Sequencing (NGS) gene-panel compared to the standard approach in a diagnostic reference laboratory setting.MethodsA multi-gene NGS panel was used to test a total of 91 probands, previously classified as non-informative by analysing the high-risk genes defined in our guidelines.ResultsNineteen deleterious mutations were detected in 16% of patients, some mutations were found in already-tested high-risk genes (BRCA1, BRCA2, MSH2) and others in non-prevalent genes (RAD51D, PALB2, ATM, TP53, MUTYH, BRIP1).ConclusionsOverall, our findings reclassify several index cases into different HCS, and change the mutational status of 14 cases from non-informative to gene mutation carriers. In conclusion, we highlight the necessity of incorporating validated multi-gene NGS panels into the HCSs diagnostic routine to increase the performance of genetic diagnosis.Electronic supplementary materialThe online version of this article (10.1186/s13053-019-0104-x) contains supplementary material, which is available to authorized users.

Background Because of their specific and biologically relevant cargo, urine extracellular vesicles (EVs) constitute a valuable source of potential non-invasive biomarkers that could support the clinical decision-making to improve the management of prostate cancer (PCa) patients. Different EV isolation methods differ in terms of complexity and yield, conditioning, as consequence, the analytical result. Methods The aim of this study was to compare three different isolation methods for urine EVs: ultracentrifugation (UC), size exclusion chromatography (SEC), and a commercial kit (Exolute® Urine Kit). Urine samples were collected from 6 PCa patients and 4 healthy donors. After filtered through 0.22 µm filters, urine was divided in 3 equal volumes to perform EVs isolation with each of the three approaches. Isolated EVs were characterized by spectrophotometric protein quantification, nanoparticle tracking analysis, transmission electron microscopy, AlphaScreen Technology, and whole miRNA Transcriptome. Results Our results showed that UC and SEC provided better results in terms of EVs yield and purity than Exolute®, non-significant differences were observed in terms of EV-size. Interestingly, luminescent AlphaScreen assay demonstrated a significant enrichment of CD9 and CD63 positive microvesicles in SEC and UC methods compared with Exolute®. This heterogeneity was also demonstrated in terms of miRNA content indicating that the best correlation was observed between UC and SEC. Conclusions Our study highlights the importance of standardizing the urine EV isolation methods to guaranty the analytical reproducibility necessary for their implementation in a clinical setting.

MicroRNAs (miRNAs) are small non-coding RNAs that negatively regulate gene expression at the post-transcriptional level, and they have been described as being associated with tumor prognosis. Here, miRNA profiling was planned to explore new molecular prognostic biomarkers in localized intestinal high-risk GIST. Paraffin tumor blocks of 14 and 86 patients were used in the discovery and expansion sets, respectively. GeneChip miRNA v3.0 was employed to identify the miRNAs differentially expressed between relapsed and non-relapsed patient samples, which were validated in the expansion set, by qRT-PCR. RT2 Profiler PCR Array was used for the screening of let-7e targets. Expression levels were correlated with relapse-free survival and overall survival. In the discovery set, 39 miRNAs were significantly deregulated, let-7e and miR-550 being the most underexpressed and overexpressed miRNAs in the relapsed group, respectively. In the expansion set, the underexpression of let-7e or the overexpression of 4 of its target genes (ACVR1B, CASP3, COL3A1, and COL5A2) were statistically associated with worse relapse-free survival. The expression of let-7e and 4 of its target genes are potential prognostic biomarkers in high-risk localized intestinal GIST. The expression of these genes is a potential molecular tool useful for a more accurate prognosis in this subset of GIST patients.

Genomic Instability (GI) is a transversal phenomenon shared by several tumor types that provide both prognostic and predictive information. In the context of high-grade serous ovarian cancer (HGSOC), response to DNA-damaging agents such as platinum-based and poly(ADP-ribose) polymerase inhibitors (PARPi) has been closely linked to deficiencies in the DNA repair machinery by homologous recombination repair (HRR) and GI. In this study, we have developed the Scarface score, an integrative algorithm based on genomic and transcriptomic data obtained from the NGS analysis of a prospective GEICO cohort of 190 formalin-fixed paraffin-embedded (FFPE) tumor samples from patients diagnosed with HGSOC with a median follow up of 31.03 months (5.87–159.27 months). In the first step, three single-source models, including the SNP-based model (accuracy = 0.8077), analyzing 8 SNPs distributed along the genome; the GI-based model (accuracy = 0.9038) interrogating 28 parameters of GI; and the HTG-based model (accuracy = 0.8077), evaluating the expression of 7 genes related with tumor biology; were proved to predict response. Then, an ensemble model called the Scarface score was found to predict response to DNA-damaging agents with an accuracy of 0.9615 and a kappa index of 0.9128 (p < 0.0001). The Scarface Score approaches the routine establishment of GI in the clinical setting, enabling its incorporation as a predictive and prognostic tool in the management of HGSOC.

BackgroundBecause of their specific and biologically relevant cargo, urine extracellular vesicles (EVs) constitute a valuable source of potential non-invasive biomarkers that could support the clinical decision-making to improve the management of prostate cancer (PCa) patients. Different EV isolation methods differ in terms of complexity and yield, conditioning, as consequence, the analytical result. MethodsThe aim of this study was to compare three different isolation methods for urine EVs: ultracentrifugation (UC), size exclusion chromatography (SEC), and a commercial kit (Exolute® Urine Kit). Urine samples were collected from 6 PCa patients and 4 healthy donors (HDs). After filtered through 0.22 µm filters, urine was divided in 3 equal volumes to perform EVs isolation with each of the three approaches. Isolated EVs were characterized by spectrophotometric protein quantification, nanoparticle tracking analysis (NTA), transmission electron microscopy (TEM), AlphaScreen Technology, and whole miRNA Transcriptome. ResultsOur results showed that UC and SEC provided better results in terms of EVs yield and purity than Exolute®, non-significant differences were observed in terms of EV-size. Interestingly, luminescent AlphaScreen assay demonstrated a significant enrichment of CD9 and CD63 positive microvesicles in SEC and UC methods compared with Exolute®. This heterogeneity was also demonstrated in terms of miRNA content indicating that the best correlation was observed between UC and SEC. ConclusionsOur study highlights the importance of standardizing the urine EV isolation methods to guaranty the analytical reproducibility necessary for their implementation in a clinical setting.