Multicentric pilot study to standardize clinical whole exome sequencing (WES) for cancer patients.

A growing number of druggable targets and national initiatives for precision oncology necessitate broad genomic profiling for many cancer patients. Whole exome sequencing (WES) offers unbiased analysis of the entire coding sequence, segmentation-based detection of copy number alterations (CNAs), and accurate determination of complex biomarkers including tumor mutational burden (TMB), homologous recombination repair deficiency (HRD), and microsatellite instability (MSI). To assess the inter-institution variability of clinical WES, we performed a comparative pilot study between German Centers of Personalized Medicine (ZPMs) from five participating institutions. Tumor and matched normal DNA from 30 patients were analyzed using custom sequencing protocols and bioinformatic pipelines. Calling of somatic variants was highly concordant with a positive percentage agreement (PPA) between 91 and 95% and a positive predictive value (PPV) between 82 and 95% compared with a three-institution consensus and full agreement for 16 of 17 druggable targets. Explanations for deviations included low VAF or coverage, differing annotations, and different filter protocols. CNAs showed overall agreement in 76% for the genomic sequence with high wet-lab variability. Complex biomarkers correlated strongly between institutions (HRD: 0.79-1, TMB: 0.97-0.99) and all institutions agreed on microsatellite instability. This study will contribute to the development of quality control frameworks for comprehensive genomic profiling and sheds light onto parameters that require stringent standardization.

MIRACUM-Pipe: An Adaptable Pipeline for Next-Generation Sequencing Analysis, Reporting, and Visualization for Clinical Decision Making.

(1) Background: Next-generation sequencing (NGS) of patients with advanced tumors is becoming an established method in Molecular Tumor Boards. However, somatic variant detection, interpretation, and report generation, require in-depth knowledge of both bioinformatics and oncology. (2) Methods: MIRACUM-Pipe combines many individual tools into a seamless workflow for comprehensive analyses and annotation of NGS data including quality control, alignment, variant calling, copy number variation estimation, evaluation of complex biomarkers, and RNA fusion detection. (3) Results: MIRACUM-Pipe offers an easy-to-use, one-prompt standardized solution to analyze NGS data, including quality control, variant calling, copy number estimation, annotation, visualization, and report generation. (4) Conclusions: MIRACUM-Pipe, a versatile pipeline for NGS, can be customized according to bioinformatics and clinical needs and to support clinical decision-making with visual processing and interactive reporting.

The protein translocation systems in plants - composition and variability on the example of Solanum lycopersicum.

BACKGROUND: Protein translocation across membranes is a central process in all cells. In the past decades the molecular composition of the translocation systems in the membranes of the endoplasmic reticulum, peroxisomes, mitochondria and chloroplasts have been established based on the analysis of model organisms. Today, these results have to be transferred to other plant species. We bioinformatically determined the inventory of putative translocation factors in tomato (Solanum lycopersicum) by orthologue search and domain architecture analyses. In addition, we investigated the diversity of such systems by comparing our findings to the model organisms Saccharomyces cerevisiae, Arabidopsis thaliana and 12 other plant species. RESULTS: The literature search end up in a total of 130 translocation components in yeast and A. thaliana, which are either experimentally confirmed or homologous to experimentally confirmed factors. From our bioinformatic analysis (PGAP and OrthoMCL), we identified (co-)orthologues in plants, which in combination yielded 148 and 143 orthologues in A. thaliana and S. lycopersicum, respectively. Interestingly, we traced 82% overlap in findings from both approaches though we did not find any orthologues for 27% of the factors by either procedure. In turn, 29% of the factors displayed the presence of more than one (co-)orthologue in tomato. Moreover, our analysis revealed that the genomic composition of the translocation machineries in the bryophyte Physcomitrella patens resemble more to higher plants than to single celled green algae. The monocots (Z. mays and O. sativa) follow more or less a similar conservation pattern for encoding the translocon components. In contrast, a diverse pattern was observed in different eudicots. CONCLUSIONS: The orthologue search shows in most cases a clear conservation of components of the translocation pathways/machineries. Only the Get-dependent integration of tail-anchored proteins seems to be distinct. Further, the complexity of the translocation pathway in terms of existing orthologues seems to vary among plant species. This might be the consequence of palaeoploidisation during evolution in plants; lineage specific whole genome duplications in Arabidopsis thaliana and triplications in Solanum lycopersicum.