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Biology subjects

Weiser, L.

Publications and source records attributed to Weiser, L..

2 recordsLinked to original sources

The ITCC-P4 PDX platform of pediatric cancers for preclinical testing

Cancer is the leading cause of disease-related deaths among children in high-income countries. Tumor heterogeneity and lack of mechanism-of-action-based therapeutic options are key challenges to overcome in order to improve pediatric cancer patients survival. Here, we report the EU-IMI-2 funded public-private partnership "ITCC-Pediatric Preclinical Proof-of-Concept Platform" (ITCC-P4), which has built a large repertoire of patient-derived xenograft (PDX) models, representing all major solid pediatric cancer types, for in vivo drug testing. Three-hundred-fifty-three PDX models from diagnostic and relapsed pediatric cancers have been established and molecularly characterized, together with matched germline/tumor samples. As proof-of-concept, we present in vivo drug screening data in neuroblastoma and rhabdomyosarcoma models. PDX data, accessible at http://r2platform.com/itcc-p4, allow the selection of models based on oncogenic drivers and/or potential biomarkers for preclinical testing. Operated by a non-profit entity (www.itccp4.com), this sustainable platform aids academic and industrial researchers in developing and prioritizing innovative therapies for pediatric cancer. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/703023v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@195ba30org.highwire.dtl.DTLVardef@f2c2d9org.highwire.dtl.DTLVardef@1d63f4dorg.highwire.dtl.DTLVardef@d60027_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

Pipeline Olympics: continuable benchmarking of computational workflows for DNA methylation sequencing data against an experimental gold-standard

DNA methylation is a widely studied epigenetic mark and a powerful biomarker of cell type, age, environmental exposures, and disease. Whole-genome sequencing following selective conversion of unmethylated cytosines into thymines via bisulfite treatment or enzymatic methods remains the reference method for DNA methylation profiling genome-wide. While numerous software tools facilitate processing of DNA methylation sequencing reads, a comprehensive benchmarking study has been lacking thus far. In this study, we systematically compared complete computational workflows for processing DNA methylation sequencing data using a dedicated benchmarking dataset generated with five genome-wide profiling protocols. As an evaluation reference, we employed highly quantitative locus-specific measurements from our preceding benchmark of targeted DNA methylation assays. Based on this experimental gold-standard assessment and several comprehensive metrics, we identified workflows that consistently demonstrated superior performance and revealed major workflow development trends. To facilitate the sustainability of our benchmark, we implemented an interactive workflow execution and data presentation platform, adaptable to user-defined criteria and seamlessly expandable to future software.

bioinformatics↗