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Biomedical subjects

Juan Maria Roldan-Romero

Publications and source records attributed to Juan Maria Roldan-Romero.

2 recordsLinked to original sources

Integrated signatures define mutational processes in prostate cancer.

Prostate cancer follows a long and heterogeneous disease course with incompletely understood aetiology1. Here we dissect the mutational processes shaping the genomes of 959 donors from the Pan Prostate Cancer Group and assess their clinical relevance. By integrating de novo extracted single-base substitution, insertion-deletion and copy-number signatures with six novel complex structural variant signatures, we identify eight integrated mutational footprints (IMFs) that collectively explain the mutational processes in 85% of primary prostate cancer genomes. IMFs were strongly influenced by regional biases in the genome, most prevalently androgen receptor-mediated mutagenesis and replication stress. Four IMFs, present in 37% of primary tumours, were significantly associated with shorter time to metastasis. These included reactive oxygen-species-driven mutagenesis and both canonical and non-canonical homologous recombination deficiency, the latter being enriched in patients of African ancestry. Extending to the metastatic setting, we found that IMFs predicted sensitivity to androgen receptor pathway inhibitors. Taken together, our study delineates the aetiologies and mutational processes that drive the genomic and clinical heterogeneity of prostate cancer, introduces IMFs as a unifying framework, and highlights their potential to improve both risk stratification and biomarker-guided treatment selection.

Journal Article↗

Associations on the Fly, a new feature aiming to facilitate exploration of the Open Targets Platform evidence.

MOTIVATION: The Open Targets Platform (https://platform.opentargets.org) is a unique, comprehensive, open-source resource supporting systematic identification and prioritisation of targets for drug discovery. The Platform combines, harmonizes and integrates data from >20 diverse sources to provide target-disease associations, covering evidence derived from genetic associations, somatic mutations, known drugs, differential expression, animal models, pathways and systems biology. An in-house target identification scoring framework weighs the evidence from each data source and type, contributing to an overall score for each of the 7.8M target-disease associations. However, the old infrastructure did not allow user-led dynamic adjustments in the contribution of different evidence types for target prioritisation, a limitation frequently raised by our user community. Furthermore, the previous Platform user interface did not support navigation and exploration of the underlying target-disease evidence on the same page, occasionally making the user journey counterintuitive. RESULTS: Here, we describe 'Associations on the Fly' (AOTF), a new Platform feature-developed with a user-centred vision-that enables the user to formulate more flexible therapeutic hypotheses through dynamic adjustment of the weight of contributing evidence from each source, altering the prioritisation of targets. AVAILABILITY AND IMPLEMENTATION: The codebases that power the Platform-including our pipelines, GraphQL API, and React UI-are all open source and licensed under the APACHE LICENSE, VERSION 2.0. You can find all of our code repositories on GitHub at https://github.com/opentargets and on Zenodo at https://zenodo.org/records/14392214. This tool was implemented using React v18 and its code is accessible here: (https://github.com/opentargets/ot-ui-apps). The tools are accessible through the Open Targets Platform web interface (https://platform.opentargets.org/) and GraphQL API (https://platform-docs.opentargets.org/data-access/graphql-api). Data is available for download here: (https://platform.opentargets.org/downloads) and from the EMBL-EBI FTP: (https://ftp.ebi.ac.uk/pub/databases/opentargets/platform/).

Software↗