Biology subjects

Carmona, M.

Publications and source records attributed to Carmona, M..

5 recordsLinked to original sources

bioRxiv2024

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

MotivationThe 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, harmonises 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 previous 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. ResultsHere, we describe "Associations on the Fly" (AOTF), a new Platform feature - developed as part of a wider product refactoring project - to enable formulation of more flexible and impactful therapeutic hypotheses through dynamic adjustment of the weight of contributing evidence from each source, altering the prioritisation of targets. Availability and implementationAll Open Targets code is available as open source: [https://github.com/opentargets]. This tool was implemented using React v18 and its code is accessible here: [https://github.com/opentargets/ot-ui-apps]. The tools described in the paper 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/]. Supplementary informationAdditional information on this tool can be found on the Platform documentation pages [https://platform-docs.opentargets.org/web-interface, https://platform-docs.opentargets.org/web-interface/associations-on-the-fly, https://platform-docs.opentargets.org/target-prioritisation] and training video [https://youtu.be/2A9bksboAag]. ContactAnnalisa Buniello, EMBL-EBI, buniello@ebi.ac.uk

bioinformatics↗

bioRxiv2024

Red blood cell-tumour cell interactions promote tumour cell progression

One critical step in the metastatic cascade is the survival of circulating tumour cells (CTCs) within the bloodstream. While numerous interactions between CTCs and various hematopoietic cells have been described, the role of red blood cells (RBCs) in this process remains underexplored. This study investigates the interactions between tumour cells and RBCs from breast and lung cancer patients, revealing significant phenotypic and functional changes in the tumour cells, unlike when the contact is with RBCs from healthy donors. In vitro co-culture of cancer cell lines with RBCs from metastatic cancer patients resulted in increased tumour cell attachment accompanied by morphological changes. Additionally, RBCs-primed tumour cells showed increased adhesion and disruption of the endothelial barrier in vitro and increased invasiveness both in vitro and in vivo. Transcriptomic analysis showed that RBCs from metastatic breast cancer patients induce significant gene expression changes, notably upregulating PAK4, which enhances migration and epithelial-mesenchymal transition. PAK4 inhibition reduced these effects. Proteomic studies revealed substantial remodelling, including actin-related changes and the accumulation of VASP at cell edges, promoting directional migration. Clinically, higher RBC distribution width (RDW) in metastatic breast cancer patients is associated with increased CTC counts and worse outcome. This study highlights the previously unrecognized role of RBCs in promoting metastatic behaviours in cancer cells and suggests potential therapeutic targets, such as PAK4, to counteract these effects. Further exploration of RBCs-tumour cell interactions could provide new insights into metastatic mechanisms and improve cancer prognosis and treatment strategies. Key PointsO_LIThis study reveals the previously unknown role of RBCs in enhancing tumour cell invasiveness and metastatic potential. C_LIO_LITumour cells undergo significant phenotypic and functional changes after contact with RBCs from cancer patients. C_LI

cancer biology↗

bioRxiv2022

Transcriptional response of the xerotolerant Arthrobacter sp. Helios strain to PEG-induced drought stress

A new bacterial strain highly tolerant to desiccation and to UV radiation has been isolated from the microbiome of solar panels. This strain showed a high xerotolerance in the exponential and the stationary phase of growth and it has been classified as Arthrobacter sp. Helios according to its 16S rDNA, positioning this new strain in the Arthrobacter citreus group. The complete genome of Arthrobacter sp. Helios consists in a single circular chromosome of 3,895,998 bp, with a 66% GC content and no plasmids. A total of 3,586 genes were predicted, of which 2,275 protein-encoding genes were functionally assigned. The genome analysis suggests that it is motile, ecologically versatile, capable of growing in a variety of carbon sources and well poised to respond to environmental stresses. Using PEG6000 to mimic arid stress conditions, we have studied the transcriptional response of this strain to matric stress when cells are cultured on media containing 10% (PEG10) and 35% PEG (PEG35). The transcriptomic analysis revealed that cells can be easily adapted to moderate matric stress (PEG10) by modifying the expression of a small number of genes to maintain a high growth rate, while a higher matric stress (PEG35) altered the expression of many more genes. Remarkably, these metabolic changes do not confer the cells a higher tolerance to desiccation, suggesting that mechanisms to support matric stress and desiccation tolerance are different. The peculiar observation that Arthrobacter sp. Helios seems to be permanently prepared to handle the desiccation stress makes it an exciting chassis for biotechnological applications.

microbiology↗

bioRxiv2021

Stress-dependent inhibition of cell polarity through unbalancing the GEF/GAP regulation of Cdc42

Cdc42 rules cell polarity and growth in fission yeast. It is negatively and positively regulated by GTPase-activating proteins (GAPs) and by Guanine nucleotide Exchange factors (GEFs), respectively. Active Cdc42-GTP localizes to the poles, where it associates with numerous proteins constituting the polarity module. However, little is known about its down-regulation. We describe here that oxidative stress causes Sty1 kinase-dependent Cdc42 inactivation at cell poles. Both the amount of active Cdc42 at poles and cell length inversely correlate with Sty1 activity, explaining the elongated morphology of{Delta} sty1 cells. We have created stress-blinded cell poles by either eliminating two Cdc42 GAPs or through the constitutive tethering of a GEF to the cell tips, and biochemically demonstrate that Rga3 is a direct substrate of Sty1. We propose that stress-activated Sty1 promotes GTP hydrolysis and prevents GEF activity at the cell tips, thus leading to the inhibition of Cdc42 and polarized growth cessation.

cell biology↗

bioRxiv2020

Open Targets Genetics: An open approach to systematically prioritize causal variants and genes at all published GWAS trait-associated loci

Genome-wide association studies (GWAS) have identified many variants robustly associated with complex traits but identifying the gene(s) mediating such associations is a major challenge. Here we present an open resource that provides systematic fine-mapping and protein-coding gene prioritization across 133,441 published human GWAS loci. We integrate diverse data sources, including genetics (from GWAS Catalog and UK Biobank) as well as transcriptomic, proteomic and epigenomic data across many tissues and cell types. We also provide systematic disease-disease and disease-molecular trait colocalization results across 92 cell types and tissues and identify 729 loci fine-mapped to a single coding causal variant and colocalized with a single gene. We trained a machine learning model using the fine mapped genetics and functional genomics data using 445 gold standard curated GWAS loci to distinguish causal genes from background genes at the same loci, outperforming a naive distance based model. Genes prioritized by our model are enriched for known approved drug targets (OR = 8.1, 95% CI: [5.7, 11.5]). These results will be regularly updated and are publicly available through a web portal, Open Targets Genetics (OTG, http://genetics.opentargets.org), enabling users to easily prioritize genes at disease-associated loci and assess their potential as drug targets.

genetics↗