OncoGEMINI: Software for Investigating Tumor Variants From Multiple Biopsies With Integrated Cancer Annotations

Nicholas, Thomas J.; Cormier, Michael; Huang, Xiaomeng; Qiao, Yi; Marth, Gábor; Quinlan, Aaron R.

doi:10.1101/2020.03.10.979591

Cited by 3 publications

(2 citation statements)

References 26 publications

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“…NDex is the latest in a number of community resources that have integrated DGIdb. Existing data clients include GeneCards ( 8 ), BioGPS ( 9 ), CancerTracer ( 10 ), Gene4Denovo ( 11 ), SL-BioDP ( 12 ), TargetDB ( 13 ) and OncoGemini ( 14 ), among others.…”

Section: Introductionmentioning

confidence: 99%

Integration of the Drug–Gene Interaction Database (DGIdb 4.0) with open crowdsource efforts

Freshour

Kiwala

Cotto

et al. 2020

Nucleic Acids Research

659

435

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The Drug-Gene Interaction Database (DGIdb, www.dgidb.org) is a web resource that provides information on drug-gene interactions and druggable genes from publications, databases, and other web-based sources. Drug, gene, and interaction data are normalized and merged into conceptual groups. The information contained in this resource is available to users through a straightforward search interface, an application programming interface (API), and TSV data downloads. DGIdb 4.0 is the latest major version release of this database. A primary focus of this update was integration with crowdsourced efforts, leveraging the Drug Target Commons for community-contributed interaction data, Wikidata to facilitate term normalization, and export to NDEx for drug-gene interaction network representations. Seven new sources have been added since the last major version release, bringing the total number of sources included to 41. Of the previously aggregated sources, 15 have been updated. DGIdb 4.0 also includes improvements to the process of drug normalization and grouping of imported sources. Other notable updates include the introduction of a more sophisticated Query Score for interaction search results, an updated Interaction Score, the inclusion of interaction directionality, and several additional improvements to search features, data releases, licensing documentation and the application framework.

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Section: Introductionmentioning

confidence: 99%

Integration of the Drug–Gene Interaction Database (DGIdb 4.0) with open crowdsource efforts

Freshour

Kiwala

Cotto

et al. 2020

Nucleic Acids Research

659

435

View full text Add to dashboard Cite

show abstract

“…Previously, DGIdb has been integrated with other community resources such as GeneCards (24), which uses DGIdb as a source for interactions between GeneCards gene entries and drugs, and BioGPS (25), which offers a DGIdb plug-in for searching drug-gene interactions. Since the publication of DGIdb 3.0, DGIdb has been regularly integrated with additional resources such as CancerTracer (26), Gene4Denovo (27), SL-BioDP(28), TargetDB (29), and OncoGemini (30).…”

Section: Integration With Ndex and Other External Resourcesmentioning

confidence: 99%

Integration of the Drug-Gene Interaction Database (DGIdb) with open crowdsource efforts

Freshour

Kiwala

Cotto

et al. 2020

Preprint

View full text Add to dashboard Cite

The Drug-Gene Interaction Database (DGIdb, www.dgidb.org) is a web resource that provides information on drug-gene interactions and druggable genes from various sources including publications, databases, and other web-based sources in one resource. These drug, gene, and interaction claims are normalized and grouped to identify aliases, merge concepts, and reduce redundancy. The information contained in this resource is available to users through a straightforward search interface, an application programming interface (API), and TSV data downloads. DGIdb 4.0 is the latest major update of this database. Seven new sources have been added, bringing the total number of sources included to 41. Of the previously aggregated sources, 15 have been updated. DGIdb 4.0 also includes improvements to the process of drug normalization and grouping of imported sources. Other notable updates include further development of automatic jobs for routine data updates, more sophisticated query scores for interaction search results, extensive manual curation of interaction source link outs, and the inclusion of interaction directionality. A major focus of this update was integration with crowd-sourced efforts, including leveraging the curation activities of Drug Target Commons, using Wikidata to facilitate term normalization, and integrating into NDEx for producing network representations.

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Immune profiling-based targeting of pathogenic T cells with ustekinumab in ANCA-associated glomerulonephritis

Engesser,

Khatri,

Schaub

et al. 2024

Preprint

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Antineutrophil cytoplasmic antibody (ANCA)–associated vasculitis is a life-threatening autoimmune disease that often results in kidney failure caused by crescentic glomerulonephritis (ANCA-GN). To date, treatment of most patients with ANCA-GN relies on unspecific immunosuppressive agents that harbor serious adverse effects and are sometimes only partially effective. By performing spatial and single cell transcriptome analysis, we characterized inflammatory niches in the kidneys of 34 patients with ANCA-GN and identified proinflammatory, cytokine producing CD4+ (Th1 and Th17 subsets) and CD8+ T cells (Tc1 and Tc17-like subsets) as a key pathogenic signature. Digital pharmacology identified ustekinumab, a monoclonal antibody targeting IL-12 and IL-23, as the most promising therapeutic drug to target. Based on these findings, four patients with relapsing ANCA-GN were treated with ustekinumab in combination with low-dose cyclophosphamide and steroids. Ustekinumab was given subcutaneously (90 mg) at weeks 0, 4, 12, and 24. Patients were followed up for 26 weeks. This treatment was well-tolerated and induced clinical response in all ANCA-GN patients, including improved kidney function and Birmingham Vasculitis Activity Score. Our findings suggest that immune-profiling-based targeting of pathogenic T cells in ANCA-GN patients with ustekinumab is a promising approach and warrants further investigation in clinical trials.

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OncoGEMINI: Software for Investigating Tumor Variants From Multiple Biopsies With Integrated Cancer Annotations

Cited by 3 publications

References 26 publications

Integration of the Drug–Gene Interaction Database (DGIdb 4.0) with open crowdsource efforts

Integration of the Drug–Gene Interaction Database (DGIdb 4.0) with open crowdsource efforts

Integration of the Drug-Gene Interaction Database (DGIdb) with open crowdsource efforts

Immune profiling-based targeting of pathogenic T cells with ustekinumab in ANCA-associated glomerulonephritis

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