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• W2898454920 abstract "Radiation therapy is among the most effective and widely used modalities of cancer therapy in current clinical practice. With the advent of new high throughput genomic technologies and the continuous inflow of transcriptomic data, there has been a paradigm shift in the landscape of radiation oncology. In this era of personalized radiation medicine, genomic datasets hold great promise to investigate novel biomarkers predictive of radiation response. These biomarkers may be used to investigate radiation-induced biological events, and to predict clinical outcomes. In this regard, the number of available gene expression based signatures built under oxic and hypoxic conditions is getting larger. This poses two main questions in the field, namely, i) how reliable are these signatures when applied across a compendium of datasets in different model systems; and ii) is there redundancy of gene signatures. To address these fundamental radiobiologic questions, we curated a database of gene expression signatures predictive of radiation response under oxic and hypoxic conditions. RadiationGeneSigDB has a collection of 11 oxic and 24 hypoxic signatures with the standardized gene list as a gene symbol, Entrez gene id along with its function. We present the utility of this database through two case studies: i) comparing breast cancer oxic signatures in cell line data vs. patient data; and ii) comparing the similarity of head and neck cancer hypoxia signatures in clinical tumor data. This valuable, curated repertoire of published gene expression signatures provides a motivating example for how to search for similarities in radiation response for tumors arising from different tissues across model systems under oxic and hypoxic conditions." @default.
• W2898454920 created "2018-11-02" @default.
• W2898454920 creator A5031495936 @default.
• W2898454920 creator A5044648533 @default.
• W2898454920 date "2018-10-29" @default.
• W2898454920 modified "2023-09-23" @default.
• W2898454920 title "RadiationGeneSigDB: A comprehensive database of oxic and hypoxic radiation response gene expression signatures" @default.
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