RadiationGeneSigDB: a database of oxic and hypoxic radiation response gene signatures and their utility in pre-clinical research.

Abstract

Radiation therapy is among the most effective and widely used modalities of cancer therapy in current clinical practice. In this era of personalized radiation medicine, high-throughput data now provide the means to investigate novel biomarkers of radiation response. Large-scale efforts have identified several radiation response signatures, which poses two challenges, namely, their analytical validity and redundancy of gene signatures. To address these fundamental radiogenomics 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, and its function. We present the utility of this database by gaining an understanding of hypoxia-associated miRNA by applying a penalized multivariate model; by comparing breast cancer oxic signatures in cell line data vs patient data; and by comparing the similarity of head and neck cancer hypoxia signatures at the pathway level in clinical tumour data. We obtained a set of miRNA highly associated both positively and negatively to the hypoxia gene signatures, across pan-cancer. In addition, we identified moderate correlations between breast cancer oxic signatures in patient data, and significant differences across molecular subtypes. Moreover, we also found that different set of pathways to be enriched using the head and neck hypoxia signatures, although, they are found to be concordant when applied on the patient data. This valuable, curated repertoire of published gene expression signatures provides motivating case studies for how to search for similarities in radiation response for tumours arising from different tissues across model systems under oxic and hypoxic conditions, and how a well-curated set of gene signatures can be used to generate novel biological hypotheses about the functions of non-coding RNA. We envision that RadiationSigDB database will help accelerate preclinical radiotherapeutic discovery pipelines in terms of analytical validity of novel biomarkers of radiation response and the need for ensemble approaches to clinical genomic biomarkers.