The nuclear receptor (NR) superfamily is one of the major druggable gene families, representing targets of approximately 13.5% of approved drugs. Certain NRs, such as estrogen receptor and androgen receptor, have been well demonstrated to be functionally involved in cancer and serve as informative biomarkers and therapeutic targets in oncology. However, the spectrum of NR dysregulation across cancers remains to be comprehensively characterized. Through computational integration of genetic, genomic, and pharmacologic profiles, we characterized the expression, recurrent genomic alterations, and cancer dependency of NRs at a large scale across primary tumor specimens and cancer cell lines. Expression levels of NRs were highly cancer-type specific and globally downregulated in tumors compared with corresponding normal tissue. Although the majority of NRs showed copy-number losses in cancer, both recurrent focal gains and losses were identified in select NRs. Recurrent mutations and transcript fusions of NRs were observed in a small portion of cancers, serving as actionable genomic alterations. Analysis of large-scale CRISPR and RNAi screening datasets identified 10 NRs as strongly selective essential genes for cancer cell growth. In a subpopulation of tumor cells, growth dependencies correlated significantly with expression or genomic alterations. Overall, our comprehensive characterization of NRs across cancers may facilitate the identification and prioritization of potential biomarkers and therapeutic targets, as well as the selection of patients for precision cancer treatment.

Significance:

Computational analysis of nuclear receptors across multiple cancer types provides a series of biomarkers and therapeutic targets within this protein family.

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