Computational drug discovery pipelines identify NAMPT as a therapeutic target in neuroendocrine prostate cancer

Abstract

Abstract Neuroendocrine prostate cancer (NEPC) is an aggressive advanced subtype of prostate cancer that exhibits poor prognosis and broad resistance to therapies. Currently, few treatment options are available, highlighting a need for new therapeutics to help curb the high mortality rates of this disease. We designed a comprehensive drug discovery pipeline that quickly generates drug candidates ready to be tested. Our method estimated patient response to various therapeutics in three independent prostate cancer patient cohorts and selected robust candidate drugs showing high predicted potency in NEPC tumors. Using this pipeline, we nominated NAMPT as a molecular target to effectively treat NEPC tumors. Our in vitro experiments validated the efficacy of NAMPT inhibitors in NEPC cells. Compared with adenocarcinoma LNCaP cells, NAMPT inhibitors induced significantly higher growth inhibition in the NEPC cell line model NCI‐H660. Moreover, to further assist clinical development, we implemented a causal feature selection method to detect biomarkers indicative of sensitivity to NAMPT inhibitors. Gene expression modifications of selected biomarkers resulted in changes in sensitivity to NAMPT inhibitors consistent with expectations in NEPC cells. Validation of these markers in an independent prostate cancer patient dataset supported their use to inform clinical efficacy. Our findings pave the way for new treatments to combat pervasive drug resistance and reduce mortality. Furthermore, this research highlights the use of drug sensitivity‐related biomarkers to understand mechanisms and potentially indicate clinical efficacy.