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Biology subjects

Egan, J. B.

Publications and source records attributed to Egan, J. B..

2 recordsLinked to original sources

Synergistic Combination of Cytotoxic Chemotherapy and Cyclin Dependent Kinase 4/6 Inhibitors in Biliary Tract Cancers

Biliary tract cancers (BTCs) are uncommon but highly lethal gastrointestinal malignancies. Gemcitabine/cisplatin is a standard-of-care (SOC) systemic therapy, but has a modest impact on survival and harbor toxicities including myelosuppression, nephropathy, neuropathy and ototoxicity. While BTCs are characterized by aberrations activating the cyclinD1-CDK4/6-CDKN2A-RB pathway, clinical use of CDK4/6 inhibitors as monotherapy is limited by lack of validated biomarkers, diffident pre-clinical efficacy and development of acquired drug resistance. Emerging studies have explored therapeutic strategies to enhance the anti-tumor efficacy of CDK4/6 inhibitors by combination with chemotherapy-regimens but their mechanism of action remains elusive. Here, we report in vitro and in vivo synergy in BTC models, showing enhanced efficacy, reduced toxicity and better survival with a combination comprising gemcitabine/cisplatin and CDK4/6 inhibitors. Furthermore, we demonstrated that abemaciclib monotherapy had only modest efficacy due to autophagy induced resistance. Notably, triplettherapy was able to potentiate efficacy through elimination of the autophagic flux. Correspondingly, abemaciclib potentiated RRM1 reduction, resulting in sensitization to gemcitabine. Conclusions: As such, these data provide robust pre-clinical mechanistic evidence of synergy between gemcitabine/cisplatin and CDK4/6 inhibitors, and delineate a path forward for translation of these findings to preliminary clinical studies in advanced BTC patients.

cancer biology↗

Contextual Classifications of Cancer Driver Genes

Functions of cancer driver genes depend on cellular contexts that vary substantially across tissues and organs. Distinguishing oncogenes (OGs) and tumor suppressor genes (TSGs) for each cancer type is critical to identifying clinically actionable targets. However, current resources for context-aware classifications of cancer drivers are limited. In this study, we show that the direction and magnitude of somatic selection of missense and truncating mutations of a gene are suggestive of its contextual activities. By integrating these features with ratiometric and conservation measures, we developed a computational method to categorize OGs and TSGs using exome sequencing data. This new method, named genes under selection in tumors (GUST) shows an overall accuracy of 0.94 when tested on manually curated benchmarks. Application of GUST to 10,172 tumor exomes of 33 cancer types identified 98 OGs and 179 TSGs, >70% of which promote tumorigenesis in only one cancer type. In broad-spectrum drivers shared across multiple cancer types, we found heterogeneous mutational hotspots modifying distinct functional domains, implicating the synchrony of convergent and divergent disease mechanisms. We further discovered two novel OGs and 28 novel TSGs with high confidence. The GUST program is available at https://github.com/liliulab/gust. A database with pre-computed classifications is available at https://liliulab.shinyapps.io/gust

bioinformatics↗