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Cholangiocarcinoma (CCA) is a fatal disease without effective targeted therapy. We screened a small-molecule library of 116 inhibitors targeting different targets of the cell cycle and discovered several kinases, including Cyclin-dependent kinase 7 (CDK7) as vulnerabilities in CCA. Analysis of multiple CCA data sets demonstrated that CDK7 was overexpressed in CCA tissues. Further studies demonstrated that CDK7 inhibitor THZ1 inhibited cell viability and induced apoptosis in CCA cells. We also showed that THZ1 inhibited CCA cell growth in a xenograft model. RNA-sequencing followed by Gene ontology analysis showed a striking impact of THZ1 on DNA-templated transcriptional programs. THZ1 downregulated CDK7-mediated phosphorylation of RNA polymerase II, indicative of transcriptional inhibition. A number of oncogenic transcription factors and survival proteins, like MCL1, FOSL1, and RUNX1, were repressed by THZ1. MCL1, one of the antiapoptotic BCL2 family members, was significantly inhibited upon THZ1 treatment. Accordingly, combining THZ1 with a BCL2/BCL-XL inhibitor ABT-263 synergized in impairing cell growth and driving apoptosis. Our results demonstrate CDK7 as a potential target in treating CCA. Combinations of CDK7 inhibition and BCL2/BCL-XL inhibition may offer a novel therapeutic strategy for CCA.
Pubmed ID: 31399555
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Bioinformatics resource system including web server and web service for functional annotation and enrichment analyses of gene lists. Consists of comprehensive knowledgebase and set of functional analysis tools. Includes gene centered database integrating heterogeneous gene annotation resources to facilitate high throughput gene functional analysis.
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View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.
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View all literature mentionsCell line HuCC-T1 is a Cancer cell line with a species of origin Homo sapiens (Human)
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