Inactivation of the Kinase Domain of CDK10 Prevents Tumor Growth in a Preclinical Model of Colorectal Cancer, and Is Accompanied by Downregulation of Bcl-2
Bibliographic record
Abstract
Abstract Cyclin-dependent kinase 10 (CDK10), a CDC2-related kinase, is highly expressed in colorectal cancer. Its role in the pathogenesis of colorectal cancer is unknown. This study examines the function of CDK10 in colorectal cancer, and demonstrates its role in suppressing apoptosis and in promoting tumor growth in vitro and in vivo. Modulation of CDK10 expression in colorectal cancer cell lines demonstrates that CDK10 promotes cell growth, reduces chemosensitivity and inhibits apoptosis by upregulating the expression of Bcl-2. This effect appears to depend on its kinase activity, as kinase-defective mutant colorectal cancer cell lines have an exaggerated apoptotic response and reduced proliferative capacity. In vivo, inhibiting CDK10 in colorectal cancer following intratumoral injections of lentivirus-mediated CDK10 siRNA in a patient-derived xenograft mouse model demonstrated its efficacy in suppressing tumor growth. Furthermore, using a tissue microarray of human colorectal cancer tissues, the potential for CDK10 to be a prognostic biomarker in colorectal cancer was explored. In tumors of individuals with colorectal cancer, high expression of CDK10 correlates with earlier relapse and shorter overall survival. The findings of this study indicate that CDK10 plays a role in the pathogenesis in colorectal cancer and may be a potential therapeutic target for treatment. Mol Cancer Ther; 16(10); 2292–303. ©2017 AACR.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".