CCDC106 promotes the proliferation and invasion of ovarian cancer cells by suppressing p21 transcription through a p53-independent pathway
Bibliographic record
Abstract
Ovarian cancers are the major cause of mortality for women worldwide. This study was aimed to elucidate the biological activities of CCDC106 in the proliferation and invasion of mutant p53 and of wild-type p53 ovarian cancer cells. CAOV3 (mutant p53) cells showed high expression levels of CCDC106, but it was expressed at low levels in SKOV3 (mutant p53) and in A2780 (wild-type p53) cells. The overexpression of CCDC106 promoted the expression of proliferation markers (cyclin family members), invasion and Epithelial-to-mesenchymal transition (EMT) markers (claudin-1, claudin-4, N-cadherin, snail, slug) while the knockdown of CCDC106 inhibited their expression in mutant p53 cells but not in wild-type p53 cells. Treatment with a CK2 inhibitor blocked the translocation of CCDC106 into the nuclei of mutant p53 cells. Immunoprecipitation assays confirmed that ATF4 is a potential binding partner of CCDC106. The overexpression of CCDC106 reduced p21 and p27 protein expression levels while treatment with an ATF4 siRNA rescued their expression. The overexpression of CCDC106 promoted colony formation and invasion of mutant p53 cells, which was suppressed by treatment with an ATF4 siRNA. Immunohistochemistry results showed that CCDC106 and ATF4 are expressed at high levels but p21 is expressed at low levels in FIGO III–IV stage and in mutant p53 ovarian cancer samples. A significant association between poor overall survival and high CCDC106 and ATF4 expression levels was observed in human ovarian cancer samples. In conclusion, CCDC106 promotes proliferation, invasion and EMT of mutant p53 ovarian cancer cells via the ATF4 mediated inhibition of p21.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".