Transcriptional and Epigenetic Regulation of KIF14 Overexpression in Ovarian Cancer
Bibliographic record
Abstract
KIF14 (kinesin family member 14) is a mitotic kinesin and an important oncogene in several cancers. Tumor KIF14 expression levels are independently predictive of poor outcome, and in cancer cells KIF14 can modulate metastatic behavior by maintaining appropriate levels of cell adhesion and migration proteins at the cell membrane. Thus KIF14 is an exciting potential therapeutic target. Understanding KIF14's regulation in cancer cells is crucial to the development of effective and selective therapies to block its tumorigenic function(s). We previously determined that close to 30% of serous ovarian cancers (OvCa tumors) exhibit low-level genomic gain, indicating one mechanism of KIF14 overexpression in tumors. We now report on transcriptional and epigenetic regulation of KIF14. Through promoter deletion analyses, we identified one cis-regulatory region containing binding sites for Sp1, HSF1 and YY1. siRNA-mediated knockdown of these transcription factors demonstrated endogenous regulation of KIF14 overexpression by Sp1 and YY1, but not HSF1. ChIP experiments confirmed an enrichment of both Sp1 and YY1 binding to the endogenous KIF14 promoter in OvCa cell lines with high KIF14 expression. A strong correlation was seen in primary serous OvCa tumors between Sp1, YY1 and KIF14 expression, further evidence that these transcription factors are important players in KIF14 overexpression. Hypomethylation patterns were observed in primary serous OvCa tumors, suggesting a minor role for promoter methylation in the control of KIF14 gene expression. miRNA expression analysis determined that miR-93, miR-144 and miR-382 had significantly lower levels of expression in primary serous OvCa tumors than normal tissues; treatment of an OvCa cell line with miRNA mimics and inhibitors specifically modulated KIF14 mRNA levels, pointing to potential novel mechanisms of KIF14 overexpression in primary tumors. Our findings reveal multiple mechanisms of KIF14 upregulation in cancer cells, offering new targets for therapeutic interventions to reduce KIF14 in tumors, aiming at improved prognosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".