PRP4K is a HER2-regulated modifier of taxane sensitivity
Bibliographic record
Abstract
The taxanes are used alone or in combination with anthracyclines or platinum drugs to treat breast and ovarian cancer, respectively. Taxanes target microtubules in cancer cells and modifiers of taxane sensitivity have been identified in vitro, including drug efflux and mitotic checkpoint proteins. Human epidermal growth factor receptor 2 (HER2/ERBB2) gene amplification is associated with benefit from taxane therapy in breast cancer yet high HER2 expression also correlates with poor survival in both breast and ovarian cancer. The pre-mRNA splicing factor 4 kinase PRP4K (PRPF4B), which we identified as a component of the U5 snRNP also plays a role in regulating the spindle assembly checkpoint (SAC) in response to microtubule-targeting drugs. In this study, we found a positive correlation between PRP4K expression and HER2 status in breast and ovarian cancer patient tumors, which we determined was a direct result of PRP4K regulation by HER2 signaling. Knock-down of PRP4K expression reduced the sensitivity of breast and ovarian cancer cell lines to taxanes, and low PRP4K levels correlated with in vitro-derived and patient acquired taxane resistance in breast and ovarian cancer. Patients with high-grade serous ovarian cancer and high HER2 levels had poor overall survival; however, better survival in the low HER2 patient subgroup treated with platinum/taxane-based therapy correlated positively with PRP4K expression (HR = 0.37 [95% CI 0.15-0.88]; p = 0.03). Thus, PRP4K functions as a HER2-regulated modifier of taxane sensitivity that may have prognostic value as a marker of better overall survival in taxane-treated ovarian cancer patients.
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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".