Type I gamma phosphatidylinositol phosphate kinase modulates invasion and proliferation and its expression correlates with poor prognosis in breast cancer
Bibliographic record
Abstract
INTRODUCTION: The loss of E-cadherin based cell-cell contacts and tumor cell migration to the vasculature and lymphatic system are hallmarks of metastasis of epithelial cancers. Type I gamma phosphatidylinositol phosphate kinase (PIPKIgamma), an enzyme that generates phosphatidylinositol 4,5-bisphosphate (PI4,5P2) a lipid messenger and precursor to many additional second messengers, was found to regulate E-cadherin cell-cell contacts and growth factor-stimulated directional cell migration, indicating that PIPKIgamma regulates key steps in metastasis. Here, we assess the expression of PIPKIgamma in breast cancers and have shown that expression correlated with disease progression and outcome. METHODS: Using a tissue microarray, we analyzed 438 breast carcinomas for the levels of PIPKIgamma and investigated the correlation of PIPKIgamma expression with patient survival via Kaplan-Meier survival analysis. Moreover, via knockdown of the expression of PIPKIgamma in cultured breast cancer cells with siRNA, the roles of PIPKIgamma in breast cancer migration, invasion, and proliferation were examined. RESULTS: Tissue microarray data shows that approximately 18% of the cohort immunostained showed high expression of PIPKIgamma. The Kaplan-Meier survival analysis revealed a significant inverse correlation between strong PIPKIgamma expression and overall patient survival. Expression of PIPKIgamma correlated positively with epidermal growth factor receptor (EGFR) expression, which regulates breast cancer progression and metastasis. In cultured breast cancer cells, PIPKIgamma is required for growth factor stimulated migration, invasion, and proliferation of cells. CONCLUSIONS: The results reveal a significant correlation between PIPKIgamma expression and the progression of breast cancer. This is consistent with PIPKIgamma 's role in breast cancer cell migration, invasion, and proliferation.
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 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".