KISS1R Induces Invasiveness of Estrogen Receptor-Negative Human Mammary Epithelial and Breast Cancer Cells
Bibliographic record
Abstract
Kisspeptins (KPs), peptide products of the KISS1 metastasis-suppressor gene, are endogenous ligands for a G protein-coupled receptor (KISS1R). KISS1 acts as a metastasis suppressor in numerous human cancers. However, recent studies have demonstrated that an increase in KISS1 and KISS1R expression in patient breast tumors correlates with higher tumor grade and metastatic potential. We have shown that KP-10 stimulates invasion of estrogen receptor α (ERα)-negative MDA-MB-231 breast cancer cells via transactivation of the epidermal growth factor receptor (EGFR). Here, we report that either KP-10 treatment of ERα-negative nonmalignant mammary epithelial MCF10A cells or expression of KISS1R in MCF10A cells induced a mesenchymal phenotype and stimulated invasiveness. Similarly, exogenous expression of KISS1R in ERα-negative SKBR3 breast cancer cells was sufficient to trigger invasion and induced extravasation in vivo. In contrast, KP-10 failed to transactivate EGFR or stimulate invasiveness in the ERα-positive MCF7 and T47D breast cancer cells. This suggested that ERα negatively regulates KISS1R-dependent breast cancer cell migration, invasion, and EGFR transactivation. In support of this, we found that these KP-10-induced effects were ablated upon exogenous expression of ERα in the MDA-MB-231 cells, by down-regulating KISS1R expression. Lastly, we have identified IQGAP1, an actin cytoskeletal binding protein as a novel binding partner of KISS1R, and have shown that KISS1R regulates EGFR transactivation in breast cancer cells in an IQGAP1-dependent manner. Overall, our data strongly suggest that the ERα status of mammary cells dictates whether KISS1R may be a novel clinical target for treating breast cancer metastasis.
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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".