KANK1 promotes breast cancer development by compromising Scribble-mediated Hippo activation
Bibliographic record
Abstract
KANK1 is expressed in epithelial cells and connects focal adhesions with the adjacent cortical microtubule stabilizing complex. Although KANK1 was shown to suppress cancer cell growth in vitro, TCGA database points to high KANK1 levels associated with poor prognosis in a wide spectrum of human malignancies. Here, we address this discrepancy and report that KANK1 promotes proliferation and survival of PyMT-transformed mammary tumor cells in vivo. Mechanistically, KANK1 localizes to the basal side of basement membrane (BM)-attached transformed luminal epithelial cells. When these cells lose the contact with the BM and disassemble integrin adhesions, KANK1 is found at cell-cell junctions where it competes with the polarity and tumor suppressor Scribble for NOS1AP binding, which curbs the ability of Scribble to promote Hippo pathway activity. The consequences are stabilization and nuclear accumulation of TAZ, growth and survival of tumor cells and elevated breast cancer development.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".