ATIP3, a Novel Prognostic Marker of Breast Cancer Patient Survival, Limits Cancer Cell Migration and Slows Metastatic Progression by Regulating Microtubule Dynamics
Bibliographic record
Abstract
Metastasis, a fatal complication of breast cancer, does not fully benefit from available therapies. In this study, we investigated whether ATIP3, the major product of 8p22 MTUS1 gene, may be a novel biomarker and therapeutic target for metastatic breast tumors. We show that ATIP3 is a prognostic marker for overall survival among patients with breast cancer. Notably, among metastatic tumors, low ATIP3 levels associate with decreased survival of the patients. By using a well-defined experimental mouse model of cancer metastasis, we show that ATIP3 expression delays the time-course of metastatic progression and limits the number and size of metastases in vivo. In functional studies, ATIP3 silencing increases breast cancer cell migration, whereas ATIP3 expression significantly reduces cell motility and directionality. We report here that ATIP3 is a potent microtubule-stabilizing protein whose depletion increases microtubule dynamics. Our data support the notion that by decreasing microtubule dynamics, ATIP3 controls the ability of microtubule tips to reach the cell cortex during migration, a mechanism that may account for reduced cancer cell motility and metastasis. Of interest, we identify a functional ATIP3 domain that associates with microtubules and recapitulates the effects of ATIP3 on microtubule dynamics, cell proliferation, and migration. Our study is a major step toward the development of new personalized treatments against metastatic breast tumors that have lost ATIP3 expression.
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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".