Neural Cell Adhesion Protein CNTN1 Promotes the Metastatic Progression of Prostate Cancer
Bibliographic record
Abstract
Prostate cancer metastasis is the main cause of disease-related mortality. Elucidating the mechanisms underlying prostate cancer metastasis is critical for effective therapeutic intervention. In this study, we performed gene-expression profiling of prostate cancer stem-like cells (PCSC) derived from DU145 human prostate cancer cells to identify factors involved in metastatic progression. Our studies revealed contactin 1 (CNTN1), a neural cell adhesion protein, to be a prostate cancer-promoting factor. CNTN1 knockdown reduced PCSC-mediated tumor initiation, whereas CNTN1 overexpression enhanced prostate cancer cell invasion in vitro and promoted xenograft tumor formation and lung metastasis in vivo. In addition, CNTN1 overexpression in DU145 cells and corresponding xenograft tumors resulted in elevated AKT activation and reduced E-cadherin (CDH1) expression. CNTN1 expression was not readily detected in normal prostate glands, but was clearly evident on prostate cancer cells in primary tumors and lymph node and bone metastases. Tumors from 637 patients expressing CNTN1 were associated with prostate cancer progression and worse biochemical recurrence-free survival following radical prostatectomy (P < 0.05). Collectively, our findings demonstrate that CNTN1 promotes prostate cancer progression and metastasis, prompting further investigation into the mechanisms that enable neural proteins to become aberrantly expressed in non-neural malignancies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".