Faculty Opinions recommendation of Cancer/testis antigen-Plac1 promotes invasion and metastasis of breast cancer through Furin/NICD/PTEN signaling pathway.
Bibliographic record
Abstract
Placenta-specific protein 1 (Plac1) is a cancer/testis antigen that plays a critical role in promoting cancer initiation and progression. However, the clinical significance and mechanism of Plac1 in cancer progression remain elusive. Here, we report that Plac1 is an important oncogenic and prognostic factor, which physically interacts with Furin to drive breast cancer invasion and metastasis. We have shown that Plac1 expression positively correlates with clinical stage, lymph node metastasis, hormone receptor status, and overall patient survival. Overexpression of Plac1 promoted invasion and metastasis of breast cancer cells in vitro and in vivo. Co-immunoprecipitation and immunofluorescence cell staining assays revealed that interaction of Plac1 and Furin degraded Notch1 and generated Notch1 intracellular domain (NICD) that could inhibit PTEN activity. These findings are consistent with the results of microarray study in MDA-MB-231 cells overexpressing Plac1. A rescue study showed that inhibition of Furin and overexpression of PTEN in Plac1 overexpression cells blocked Plac1-induced tumor cell progression. Taken together, our findings suggest that functional interaction between Plac1 and Furin enhances breast cancer invasion and metastasis and the Furin/NICD/PTEN axis may act as an important therapeutic target for breast cancer treatment.© 2018 The Authors. Published by FEBS Press and John Wiley & Sons Ltd. PMID: 29704427
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 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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.289 | 0.155 |
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".