Knockdown of CEMIP suppresses proliferation and induces apoptosis in colorectal cancer cells: downregulation of GRP78 and attenuation of unfolded protein response
Bibliographic record
Abstract
It has been suggested that cell migration inducing hyaluronan binding protein (CEMIP) contributes to the carcinogenesis of colorectal cancer (CRC). Cancer cells can adapt to endoplasmic reticulum (ER) stress by initiating an unfolded protein response (UPR). This study aimed to investigate whether CEMIP affects the UPR of CRC cells, with a focus on 78 kDa glucose-regulated protein (GRP78, a major ER chaperone). We found that knockdown of CEMIP inhibited cell proliferation and induced a G1 arrest in SW480 CRC cells. The levels of cyclin D1 and cyclin E1 and phospho-retinoblastoma, which are known to promote the cell cycle progression from G0 or G1 into S phase, were decreased in CEMIP-silenced cells. CEMIP shRNA induced apoptosis and inhibited GRP78 expression in SW480 and Colo205 cells. The basal UPR of cancer cells was attenuated by CEMIP shRNA, as evidenced by the decreased expression of UPR sensors, protein kinase R-like endoplasmic reticulum kinase (PERK), inositol requiring enzyme 1 (IRE1), and activating transcription factor 6 (ATF6). Furthermore, CEMIP silencing sensitized CRC cells to thapsigargin-induced apoptosis. Our study demonstrates that the in-vitro anti-proliferative and pro-apoptotic effects in CRC cells that were induced by silencing CEMIP may be associated with GRP78 repression and UPR attenuation.
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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 | 0.000 |
| 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 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".