Down-regulation of CXCL 11 inhibits colorectal cancer cell growth and epithelial-mesenchymal transition
Bibliographic record
Abstract
BACKGROUND: The poor prognosis of colorectal cancer (CRC) largely results from local invasion and tumor metastases. Epithelial-mesenchymal transition (EMT) is a key step in the progression of solid tumors and plays a vital role in tumor metastasis. Recent studies demonstrate that C-X-C motif chemokine 11 (CXCL11) is involved in various cancers' progression. However, its biological activity in CRC needs deeper exploration. METHODS: The level of CXCL11 in CRC tissues and cell lines was determined using the quantitative real-time PCR (qRT-PCR) assay. The MTT, colony formation, wound healing and Transwell invasion assays were applied to assess the role of CXCL11 in CRC cell growth, migration and invasion, in vitro, respectively. A xenograft model was constructed to analyze the function of CXCL11 in CRC cell growth in vivo. RESULTS: CXCL11 was over-expressed in CRC tissues and cell lines. Repression of CXCL11 significantly inhibited CRC cell migration, invasion and EMT in vitro. In addition, down-regulation of CXCL11 reduced CRC cell growth and metastasis in vivo. Finally, we revealed that repression of CXCL11 inhibited the metastatic ability of CRC cell in a N-cadherin dependent manner. CONCLUSION: In summary, this study explicates the oncogenic activities of CXCL11 in CRC cell growth and metastasis.
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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 | 0.000 |
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".