Tissue Microenvironment Modulates CXCR4 Expression and Tumor Metastasis in Neuroblastoma
Bibliographic record
Abstract
Neuroblastoma (NB) is derived from intrinsic migratory neural crest cells and has a high potential for distant metastasis. Growing evidence has implicated chemokine receptors, especially CXCR4, which normally control immune and inflammatory cell migration, as having important roles in tumor progression. In this study, we investigated the expression of CXCR4 in eight different NB cell lines and found that CXCR4 expression is dynamically regulated in NB and can be modulated by different tissue stromata. In addition, we demonstrate that IL-5 and IFN-gamma are released from stromal cells and act as differential mediators for CXCR4 expression. We also overexpressed CXCR4 in two NB cell lines, NUB-7 and SK-N-BE(2), and studied the role of CXCR4 in NB metastasis both in vitro and in vivo. In vitro transwell invasion assay showed that CXCR4 overexpression promoted NB cell migration preferentially toward a bone marrow stromal cell-conditioned medium. Using an in vivo xenograft model, CXCR4-overexpressing cells showed an increased incidence of metastasis, most notably bone marrow metastasis. Our studies reveal critical roles for CXCR4 in NB metastasis and provide insights into the regulatory mechanism of chemokine receptors in NB and the importance of the tissue microenvironment in modulating tumor cell behavior.
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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".