Tumor-associated macrophages induce the expression of FOXQ1 to promote epithelial-mesenchymal transition and metastasis in gastric cancer cells
Bibliographic record
Abstract
Gastric cancer (GC) is one of the most common malignancies, and is the second leading cause of cancer-related deaths worldwide. Macrophages infiltrated in the tumor microenvironment (TME) called tumor-associated macrophages (TAMs) are key orchestrators in TME. In GC, it has been reported that infiltration of TAMs is associated with epithelial-mesenchymal transition (EMT)-related proteins in human GC tissues, but the exactly mechanism has not been clarified. In the present study, we aimed to elucidate the underlying mechanism of TAMs on GC cells. THP-1 cells were used to investigate the effects of TAMs on GC cells. The effects of invasion and migration induced by coculture with TAMs were investigated by Transwell invasion and wound healing assays. The expression of EMT-related genes and forkhead box Q1 (FOXQ1) were examined in MKN45 and MKN74 cells after being co-cultured with TAMs. The density of TAMs and the expression of FOXQ1 were analyzed by immunohistochemistry in GC tissues. Our results revealed that, co-culture with TAMs promoted the invasion and migration of GC cells. Co-culture with TAMs induced EMT in GC cells. FOXQ1 is essential for TAM-induced EMT and metastasis in GC cells. Furthermore, silencing of FOXQ1 blocked the effect of TAM-enhanced EMT and metastasis of GC cells. High expression of CD68 was correlated with positive FOXQ1 expression (r=0.613; P<0.001) in clinical GC samples. Our data provided evidence that TAMs promote EMT, invasion and migration of GC cells via FOXQ1. Therefore, the TAM/FOXQ1 axis may represent a novel target for GC cells.
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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".