IL-17 Enhances the Net Angiogenic Activity and In Vivo Growth of Human Non-Small Cell Lung Cancer in SCID Mice through Promoting CXCR-2-Dependent Angiogenesis
Why this work is in the frame
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Bibliographic record
Abstract
In this study, we examined the biological action of IL-17 on human non-small cell lung cancer (NSCLC). Although IL-17 had no direct effect on the in vitro growth rate of NSCLC, IL-17 selectively augmented the secretion of an array of angiogenic CXC chemokines, including CXCL1, CXCL5, CXCL6, and CXCL8 but not angiostatic chemokines, by three different NSCLC lines. Endothelial cell chemotactic activity (as a measure of net angiogenic potential) was increased in response to conditioned medium from NSCLC stimulated with IL-17 compared with those from unstimulated NSCLC. Enhanced chemotactic activity was suppressed by neutralizing mAb(s) to CXCL1, CXCL5, and CXCL8 or to CXCR-2 but not to vascular endothelial growth factor-A. Transfection with IL-17 into NSCLC had no effect on the in vitro growth, whereas IL-17 transfectants grew more rapidly compared with controls when transplanted in SCID mice. This IL-17-elicited enhancement of NSCLC growth was associated with increased tumor vascularity. Moreover, treatment with anti-mouse CXCR-2-neutralizing Ab significantly attenuated the growth of both neomycin phosphotransferase gene-transfected and IL-17-transfected NSCLC tumors in SCID mice. A potential role for IL-17 in modulation of the human NSCLC phenotype was supported by the findings that, in primary NSCLC tissues, IL-17 expression was frequently detected in accumulating and infiltrating inflammatory cells and that high levels of IL-17 expression were associated with increased tumor vascularity. These results demonstrate that IL-17 increases the net angiogenic activity and in vivo growth of NSCLC via promoting CXCR-2-dependent angiogenesis and suggest that targeting CXCR-2 signaling may be a novel promising strategy to treat patients with NSCLC.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 it