Fractalkine Elicits Chemotactic, Phenotypic, and Functional Effects on CX3CR1+CD27− NK Cells in Obesity-Associated Cancer
Bibliographic record
Abstract
Abstract Esophagogastric adenocarcinomas (EAC) are obesity-associated malignancies underpinned by severe immune dysregulation and inflammation. Our previous work indicates that NK cells migrate to EAC omentum, where they undergo phenotypic and functional alterations and apoptosis. In this study, we investigate whether such erroneous chemotaxis to omentum is paralleled by compromised NK cell infiltration of EAC patient tumor and examine the role of the inflammatory chemokine fractalkine in shaping the NK cell–mediated response. Our data show diminished NK cell frequencies in EAC tumor compared with those in the circulation and reveal that intratumoral NK cell frequencies decline as visceral obesity increases in EAC patients. Our in vitro findings demonstrate that antagonism of fractalkine receptor CX3CR1 significantly reduces NK cell migration to EAC patient–derived, omental adipose tissue–conditioned media, but not toward tumor-conditioned media. These data suggest fractalkine is a key driver of NK cell chemotaxis to omentum but has a lesser role in NK cell homing to tumor in EAC. We propose that this may offer a novel therapeutic strategy to limit NK cell depletion in the omentum of obese EAC patients, and our data suggest the optimal timing for CX3CR1 antagonism is after neoadjuvant chemoradiotherapy. Our functional studies demonstrate that fractalkine induces the conversion from CX3CR1+CD27− to CX3CR1−CD27+ NK cells and increases their IFN-γ and TNF-α production, indicative of its role in shaping the dominant NK cell phenotype in EAC omentum. This study uncovers crucial and potentially druggable pathways underpinning NK cell dysfunction in obesity-associated cancer and provides compelling insights into fractalkine’s diverse biological functions.
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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".