Neutrophils assist the metastasis of circulating tumor cells in pancreatic ductal adenocarcinoma
Bibliographic record
Abstract
During our research on circulating tumor cells (CTCs) derived from tumor-adjacent vessels in pancreatic ductal adenocarcinoma (PDAC), we found that CTCs are sometimes surrounded by white blood cells (WBCs) in blood. We hypothesize that such interaction between WBCs and CTCs in blood is a mechanism by which WBCs assist in the metastasis of CTCs. We present our laboratory finding, with our evaluation of the association between the neutrophil-to-lymphocyte ratio (NLR, the most investigated clinical parameter of WBCs) and distant metastasis after curative surgery in PDAC. The laboratory finding was presented through immunofluorescence. In the clinical segment, we performed a retrospective study on PDAC patients with distant metastasis after curative surgery who were referred to Peking University Third Hospital between 2005 and 2014. The data on the possible clinical factors were collected by a retrospective review of the patients' records. Immunofluorescence results showed that CTCs are surrounded by WBCs in tumor-adjacent vessels of PDAC patients. In the clinical segment, 112 (70%) of a total of 160 PDAC patients were found to have developed distant metastases after surgery; among the 112 patients, only 89 had entire data and were enrolled for further analysis (84.3% patients had liver metastasis). No significant association was found between the NLR and overall survival (hazard ratio [HR] = 1.027, 95% confidence interval [CI] 0.723-1.459, P = 0.88); however, a significant relationship between the NLR and distant metastasis after curative surgery was found on the univariate (HR = 1.641, 95% CI 1.058-2.545, P = 0.027) and multivariate analyses (HR = 2.15, 95% CI 1.279-3.615, P = 0.004). Neutrophils might assist in distant metastasis through interaction with CTCs in blood. Moreover, NLR is an effective predictor for distant metastasis after curative surgery for PDAC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".