Interleukin-1β-induced pancreatitis promotes pancreatic ductal adenocarcinoma via B lymphocyte–mediated immune suppression
Bibliographic record
Abstract
Objective Long-standing chronic pancreatitis is an established risk factor for pancreatic ductal adenocarcinoma (PDAC). Interleukin-1β (IL-1β) has been associated in PDAC with shorter survival. We employed murine models to investigate the mechanisms by which IL-1β and chronic pancreatitis might contribute to PDAC progression. Design We crossed LSL- Kras +/G12D ; Pdx1 -Cre (KC) mice with transgenic mice overexpressing IL-1β to generate KC-IL1β mice, and followed them longitudinally. We used pancreatic 3D in vitro culture to assess acinar-to-ductal metaplasia formation. Immune cells were analysed by flow cytometry and immunohistochemical staining. B lymphocytes were adoptively transferred or depleted in Kras-mutant mice. B-cell infiltration was analysed in human PDAC samples. Results KC-IL1β mice developed PDAC with liver metastases. IL-1β treatment increased Kras +/G12D pancreatic spheroid formation. CXCL13 expression and B lymphocyte infiltration were increased in KC-IL1β pancreata. Adoptive transfer of B lymphocytes from KC-IL1β mice promoted tumour formation, while depletion of B cells prevented tumour progression in KC-IL1β mice. B cells isolated from KC-IL1β mice had much higher expression of PD-L1, more regulatory B cells, impaired CD8 + T cell activity and promoted tumorigenesis. IL-35 was increased in the KC-IL1β pancreata, and depletion of IL-35 decreased the number of PD-L1 + B cells. Finally, in human PDAC samples, patients with PDAC with higher B-cell infiltration within tumours showed significantly shorter survival. Conclusion We show here that IL-1β promotes tumorigenesis in part by inducing an expansion of immune-suppressive B cells. These findings point to the growing significance of B suppressor cells in pancreatic tumorigenesis.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
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".