Role of Immune Microenvironment in Pancreatic Ductal Adenocarcinoma: Could It Be Considered a Predictor of Prognosis?
Bibliographic record
Abstract
Background: Pancreatic ductal adenocarcinoma (PDAC) is characterized by a highly immunosuppressive tumor microenvironment (TME). The aim of this study is to determine the potential significant TME immune markers of long-term survival. Methods: We retrospectively included patients with a diagnosis of resectable PDAC having undergone upfront surgery. Immunohistochemical (IHC) staining using tissue microarray for PD-L1, CD3, CD4, CD8, FOXP3, CD20, iNOS and CD163 was performed in order to characterize the TME. The primary endpoint was long-term survival, defined as the Overall Survival > 24 months from surgery. Results: A total of 38 consecutive patients were included, and 14 (36%) of them were long-term survivors. Long-term survivors showed a higher density of CD8+ lymphocytes intra- and peri-acinar (p = 0.08), and a higher CD8/FOXP3 intra- and peri-tumoral ratio (p = 0.05). A low density of intra- and peri-tumoral FOXP3 infiltration is a good predictor of long-term survival (p = 0.04). A significant association of the low density of intra- and peri-tumoral tumor-associated macrophages (TAMs) iNOS+ with long-term survival was detected (p = 0.04). Conclusions: Despite the retrospective nature and small sample size, our study showed that the high infiltration of CD8+ lymphocytes and low infiltration of FOXP3+ and TAMs iNOS+ are predictors of good prognosis. A preoperative assessment of these potential immune markers could be useful and determinant in the staging process and in PDAC management.
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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 | 0.001 | 0.002 |
| 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".