Spatial and phenotypic characterization of pancreatic cancer-associated fibroblasts after neoadjuvant treatment.
Bibliographic record
Abstract
Pancreatic ductal adenocarcinoma (PC) is characterized by a highly fibrotic desmoplastic stroma. Subtypes of cancer-associated fibroblasts (CAFs) have been identified in chemotherapy-naïve PC (CTN-PC), but their precise functions are still unclear. Our knowledge regarding the properties of CAFs in the regressive stroma after neoadjuvant treatment (NAT) of PC (NAT-PC) is particularly limited. We aimed to examine the marker phenotypic properties of CAFs in the regressive stroma of PC. Surgical specimens from patients with CTN-PC (n=10) and NAT-PC (n=10) were included. Juxtatumoural, peripheral, lobular, septal, peripancreatic, and regressive stromal compartments were manually outlined using digital imaging analysis (DIA) for area quantification. The compartment-specific expression of CD271, cytoglobin, DOG-1, miR-21, osteonectin, PDGF-Rβ, and tenascin C was evaluated by immunohistochemistry or in situ hybridization, using manual scoring and automated DIA. The area fraction of the regressive stroma was significantly higher in NAT-PC than in CTN-PC (P=0.0002). CD271 (P<0.01), cytoglobin (P<0.05), DOG1 (P<0.05), miR-21 (P<0.05), and tenascin C (P<0.05) exhibited significant differences in their expression profiles between the juxtatumoural compared to the peripheral and regressive stroma. PDGF-Rβ expression was significantly higher in juxtatumoural than in peripheral CAFs (P<0.05). Our data provide further support of the concept of stromal heterogeneity and phenotypic different CAF subtypes in PC. CAFs in the regressive stroma of NAT-PC show a marker phenotype similar to some (namely, peripheral) and different from other (namely, juxtatumoural) previously defined CAF subtypes. It may be hypothesized that phenotypic CAF subtypes, at least in part, also may share functional properties. Studies examining the precise functional characteristics of CAF subtypes in PC are needed.
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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".