Coexisting morpho-biotypes unveil the regulatory bases of phenotypic plasticity in pancreatic ductal adenocarcinoma
Bibliographic record
Abstract
Abstract Intratumor morphological heterogeneity predicts clinical outcomes of pancreatic ductal adenocarcinoma (PDAC). However, it is only partially understood at the molecular level and devoid of clinical actionability. In this study we set out to determine the gene regulatory networks and expression programs underpinning intra-tumor morphological variation in PDAC. To this aim, we identified and deconvoluted at single cell level the molecular profiles characteristic of morphologically distinguishable clusters of PDAC cells that coexisted in individual tumors. We identified three major morpho-biotypes that co-occurred in various proportions in most PDACs: a glandular biotype with classical epithelial ductal features; a biotype with abortive ductal structures and expressing a partial epithelial-to-mesenchymal transition program; and a poorly differentiated biotype showing partial neuronal lineage priming and absence of both ductal features and basement membrane. The identification of PDAC morpho-biotypes may help improve patient stratification and therapeutic schemes taking into account the spectrum of actionable targets expressed by coexisting tumor components.
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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".