Investigating the Effect of Microenvironmental Gradients on Tumour Cell Heterogeneity Using a 3D In Vitro Model of Pancreatic Cancer
Bibliographic record
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is a high-mortality cancer with no effective treatment options for the majority of patients. Notably, tumour cell behaviour and response to therapy in PDAC is heavily influenced by the characteristic hypoxic and immunosuppressive tumour microenvironment (TME). The emergence of 3D in vitro models that capture a variety of TME features offers a new opportunity for exploring the complexity of tumour-TME interactions in PDAC. Patient-derived organoids (PDOs) have advanced our capacity to model tumour heterogeneity in vitro but lack important microenvironmental components. Conversely, complex 3D in vitro models, such as the Tissue Roll for Analysis of Cellular Environment and Response (TRACER), recapitulate key TME features but have largely been restricted to use with cell lines with limited disease relevance. In this work, we adapted the TRACER platform to facilitate the incorporation of PDOs and create an engineered tissue model that leverages the advantages of both platforms for investigations of tumour biology (TRACER2). We demonstrated that PDOs cultured in TRACER2 establish microenvironmental oxygen gradients and show phenotypic changes in response to this gradient, including changes in cell proliferation, immunosuppressive capacity, and response to gemcitabine treatment. Subsequently, we performed single cell RNA-sequencing (scRNA-seq) of TRACER2, revealing location-dependent changes in the transcriptional patterns of PDOs. Significantly, we demonstrated that microenvironmental gradients, and hypoxia in particular, likely promote a more basal-like transcriptional phenotype in PDAC tumour cells, which has been linked to poor disease prognosis. Taken together, this work demonstrates the value of applying high-dimensional single cell analysis to a complex PDO-based 3D in vitro model of the TME to gain novel insight into tumour-microenvironment interactions. Looking to the future, we believe that this approach will pave the way to identifying novel therapeutic strategies that can meaningfully improve patient outcomes in PDAC.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".