Culture Shock! Investigating the Importance of Physiological Tumour-Like Conditions on Cultured Cancer Cells
Bibliographic record
Abstract
The tumour microenvironment (TME) is complex and dynamic, characterized by poor vascularization, limited nutrient availability, hypoxia, and an acidic pH. This environment plays a critical role in cancer progression, driving hallmark changes in cancer cell metabolism, morphology, proliferation, and motility. Although mammalian cell culture is a foundational tool for investigating cancer cell biology in vitro, standard cell culture practices fall short of replicating the in vivo conditions of tumours. Recently, ‘physiologic’ cell culture media that closely resemble human plasma (e.g., Plasmax, HPLM) have been developed, along with more frequent adoption of physiological oxygen conditions (2-8% O 2 ) rather than standard atmosphere (~18% O 2 ). Although an improvement, these conditions are not representative of all in vivo cellular environments, particularly that of the TME. Considering the tight regulatory capacity of cancer cells to sense and respond to changes in metabolic availability, we hypothesized that alterations in nutrient and oxygen availability, even if within the physiological range, may subtly rewire the metabolism in cultured cancer cells. This may necessitate further refinement of cell-specific physiologic culture conditions to better maintain the in vivo biology of cells. In this study, we directly address this hypothesis by describing the development of a tumour microenvironment-like medium (TMEM) based on metabolomic profiling of murine pancreatic ductal adenocarcinoma tumour interstitial fluid from relevant literature. We found that murine pancreatic ductal adenocarcinoma (KPCY) cells cultured under TME-like conditions (TMEM, pH 7.0, 1.5% O 2 ) exhibited increased glucose uptake and lactate production rates compared to those cultured under healthy plasma-like conditions (Mouse Plasma-like Medium, pH 7.4, 5% O 2 ), despite lower initial glucose concentrations in TMEM (2.3 mM vs. 4.4 mM in Mouse Plasma-like Medium). Moreover, cell proliferation rates were lower in TMEM, suggesting an overall reduction in ATP consumption fueling cell division. Seahorse Extracellular Flux Analysis is being performed to determine effects on cellular bioenergetics. Metabolomic amino acid uptake using LCMS is also being performed to further assess the effect of TMEM on nutrient utilization. Using RNA-sequencing, we showed that culture in TMEM increased expression of genes associated with angiogenesis, amino acids biosynthesis, cell migration, and endothelial-to-mesenchymal transition. Migration assays confirmed increased motility in KPCY cells cultured in TMEM. Taken together, these results demonstrate that growth in a medium designed to simulate the TME alters KPCY cell biology in ways that are relevant to their pathology, which highlights the significance of maintaining TME-like conditions in culture. This research was funded by a Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant from JAS and a NSERC Canadian Graduate Student (Masters) Grant awarded to GLG. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".