Abstract A203: An in vitro tumor model to characterize tumor cell metabolism in heterogeneous complex microenvironments.
Bibliographic record
Abstract
Abstract Tumor cells often exhibit altered metabolic behaviors that are influenced by the heterogeneity of the tumor microenvironment. This heterogeneity arises from the presence of multiple cell types, variable ECM compositions, and variable protein expression due to the presence of oxygen and nutrient gradients. Conventional methods of identifying tumor therapies fail to account for these metabolic variations in the context of a heterogeneous microenvironment. To address this shortfall, we have developed a layered, three-dimensional, heterogeneous tumor model that allows spatiotemporal metabolite collection on a timescale relevant for metabolomics profiling. SKOV-3 ovarian cancer cells were mixed with collagen and infiltrated into a scaffolding material to create a thin layer. Multiple layers were then stacked to make a thick section of tumor tissue which is then combined with a customized oxygen impermeable bioreactor. EF5 immunofluorescence was used to confirm the presence of an oxygen gradient and to quantify the spatial PO2 values, which mimic those found in solid tumors. Cell viability and nutrient, and drug distribution profiles were also characterized and profiles were found to resemble those found in spheroid culture and in vivo. Cellular response to hypoxia was confirmed through qPCR analysis of mRNA of hypoxia-inducible genes such as CA9 and CHOP, and with HIF1α staining. Our technology allows for the creation of complex, yet controlled tumor microenvironments while facilitating “snap shot” data acquisition, and will allow researchers to decouple the influence of heterogeneity on metabolic response in cancerous solid tumors. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):A203. Citation Format: Darren Rodenhizer, Dan Cojocari, Bradley G. Wouters, Alison P. McGuigan. An in vitro tumor model to characterize tumor cell metabolism in heterogeneous complex microenvironments. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr A203.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".