Benchmarking to the Gold Standard: Hyaluronan‐Oxime Hydrogels Recapitulate Xenograft Models with In Vitro Breast Cancer Spheroid Culture
Bibliographic record
Abstract
Many 3D in vitro models induce breast cancer spheroid formation; however, this alone does not recapitulate the complex in vivo phenotype. To effectively screen therapeutics, it is urgently needed to validate in vitro cancer spheroid models against the gold standard of xenografts. A new oxime-crosslinked hyaluronan (HA) hydrogel is designed, manipulating gelation rate and mechanical properties to grow breast cancer spheroids in 3D. This HA-oxime breast cancer model maintains the gene expression profile most similar to that of tumor xenografts based on a pan-cancer gene expression profile (comprising 730 genes) of three different human breast cancer subtypes compared to Matrigel or conventional 2D culture. Differences in gene expression between breast cancer cultures in HA-oxime versus Matrigel or 2D are confirmed for 12 canonical pathways by gene set variation analysis. Importantly, drug response is dependent on the culture method. Breast cancer cells respond better to the Rac inhibitor (EHT-1864) and the PI3K inhibitor (AZD6482) when cultured in HA-oxime versus Matrigel. This study demonstrates the superiority of an HA-based hydrogel as a platform for in vitro breast cancer culture of both primary, patient-derived cells and cell lines, and provides a hydrogel culture model that closely matches that in vivo.
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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 | 0.001 | 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 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".