Abstract P1-05-20: Fluorescent Hyaluronan Probes Distinguish Heterogeneous Breast Cancer Cell Subsets and Predict their Invasive Behavior
Bibliographic record
Abstract
Abstract Background: Tumor heterogeneity is a determining factor in diagnosis and therapy of breast cancer (Bca). We investigated Bca cellular heterogeneity by a functional fluorescent hyaluronan (HA) probe, and monitored its binding characteristics in relation to the degree of Bca aggression. HA is a polysaccharide ligand for CD44 and RHAMM receptors, which are linked to cell plasticity and predict poor clinical outcome in Bca. Methods: Fluorescent HA probes, multiplexed profiling, and cell sorting strategies were developed and used to detect/capture tumor cell subpopulations with differences in HA binding (HA−/low vs. HAhigh) and HA receptors surface display. Whereas we concentrated on the most metastatic cell line, MDA-MB-231, we also monitored the presence of subpopulations in other Bca lines and showed heterogeneity in all. Results: The HA probe binding was highly heterogeneous, and the highest binding level was detected in highly invasive triple-negative basal subtypes such as MDA-MB-231. HA probes bound to the cell surface but also accumulated in cytoplasm and nucleus. Binding levels were dramatically reduced upon ‘reversion’ of highly malignant cells to a non-malignant phenotype in three-dimensional cultures, suggesting that the level of cellular binding to fluorescent HA probe provides a measure of malignant behavior. Comparison between HAhigh and HA−/low subpopulations revealed surprising differences in morphology, proliferation and invasion in culture, which were retained in two in vivo models. HAhigh subpopulations exhibited higher levels of invasion but surprisingly lower levels of proliferation compared to either unsorted parental cells or the HA−/low subpopulation. Conclusions: Querying HA binding in Bca lines reveals an unexpected heterogeneity with respect to tumor phenotype in vivo, morphology in 3D, invasion and proliferation. These results may aid in diagnosis and therapy of invasive Bca subpopulations and early sorting of cancer patients needing intensive chemotherapy. Keywords: Heterogeneity, 3D cultures, Hyaluronan, CD44, RHAMM/HMMR, Tumor phenotype, Breast cancer, Invasion. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P1-05-20.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".