Phenotypic Reversion or Death of Cancer Cells by Altering Signaling Pathways in Three-Dimensional Contexts
Bibliographic record
Abstract
BACKGROUND: We previously used a three-dimensional (3D) reconstituted basement membrane (rBM) assay to demonstrate that tumorigenic HMT-3522 T4-2 human breast cells can be induced to form morphologically normal structures ("reversion") by treatment with inhibitors of beta1 integrin, the epidermal growth factor receptor (EGFR), or mitogen-activated protein kinase (MAPK). We have now used this assay to identify reversion and/or death requirements of several more aggressive human breast cancer cell lines. METHODS: Breast tumor cell lines MCF7, Hs578T, and MDA-MB-231 were cultured in 3D rBM and treated with inhibitors of beta1 integrin, MAPK, or phosphatidylinositol 3-kinase (PI3K). MDA-MB-231 cells, which lack E-cadherin, were transfected with an E-cadherin cDNA. The extent of reversion was assessed by changes in morphology and polarity, growth in 3D rBM or soft agar, level of invasiveness, and tumor formation in nude mice. RESULTS: All three cell lines showed partial reversion (MCF7 the greatest and Hs578T the least) of tumorigenic properties treated with a single beta1 integrin, MAPK, or PI3K inhibitor. Combined inhibition of beta1 integrin and either PI3K or MAPK resulted in nearly complete phenotypic reversion (MDA-MB-231, MCF7) or in cell death (Hs578T). E-cadherin-transfected MDA-MB-231 cells showed partial reversion, but exposure of the transfectants to an inhibitor of beta1 integrin, PI3K, or MAPK led to nearly complete reversion. CONCLUSION: The 3D rBM assay can be used to identify signaling pathways that, when manipulated in concert, can lead to the restoration of morphologically normal breast structures or to death of the tumor cells, even highly metastatic cells. This approach may be useful to design therapeutic intervention strategies for aggressive breast cancers.
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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 | 0.000 | 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 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".