Development of preclinical models of human BT474 and MDA-MB-361 breast cancer that endogenously overexpress HER2 and that respond to trastuzumab.
Bibliographic record
Abstract
e11061 Background: The anti-Her-2 antibody trastuzumab can be effectively combined with chemotherapy to treat Her-2 positive metastatic breast cancers. However, Her-2 positive breast cancers readily develop resistance to trastuzumab based therapies, and new models are needed to study such resistance, and to find new therapeutic options. Methods: We began the in vivo selection of human Her-2 positive breast cancer cell lines, BT474 and MDA-MB-361, in Severely Compromised Immunodeficient (SCID) mice. Tumor cells were implanted orthotopically into the mammary fat pad of SCID mice, and resulting tumors were serially passaged into new hosts over a 3 year period. Results: The resulting variants grow rapidly in SCID mice. Variants of both BT474 and MDA-MB-361 respond in vivo to trastuzumab monotherapy (20mg/kg twice weekly, i.p.) compared to controls (p<0.05). After 2-6 months of trastuzumab monotherapy, all variants developed resistance to trastuzumab; such resistant variants were adapted to tissue culture. BT474 variants produced a spontaneous lymph node metastasis in SCID mice, 10 months after the surgical resection of the orthotopically implanted primary tumor; this metastatic variant was also adapted to tissue culture. BT474 variants were tagged with luciferase and then implanted intracranially into SCID mice; the progressive growth of the tumors cells in the mouse brain was thereafter monitored for 3 months by bioluminescence imaging, which provides ample opportunity to test new treatments for brain metastases. MDA-MB-361 variants growing orthotopically responded (i.e. p<0.05 vs. controls) to the combination therapy of trastuzumab (20mg/kg twice weekly, i.p.) plus chemotherapy; chemotherapy consisted of a bolus of cyclophosphamide (CTX, 100mg/kg, i.p) followed by a maintenance metronomic CTX (20mg/kg/day, p.o.) regimen. Conclusions: We developed two preclinical models of human Her-2 positive breast cancer which may be used to study trastuzumab based therapies, Her-positive metastatic breast cancer, the growth of Her-2 positive breast cancer at a secondary site (i.e. the brain), as well as the evolution of tumor resistance to trastuzumab based therapies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".