Loss of Kaiso expression in breast cancer cells prevents intra-vascular invasion in the lung and secondary metastasis
Bibliographic record
Abstract
The metastatic activity of breast carcinomas results from complex genetic changes in epithelial tumor cells and accounts for 90% of deaths in affected patients. Although the invasion of the local lymphatic vessels and veins by malignant breast tumor cells and their subsequent metastasis to the lung, has been recognized, the mechanisms behind the metastatic activity of breast tumor cells to other distal organs and the pathogenesis of metastatic cancer are not well understood. In this study, we utilized derivatives of the well-established and highly metastatic triple negative breast cancer (TNBC) cell line MDA-MB-231 (MDA-231) to study breast tumor metastasis in a mouse model. These MDA-231 derivatives had depleted expression of Kaiso, a POZ-ZF transcription factor that is highly expressed in malignant, triple negative breast cancers. We previously reported that Kaiso depletion attenuates the metastasis of xenografted MDA-231 cells. Herein, we describe the pathological features of the metastatic activity of parental (Kaisopositive) versus Kaisodepleted MDA-231 cells. Both Kaisopositive and Kaisodepleted MDA-231 cells metastasized from the original tumor in the mammary fat pad to the lung. However, while Kaisopositive cells formed large masses in the lung parenchyma, invaded large pulmonary blood vessels and formed secondary metastases and large tumors in the distal organs, Kaisodepleted cells metastasized only to the lung where they formed small metastatic lesions. Importantly, intravascular invasion and secondary metastases in distal organs were not observed in mice xenografted with Kaisodepleted cells. It thus appears that the lung may constitute a barrier for less invasive breast tumors such as the Kaisodepleted TNBC cells; this barrier may limit tumor growth and prevents Kaisodepleted TNBC cells from invading the pulmonary blood vessels and forming secondary metastases in distal organs.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".