Abstract 2379: The lung microenvironment influences the metastatic behavior of breast cancer cells in an innovative 3D ex vivo pulmonary metastasis model
Bibliographic record
Abstract
Abstract Breast cancer remains a leading cause of mortality among women, with the majority of deaths attributed to metastatic disease. In particular, the lung is one of the most common and deadly sites of breast cancer metastasis, particular in women with more aggressive molecular subtypes such as Her2+ and triple-negative breast cancer. However, it still remains unclear whether the propensity of breast cancer cells to metastasize to the lung reflects properties of cancer cells themselves, properties of the lung microenvironment, or a combination of both. Both cancer initiation and progression can in part be attributed to small subsets of “stem cell-like” tumor cells, which in breast cancer are characterized by high aldehyde dehydrogenase (ALDH) activity and/or expression of the CD44+CD24- phenotype (ALDHhiCD44+). We have previously shown that ALDHhiCD44+ breast cancer cells demonstrate preferential migration and growth in response to lung-derived soluble factors, and an increased propensity to metastasize to the lung in vivo. The objective of this study was to use an innovative 3D ex vivo pulmonary metastasis model (PuMA) that incorporates the native 3D architecture of the lung in order to test the hypothesis that whole population and stem-like ALDHhiCD44+ breast cancer cell metastatic behavior is influenced by the lung microenvironment. Red fluorescent protein (RFP)-expressing MDA-MB-231 and MDA-MD-468 breast cancer cells were seeded (5×105 cells) to the lungs of female nude mice by tail vein injection. Following euthanasia, lungs were excised, sliced into 1 mm transverse sections, and grown in culture under serum-free conditions over 21 days. Sections were imaged at 0, 7, 14 and 21 days to observe growth and progression. Using H&E and Masson's Trichrome staining, we confirmed that lung sections remained healthy with intact pulmonary architecture over 21 days in culture. Over a 14-day period, we observed significant growth of MDA-MB-231 whole breast cancer cell populations in this assay at day 14 relative to day 7 and day 0 (p≤0.05). Sorted populations of MDA-MB-231 ALDHhiCD44+ cells showed significant growth at days 14 (p≤0.001) and 21 (p≤0.0001) compared to their ALDHlowCD44- counterparts. ALDHhiCD44+ cells also progressed from the single cell state (<50 μm) to micrometastatic (200-400 μm) to macrometastatic (>400 μm) colonies during 21 days. Conversely, ALDHlowCD44- cells showed no such progression and remained predominantly as single cells throughout the assay. Together these results demonstrate that the PuMA assay sustains healthy lung architecture over 21 days, and that aggressive breast cancer cells interact with the lung to grow and progress as metastatic colonies. Ultimately, the results of this study will provide a greater understanding of the contribution of the lung microenvironment in mediating breast cancer metastasis. Citation Format: Matthew Piaseczny, David Goodale, Alison Allan. The lung microenvironment influences the metastatic behavior of breast cancer cells in an innovative 3D ex vivo pulmonary metastasis model. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2379. doi:10.1158/1538-7445.AM2015-2379
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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".