Abstract 3910: Analysis of metastatic potential by breast cancer type through a microfluidic blood-brain niche
Bibliographic record
Abstract
Abstract Metastasis from the primary tumor site to the brain is the most lethal complication from advanced cancer. 15% of breast cancers metastasize in the brain with a median survival of 5-14 months depending on the subtype. Therefore it is critical to identify when a tumor has the clonal potential to metastasize to the brain. Current detection methods and treatment therapies have continued to improve but do not shed light on clonal metastatic potential. Models for characterizing metastatic potential of clonal populations currently used include murine in vivo and simple in vitro systems. Murine models are costly, time intensive, slow to manifest metastasis and are not easy to analyze. On the other hand, in vitro systems are faster and more cost effective but currently do not recapitulate the complexity of the “live” micro-environment. We have developed a microfluidic device that mimics the cellular and physical components of the human blood-brain niche to study the brain metastatic process. The device is composed of two chambers separate by a porous membrane. The top chamber and apical side of the membrane is seeded with human brain endothelial cells and uses flow to mimic shear stress encountered within the vasculature. Cancer cells are introduced into this chamber in which they adhere to and migrate through the endothelium into the bottom chamber. The bottom chamber contains astrocytes suspended in a collagen gel to mimic the brain stroma and provide room for invading cancer cells to colonize and grow. Barrier integrity is monitored using TEER (trans-endothelial electrical resistance), and fluctuates as the tight junctions of the endothelium are compromised by invading cancer cells. This is characterized by IF and tight junction staining. Throughout all time points, from introduction into the flow chamber, adherence to the endothelium, extravasation through the barrier, migration into the stroma, and proliferation the cancer cells can be monitored via both microscopy and TEER. We have applied this microfluidic blood-brain niche model to compare brain-seeking subclones of breast cancer cell lines of known whole exome sequence and normal-like cell lines (MCF10A) in terms of their ability to extravasate, migrate and survive in the niche. We characterize their migratory behavior from live-cell microscopy and correlate it to the TEER measurements to establish a metastatic model. We then compare metastatic markers for ∝BBN traversing and non-traversing cells when appropriate. Citation Format: Christopher Ryan Oliver, Megan Altemus, Brendan Leung, Aki Morikawa, Michele Dziubinski, Maria Castro, Sofai Merajver. Analysis of metastatic potential by breast cancer type through a microfluidic blood-brain niche [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3910. doi:10.1158/1538-7445.AM2017-3910
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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".