Abstract 2912: Size based enrichment and sorting of Ov90 cancer cells and clusters with a new multistage filtration cartridge reveals distinct phenotypes
Bibliographic record
Abstract
Abstract Background: Circulating tumor cells (CTCs) are released in blood from the primary tumor, but although very heterogeneous both in size and marker expression, are very rare and provide information not available from the primary tumor. The identification of CTC cells and clusters could advance our understanding of metastasis and help personalize therapy.1,2 Notably, CTC clusters were shown to have a higher metastatic potential than single cells3 but the process remains poorly understood. We present a multistage filtration system with pore sizes from 20 down to 8 μm for the size-selective enrichment of Ov90 ovarian cancer cells and clusters from blood. Each captured cell population was released, cultured and characterized independently. Methods: We developed a 3D printed multistage filtration cartridge and polymer filters with 20, 15, 12, 10 and 8 μm-diameter pores. Filters were stacked from 20 (top) to 8 μm (bottom) and used to enrich and sort Ov-90 cells spiked in 1:6 mL of blood:PBS. Captured cells were released by removing individual filters from the cartridge, reverse flowing OSE medium, and then cultured separately. Results: Ov-90 clusters were found mostly on the top filter (20 μm) and interestingly, few small clusters (3-4 cells) were found on the 8 and 10 μm filters, suggesting alignment of cluster cells as they pass through the pores.4 Cell and nucleus diameters were measured, and a general correlation was found between filter pore size and cell and nucleus size. Interestingly, nucleus size was found to be the single most significant parameter in determining passage of single cells and small clusters through pores. Following cell culture, two distinct phenotypes were observed: cell captured on small pore filters (8-12 μm) grew primarily in a monolayer. Cells captured on filters with larger pores (15-20 μm) first grew as monolayer, but rapidly formed cell aggregates that subsequently detached from the surface. Staining for E-Cadherin, a cell-cell adhesion protein, revealed a loss of expression of cells from filter with larger pores. Conclusion: We developed a new multistage filtration method and selectively enriched and sorted cells based primarily on their nucleus size. We identified two Ov-90 populations with different growth behaviors with low E-cadherin expression on the cells forming clusters, which is known to correlate with metastasis. The application of multistage filters may also reveal different CTC populations based on nucleus and cell size. References: (1) Baccelli, I. et al. A. Nat. Biotech. 2013, 31, 539-544. (2) Pecot, C. V. et al. Cancer discovery 2011, 1, 580-586. (3) Cheung, K. J. et al. Proc. Natl. Acad. Sci. U.S.A. 2016, 113, E854-E863. (4) Au, S. H. et al. Proc. Natl. Acad. Sci. U.S.A. 2016, 113, 4947-4952. Citation Format: Anne Meunier, Sara kheireddine, J. Alejandro Hernández-Castro, Teodor Veres, David Juncker. Size based enrichment and sorting of Ov90 cancer cells and clusters with a new multistage filtration cartridge reveals distinct phenotypes [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 2912. doi:10.1158/1538-7445.AM2017-2912
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".