P4-07-02: Detection, Enrichment, Characterization and Propagation of Circulating Tumour Cells from Patients with Advanced Metastatic Breast Cancer.
Bibliographic record
Abstract
Abstract Background: Circulating tumour cells (CTCs) have attracted much attention lately due to their potential utility in diagnostic, therapeutic and prognostic applications. Characterization of these cells may indeed permit more targeted and individualized therapeutic approaches, as well as provide a means to monitor treatment response. Although detection of CTCs in peripheral blood (PB) is relatively easy using current methodologies, characterization of the CTC pool has proven more challenging due to their low abundance. Furthermore, in-vitro expansion of this elusive cell pool in mammosphere cultures has not yet been reported. In order to achieve a more complete characterization of CTCs and attempt to obtain live cells in sufficient quantity for in vitro expansion, we have used aphaeresis as a means to collect a large initial cell fraction from which to enrich CTCs from peripheral blood. Methods: A cohort (n=17) of late stage breast cancer patients were first screened using 10ml PB. Peripheral blood mononuclear cells (PBMCs) were isolated using a Ficoll gradient and then enriched for CTCs by anti-CD45 negative selection using an automated system (RoboSep) based on magnetic bead separation. CTCs were detected by immunocytochemistry (ICC) for cytokeratin expression and patients classified as CTC-positive were selected for the aphaeresis procedure. Following collection of aphaeresis material (APM), PBMCs were isolated using a Ficoll gradient, enriched by automated anti-CD45 negative selection and characterized for a variety of markers by ICC, immunofluorescence and flow cytometry. CTCs were then cultured in serum-free medium as monolayers and suspensions. Recovery at the various steps of the isolation process was determined using PB from healthy subjects spiked with MCF-7 breast cancer cells and processed using the same approach. Results: Recovery of spiked MCF-7 cells was about 40% after Ficoll and magnetic bead separation. Using this negative selection procedure 17/17 (100%) of subjects tested were positive at screening. Most patients (14/17) underwent aphaeresis and a large number (9,600 to 108,000) of enriched CTCs was recovered from APM in all patients tested, either as individual cells or as CTC clusters. Using dual immunofluorescence labelling, co-localization of the epithelial cell marker CK8 and the chemokine receptor CXCR4 was observed within CTCs. Furthermore, over 20% of CTCs were positive for both CK8 and ALDH1, indicative of a stem-like phenotype. APM-derived CTCs from all patients (14/14) could be propagated, both as attached cells and in suspension culture. They formed colonies in monolayer culture, and clusters in mammosphere culture, indicating stem cell-like properties. They replicated for at least three passages in mammosphere culture. Conclusion: Our CTC detection and enrichment method using negative selection offers a distinct advantage over current methodologies, including collection of clusters, and the ability to grow and expand CTCs in serum-free culture conditions. Furthermore, these cells demonstrate breast cancer stem cell-like characteristics, the ability to replicate for multiple passages as mammospheres in suspensions and a metastatic signature. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P4-07-02.
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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 | 0.001 |
| 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) | 0.003 | 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".