Abstract 1451: Microfluidic-based unbiased enrichment (negative selection) of circulating non-hematopoietic tumor cells directly from whole blood without centrifugation.
Bibliographic record
Abstract
Abstract The enumeration and analysis of circulating non-hematopoietic tumor cells (CTCs) is of increasing interest for monitoring disease progression or response to treatment, specifically as a companion diagnostic for new anti-cancer drugs, and for research into the mechanisms of disease progression and metastases. Ideally, CTCs would be enriched from very small samples, with minimal handling, high recovery, and no requirement for the expression of specific surface markers. Two technologies have been combined to meet these requirements. Hematopoietic white blood cells (WBCs) in whole blood were first cross-linked to magnetic particles using EasySep™ anti-CD45 TAC. The sample was diluted and placed in a magnet for 30 min.; an outlet in the bottom of the sample tube was then opened and the sample flowed by gravity into a microfluidic chamber containing a high-precision micro-slit membrane. Red blood cells (RBCs) flowed through the microfluidic chamber, while larger cells such as CTCs were retained in the chamber. The cells in the chamber were washed with PBS and then identified by staining with Hoechst [nuclear], anti-cytokeratin antibodies [epithelial cells], and anti-CD45 antibodies [hematopoietic cells]. CTCs were defined as Hoechst+, cytokeratin+ and CD45-. The recovery of MCF-7 breast adenocarcinoma cells spiked into normal whole blood, at 10, 30, 50, or 100 cells / 2 mL blood was 95 ± 23% (7 ± 1, n=3 for 10 cells; 24 ± 3, n=3 for 30 cells; 57 ± 3, n=3 for 50 cells; 113 ± 27, n=3 for 100 cells) and the log depletion of WBCs exceeded 2.3. The recovery of H1975 lung adenocarcinoma cells spiked into normal whole blood, at 10, 30, 50, or 100 cells / 2 mL blood was 93 ± 8% (9 ± 1, n=3 for 10 cells; 28 ± 3, n=3 for 30 cells; 48 ± 6, n=3 for 50 cells; 94 ± 2, n=3 for 100 cells), and the log depletion of WBCs exceeded 2.14. 13 patient samples [10 NSCLC and 3 CRC] were processed with this method and CTCs were detected in every sample. The number of CTC detected from 2 mL of blood ranged from 1 to 51. WBC log depletion ranged from 2.01 to 2.79. No RBCs were observed on the membrane of the microfluidic chamber. The entire process requires ∼ 60 minutes and could easily be automated. RBC depletion is essentially complete without the use of centrifugation or chemicals which may be deleterious to CTCs. The minimal sample handling permits high recovery of desired cells, allowing the detection of CTCs in much smaller samples than are currently used for clinical evaluation. CTCs are enriched without bias as to their surface antigen expression, and are not labeled with antibodies prior to detection. CTCs can be stained and visualized directly on the microfluidic chip. This unbiased enrichment approach could be used to assess the mutation status of CTC in real time. Citation Format: Carrie E. Peters, Hamizah Ahmad, Drew Kellerman, Bhuvanendran Nair Gourikutty Sajay, Chang Chia-Pin, Wong Chee Chung, Abdur Rub Abdur Rahman, Karina L. McQueen, Terry E. Thomas. Microfluidic-based unbiased enrichment (negative selection) of circulating non-hematopoietic tumor cells directly from whole blood without centrifugation. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1451. doi:10.1158/1538-7445.AM2013-1451
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".