Abstract P6-04-09: Single Cell Whole Genome Amplification for High Density SNP Analysis of Circulating Tumour Cells in Early Breast Cancer
Bibliographic record
Abstract
Abstract Background: Despite progressive advances in the fields of radiation and chemotherapy, metastasis remains the leading cause of death in women with recurrent breast cancer. In metastasis, cells disseminate from the primary tumor, and circulate via the vascular system to distant organs, developing tumors at these new sites. Recent studies have suggested that tumor cells disseminate early on and develop the capacity to metastasize independently from the primary tumor. These circulating tumour cells (CTCs) represent the intermediate cells between primary tumours and metastases. The presence of CTCs in blood is an established prognostic marker of shorter progression-free and overall survival. It is currently impossible to distinguish CTCs from normal epithelial cells. They are also a rare population (approximately 1 out of 109 blood cells), making genomic profiling unachievable thus far. If the whole genome of CTCs can be screened for genomic alterations, two fundamental problems can be addressed (a) identifying a gene signature describing specific genomic alterations in early breast cancer that are associated with metastasis; and (b) utilizing this signature in the development of specific markers for CTCs in blood. Materials and Methods: We have successfully designed a protocol for the isolation of CTCs from blood for subsequent whole genome amplification (WGA) and microarray analysis. Blood samples from healthy donors were spiked with MCF7 tumor cells, and then enriched by automated immunomagnetic column separation. Enriched cell smears were stained for cytokeratin, using a glucose oxidase (GO) detection system. GO is absent from mammalian cells, which abolishes false positives seen with alkaline phosphatase and horse raddish peroxidase detection. Positively stained cells were isolated by single-cell laser capture microdissection, followed by WGA. Results: Genomic amplification was observed from as few as 2 MCF7 cells; with a sufficient yield of 1.5-3 μg of DNA. Microarray analysis was carried out on the high density Affymetrix Genome Wide SNP 6.0 array. Expected regions of amplification and deletion in the MCF7 cell line were identified in WGA samples. Copy number states were found to be strictly conserved across samples with single cell starting material (P<0.0001). We achieved up to 84% SNP call concordance between amplified single cell DNA and unamplified genomic DNA (P<0.0001). Discussion: We are isolating CTCs from the peripheral blood of 60 patients with early breast cancer. We have isolated CTCs and amplified DNA from 11 of 20 patients recruited so far. This preliminary study shows regions of DNA amplification that are unique to CTCs. We hypothesize that genes within these regions have the potential of being developed into CTC specific markers, and include genes associated with epithelial-mesenchymal transition, dormancy, cancer cell-stemness, migration, and invasion of the extracellular matrix. Identification of novel genomic alterations in CTCs associated with metastasis will pave the way for the development of a robust molecular or immunohistochemical prognostic test in patients with early breast cancer, to better identify those patients whose disease will progress to metastasis. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P6-04-09.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".