Abstract 2120: Single cell whole genome amplification for high density SNP analysis of circulating tumor cells in early breast cancer
Bibliographic record
Abstract
Abstract 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, a small, select group of cells disseminate from the primary breast 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. Furthermore, the enumeration of circulating tumour cells (CTCs) in blood is an established prognostic marker whereby, patients with more than 5 CTCs per 7.5mL of blood have shorter progression-free and overall survival. It is currently impossible to distinguish CTCs from normal epithelial cells. 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 makers for CTCs in blood. We have designed a protocol for the isolation of tumor cells 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. Genomic amplification was observed from as few as 2 MCF7 cells; with a sufficient yield of 1.5-3 µg. 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, as well as conserved across samples with single cell starting material (p<0.0001). Concordance of 75% was achieved from WGA of 3 single cells (p<0.0001). We propose to isolate CTCs from peripheral blood of 60 patients seen at the Locally Advanced Breast Cancer clinic at Princess Margaret Hospital. We have amplified genomic DNA from 6 out of 12 patients recruited so far, each having between 3-10 CTCs. Matched normal samples were obtained from the residual WBC pellet of each patient to allow for paired analysis. Optimization of WGA concordance will be followed by analysis of CTC DNA obtained from patients. 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 Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2120.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".