Abstract 3410: Identification of frequently gained genomic regions in breast circulating tumor cells
Bibliographic record
Abstract
Abstract Introduction: Cells disseminate from the primary tumor and enter the blood circulation early on. Circulating tumor cells (CTCs) might be the earliest detectable cells with metastatic abilities. Clinically, the presence of CTCs is indicative of a negative prognostic impact. Decreased numbers of CTCs are seen in response to chemotherapy, and persistent chemo-resistant CTCs have been shown to be HER2+ although they originated from HER2- primary tumors. Such discrepancies were also found with ER, PR and EGFR status and have important implications with respect to treatment alterations over the course of the disease. If the whole genome of CTCs can be profiled, we could identify genomic alterations which may be developed into CTC specific markers, to monitor and target them, to prevent their spread to distant sites. We could also investigate how these cells are represented in primary tumors and how they respond to chemotherapy. Methods: CTCs were enriched from blood by immunomagnetic CD45+ leukocyte depletion; fixed onto glass slides and stained for the epithelial cell marker, pancytokeratin. Positively stained CTCs were isolated by single-cell laser capture microdissection for whole genome amplification (WGA) and copy number (CN) analysis with the Affymetrix Genome wide SNP 6.0 array. CTCs were isolated from peripheral blood of 21/39 patients (54%, range of 1-20 cells) with locally advanced breast cancer. Normal samples were obtained by performing WGA on the white blood cell fraction of blood. Results: CN gains and losses were detected by genomic segmentation, using a paired CTC-normal sample approach (Partek Genomic Suite). Overall, regions with gains were more prevalent than losses. The most frequent gains were on chromosome 1q21.3, 4q26, 6q16.3, 9q34.1-34.3, 11p15.4-15.5, 17q21-25, and 19. Regions 17q21-25 and 9q34 were associated with lymph node metastasis, tumor size, and higher CTC counts. Genes within these regions which could potentially be implicated in CTC dissemination are CCL5 (breast cancer progression), MMP28 (invasion), and PTPN1 (migration). Notably, CTCs were more homogenous for gains on chromosome 19, which has been implicated in many types of cancers. It houses the entire family of kallikrein protease genes, a hallmark in prostate, ovarian and colorectal cancers; and was recently found to contain 5 SNPs which are associated with BRCA1 mutations and high risk breast cancer. We identified 5 peaks (0.3 - 9.5Mb) between 19p13.3-13.1 and 19q13.32-13.4, with an average CN of 3, in 15/17 patients. Conclusions: Whole genomic profiling of CTCs from breast cancer revealed regions of CN gain, as well as specific CN signatures associated with poor prognosis. Gains on chromosome 19 were most frequent, warranting further investigations of genes that confer CTC-like functionality to tumor cells. We will determine the heterogeneity of these regions in primary breast cancer, and how they respond to chemotherapy. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3410. doi:1538-7445.AM2012-3410
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".