Gene expression differences between disseminated tumor cells and tumor cells from overt bone metastases in patients with metastatic breast cancer
Bibliographic record
Abstract
1040 Background: Despite extensive work evaluating molecular differences between primary tumors, circulating tumor cells, disseminated tumor cells (DTCs) and established metastases, it is not apparent which genetic alterations are required to form viable, independent bone metastases (BM). A major limitation in exploring the genetic differences between DTCs and established BM is the paucity of fresh BM tissue available. Methods: Ten breast cancer patients with BM underwent a CT-guided BM biopsy and a bone marrow aspiration (for DTCs). Tumor cells were enriched by immunomagnetic separation and RNA was extracted from each sample. Gene expression profiling was conducted using Illumina Human Ref-8 bead arrays. Microarray data was analyzed using BeadStudio software to identify differentially expressed genes. Ingenuity Pathway Analysis software was used to identify genes integral to specific pathways involved in tumor dissemination. Results: The yield of analyzable malignant cells from BM and bone marrow aspirates was 60% and 80%, respectively. A signature of 133 genes was identified that was differentially expressed between the two sample types. Paired analysis of samples from the same patients identified a subset of 161 genes, of which 52 overlapped with the initial unmatched signature. Several genes relevant to breast cancer metastasis to bone (i.e., osteopontin, CTGF, parathyroid hormone receptor, EGFR) were significantly over-expressed in the BM compared to the DTCs. Conclusions: Results suggest that there are specific subsets of genes, which are required for DTCs in the bone marrow to form overt BM. A number of genes identified are already known to participate in osteolytic BM formation. This signature may allow identification of patients at increased risk for developing BM. No significant financial relationships to disclose.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.000 | 0.000 |
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 teacher head, 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".