NVTG-03 IDENTIFYING THE DRIVERS OF EARLY BRAIN METASTASES ESTABLISHMENT IN BREAST CANCER PATIENTS
Bibliographic record
Abstract
Abstract Breast cancer is the most common type of cancer in women. It is also the 2nd most common cause of brain metastases (BrM), with 30-50% of breast cancer patients developing BrM over the course of their disease. Despite aggressive therapy and novel systemic treatment options, prognosis for these patients remains poor. The objectives of our work were to identify the underlying genomic and transcriptomic signatures that characterise early BrM establishment in patients with breast cancer, and to identify brain-intrinsic molecular mechanisms critical to BrM development. We performed transcriptomic and genomic profiling on fresh frozen (FF) brain metastases tumour samples of patients who required surgical resection of an intracranial metastatic early (<3 years from initial diagnosis) or late (>3 years from initial diagnosis) in the disease course. Findings were validated by immunohistochemistry and immunofluorescence staining for genes of interest in BrM, matched primary breast tumour samples, and healthy brain tissue. The findings were complemented with scRNA sequencing studies to resolve cellular contributions of individual cell types and subtypes and uncover specific cell-type interactions in BrM establishment. In patients with early metastatic disease, pathway enrichment analysis identified TGF-β pathway upregulation, which stimulates epithelial-to-mesenchymal transition, integrin-mediated invasion, recruitment and activation of cancer-associated fibroblasts. We identified collagen-extracellular matrix interactions as key oncogenic features of the metastatic tumour microenvironment. We have selected lead candidates that can play significant role in early colonisation of breast cancer cells to the brain from the primary breast tumour and enhance tumorigenesis. These markers will be challenged in an in vivo brain metastasis model to attenuate the establishment of metastatic disease. Our goal is to identify a modifiable marker that could be clinically targeted to prevent the establishment of brain metastases in patients diagnosed with breast cancer.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".