The role of circulating tumor cell-associated genes in the progression of estrogen receptor-positive breast cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Estrogen receptor-positive, human epidermal growth factor receptor negative (ER + /HER2-) breast cancer, poses challenges in adjuvant treatment decisions due to its propensity for late recurrence. We propose a model that leverages our previously identified circulating tumor cell (CTC) genomic signature, linked to metastasis. Furthermore, we investigated the impact of CTC signature intratumour heterogeneity (ITH) on recurrence risk. Using Oncotype DX recurrence score as a surrogate for survival, we trained expression and copy number-based models using 194 early stage ER + /HER2- breast cancer patients and validated them in the METABRIC dataset. Multispectral fluorescence in situ hybridization (Multiplex-FISH) was used to evaluate the ITH of 6 CTC genomic regions in primary tumors. The expression-based model strongly correlated with Oncotype DX, while the copy number-based model achieved a moderate correlation. Both models were able to predict long-term recurrence free survival in METABRIC. Higher CTC signature ITH was associated with increased Oncotype DX risk and higher overall grade. These findings highlight the value of our CTC signature in disease progression and the role of ITH on recurrence risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.000 | 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 it