Peripheral blood cells inform on the presence of breast cancer: A population‐based case–control study
Why this work is in the frame
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Bibliographic record
Abstract
Tumor-host interactions extend beyond the local microenvironment and cancer development largely depends on the ability of malignant cells to hijack and exploit the normal physiological processes of the host. Here, we established that many genes within peripheral blood cells show differential expression when an untreated breast cancer (BC) is present, and harnessed this fact to construct a 50-gene signature that distinguish BC patients from population-based controls. Our results were derived from a series of large datasets within our unique population-based Norwegian Women and Cancer cohort that allowed us to investigate the influence of medications and tumor characteristics on our blood-based test, and were further tested in two external datasets. Our 50-gene signature contained cytostatic signals including the specific suppression of the immune response and medications influencing transcription involved in those processes were identified as confounders. Through analysis of the biological processes differentially expressed in blood, we were able to provide a rationale as to why the systemic response of the host may be a reliable marker of BC, characterized by the underexpression of both immune-specific pathways and "universal" cell programs driven by MYC (i.e., metabolism, growth and cell cycle). In conclusion, gene expression of peripheral blood cells is markedly perturbed by the specific presence of carcinoma in the breast and these changes simultaneously engage a number of systemic cytostatic signals emerging connections with immune escape of BC.
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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 it