Wnt signaling in triple negative breast cancer is associated with metastasis
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Triple Negative subset of (TN) Breast Cancers (BC), a close associate of the basal-like subtype (with limited discordance) is an aggressive form of the disease which convey unpredictable, and poor prognosis due to limited treatment options and lack of proven effective targeted therapies. METHODS: We conducted an expression study of 240 formalin-fixed, paraffin-embedded (FFPE) primary biopsies from two cohorts, including 130 TN tumors, to identify molecular mechanisms of TN disease. RESULTS: The annotation of differentially expressed genes in TN tumors contained an overrepresentation of canonical Wnt signaling components in our cohort and others. These observations were supported by upregulation of experimentally induced oncogenic Wnt/β-catenin genes in TN tumors, recapitulated using targets induced by Wnt3A. A functional blockade of Wnt/β-catenin pathway by either a pharmacological Wnt-antagonist, WntC59, sulidac sulfide, or β-catenin (functional read out of Wnt/β-catenin pathway) SiRNA mediated genetic manipulation demonstrated that a functional perturbation of the pathway is causal to the metastasis- associated phenotypes including fibronectin-directed migration, F-actin organization, and invasion in TNBC cells. A classifier, trained on microarray data from β-catenin transfected mammary cells, identified a disproportionate number of TNBC breast tumors as compared to other breast cancer subtypes in a meta-analysis of 11 studies and 1,878 breast cancer patients, including the two cohorts published here. Patients identified by the Wnt/β-catenin classifier had a greater risk of lung and brain, but not bone metastases. CONCLUSION: These data implicate transcriptional Wnt signaling as a hallmark of TNBC disease associated with specific metastatic pathways.
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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) | 0.002 | 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