Breast cancer diagnosis is associated with relative left ventricular hypertrophy and elevated endothelin-1 signaling
Bibliographic record
Abstract
BACKGROUND: The survival rates of women with breast cancer have improved significantly over the last four decades due to advances in breast cancer early diagnosis and therapy. However, breast cancer survivors have an increased risk of cardiovascular complications following chemotherapy. While this increased risk of later occurring structural cardiac remodeling and/or dysfunction has largely been attributed to the cardiotoxic effects of breast cancer therapies, the effect of the breast tumor itself on the heart prior to cancer treatment has been largely overlooked. Thus, the objectives of this study were to assess the cardiac phenotype in breast cancer patients prior to cancer chemotherapy and to determine the effects of human breast cancer cells on cardiomyocytes. METHODS: We investigated left ventricular (LV) function and structure using cardiac magnetic resonance imaging in women with breast cancer prior to systemic therapy and a control cohort of women with comparable baseline factors. In addition, we explored how breast cancer cells communicate with the cardiomyocytes using cultured human cardiac and breast cancer cells. RESULTS: Our results indicate that even prior to full cancer treatment, breast cancer patients already exhibit relative LV hypertrophy (LVH). We further demonstrate that breast cancer cells likely contribute to cardiomyocyte hypertrophy through the secretion of soluble factors and that at least one of these factors is endothelin-1. CONCLUSION: Overall, the findings of this study suggest that breast cancer cells play a greater role in inducing structural cardiac remodeling than previously appreciated and that tumor-derived endothelin-1 may play a pivotal role in this process.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".