Cancer Affects microRNA Expression, Release, and Function in Cardiac and Skeletal Muscle
Bibliographic record
Abstract
Circulating microRNAs (miRNA) are emerging as important biomarkers of various diseases, including cancer. Intriguingly, circulating levels of several miRNAs are lower in patients with cancer compared with healthy individuals. In this study, we tested the hypothesis that a circulating miRNA might serve as a surrogate of the effects of cancer on miRNA expression or release in distant organs. Here we report that circulating levels of the muscle-enriched miR486 is lower in patients with breast cancer compared with healthy individuals and that this difference is replicated faithfully in MMTV-PyMT and MMTV-Her2 transgenic mouse models of breast cancer. In tumor-bearing mice, levels of miR486 were relatively reduced in muscle, where there was elevated expression of the miR486 target genes PTEN and FOXO1A and dampened signaling through the PI3K/AKT pathway. Skeletal muscle expressed lower levels of the transcription factor MyoD, which controls miR486 expression. Conditioned media (CM) obtained from MMTV-PyMT and MMTV-Her2/Neu tumor cells cultured in vitro were sufficient to elicit reduced levels of miR486 and increased PTEN and FOXO1A expression in C2C12 murine myoblasts. Cytokine analysis implicated tumor necrosis factor α (TNFα) and four additional cytokines as mediators of miR486 expression in CM-treated cells. Because miR486 is a potent modulator of PI3K/AKT signaling and the muscle-enriched transcription factor network in cardiac/skeletal muscle, our findings implicated TNFα-dependent miRNA circuitry in muscle differentiation and survival pathways in 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".