CircPVT1 sponges miR-33a-5p unleashing the c-MYC/GLS1 metabolic axis in breast cancer
Bibliographic record
Abstract
Abstract Altered metabolism is one of the cancer hallmarks. The role of circRNAs in cancer metabolism is still unexplored. Herein, we initially found that the expression of circPVT1 was significantly higher in tumoral tissues than in non-tumoral breast tissues. Basal like breast cancer patients with higher levels of circPVT1 exhibited shorter disease-free survival compared to those with lower expression. CircPVT1 ectopic expression rendered fully transformed MCF-10A immortalized breast cells and increased tumorigenicity of TNBC cell lines. Depletion of endogenous circPVT1 reduced tumorigenicity of SUM-159PT and MDA-MB-468 cells. 1H-NMR spectroscopy metabolic profiling of circPVT1 depleted breast cancer cell lines revealed reduced glycolysis and glutaminolitic fluxes. Conversely, MCF-10A cells stably overexpressing circPVT1 exhibited increased glutaminolysis. Mechanistically, circPVT1 sponges miR-33a-5p, a well know metabolic microRNA, which in turn releases c-MYC activity which promotes transcriptionally glutaminase, which converts glutamine to glutamate. CircPVT1 depletion synergizes with GLS1 inhibitors BPTES or CB839 to reduce cell viability of breast cancer cell lines and breast cancer-derived organoids. In aggregate, our findings unveil the circPVT1/miR-33a-5p/Myc/GLS1 axis as a pro-tumorigenic metabolic event sustaining breast cancer transformation with potential therapeutic implications.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".