Targeting fatty acid oxidation enhances response to HER2-targeted therapy
Bibliographic record
Abstract
Metabolic reprogramming, a hallmark of tumorigenesis, involves alterations in glucose and fatty acid metabolism. Here, we investigate the role of Carnitine palmitoyl transferase 1a (Cpt1a), a key enzyme in long-chain fatty acid (LCFA) oxidation, in ErbB2-driven breast cancers. In ErbB2+ breast cancer models, ablation of Cpt1a delays tumor onset, growth, and metastasis. However, Cpt1a-deficient cells exhibit increased glucose dependency that enables survival and eventual tumor progression. Consequently, these cells exhibit heightened oxidative stress and upregulated nuclear factor erythroid 2-related factor 2 (Nrf2) activity. Inhibiting Nrf2 or silencing its expression reduces proliferation and glucose consumption in Cpt1a-deficient cells. Combining the ketogenic diet, composed of LCFAs, or an anti-ErbB2 monoclonal antibody (mAb) with Cpt1a deficiency significantly perturbs tumor growth, enhances apoptosis, and reduces lung metastasis. Using an immunocompetent model, we show that Cpt1a inhibition promotes an antitumor immune microenvironment, thereby enhancing the efficacy of anti-ErbB2 mAbs. Our findings underscore the importance of targeting fatty acid oxidation alongside HER2-targeted therapies to combat resistance in HER2+ breast cancer patients.
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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 | 0.001 |
| 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".