Muscle p62 stimulates the expression of antioxidant proteins alleviating cancer cachexia
Bibliographic record
Abstract
Oxidative stress plays an important role in skeletal muscle atrophy during cancer cachexia, and more glycolytic muscles are preferentially affected. Sequestosome1/SQSTM1 (i.e., p62), particularly when phosphorylated at Ser 349 (Ser 351 in mice), competitively binds to the Kelch-like ECH-associated protein 1 (Keap1) activating Nuclear factor erythroid 2-related factor 2 (Nrf2). Nrf2 then stimulates the transcription of antioxidant/electrophile-responsive elements in target genes. However, a potential role for p62 in the protection of muscle wasting in cachexia remains to be determined. Here, using the well-established cachexia-inducing model of Lewis Lung Carcinoma (LLC) in mice we demonstrate higher expression of antioxidant proteins (i.e., NQO1, HO-1, GSTM1, CuZnSOD, MnSOD, and EcSOD) in the more oxidative and cachexia resistant soleus muscle than in the more glycolytic and cachexia prone extensor digitorum longus muscle. This was accompanied by higher p62 (total and phosphorylated) and nuclear Nrf2 levels in the soleus, which were paralleled by higher expression of proteins known to either phosphorylate or promote p62 phosphorylation (i.e., NBR1, CK1, PKCδ, and TAK1). Muscle-specific p62 gain-of-function (i.e., in p62 mTg mice) activated Nrf2 nuclear translocation and increased the expression of multiple antioxidant proteins (i.e., CuZnSOD, MnSOD, EcSOD, NQO1, and GSTM1) in glycolytic muscles. Interestingly, skeletal muscle Nrf2 haplodeficiency blunted the increases of most of these proteins (i.e., CuZnSOD, EcSOD, and NQO1) suggesting that muscle p62 stimulates antioxidant protein expression also via additional, yet to be determined mechanisms. Of note, p62 gain-of-function mitigated glycolytic muscle wasting in LLC-affected mice. Collectively, our findings identify skeletal muscle p62 as a potential therapeutic target for cancer cachexia.
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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) | 0.000 | 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".