C/EBPβ promotes the expression of atrophy‐inducing factors by tumours and is a central regulator of cancer cachexia
Bibliographic record
Abstract
BACKGROUND: CCAAT/enhancer-binding protein β (C/EBPβ) is a transcription factor whose high expression in human cancers is associated with tumour aggressiveness and poor outcomes. Most advanced cancer patients will develop cachexia, characterized by loss of skeletal muscle mass. In response to secreted factors from cachexia-inducing tumours, C/EBPβ is stimulated in muscle, leading to both myofibre atrophy and the inhibition of muscle regeneration. Involved in the regulation of immune responses, C/EBPβ induces the expression of many secreted factors, including cytokines. Because tumour-secreted factors drive cachexia and aggressive tumours have higher expression of C/EBPβ, we examined a potential role for C/EBPβ in the expression of tumour-derived cachexia-inducing factors. METHODS: We used gain-of-function and loss-of-function approaches in vitro and in vivo to evaluate the role of tumour C/EBPβ expression on the secretion of cachexia-inducing factors. RESULTS: We report that C/EBPβ overexpression up-regulates the expression of 260 secreted protein genes, resulting in a secretome that inhibits myogenic differentiation (-31%, P < 0.05) and myotube maturation [-38% (fusion index) and -25% (myotube diameter), P < 0.05]. We find that knockdown of C/EBPβ in cachexia-inducing Lewis lung carcinoma cells restores myogenic differentiation (+25%, P < 0.0001) and myotube diameter (+90%, P < 0.0001) in conditioned medium experiments and, in vivo, prevents muscle wasting (-51% for small myofibres vs. controls, P < 0.01; +140% for large myofibres, P < 0.01). Conversely, overexpression of C/EBPβ in non-cachectic tumours converts their secretome into a cachexia-inducing one, resulting in reduced myotube diameter (-41%, P < 0.0001, EL4 model) and inhibition of differentiation in culture (-26%, P < 0.01, EL4 model) and muscle wasting in vivo (+98% small fibres, P < 0.001; -76% large fibres, P < 0.001). Comparison of the differently expressed transcripts coding for secreted proteins in C/EBPβ-overexpressing myoblasts with the secretome from 27 different types of human cancers revealed ~18% similarity between C/EBPβ-regulated secreted proteins and those secreted by highly cachectic tumours (brain, pancreatic, and stomach cancers). At the protein level, we identified 16 novel secreted factors that are present in human cancer secretomes and are up-regulated by C/EBPβ. Of these, we tested the effect of three factors (SERPINF1, TNFRSF11B, and CD93) on myotubes and found that all had atrophic potential (-33 to -36% for myotube diameter, P < 0.01). CONCLUSIONS: We find that C/EBPβ is necessary and sufficient to induce the secretion of cachexia-inducing factors by cancer cells and loss of C/EBPβ in tumours attenuates muscle atrophy in an animal model of cancer cachexia. Our findings establish C/EBPβ as a central regulator of cancer cachexia and an important therapeutic target.
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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 | 0.001 |
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".