HERC3-Mediated SMAD7 Ubiquitination Degradation Promotes Autophagy-Induced EMT and Chemoresistance in Glioblastoma
Bibliographic record
Abstract
Abstract Purpose: Glioblastoma, a common malignant intracranial tumor, has the most dismal prognosis. Autophagy was reported to act as a survival-promoting mechanism in gliomas by inducing epithelial-to-mesenchymal transition (EMT). Here, we determined the critical molecules involved in autophagy-induced EMT and elucidated the possible mechanism of chemoradiotherapy resistance and tumor recurrence. Experimental Design: We used isobaric tags for relative and absolute quantitation to identify the critical proteins and pathway mediating EMT via autophagy inducer treatment, and tested the expression of these proteins using tissue microarray of gliomas and clinical glioblastoma samples as well as tissues and cells separated from the core lesion and tumor-peripheral region. Analysis of the Cancer Genome Atlas database and 110 glioblastoma cases revealed the prognostic value of these molecules. The functional role of these critical molecules was further confirmed by in vitro experiments and intracranial xenograft in nude mice. Results: Autophagy inducers significantly upregulated the expression of HERC3, which promotes ubiquitination-mediated degradation of SMAD7 in an autolysosome-dependent manner. The corresponding increase in p-SMAD2/3 level and TGFβ pathway activation finally induced EMT in cell lines and primary glioblastoma cells. Moreover, HERC3 overexpression was observed in pseudo-palisade cells surrounding tumor necrosis and in tumor-adjacent tissue; high HERC3 and low SMAD7 levels predicted poor clinical outcome in glioblastoma; xenograft of nude mice and in vitro experiments confirmed these findings. Conclusions: Together, our findings reveal the indispensable role of HERC3 in regulating canonical SMAD2/3-dependent TGFβ pathway involvement in autophagy-induced EMT, providing insights toward a better understanding of the mechanism of resistance to temozolomide and peripheral recurrence of glioblastoma.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".