Tetraspanin-29 activates Notch signaling by interacting with ADAM10 to enhance its activity in colorectal cancer
Bibliographic record
Abstract
ADAM10 acts upstream of Notch signaling and plays oncogenic roles in various cancers. Tetraspanin family proteins regulate ADAM10 trafficking and activity. Here, we aimed to investigate whether and how tetraspanin-29 modulates ADAM10 in colorectal cancer (CRC). We found that ADAM10 expression was upregulated in CRC tissues and this was cross-validated in the TCGA COAD data set. The ADAM10 protein level and its α-secretase activity were enhanced in CRC cell lines compared with control cell lines. Co-immunoprecipitation showed ADAM10 interacted with tetraspanin-29 in the LoVo cell line. Tetraspanin-29 knockdown reduced the cell surface trafficking and α-secretase activity of ADAM10. In addition, tetraspanin-29 knockdown inhibited Notch activity in a luciferase reporter assay and reduced the levels of cleaved Notch1 and Notch target genes such as HES2, c-MYC, and cyclin D3. Consistently, tetraspanin-29 overexpression increased cleaved Notch1 and this effect was blocked by ADAM10 inhibitors. The TCGA COAD data set confirmed the positive correlations of tetraspanin-29 with HES2, c-MYC, and cyclin D3. Thus, the tetraspanin-29/ADAM10/Notch pathway plays an important role in CRC.
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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 | 0.000 |
| 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 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".