Complement component 1, q subcomponent binding protein (C1QBP) in lipid rafts mediates hepatic metastasis of pancreatic cancer by regulating IGF‐1/IGF‐1R signaling
Bibliographic record
Abstract
Pancreatic cancer shows a remarkable predilection for hepatic metastasis. Complement component 1, q subcomponent binding protein (C1QBP) can mediate growth factor-induced cancer cell chemotaxis and distant metastasis by activation of receptor tyrosine kinases. Coincidentally, insulin-like growth factor-1 (IGF-1) derived from the liver and cancer cells itself has been recognized as a critical inducer of hepatic metastasis. However, the mechanism underlying IGF-1-dependent hepatic metastasis of pancreatic cancer, in which C1QBP may be involved, remains unknown. In the study, we demonstrated a significant association between C1QBP expression and hepatic metastasis in patients with pancreatic cancer. IGF-1 induced the translocation of C1QBP from cytoplasm to lipid rafts and further drove the formation of CD44 variant 6 (CD44v6)/C1QBP complex in pancreatic cancer cells. C1QBP interacting with CD44v6 in lipid rafts promoted phosphorylation of IGF-1R and thus activated downstream PI3K and MAPK signaling pathways which mediated metastatic potential of pancreatic cancer cells including proliferation, apoptosis, invasion, adhesion and energy metabolism. Furthermore, C1QBP knockdown suppressed hepatic metastasis of pancreatic cancer cells in nude mice. We therefore conclude that C1QBP in lipid rafts serves a key regulator of IGF-1/IGF-1R-induced hepatic metastasis from pancreatic cancer. Our findings about C1QBP in lipid rafts provide a novel strategy to block IGF-1/IGF-1R signaling in pancreatic cancer and a reliable premise for more efficient combined modality therapies.
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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".