cIAP2 promotes gallbladder cancer invasion and lymphangiogenesis by activating the NF‐κB pathway
Bibliographic record
Abstract
Several studies have produced contradictory findings about the prognostic implications for inhibitor of apoptosis proteins (IAP) in different types of cancer. Cellular inhibitor of apoptosis 2 (cIAP2/BIRC) is one of the most extensively characterized human IAP. To date, no studies have focused on the expression level of cIAP2 in human gallbladder cancer (GBC), and the mechanism of cIAP2 in GBC invasion and lymphangiogenesis remains unclear. Therefore, in the present study, cIAP2 expression in GBC was detected using quantitative real-time polymerase chain reaction and immunohistochemistry, and the relationship between cIAP2 levels in cancer tissues and the clinicopathological characteristics of patients was analyzed. The biological effect of cIAP2 in GBC cells was tested using the Cell Counting Kit-8 Assay, Transwell assays and the ability of human dermal lymphatic endothelial cells (HDLEC) to undergo tube formation. The role of cIAP2 in activating the NF-κB pathway was determined using a dual-luciferase reporter assay, immunofluorescence staining, western blotting and ELISA. Finally, an animal model was used to further confirm the role of cIAP2 in lymphangiogenesis. We showed that cIAP2 expression was elevated in human GBC tissues and correlated with a negative prognosis for patients. Moreover, cIAP2 was identified as a lymphangiogenic factor of GBC cells and, thus, promoted lymph node metastasis in GBC cells. Our study is the first to suggest that cIAP2 can promote GBC invasion and lymphangiogenesis by activating the NF-κB pathway.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
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".