Immunohistochemical analysis of changes in signaling pathway activation downstream of growth factor receptors in pancreatic duct cell carcinogenesis
Bibliographic record
Abstract
BACKGROUND: The pathogenesis of pancreatic ductal adenocarcinoma (PDAC) involves multi-stage development of molecular aberrations affecting signaling pathways that regulate cancer growth and progression. This study was performed to gain a better understanding of the abnormal signaling that occurs in PDAC compared with normal duct epithelia. METHODS: We performed immunohistochemistry on a tissue microarray of 26 PDAC, 13 normal appearing adjacent pancreatic ductal epithelia, and 12 normal non-PDAC ducts. We compared the levels of 18 signaling proteins including growth factor receptors, tumor suppressors and 13 of their putative downstream phosphorylated (p-) signal transducers in PDAC to those in normal ductal epithelia. RESULTS: The overall profiles of signaling protein expression levels, activation states and sub-cellular distribution in PDAC cells were distinguishable from non-neoplastic ductal epithelia. The ERK pathway activation was correlated with high levels of S2448p-mTOR (100%, p = 0.05), T389p-S6K (100%, p = 0.02 and S235/236p-S6 (86%, p = 0.005). Additionally, T389p-S6K correlated with S727p-STAT3 (86%, p = 0.005). Advanced tumors with lymph node metastasis were characterized by high levels of S276p-NFkappaB (100%, p = 0.05) and S9p-GSK3beta (100%, p = 0.05). High levels of PKBbeta/AKT2, EGFR, as well as nuclear T202/Y204p-ERK and T180/Y182p-p38 were observed in normal ducts adjacent to PDAC compared with non-cancerous pancreas. CONCLUSION: Multiple signaling proteins are activated in pancreatic duct cell carcinogenesis including those associated with the ERK, PKB/AKT, mTOR and STAT3 pathways. The ERK pathway activation appears also increased in duct epithelia adjacent to carcinoma, suggesting tumor micro-environmental effects.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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 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".