Abstract 4087: Epithelial to mesenchymal transition in the metastatic progression of gastroenteropancreatic neuroendocrine tumors
Bibliographic record
Abstract
Abstract Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are malignant epithelial cancer arising from the diffuse neuroendocrine system. Diagnosis is usually made late in the disease course, with 60-80% of diagnosed cases presenting with, or developing metastatic disease. The lack of biomarkers indicative of aggressive behavior, in particular metastasis, hinders prognosis and proper treatment of GEP-NETs. A cellular process underlying the aggressive behavior of cancer is epithelial to mesenchymal transition (EMT). In this study, we aimed to determine whether EMT is involved in the pathogenesis of NETs. Using tissue samples from NETs arising from small intestine (SI-NET), pancreas (P-NETs), and colorectum (C-NETs), we have examined EMT and profiled the signaling mechanisms involved. Initial studies utilizing targeted real-time PCR-based gene profiling comparing primary (n = 9) and metastatic (n = 4) SI-NETs relative to control (normal small bowel epithelium, n = 3) revealed gene expression profiles suggestive of EMT and cell guidance in both primary and metastatic tumors, including elevation of vascular endothelial growth factor signaling, changes in matrix remodeling genes, and abundant transforming growth factor-β (TGF-β) receptor 1. A more comprehensive examination of the EMT phenotype was then undertaken based on primary site of origin. RNA samples from P-NETs (n = 9), SI-NETs (n = 8), and C-NETs (n = 8) were used for gene expression studies utilizing an EMT-focused PCR array. Changes in gene expression profiles consistent with an EMT phenotype were seen across all primary sites, including elevated expression of transcription factors SMAD2, ZEB1/2, HIF-1α. Differential expression of TGF-β family receptor ligands, including TGF-β1 and BMP2, was observed when comparing results from NETs of different primary sites, suggesting alternate signaling pathways leading to EMT. Confirmatory immunohistochemistry studies were then carried out, demonstrating an EMT phenotype as evidenced by loss of E-cadherin/β-catenin expression and/or vimentin induction in 42% of cases (n = 52). Well-differentiated GEP-NETs, while morphologically similar, are extremely heterogeneous in both clinical presentation and outcome. We have examined a series of 52 GEP-NETs, of which 77% either presented with, or eventually developed metastatic disease. EMT is likely a key process by which this occurs, as we observe expression changes in EMT-associated genes across all subtypes of GEP-NETs, and an EMT phenotype by immunohistochemistry in 42% of the tumors. Our gene expression studies suggest that differential TGF-β family signaling is a key mediator in driving EMT, however, the specific pathway may involve different factors depending on the site of NET origin. Future studies are needed to elucidate the exact pathways involved in this process. Citation Format: Stephanie Mok, Zia A. Khan, Douglas Quan, Christopher J. Howlett. Epithelial to mesenchymal transition in the metastatic progression of gastroenteropancreatic neuroendocrine tumors. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4087. doi:10.1158/1538-7445.AM2015-4087
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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) | 0.002 | 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".