Abstract 4309: Establishment of the chick chorioallantoic membrane (CAM) as an ex vivo model system to study mechanisms underlying epithelial ovarian tumour growth and metastasis
Bibliographic record
Abstract
Abstract Epithelial ovarian cancer (EOC) accounts for approximately 90% of all human ovarian malignancies. Unfortunately, 75% of EOC cases are not diagnosed until advanced stages when the tumour has metastasized, after which standard therapy is less effective. Therefore, it remains vital to directly study the molecular and cellular mechanisms contributing to EOC metastasis in an experimentally-tractable system. The chick chorioallantoic membrane (CAM) is a highly-vascularized tissue responsible for gas and nutrient exchange in the avian embryo, and has been used extensively to study angiogenesis and tumour formation by highly-aggressive cancer cell lines. Herein, we report that ascites-derived primary human EOC cells and established EOC cell lines readily form well-vascularized tumours on the chick CAM. To investigate this property further, we have generated GFP-expressing clones from the mouse ovarian tumour cell lines MOSE-RM (oncogenic Ras & Myc overexpression, SV40 TAg), MASC-2 (SV40 TAg), and 4306 (oncogenic Kras & Pten-null) which will facilitate visualization of tumour growth on the CAM as well as complementary studies in syngeneic mouse models for future studies. Xenografts of MOSE-RM and 4306 cell lines onto the surface of the chick CAM establish tumours that are significantly larger in mass and size compared with MASC-2 cells. Importantly, EOC tumours grown on the chick CAM are histologically identical to those arising within the peritoneal cavity. MOSE-RM and 4306 cell lines promote angiogenesis using HUVEC cells and the chick CAM, whereas MASC-2 cells lack this ability. Overall, these results demonstrate that EOC tumour growth on the chick CAM can be exploited as a highly amenable model system for studying late-stage EOC metastasis. Our findings also indicate that neo-vascularization is an obligatory process for establishment of secondary tumours; thus, we are currently investigating signaling pathways that impact primary human EOC tumour growth and angiogenesis using the chick CAM. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4309. doi:10.1158/1538-7445.AM2011-4309
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".