Abstract 409: The influence of chronic low grade systemic inflammation on the progression of epithelial ovarian cancer
Bibliographic record
Abstract
Abstract It is established that inflammation can create a protumorigenic environment. Many sources of chronic inflammation, including viral and bacterial, have been associated with accelerated tumorigenesis. An epidemiological link has been discovered between chronic inflammatory diseases and ovarian cancer suggesting that inflammation can increase the risk of epithelial ovarian cancer (EOC) potentially by synergizing with the local ovarian inflammation associated with ovulation. The purpose of this study is to identify the impact of prolonged exposure to chronic low-grade inflammation on epithelial ovarian cancer cell viability in vitro and EOC tumor progression in vivo. We hypothesize that this level of systemic inflammation will enhance the growth and survival of epithelial ovarian tumors by increasing angiogenesis, cell survival and metastatic capability. We believe these effects will occur in part due to the interactions between the malignant ovarian surface epithelial cells and the various immune cells recruited to the stromal microenvironment of the tumor. The first objective to examine these relationships was to determine the effect of a proinflammatory environment in an in vitro model using normal ovarian surface epithelium (NOSE) and transformed human ovarian epithelial cell lines CAOV-3, ES-2, OVCAR-3 and SKOV-3. Cells were exposed to proinflammatory cytokines interleukin (IL)-1β, IL-6 and tumor necrosis factor (TNF)-α and in response to this exposure, the ovarian cancer cells showed enhanced viability and proliferation. The next objective involves examining the influence of the epithelial-stromal interactions of tumor cells by utilizing a co-culture model to initiate communication between the human epithelial cell lines in objective one with a differentiated macrophage cell line. In additional trials with transformed murine epithelial and microvascular cell lines we have identified the expression of Toll-like receptor 4 (TLR4) using reverse transcription-PCR. TLR4 is the receptor through which the bacterial endotoxin lipopolysaccharide (LPS) acts as an inflammatory agent. Based on these preliminary results, we propose to evaluate the role of chronic inflammation in the progression of EOC in an established mouse model using LPS to induce a low-grade level of chronic inflammation. Analysis of tumor cell survival, angiogenesis, and local and systemic inflammation will be evaluated western blot, PCR, ELISA assay and immunofluorescence. Evaluation of the relationship between chronic, systemic inflammation and the progression of EOC may be useful in developing treatment approaches for EOC, specifically in terms of anti-inflammatory therapies, and could provide insight into the role of inflammation in the progression of other human cancers. 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 409. doi:10.1158/1538-7445.AM2011-409
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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) | 0.003 | 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".