The Transcoelomic Ecosystem and Epithelial Ovarian Cancer Dissemination
Bibliographic record
Abstract
Epithelial ovarian cancer (EOC) is considered the deadliest gynecological disease and is normally diagnosed at late stages, at which point metastasis has already occurred. Throughout disease progression, EOC will encounter various ecosystems and the communication between cancer cells and these microenvironments will promote the survival and dissemination of EOC. The primary tumor is thought to develop within the ovaries or the fallopian tubes, both of which provide a microenvironment with high risk of causing DNA damage and enhanced proliferation. EOC disseminates by direct extension from the primary tumors, as single cells or multicellular aggregates. Under the influence of cellular and non-cellular factors, EOC spheroids use the natural flow of peritoneal fluid to reach distant organs within the peritoneal cavity. These cells can then implant and seed distant organs or tissues, which develop rapidly into secondary tumor nodules. The peritoneal tissue and the omentum are two common sites of EOC metastasis, providing a microenvironment that supports EOC invasion and survival. Current treatment for EOC involves debulking surgery followed by platinum-taxane combination chemotherapy; however, most patients will relapse with a chemoresistant disease with tumors developed within the peritoneum. Therefore, understanding the role of the unique microenvironments that promote EOC transcoelomic dissemination is important in improving patient outcomes from this disease. In this review article, we address the process of ovarian cancer cellular fate at the site of its origin in the secretory cells of the fallopian tube or in the ovarian surface epithelial cells, their detachment process, how the cells survive in the peritoneal fluid avoiding cell death triggers, and how cancer- associated cells help them in the process. Finally, we report the mechanisms used by the ovarian cancer cells to adhere and migrate through the mesothelial monolayer lining the peritoneum. We also discuss the involvement of the transcoelomic ecosystem on the development of chemoresistance of EOC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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".