The impact of the ovarian microenvironment on the anti-tumor effect of SPARC on ovarian cancer<sup>1</sup>This article is part of Special Issue entitled Asilomar Chromatin and has undergone the Journal’s usual peer review process.
Bibliographic record
Abstract
A lack of host-derived SPARC promotes disease progression in an intraperitoneal (IP) ID8 mouse model of epithelial ovarian cancer (EOC). Since orthotopic injection (OT) of ID8 cells better recapitulates high-grade serous cancer, we examined the impact of host-derived SPARC following OT injection. Sparc(-/-) and wild-type (WT) mice were injected with ID8 cells either OT or IP and tumors were analyzed at the moribund stage. Sparc(-/-) mice had reduced survival and fewer well-defined abdominal lesions compared with WT controls after IP injection, whereas no differences were observed in survival or abdominal lesions between Sparc(-/-) and WT mice after OT injection. No differences in mass or collagen content were observed in ovarian tumors between OT-injected Sparc(-/-) and WT mice. The abdominal wall of the IP-injected Sparc(-/-) mice exhibited immature and less abundant collagen fibrils compared with WT mice both in injected and non-injected controls. In contrast to human EOC, SPARC was expressed by the tumor cells but was absent in reactive stroma of WT mice. Exposure to the ovarian microenvironment through OT injections alters the metastatic behaviour of ID8 cells, which is not affected by the absence of host-derived SPARC.
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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".