The Angiogenic Secretome in VEGF overexpressing Breast Cancer Xenografts
Bibliographic record
Abstract
The plasticity of cancer cells and the fluidity of the tumor microenvironment continue to present major challenges in the comprehensive understanding of cancer that is essential to design effective treatments. The tumor interstitial fluid (TIF) encompasses the secretome and holds the key to several of the phenotypic characteristics of cancer. Difficulties in sampling this fluid have resulted in limited characterization of its components. Here we have sampled TIF from triple negative and estrogen receptor (ER)-positive human breast tumor xenografts with or without VEGF overexpression. Angiogenesis-related factors were characterized in the TIF and plasma, to understand the relationship between the TIF and plasma secretomes. Clear differences were observed between the TIF and plasma angiogenic secretomes in triple negative MDA-MB-231 breast cancer xenografts compared to ER-positive MCF-7 xenografts with or without VEGF overexpression that provide new insights into TIF components and the role of VEGF in modifying the angiogenic secretome.
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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) | 0.000 | 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 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".