Cyr61, a Member of the CCN Family, Is Required for MCF-7 Cell Proliferation: Regulation by 17β-Estradiol and Overexpression in Human Breast Cancer
Bibliographic record
Abstract
Cyr61, a member of the CCN (CTGF/Cyr61/NOV) family of growth regulators, is a secreted cysteine-rich proangiogenic factor that has been implicated in tumorigenesis. Previous studies have also demonstrated that Cyr61 is regulated by 17beta-estradiol (E(2)) in the uterus. Therefore, we hypothesized that hormonal regulation of Cyr61 may be important in estrogen-dependent pathogenic processes such as breast tumorigenesis. Our study demonstrates that both Cyr61 messenger RNA and protein are induced by E(2) in MCF-7 mammary adenocarcinoma cells that primarily overexpress estrogen receptor alpha (ERalpha) in a dose-dependent and immediate early fashion. Cyr61 gene induction by E(2) is transcriptionally regulated by ERalpha as the antiestrogen, ICI 182,780, and actinomycin D blocked induction completely. In addition, Cyr61 is up-regulated in MCF-7 cells by epidermal growth factor (EGF) in an immediate early fashion as well. The functional relevance of steroid induction of Cyr61 in breast cancer cell growth is demonstrated by anti-Cyr61 neutralizing antibodies, which diminished E(2) and EGF-dependent DNA synthesis and dramatically reduced E(2)-driven cell proliferation by more than 70%. Most importantly, Cyr61 is overexpressed in 70% (28 of 40) of breast cancer patients with infiltrating ductal carcinoma and is localized exclusively to hyperplastic ductal epithelial cells. Moreover, the levels of Cyr61 protein are higher in breast tumors that are ER(+)/EGF receptor(+) than those that are ER(-)/EGF receptor(+), suggesting that estrogens may mediate Cyr61 expression in vivo. Collectively, our data suggest that Cyr61 may play a critical role in estrogen- as well as growth factor-dependent breast tumor growth.
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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 | 0.001 |
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".