Androgens act synergistically to enhance estrogen‐induced upregulation of human tissue kallikreins 10, 11, and 14 in breast cancer cells via a membrane bound androgen receptor
Bibliographic record
Abstract
The regulation of gene expression by steroid hormones plays an important role in the normal development and function of many organs, as well as in the pathogenesis of endocrine-related cancers, especially breast cancer. However, clinical data suggest that combined testosterone and estrogen treatments on post-menopausal women increase the risk of breast cancer. Experiments have shown that many, if not all kallikreins are under steroid hormone regulation in breast cancer cell lines. Their implication as prognostic and diagnostic markers has also been well-documented. Thus, we investigated the effect of combined hormone stimulation with androgens and 17beta-estradiol on the ductal caricinoma cell line BT474. This cell line has been shown to be sensitive to both, androgens (secreting PSA) and estrogens (secreting a number of kallikreins including KLK10, 11, and KLK14). We found that PSA expression was downregulated upon combined hormone stimulation, confirming reports that estrogen can antagonize and block the activity of the androgen receptor. Upon analysis of estrogen-sensitive kallikreins 10, 11, and 14, all showed to be synergistically enhanced in their expression three- to fourfold, upon joint hormone treatment versus individual hormone stimulation. The enhancement is dependent upon the action of androgens as treatment with the androgen receptor antagonist cyproterone actetate normalized the expression of KLK10, 11, and KLK14 to estrogen-stimulation levels. The synergistic effects between estrogens and androgens on estrogen-sensitive genes may have implications on the role of the kallikreins in associated risk of breast cancer and progression.
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) | 0.001 | 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".