The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Different Regions in Activation Function-1 of the Human Estrogen Receptor Required for Antiestrogen- and Estradiol-dependent Transcription Activation
Open accessAbstract
The human estrogen receptor (ER) is a ligand-inducible transcription factor that contains two transcriptional activation functions, one located in the NH2-terminal region of the protein (AF-1) and the second in the COOH-terminal region (AF-2). Antiestrogens, such as trans-hydroxytamoxifen (TOT), have partial agonistic activity in certain cell types, and studies have implied that this agonism is AF-1-dependent. We have made progressive NH2-terminal and other segment deletions and ligations in the A/B domain, and studied the transcriptional activity of these mutant ERs in ER-negative MDA-MB-231 human breast cancer and HEC-1 human endometrial cancer cells. Using several estrogens and several partial agonist/antagonist antiestrogens, we find that estrogens and antiestrogens require different regions of AF-1 for transcriptional activation. Deletion of the first 40 amino acids has no effect on receptor activity. Antiestrogen agonism is lost upon deletion to amino acid 87, while estrogen agonism is not lost until deletions progress to amino acid 109. Antiestrogen agonism has been further defined to require amino acids 41-64, as deletion of only these amino acids results in an ER that exhibits 100% activity with E2, but no longer shows an agonist response to TOT. With A/B-modified receptors in which antiestrogens lose their agonistic activity, the antiestrogens then function as pure estrogen antagonists. Our studies show that in these cellular contexts, hormone-dependent transcription utilizes a range of the amino acid sequence within the A/B domain. Furthermore, the agonist/antagonist balance and activity of antiestrogens such as TOT are determined by specific sequences within the A/B domain and thus may be influenced by differences in levels of specific factors that interact with these regions of the ER.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The nuclear receptor superfamily: the second decade
Mangelsdorf, D. J., Thummel, C., Beato, M., Herrlich, P., Schütz, G., Umesono, K., Blumberg, B., Kastner, P., Mark, M., Chambon, P., et al. (1995) · Cell · doi:10.1016/0092-8674(95)90199-x · Cited by 6,964
Cited by
Molecular basis of agonism and antagonism in the oestrogen receptor
Brzozowski, A. M., Pike, A. C. W., Dauter, Z., Hubbard, R. E., Bonn, T., Engström, O., Öhman, L., Greene, G. L., Gustafsson, J.-Å., & Carlquist, M. (1997) · Nature · doi:10.1038/39645 · Cited by 3,355
Overview of nomenclature of nuclear receptors
Germain, P., Staels, B., Dacquet, C., Spedding, M., & Laudet, V. (2006) · Pharmacological Reviews · doi:10.1124/pr.58.4.2 · Cited by 688
Meyers, M. J., Sun, J., Carlson, K. E., Marriner, G. A., Katzenellenbogen, B. S., & Katzenellenbogen, J. A. (2001) · Journal of Medicinal Chemistry · doi:10.1021/jm010254a · Cited by 678
Self-citationDiverse signaling pathways modulate nuclear receptor recruitment of N-CoR and SMRT complexes.
Lavinsky, R. M., Jepsen, K., Heinzel, T., Torchia, J., Mullen, T.-M., Schiff, R., Del-Rio, A. L., Ricote, M., Ngo, S., Gemsch, J., et al. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.6.2920 · Cited by 660
Patel, H. K., & Bihani, T. (2018) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2017.12.012 · Cited by 499
Metadata
- Authors
- McInerney, E. M., & Katzenellenbogen, B. S.
- Venue
- Journal of Biological Chemistry
- Publisher
- Elsevier BV
- Published
- 1996-09
- Volume
- 271
- Issue
- 39
- Pages
- 24172-24178
- ISSN
- 0021-9258 (ISSN-L)
- OpenAlex
- W1980040001
- Cited by
- 222
- References
- 1
- FWCI
- 7.42
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Different Regions in Activation Function-1 of the Human Estrogen Receptor Required for Antiestrogen- and Estradiol-dependent Transcription Activation. https://app.cochat.ai/papers/10.1074/jbc.271.39.24172
- The paper
- McInerney, E. M., & Katzenellenbogen, B. S. (1996). Different Regions in Activation Function-1 of the Human Estrogen Receptor Required for Antiestrogen- and Estradiol-dependent Transcription Activation. Journal of Biological Chemistry. https://doi.org/10.1074/jbc.271.39.24172
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.