LRH-1 Governs Vital Transcriptional Programs in Endocrine-Sensitive and -Resistant Breast Cancer Cells
Bibliographic record
Abstract
Tumor characteristics are decisive in the determination of treatment strategy for patients with breast cancer. Patients with estrogen receptor α (ERα)-positive breast cancer can benefit from long-term hormonal treatment. Nonetheless, the majority of patients will develop resistance to these therapies. Here, we investigated the role of the nuclear receptor liver receptor homolog-1 (LRH-1, NR5A2) in antiestrogen-sensitive and -resistant breast cancer cells. We identified genome-wide LRH-1-binding sites using ChIP-seq (chromatin immunoprecipitation sequencing), uncovering preferential binding to regions distal to transcriptional start sites. We further characterized these LRH-1-binding sites by integrating overlapping layers of specific chromatin marks, revealing that many LRH-1-binding sites are active and could be involved in long-range enhancer-promoter looping. Combined with transcriptome analysis of LRH-1-depleted cells, these results show that LRH-1 regulates specific subsets of genes involved in cell proliferation in antiestrogen-sensitive and antiestrogen-resistant breast cancer cells. Furthermore, the LRH-1 transcriptional program is highly associated with a signature of poor outcome and high-grade breast cancer tumors in vivo. Herein, we report the genome-wide location and molecular function of LRH-1 in breast cancer cells and reveal its therapeutic potential for the treatment of breast cancers, notably for tumors resistant to treatments currently used in therapies.
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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 | 0.001 | 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 | 0.001 |
| 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 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".