Liver x receptor alpha drives chemoresistance in response to side-chain hydroxycholesterols in triple negative breast cancer
Bibliographic record
Abstract
Abstract Triple negative breast cancer (TNBC) is challenging to treat successfully because targeted therapies do not exist. Instead, systemic therapy is typically restricted to cytotoxic chemotherapy, which fails more often in patients with elevated circulating cholesterol. Liver x receptors are ligand-dependent transcription factors that are homeostatic regulators of cholesterol, and are linked to regulation of broad-affinity xenobiotic transporter activity in non-tumor tissues. We show that LXR ligands confer chemotherapy resistance in TNBC cell lines and xenografts, and that LXRalpha is necessary and sufficient to mediate this resistance. Furthermore, in TNBC patients who had cancer recurrences, LXRalpha and ligands were independent markers of poor prognosis and correlated with P-glycoprotein expression. However, in patients who survived their disease, LXRalpha signaling and P-glycoprotein were decoupled. These data reveal a novel chemotherapy resistance mechanism in this poor prognosis subtype of breast cancer. We conclude that systemic chemotherapy failure in some TNBC patients is caused by co-opting the LXRalpha:P-glycoprotein axis, a pathway highly targetable by therapies that are already used for prevention and treatment of other diseases.
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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".