Tamoxifen reduces mitochondrial respiration, oncogenic signaling and mutant allele burden in a myeloproliferative neoplasm subset
Bibliographic record
Abstract
Abstract Current therapies for myeloproliferative neoplasms (MPN) improve symptoms but have limited effect on tumor size. In preclinical studies, tamoxifen restored normal apoptosis in mutated hematopoietic stem and progenitor cells (HSPCs). TAMARIN is a Phase-II, multicenter, single-arm clinical trial assessing tamoxifen’s safety and activity in patients with stable MPNs, no prior thrombotic events and mutated JAK2V617F, CALRins5 or CALRdel52 peripheral blood allele burden ≥20%. The primary outcome (≥50% allele burden reduction at 24 weeks) was met by 3/38 patients; 5/38 additional patients showed ≥25% reductions. Tamoxifen was well tolerated. Baseline analysis of HSPC transcriptome segregated responders and non-responders, suggesting a predictive signature. In responder HSPCs, longitudinal analysis showed high baseline expression of JAK-STAT signaling and oxidative phosphorylation genes, which were downregulated by tamoxifen. In JAK2V617F+ cells, 4-hydroxytamoxifen inhibited mitochondrial complex-I, activating proapoptotic integrated stress response (ISR) and decreasing pathogenic JAK2 signaling. Therefore, tamoxifen inhibits mitochondrial respiration, modulates ISR and suppresses pathogenic JAK-STAT signaling in a subset of prospectively identifiable MPN patients.
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 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 | 0.000 |
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 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".