Data from Targeting CHAF1B Enhances IFN Activity against Myeloproliferative Neoplasm Cells
Bibliographic record
Abstract
Interferons (IFNs) are cytokines with potent antineoplastic and antiviral properties. IFNα has significant clinical activity in the treatment of myeloproliferative neoplasms (MPN), but the precise mechanisms by which it acts are not well understood. Here, we demonstrate that chromatin assembly factor 1 subunit B (CHAF1B), an Unc-51-like kinase 1 (ULK1)-interactive protein in the nuclear compartment of malignant cells, is overexpressed in patients with MPN. Remarkably, targeted silencing of CHAF1B enhances transcription of IFNα-stimulated genes and promotes IFNα-dependent antineoplastic responses in primary MPN progenitor cells. Taken together, our findings indicate that CHAF1B is a promising newly identified therapeutic target in MPN and that CHAF1B inhibition in combination with IFNα therapy might offer a novel strategy for treating patients with MPN. Significance: Our findings raise the potential for clinical development of drugs targeting CHAF1B to enhance IFN antitumor responses in the treatment of patients with MPN and should have important clinical translational implications for the treatment of MPN and possibly in other malignancies.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".