The therapeutic hope for HDAC6 inhibitors in malignancy and chronic disease
Bibliographic record
Abstract
Recent years have witnessed an emergence of a new class of therapeutic agents, termed histone deacetylase 6 (HDAC6) inhibitors. HDAC6 is one isoform of a family of HDAC enzymes that catalyse the removal of functional acetyl groups from proteins. It stands out from its cousins in almost exclusively deacetylating cytoplasmic proteins, in exerting deacetylation-independent effects and in the success that has been achieved in developing relatively isoform-specific inhibitors of its enzymatic action that have reached clinical trial. HDAC6 plays a pivotal role in the removal of misfolded proteins and it is this role that has been most successfully targeted to date. HDAC6 inhibitors are being investigated for use in combination with proteasome inhibitors for the treatment of lymphoid malignancies, whereby HDAC6-dependent protein disposal currently limits the cytotoxic effectiveness of the latter. Similarly, numerous recent studies have linked altered HDAC6 activity to the pathogenesis of neurodegenerative diseases that are characterized by misfolded protein accumulation. It seems likely though that the function of HDAC6 is not limited to malignancy and neurodegeneration, the deacetylase being implicated in a number of other cellular processes and diseases including in cardiovascular disease, inflammation, renal fibrosis and cystogenesis. Here, we review the unique features of HDAC6 that make it so appealing as a drug target and its currently understood role in health and disease. Whether HDAC6 inhibition will ultimately find a clinical niche in the treatment of malignancy or prevalent complex chronic diseases remains to be determined.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".