The therapeutic hope for HDAC6 inhibitors in malignancy and chronic disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.003 | 0.002 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it