Evidence map›Paper›PMID 36175584›Full record

ArticleMedical oncology (Northwood, London, England)2022

Expression patterns and therapeutic implications of histone deacetylase-1 across carcinomas: a comprehensive molecular docking and MD simulation study.

Bader Alshehri

Abstract read
PubMed Publisher
In one paragraph

Article in Medical oncology (Northwood, London, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 52% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Bader AlshehriDepartment of Medical Laboratory Sciences, College of Applied Medical Sciences, Majmaah University, Almajmaah, 11952, Kingdom of Saudi Arabia. b.alshehri@mu.edu.sa.ORCID http://orcid.org/0000-0002-4933-1711
Majmaah University · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Histone deacetylases (HDACs) are a group of enzymes that control the expression of genes by deacetylating lysine residues on histone and nonhistone proteins. They control the expression of several proteins linked to the development and spread of cancer. Deregulation of HDAC1 has been reported across several tumors, and targeting HDAC1 with specific inhibitors has demonstrated a promising therapeutic strategy. Mocetinostat, an HDAC1 inhibitor, is yielding promising results both in vitro and in vivo studies. However, toxicities associated with Mocetinostat limit its therapeutic efficacy, so there is an urgent need to investigate novel HDAC1 inhibitors. The present study aimed to explore novel HDAC1 inhibitors and investigate the expression profile, and the prognostic and diagnostic significance of HDAC1 across pan-cancers. HDAC1 was found overexpressed across several tumors and its high expression signifies worse OS and RFS. Also, the study identified two novel HDAC1 inhibitors using an in-silico approach with high binding affinity for HDAC1 compared to Mocetinostat and formed significantly stable complexes. In conclusion, the study signifies that targeting HDAC1 is a promising therapeutic strategy, and exploring novel therapeutic agents through basic, translational design may lead to their ultimate use in cancer prevention.

Indexed as

CarcinomaHistonesBenzamidesHistone DeacetylasesHumansLysineMolecular Docking SimulationPyrimidinesBenzamidesHistone DeacetylasesHistonesLysinemocetinostatPyrimidinesCancerDrug analogsEpigeneticsHDAC1MD simulationMocetinostatMolecular docking

Identifiers

PMID36175584
OpenAlexW4297954566

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.