Evidence map›Paper›PMID 38213901›Full record

ArticleComputational and structural biotechnology journal2023

Comprehensive exploration of JQ1 and GSK2801 targets in breast cancer using network pharmacology and molecular modeling approaches.

Nanda Kumar Yellapu, Dong Pei, Emily Nissen, Jeffrey A Thompson, Devin C Koestler

Open access · goldAbstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2023. 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 48% 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, 1 citations in OpenAlex.

  1. Elucidating the Multi-Target Anti-Pruritic Mechanism ofCurrent issues in molecular biology · 2026
    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

5 authors at 1 institution in 1 country.

Nanda Kumar YellapuDepartment of Biostatistics & Data Science, University of Kansas, Medical Center, Kansas City, KS, USA.
Dong PeiDepartment of Biostatistics & Data Science, University of Kansas, Medical Center, Kansas City, KS, USA.
Emily NissenDepartment of Biostatistics & Data Science, University of Kansas, Medical Center, Kansas City, KS, USA.
Jeffrey A ThompsonDepartment of Biostatistics & Data Science, University of Kansas, Medical Center, Kansas City, KS, USA.
Devin C KoestlerDepartment of Biostatistics & Data Science, University of Kansas, Medical Center, Kansas City, KS, USA.
University of Kansas Medical Center · US

Funding

Using Integrated Omics to Identify Dysfunctional Genetic Mechanisms Influencing Schizophrenia and Sleep DisturbancesP20GM130423 · NIGMS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI Diane E Mahoney · 2019 to 2026
$21.5M
NIGMS NIH HHS P20 GM130423
6 · The paper itself

Abstract

JQ1 and GSK2801 are bromo domain inhibitors (BDI) known to exhibit enhanced anti-cancer activity when combined with other agents. However, the underlying molecular mechanisms behind such enhanced activity remain unclear. We used network-pharmacology approaches to understand the shared molecular mechanisms behind the enhanced activity of JQ1 and GSK2801 when used together to treat breast cancer (BC). The gene targets of JQ1 and GSK2801 were intersected with known BC-targets and their putative targets against BC were derived. The key genes were explored through gene-ontology-enrichment, Protein-Protein-Interaction (PPI) networking, survival analysis, and molecular modeling simulations. The genes, CTSB, MAPK14, MET, PSEN2 and STAT3, were found to be common targets for both drugs. In total, 49 biological processes, five molecular functions and 61 metabolic pathways were similarly enriched for JQ1 and GSK2801 BC targets among which several terms are related to cancer: IL-17, TNF and JAK-STAT signaling pathways. Survival analyses revealed that all five putative synergistic targets are significantly associated with survival in BC (log-rank

Indexed as

Breast cancerDrug targetsNetwork pharmacologyProtein-Protein Interaction network maps

Identifiers

PMID38213901
PMCPMC10781883
OpenAlexW4379259448

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.