Evidence map›Paper›PMID 30297806›Full record

ArticleScientific reports2018

LINCS L1000 dataset-based repositioning of CGP-60474 as a highly potent anti-endotoxemic agent.

Hyun-Wook Han, Soojung Hahn, Hye Yun Jeong, Joo-Hyun Jee, Myoung-Ok Nam, Han Kyung Kim, Dong Hyeon Lee, So-Young Lee, Dong Kyu Choi, Ji Hoon Yu and 2 more

Abstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–field-weighted citation impact
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

23 citing papers in PubMed.

  1. Article
  2. Single-cell analysis reveals neuroprotective histone deacetylase inhibitor pathways.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
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  17. Topological network measures for drug repositioning.Briefings in bioinformatics · 2021
    Article
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  20. Review
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

12 authors.

Hyun-Wook HanDepartment of Medical Informatics, CHA University, Seongnam-si, Gyeonggi-do, South Korea.
Soojung HahnDepartment of Microbiology, CHA University, Seongnam-si, Gyeonggi-do, South Korea.
Hye Yun JeongOrganoid Research Center, School of Medicine, CHA University, Seongnam-si, Gyeonggi-do, South Korea.
Joo-Hyun JeeDepartment of Microbiology, CHA University, Seongnam-si, Gyeonggi-do, South Korea.
Myoung-Ok NamDepartment of Microbiology, CHA University, Seongnam-si, Gyeonggi-do, South Korea.
Han Kyung KimDepartment of Microbiology, CHA University, Seongnam-si, Gyeonggi-do, South Korea.
Dong Hyeon LeeOrganoid Research Center, School of Medicine, CHA University, Seongnam-si, Gyeonggi-do, South Korea.
So-Young LeeDepartment of Internal Medicine, CHA Bundang Medical Center, CHA University, Seongnam-si, Gyeonggi-do, South Korea.
Dong Kyu ChoiNew Drug Development Center, Daegu-Gyeongbuk Medical Innovation Foundation, Dong-gu, Daegu, South Korea.
Ji Hoon YuNew Drug Development Center, Daegu-Gyeongbuk Medical Innovation Foundation, Dong-gu, Daegu, South Korea.
Sang-Hyun MinNew Drug Development Center, Daegu-Gyeongbuk Medical Innovation Foundation, Dong-gu, Daegu, South Korea. shmin03@dgmif.re.kr.
Jongman YooDepartment of Microbiology, CHA University, Seongnam-si, Gyeonggi-do, South Korea. jongmanyoo@cha.ac.kr.

Funding

National Research Foundation of Korea (NRF) NRF-2015R1C1A1A01053325National Research Foundation of Korea (NRF) NRF-2016M3A9D9945475
6 · The paper itself

Abstract

Sepsis is one of the most common clinical syndromes that causes death and disability. Although many studies have developed drugs for sepsis treatment, none have decreased the mortality rate. The aim of this study was to identify a novel treatment option for sepsis using the library of integrated network-based cellular signatures (LINCS) L1000 perturbation dataset based on an in vitro and in vivo sepsis model. Sepsis-related microarray studies of early-stage inflammatory processes in patients and innate immune cells were collected from the Gene Expression Omnibus (GEO) data repository and used for candidate drug selection based on the LINCS L1000 perturbation dataset. The anti-inflammatory effects of the selected candidate drugs were analyzed using activated macrophage cell lines. CGP-60474, an inhibitor of cyclin-dependent kinase, was the most potent drug. It alleviated tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) in activated macrophages by downregulating the NF-κB activity, and it reduced the mortality rate in LPS induced endotoxemia mice. This study shows that CGP-60474 could be a potential therapeutic candidate to attenuate the endotoxemic process. Additionally, the virtual screening strategy using the LINCS L1000 perturbation dataset could be a cost and time effective tool in the early stages of drug development.

Indexed as

AnimalsDatabases, FactualDrug RepositioningEndotoxemiaHumansInterleukin-6MaleMiceMice, Inbred C57BLNF-kappa BNitric OxidePyrimidinesSepsis3-(4-(2-(3-chlorophenylamino)pyrimidin-4-yl)pyridin-2-ylamino)propanolInterleukin-6NF-kappa BNitric OxidePyrimidines

Identifiers

PMID30297806
PMCPMC6175892

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Registered trials

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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.