Evidence map›Paper›PMID 35539920›Full record

ArticleRSC advances2018

Lac water extract inhibits IFN-γ signaling through JAK2-STAT1-IRF1 axis in human melanoma.

Luhui Li, Satoru Yokoyama, Na Han, Yoshihiro Hayakawa

Open access · goldAbstract read
In one paragraph

Article in RSC advances, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.1field-weighted citation impact, top 50% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. 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

4 authors at 2 institutions in 4 countries.

Luhui LiDivision of Pathogenic Biochemistry, Institute of Natural Medicine, University of Toyama 2630 Sugitani Toyama 930-0194 Japan yokoyama@inm.u-toyama.ac.jp.
Satoru YokoyamaDivision of Pathogenic Biochemistry, Institute of Natural Medicine, University of Toyama 2630 Sugitani Toyama 930-0194 Japan yokoyama@inm.u-toyama.ac.jp.ORCID https://orcid.org/0000-0001-8336-486X
Na HanDevelopment and Utilization Key Laboratory of Northeast Plant Materials, School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University Shenyang 110016 China.
Yoshihiro HayakawaDivision of Pathogenic Biochemistry, Institute of Natural Medicine, University of Toyama 2630 Sugitani Toyama 930-0194 Japan yokoyama@inm.u-toyama.ac.jp.
Toyama College · JPShenyang Pharmaceutical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Interferon-γ (IFN-γ) is a cytokine that plays an important role in the host defense of infectious diseases and in immune surveillance during tumor development; however, it has adverse effects in the pathogenesis of autoimmune diseases and in immunosuppressive microenvironments, promoting the immunoevasion of cancer cells. In this study, we identified lac water extract (Lac) as a candidate that can suppress IFN-γ signaling amongst 112 types of natural products, using PD-L1 promoter as a readout for the IFN-γ signaling. Moreover, we determined that Lac inhibits IFN-γ-induced PD-L1 and MHC class I expression on the cell surface in melanoma cells, both of which have been identified as the downstream molecules of IFN-γ signaling. We also determined that Lac inhibited the JAK2-STAT1-IRF1 pathway. Finally, we identified laccaic acids, encompassing laccaic acid A, B, C, and E, as the active components in Lac that inhibit IFN-γ signaling. Collectively, the laccaic acids are lead compounds for a novel inhibitor that targets the JAK2-STAT1-IRF1 pathway for diseases caused by the aberrant activation of IFN-γ signaling.

Identifiers

PMID35539920
PMCPMC9080938
OpenAlexW2807771283

What OpenQuestion holds

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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.