Evidence map›Paper›PMID 35810312›Full record

ArticleBMC cancer2022

Targeting the transcriptional activity of STAT3 by a novel fusion protein.

Yanqiong Chen, Wenting Zhang, Xiufeng Bai, Yi Liu

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2022. 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
0.3field-weighted citation impact, top 41% 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, 3 citations in OpenAlex.

  1. Article
  2. Therapeutic Fusion Proteins.The AAPS journal · 2023
    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 1 country.

Yanqiong ChenNational Clinical Research Center for Geriatrics and Laboratory of Human Disease and Immunotherapies, West China Hospital, Sichuan University, Sichuan Province, Chengdu, 610041, China.
Wenting ZhangNational Clinical Research Center for Geriatrics and Laboratory of Human Disease and Immunotherapies, West China Hospital, Sichuan University, Sichuan Province, Chengdu, 610041, China.
Xiufeng BaiNational Clinical Research Center for Geriatrics and Laboratory of Human Disease and Immunotherapies, West China Hospital, Sichuan University, Sichuan Province, Chengdu, 610041, China. baixiufeng@wchscu.cn.
Yi LiuResearch Institute of Inflammation and Immunology (RIII), Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, China. yi2006liu@163.com.
Sichuan University · CNWest China Hospital of Sichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe continuous activation of transcription factors drives many diseases, including tumors, autoimmune disease, neurodegenerative disease, and male infertility. Thus, Blocking the transcriptional activity of these proteins may inhibit disease progression. In this study, we developed a new method to specifically inhibit the activity of the transcription factor STAT3.

methodsFusing the transcriptional inhibitory domain KRAB with STAT3 successfully blocked the transcription activity of STAT3 in cancer cells without affecting its function in the mitochondria and lysosomes.

resultsthe expression of KRAB-STAT3 fusion protein inhibited the growth of tumor cells.

conclusionsThe KRAB-STAT3 fusion protein provides a novel approach for drug development for the treatment of cancer or autoimmune diseases.

Indexed as

NeoplasmsNeurodegenerative DiseasesGene Expression RegulationHumansMaleSTAT3 Transcription FactorSTAT3 protein, humanSTAT3 Transcription FactorAutoimmune diseasescancerKRABMale infertilityNeurodegenerative diseasesSTAT3Transcription

Identifiers

PMID35810312
PMCPMC9271252
OpenAlexW4284988554

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.