Evidence map›Paper›PMID 38281996›Full record

ArticleScientific reports2024

A novel anoikis-related gene signature predicts prognosis in patients with sepsis and reveals immune infiltration.

Yonghua Wang, Yanqi Chi, Cheng Zhu, Yuxuan Zhang, Ke Li, Jiajia Chen, Xiying Jiang, Kejie Chen, Shuping Li

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. 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
0.5field-weighted citation impact, top 38% 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, 2 citations in OpenAlex.

  1. Review
  2. 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

9 authors at 3 institutions in 1 country.

Yonghua Wang *Department of Emergency, The First Affiliated Hospital of Chengdu Medical College, Chengdu, 610500, Sichuan, People's Republic of China.
Yanqi Chi *School of Public Health, Chengdu Medical College, Chengdu, 610500, Sichuan, People's Republic of China.
Cheng ZhuDepartment of Emergency, The First Affiliated Hospital of Chengdu Medical College, Chengdu, 610500, Sichuan, People's Republic of China.
Yuxuan ZhangDepartment of Critical Care Medicine, The First Affiliated Hospital of Chengdu Medical College, Chengdu, 610500, Sichuan, People's Republic of China.
Ke LiDepartment of Emergency, The First Affiliated Hospital of Chengdu Medical College, Chengdu, 610500, Sichuan, People's Republic of China.
Jiajia ChenDepartment of Emergency, The First Affiliated Hospital of Chengdu Medical College, Chengdu, 610500, Sichuan, People's Republic of China.
Xiying JiangDepartment of Emergency, The First Affiliated Hospital of Chengdu Medical College, Chengdu, 610500, Sichuan, People's Republic of China.
Kejie ChenSchool of Public Health, Chengdu Medical College, Chengdu, 610500, Sichuan, People's Republic of China. ckj930@126.com.
Shuping LiDepartment of Emergency, The First Affiliated Hospital of Chengdu Medical College, Chengdu, 610500, Sichuan, People's Republic of China. 1145452419@qq.com.
First Affiliated Hospital of Chengdu Medical College · CNChengdu Medical College · CNPublic Health Clinical Center of Chengdu · CN

Funding

Natural Science Foundation of Chengdu Medical College CYZYB22-06Sichuan Science and Technology Program 2023NSFSC1462
6 · The paper itself

Abstract

Sepsis is a common acute and severe medical condition with a high mortality rate. Anoikis, an emerging form of cell death, plays a significant role in various diseases. However, the role of anoikis in sepsis remains poorly understood. Based on the datasets from Gene Expression Omnibus and anoikis-related genes from GeneCards, the differentially expressed anoikis-related genes (DEARGs) were identified. Based on hub genes of DEARGs, a novel prognostic risk model was constructed, and the pattern of immune infiltration was investigated by CIBERSORT algorithm. And small molecule compounds targeting anoikis in sepsis were analyzed using Autodock. Of 23 DEARGs, CXCL8, CFLAR, FASLG and TP53 were significantly associated with the prognosis of sepsis (P < 0.05). Based on the prognostic risk model constructed with these four genes, high-risk population of septic patients had significant lower survival probability than low-risk population (HR = 3.30, P < 0.001). And the level of CFLAR was significantly correlated with the number of neutrophils in septic patients (r = 0.54, P < 0.001). Moreover, tozasertib had low binding energy with CXCL8, CFLAR, FASLG and TP53, and would be a potential compound for sepsis. Conclusively, our results identified a new prognostic model and potential therapeutic molecular for sepsis, providing new insights on mechanism and treatment of sepsis.

Indexed as

AnoikisSepsisAlgorithmsCell DeathHumansPrognosis

Identifiers

PMID38281996
PMCPMC10822872
OpenAlexW4391286651

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.