Evidence map›Paper›PMID 33828074›Full record

ArticleCell death discovery2021

A novel defined pyroptosis-related gene signature for predicting the prognosis of ovarian cancer.

Ying Ye, Qinjin Dai, Hongbo Qi

Open access · goldAbstract read
In one paragraph

Article in Cell death discovery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 321 papers.

0numbers the graph read from it
0cells of the map it votes in
321citing papers in PubMed
41.3field-weighted citation impact, top 1% 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

321 citing papers in PubMed, 498 citations in OpenAlex.

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  6. How to recognize if a cell dies from pyroptosis?Molecular biology reports · 2026
    Review
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  14. Establishment of a Prognostic Necroptosis-Related lncRNA Signature in Ovarian Cancer.Combinatorial chemistry & high throughput screening · 2026
    Article
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261 more citing papers are in PubMed but not listed here.

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

3 authors at 2 institutions in 1 country.

Ying Ye *The Department of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
Qinjin Dai *Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, Guangdong, China.
Hongbo QiThe Department of Obstetrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China. qihongbocqmu@163.com.ORCID http://orcid.org/0000-0003-3776-0487
The Affiliated Yongchuan Hospital of Chongqing Medical University · CNGuangzhou Medical University · CN

Funding

National Natural Science Foundation of China (National Science Foundation of China) 81520108013National Natural Science Foundation of China (National Science Foundation of China) 81771613
6 · The paper itself

Abstract

Ovarian cancer (OC) is a highly malignant gynaecological tumour that has a very poor prognosis. Pyroptosis has been demonstrated in recent years to be an inflammatory form of programmed cell death. However, the expression of pyroptosis-related genes in OC and their correlations with prognosis remain unclear. In this study, we identified 31 pyroptosis regulators that were differentially expressed between OC and normal ovarian tissues. Based on these differentially expressed genes (DEGs), all OC cases could be divided into two subtypes. The prognostic value of each pyroptosis-related gene for survival was evaluated to construct a multigene signature using The Cancer Genome Atlas (TCGA) cohort. By applying the least absolute shrinkage and selection operator (LASSO) Cox regression method, a 7-gene signature was built and classified all OC patients in the TCGA cohort into a low- or high-risk group. OC patients in the low-risk group showed significantly higher survival possibilities than those in the high-risk group (P < 0.001). Utilizing the median risk score from the TCGA cohort, OC patients from a Gene Expression Omnibus (GEO) cohort were divided into two risk subgroups, and the low-risk group had increased overall survival (OS) time (P = 0.014). Combined with the clinical characteristics, the risk score was found to be an independent factor for predicting the OS of OC patients. Gene ontology (GO) and Kyoto Encylopedia of Genes and Genomes (KEGG) analyses indicated that immune-related genes were enriched and that the immune status was decreased in the high-risk group. In conclusion, pyroptosis-related genes play important roles in tumour immunity and can be used to predict the prognosis of OCs.

Identifiers

PMID33828074
PMCPMC8026591
OpenAlexW3144571741

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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.