Evidence map›Paper›PMID 37071001›Full record

ArticleAging2023

Identification of the pyroptosis-related gene signature and risk score model for esophageal squamous cell carcinoma.

Minghong Pan, Yuanyong Wang, Zhaoyang Wang, Changjian Shao, Yingtong Feng, Peng Ding, Hongtao Duan, Xiaoya Ren, Weixun Duan, Zhiqiang Ma and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.3field-weighted citation impact, top 19% 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

8 citing papers in PubMed, 5 citations in OpenAlex.

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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

11 authors at 4 institutions in 1 country.

Minghong PanDepartment of Thoracic Surgery, Tangdu Hospital, The Air Force Military Medical University, Xi’an 710038, China.
Yuanyong WangDepartment of Thoracic Surgery, Tangdu Hospital, The Air Force Military Medical University, Xi’an 710038, China.
Zhaoyang WangDepartment of Thoracic Surgery, Tangdu Hospital, The Air Force Military Medical University, Xi’an 710038, China.
Changjian ShaoDepartment of Thoracic Surgery, Tangdu Hospital, The Air Force Military Medical University, Xi’an 710038, China.
Yingtong FengDepartment of Cardiothoracic Surgery, The Affiliated Huaihai Hospital of Xuzhou Medical University/The 71st Group Army Hospital of PLA, Xuzhou 221004, China.
Peng DingDepartment of Thoracic Surgery, Tangdu Hospital, The Air Force Military Medical University, Xi’an 710038, China.
Hongtao DuanDepartment of Thoracic Surgery, Tangdu Hospital, The Air Force Military Medical University, Xi’an 710038, China.
Xiaoya RenDepartment of Thoracic Surgery, Tangdu Hospital, The Air Force Military Medical University, Xi’an 710038, China.
Weixun DuanDepartment of Cardiovascular Surgery, Xijing Hospital, The Air Force Military Medical University, Xi’an 710038, China.
Zhiqiang MaDepartment of Medical Oncology, Senior Department of Oncology, Chinese PLA General Hospital, The Fifth Medical Center, Beijing 100853, China.
Xiaolong YanDepartment of Thoracic Surgery, Tangdu Hospital, The Air Force Military Medical University, Xi’an 710038, China.
Tang Du Hospital · CNChinese PLA General Hospital · CNXijing Hospital · CNXuzhou Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advanced esophageal squamous cell carcinoma (ESCC) still has a dismal prognostic outcome. However, the current approaches are unable to evaluate patient survival. Pyroptosis represents a novel programmed cell death type which widely investigated in various disorders and can influence tumor growth, migration, and invasion. Furthermore, few existing studies have used pyroptosis-related genes (PRGs) to construct a model for predicting ESCC survival. Therefore, the present study utilized bioinformatics approaches for analyzing ESCC patient data obtained from the TCGA database to construct the prognostic risk model and applied it to the GSE53625 dataset for validation. There were 12 differentially expressed PRGs in healthy and ESCC tissue samples, among which eight were selected through univariate and LASSO cox regression for constructing the prognostic risk model. According to K-M and ROC curve analyses, our eight-gene model might be useful in predicting ESCC prognostic outcomes. Based on the cell validation analysis, C2, CD14, RTP4, FCER3A, and SLC7A7 were expressed higher in KYSE410 and KYSE510 than in normal cells (HET-1A). Hence, ESCC patient prognostic outcomes can be assessed by our PRGs-based risk model. Further, these PRGs may also serve as therapeutic targets.

Indexed as

Esophageal NeoplasmsEsophageal Squamous Cell CarcinomaAmino Acid Transport System y+LApoptosisHumansPrognosisPyroptosisRisk FactorsAmino Acid Transport System y+LSLC7A7 protein, humanESCCpyroptosisrisk scoretumor microenvironment

Identifiers

PMID37071001
PMCPMC10188338
OpenAlexW4366168962

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.