Evidence map›Paper›PMID 35840882›Full record

ArticleBMC gastroenterology2022

Identification and validation of necroptosis-related prognostic gene signature and tumor immune microenvironment infiltration characterization in esophageal carcinoma.

Kai Sun, Juan-Juan Hong, Dong-Mei Chen, Zhan-Xiong Luo, Jing-Zhang Li

Open access · goldAbstract read
In one paragraph

Article in BMC gastroenterology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 29% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
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  4. PANoptosis: potential new targets and therapeutic prospects in digestive diseases.Apoptosis : an international journal on programmed cell death · 2025
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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

5 authors at 2 institutions in 1 country.

Kai SunDepartment of Oncology, Liuzhou People's Hospital, Liuzhou, 545001, Guangxi Zhuang Autonomous Region, China. sunkai0927@foxmail.com.
Juan-Juan HongDepartment of Oncology, Liuzhou People's Hospital, Liuzhou, 545001, Guangxi Zhuang Autonomous Region, China.
Dong-Mei ChenDepartment of Oncology, Liuzhou People's Hospital, Liuzhou, 545001, Guangxi Zhuang Autonomous Region, China.
Zhan-Xiong LuoDepartment of Oncology, Liuzhou People's Hospital, Liuzhou, 545001, Guangxi Zhuang Autonomous Region, China. luozhanxionglz@yeah.net.
Jing-Zhang LiDepartment of Oncology, Liuzhou People's Hospital, Liuzhou, 545001, Guangxi Zhuang Autonomous Region, China. 429299173@qq.com.
Liuzhou General Hospital · CNGuilin Medical University · CN

Funding

Guangxi Natural Science Foundation 2019JJA140660Science and Technology Program of Liuzhou 2021CBB0104the Research Fund of Liuzhou People's Hospital lry202108the Science and Technology Base and Talent Project of Guangxi 2021AC19414the Talent Introduction Scientific Research Projects Funded Start-Up Funds of Liuzhou People's Hospital LRYGCC202114
6 · The paper itself

Abstract

backgroundEsophageal carcinoma (ESCA) is a common malignancy with a poor prognosis. Previous research has suggested that necroptosis is involved in anti-tumor immunity and promotes oncogenesis and cancer metastasis, which in turn affects tumor prognosis. However, the role of necroptosis in ESCA is unclear. This study aimed to investigate the relationships between necroptosis-related genes (NRGs) and ESCA. METHODS AND

resultsThe clinical data and gene expression profiles of ESCA patients were extracted from The Cancer Genome Atlas (TCGA), and 159 NRGs were screened from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. We then identified 52 differentially expressed NRGs associated with ESCA and used them for further analysis. Gene ontology (GO) and KEGG functional enrichment analyses showed that these NRGs were mostly associated with the regulation of necroptosis, Influenza A, apoptosis, NOD-like receptor, and NF-Kappa B signaling pathway. Next, univariate and multivariate Cox regression and LASSO analysis were used to identify the correlation between NRGs and the prognosis of ESCA. We constructed a prognostic model to predict the prognosis of ESCA based on SLC25A5, PPIA, and TNFRSF10B; the model classified patients into high- and low-risk subgroups based on the patient's risk score. Furthermore, the receiver operating characteristic (ROC) curve was plotted, and the model was affirmed to perform moderately well for prognostic predictions. In addition, Gene Expression Omnibus (GEO) datasets were selected to validate the applicability and prognostic value of our predictive model. Based on different clinical variables, we compared the risk scores between the subgroups of different clinical features. We also analyzed the predictive value of this model for drug sensitivity. Moreover, Immunohistochemical (IHC) validation experiments explored that these three NRGs were expressed significantly higher in ESCA tissues than in adjacent non-tumor tissues. In addition, a significant correlation was observed between the three NRGs and immune-cell infiltration and immune checkpoints in ESCA.

conclusionsIn summary, we successfully constructed and validated a novel necroptosis-related signature containing three genes (SLC25A5, PPIA, and TNFRSF10B) for predicting prognosis in patients with ESCA; these three genes might also play a crucial role in the progression and immune microenvironment of ESCA.

Indexed as

Esophageal NeoplasmsMicroRNAsGene Expression Regulation, NeoplasticHumansNecroptosisPrognosisTumor MicroenvironmentMicroRNAsEsophageal carcinomaImmune infiltrationNecroptosisPrognosisSignature

Identifiers

PMID35840882
PMCPMC9284853
OpenAlexW4285590835

What OpenQuestion holds

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LicenceCC BY
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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.