Evidence map›Paper›PMID 35529787›Full record

ArticleTranslational lung cancer research2022

Systematic analysis of ferroptosis-related long non-coding RNA predicting prognosis in patients with lung squamous cell carcinoma.

Ninghua Yao, Ling Zuo, Xiaodi Yan, Jing Qian, Jie Sun, Huawei Xu, Feifei Zheng, Jimmy T Efird, Izumi Kawagoe, Yan Wang and 1 more

Open access · diamondAbstract read
In one paragraph

Article in Translational lung cancer research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
3.2field-weighted citation impact, top 6% 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, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Pooled it
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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 5 institutions in 3 countries.

Ninghua Yao *Department of Cancer Center, Affiliated Hospital of Nantong University, Nantong, China.
Ling Zuo *Department of Oncology, Nantong University, Nantong, China.
Xiaodi Yan *Department of Cancer Center, Affiliated Hospital of Nantong University, Nantong, China.
Jing QianDepartment of Cancer Center, Affiliated Hospital of Nantong University, Nantong, China.
Jie SunDepartment of Cancer Center, Affiliated Hospital of Nantong University, Nantong, China.
Huawei XuDepartment of Oncology, Affiliated Tongzhou Hospital of Nantong University Nantong, China.
Feifei ZhengDepartment of Laboratory Medicine, Affiliated Hospital of Jiangnan University, Wuxi, China.
Jimmy T EfirdVA Cooperative Studies Program Coordinating Center, Boston, MA, USA.
Izumi KawagoeDepartment of Anesthesiology and Pain Medicine, Juntendo University School of Medicine, Tokyo, Japan.
Yan WangDepartment of Cancer Center, Affiliated Hospital of Nantong University, Nantong, China.
Sujie NiDepartment of Cancer Center, Affiliated Hospital of Nantong University, Nantong, China.
Nantong University · CNAffiliated Hospital of Nantong University · CNJuntendo University · JPProgram Support Center · USWuxi Fourth People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Ferroptosis is a novel iron-dependent cell death, and an increasing number of studies have shown that long non-coding RNA (lncRNAs) are involved in the ferroptosis process. However, studies on ferroptosis-related lncRNAs in lung squamous cell carcinoma (LUSC) are limited. In addition, the prognostic role of ferroptosis-related lncRNAs and their relationship with the immune microenvironment and methylation of LUSC is unclear. This study aimed to investigate the potential prognostic value of ferroptosis-related lncRNAs and their involved biological functions in LUSC. Methods: The Cancer Genome Atlas (TCGA) database and the FerrDb website were used to obtain ferroptosis-related genes for LUSC. The "limma" R package and Pearson analysis were used to find ferroptosis-related lncRNAs. The biological functions of the characterized lncRNAs were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). We evaluated the prognostic power of this model using Kaplan-Meier analysis, receiver operating characteristic (ROC), and decision curve analysis (DCA). Univariate and multifactor Cox (proportional-hazards) risk model and a nomogram were produced using risk models and clinicopathological parameters for further verification. In addition, the relationship between characterized lncRNAs and tumor immune infiltration and methylation was also discussed. Results: We identified 29 characterized lncRNAs to produce prognostic risk models. Kaplan-Meier analysis revealed the high-risk group was associated with poor prognosis in LUSC (P<0.001), and ROC (AUC =0.658) and DCA suggested that risk models could predict prognosis. Univariate and multifactorial Cox as well as nomogram further validated the prognostic model (P<0.001). Gene set enrichment analysis (GSEA) showed that the high-risk group was associated with pro-tumor pathways and high-frequency mutations in TP53 were present in both groups. Single sample gene set enrichment analysis (ssGSEA) showed significant differences in immune cell infiltration subtypes and corresponding functions between the two groups. Some immune checkpoint and methylation-related genes were significantly different between the two groups (P<0.05). Conclusions: We investigated the potential mechanisms of LUSC development from the perspective of ferroptosis-related lncRNAs, providing new insights into LUSC research, and identified 29 lncRNAs as biomarkers to predict the prognosis of LUSC patients.

Indexed as

Ferroptosislong non-coding RNA (lncRNA)lung squamous cell carcinoma (LUSC)prognostic signature

Identifiers

PMID35529787
PMCPMC9073741
OpenAlexW4229447827

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.