Evidence map›Paper›PMID 35937391›Full record

ArticleBioMed research international2022

Ferroptosis-Related lncRNA for the Establishment of Novel Prognostic Signature and Therapeutic Response Prediction to Endometrial Carcinoma.

Xin-Ying Zhou, Hai-Yan Dai, Hu Zhang, Jian-Long Zhu, Hua Hu

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in BioMed research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.9field-weighted citation impact, top 30% 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

7 citing papers in PubMed, 9 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Xin-Ying ZhouDepartment of Obstetrics and Gynecology, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, 2800 Gongwei Road, Pudong, Shanghai 201399, China.ORCID https://orcid.org/0000-0002-7165-7195
Hai-Yan DaiDepartment of Obstetrics and Gynecology, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, 2800 Gongwei Road, Pudong, Shanghai 201399, China.ORCID https://orcid.org/0000-0002-5625-5681
Hu ZhangDepartment of Obstetrics and Gynecology, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, 2800 Gongwei Road, Pudong, Shanghai 201399, China.ORCID https://orcid.org/0000-0002-8785-6279
Jian-Long ZhuDepartment of Obstetrics and Gynecology, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, 2800 Gongwei Road, Pudong, Shanghai 201399, China.
Hua HuDepartment of Obstetrics and Gynecology, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, 2800 Gongwei Road, Pudong, Shanghai 201399, China.ORCID https://orcid.org/0000-0003-2883-7104
Fudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Ferroptosis is a recently described form of intentional cellular damage that is iron-dependent and separate from apoptosis, cellular necrosis, and autophagy. It has been demonstrated to be adequately regulated by long noncoding RNAs (lncRNAs) in various cancers. However, the predictive profile of ferroptosis-related lncRNAs (FRLs) in endometrial carcinoma (EC) is unknown. Herein, FRLs associated with uterine corpus endometrial carcinoma (UCEC) prognosis were screened to predict treatment response in EC. Methods: Samples of EC and adjacent normal tissues were obtained from The Cancer Genome Atlas (TCGA) dataset repository. Limma and survival packages in R software were used to screen FRLs associated with the prognosis of EC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) chord and circle plots of FRLs were also plotted. Next, FRLs screened by the least absolute shrinkage and selection operator (LASSO) method were applied to construct and validate a multivariate Cox proportional risk regression model. Nomogram plots were created to forecast the outcome of UCEC patients, and gene set enrichment analysis (GSEA), principal component analysis (PCA), and immunoassays were performed on the prognostic models. Finally, limma, ggpubr, pRRophetic, and ggplot2 programs were used for drug sensitivity analysis of the prognostic models. Results: A signature based on nine FRLs (CFAP58-DT, LINC00443, EMSLR, HYI-AS1, ADIRF-AS1, LINC02474, CDKN2B-AS1, LINC01629, and LINC00942) was constructed. The developed FRL prognostic model effectively discriminated UCEC patients into low-risk and high-risk groups. Immunological checkpoints CD80 and CD40 were strongly expressed in the high-risk group. In addition, the nine FRLs were all more expressed in the high-risk group compared to the low-risk group. Conclusion: These findings significantly contribute to the understanding of the function of FRLs in UCEC and provide promising therapeutic strategies for UCEC.

Indexed as

Carcinoma, EndometrioidEndometrial NeoplasmsFerroptosisRNA, Long NoncodingBiomarkers, TumorFemaleGene Expression Regulation, NeoplasticHumansPrognosisBiomarkers, TumorRNA, Long Noncoding

Identifiers

PMID35937391
PMCPMC9352484
OpenAlexW4288433565

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.