Evidence map›Paper›PMID 34338139›Full record

ArticleBioengineered2021

A ferroptosis-related gene signature for graft loss prediction following renal allograft.

Zhenlei Fan, Tao Liu, Hanfei Huang, Jie Lin, Zhong Zeng

Open access · goldAbstract read
In one paragraph

Article in Bioengineered, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.5field-weighted citation impact, top 10% 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

10 citing papers in PubMed, 16 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

5 authors at 2 institutions in 1 country.

Zhenlei FanOrgan Transplantation Center, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, P. R. China.
Tao LiuOrgan Transplantation Center, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, P. R. China.
Hanfei HuangOrgan Transplantation Center, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, P. R. China.
Jie LinOrgan Transplantation Center, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, P. R. China.
Zhong ZengOrgan Transplantation Center, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, P. R. China.
First Affiliated Hospital of Kunming Medical University · CNKunming Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Allogeneic kidney transplantation (renal allograft) is the most effective treatment for advanced kidney disease. Previous studies have indicated that ferroptosis participates in the progression of acute kidney injury and renal transplant failure. However, few studies have evaluated the prognostic value of ferroptosis on renal transplantation outcomes. In this study, a total of 32 differentially expressed ferroptosis-related genes (DFGs) were identified, which were mainly enriched in infection-related pathways. Next, a ferroptosis-related gene signature, including GA-binding protein transcription factor subunit beta 1 (GABPB1), cyclin-dependent kinase inhibitor 1A (CDKN1A), Toll-like receptor 4 (TLR4), C-X-C motif chemokine ligand 2 (CXCL2), caveolin 1 (CAV1), and ribonucleotide reductase subunit M2 (RRM2), was constructed to predict graft loss following renal allograft. Moreover, receiver operating characteristic (ROC) curves (area under the ROC curve [AUC] > 0.8) demonstrated the accuracy of the gene signature and univariate Cox analysis suggested that the gene signature could play an independent role in graft loss (p < 0.05). Furthermore, the nomogram and calibration plots also indicated the good prognostic capability of the gene signature. Finally, immune-related and cytokine signaling pathways were mostly enriched in renal allograft patients with poor outcomes. Considered together, a ferroptosis-related gene signature and nomogram based on DFGs were created to predict the 1-, 2- and 3- year graft loss probability of renal allograft patients.The gene signature could serve as a valuable biomarker for predicting graft loss, contributing to improving the outcome of allogeneic kidney transplantation.

Indexed as

Graft RejectionFerroptosisHumansKidney TransplantationNomogramsPrognosisTranscriptomeTransplantation, HomologousFerroptosisgene signaturenomogramprognosisrenal allograft

Identifiers

PMID34338139
PMCPMC8806795
OpenAlexW3187498473

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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.