Evidence map›Paper›PMID 36658573›Full record

ArticleBMC medical genomics2023

Ferroptosis related gene signature in T cell-mediated rejection after kidney transplantation.

Weixun Zhang, Lian Gong, Di Zhang, Xiaopeng Hu

Abstract read
In one paragraph

Article in BMC medical genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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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

4 authors.

Weixun Zhang *Department of Urology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
Lian Gong *Department of Urology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
Di ZhangDepartment of Urology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
Xiaopeng HuDepartment of Urology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China. xiaopeng_hu@sina.com.

Funding

National Natural Science Foundation of China 81970645Natural Science Foundation of Beijing Municipality KZ202010025036
6 · The paper itself

Abstract

backgroundT cell-mediated rejection is an important factor affecting early transplant kidney survival. Ferroptosis has been shown to play a pathogenic role in a variety of diseases, which was not reported in TCMR. Here we developed a model for assessing activation of ferroptosis-related genes in TCMR to find a better screening method and explore the contribution of ferroptosis in TCMR.

methodsWe performed unsupervised consensus clustering according to expression of ferroptosis-related genes based on RNA-seq data from kidney transplant biopsies, and developed an assessment model characterized by ferroptosis gene expression through PCA, which was evaluated in multiple external datasets as well as blood and urine samples. Pathway enrichment and immune cell infiltration analysis were used to explore the possible targets and pathways involved in ferroptosis and TCMR.

resultsA ferroptosis gene expression scoring model was established. The diagnostic specificity and sensitivity of TCMR in renal biopsy samples were both over 80%, AUC = 0.843, and AUC was around 0.8 in multi-dataset validation, and was also close to 0.7 in blood and urine samples, while in predicting of graft survival at 3 years, scoring model had a good prognostic effect as well. Pathway enrichment and PPI network speculated that TLR4, CD44, IFNG, etc. may be the key genes of ferroptosis in TCMR.

conclusionsFerroptosis scoring model could better diagnose TCMR and predict graft loss, and could be used as a potential screening method in blood and urine samples. We speculate that ferroptosis plays an important role in TCMR.

Indexed as

FerroptosisGraft RejectionKidney TransplantationBiopsyKidneyT-LymphocytesAllograft rejectionFerroptosisKidney transplantationMedical bioinformaticsTCMR

Identifiers

PMID36658573
PMCPMC9850582

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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.