Evidence map›Paper›PMID 41457818›Full record

ArticleCancer reports (Hoboken, N.J.)2026

Identification of Potential Ferroptosis Biomarkers in Multiple Myeloma via WGCNA and Experiments.

Yifan Wang, Xing Xie, Mengyuan Gu, Yanting Zheng, Jing Wu, Qicai Wang, Zhian Ling, Ruolin Li

Abstract read
In one paragraph

Article in Cancer reports (Hoboken, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

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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

1 citing paper in PubMed.

  1. Article
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

8 authors.

Yifan WangDepartment of Clinical Laboratory, First Affiliated Hospital of Guangxi Medical University, Key Laboratory of Clinical Laboratory Medicine of Guangxi Department of Education, Nanning, Guangxi, China.ORCID 0009-0006-5599-4753
Xing XieDepartment of Scientific Research, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.ORCID 0000-0002-2426-7944
Mengyuan GuDepartment of Clinical Laboratory, First Affiliated Hospital of Guangxi Medical University, Key Laboratory of Clinical Laboratory Medicine of Guangxi Department of Education, Nanning, Guangxi, China.ORCID 0009-0001-0619-4403
Yanting ZhengDepartment of Clinical Laboratory, First Affiliated Hospital of Guangxi Medical University, Key Laboratory of Clinical Laboratory Medicine of Guangxi Department of Education, Nanning, Guangxi, China.ORCID 0009-0006-5537-5055
Jing WuDepartment of Scientific Research, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.ORCID 0009-0002-8308-4897
Qicai WangDepartment of Clinical Laboratory, First Affiliated Hospital of Guangxi Medical University, Key Laboratory of Clinical Laboratory Medicine of Guangxi Department of Education, Nanning, Guangxi, China.ORCID 0009-0005-3295-6458
Zhian LingDepartment of Emergency, Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.ORCID 0000-0001-7555-4460
Ruolin LiDepartment of Scientific Research, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.ORCID 0000-0002-9835-4987

Funding

Guangxi Province Health Technology Development and Application Project No. S2018076
6 · The paper itself

Abstract

introductionMultiple myeloma is a common malignant tumor of the hematologic system, and genetic alterations play a crucial role in its occurrence and development. Ferroptosis is an oxidative and iron-dependent programmed cell death, which has a strong correlation with tumor development. This study aimed to identify potential diagnostic ferroptosis-related genes of MM.

methodsMM datasets were screened from the GEO database using publicly available transcriptomic data. Ferroptosis-related hub genes were identified through enrichment analysis, WGCNA, and machine learning algorithms. ROC curves, boxplots, RT-qPCR, and ELISA were conducted to validate the expression levels of these hub genes.

resultsA total of 178 ferroptosis-related DEGs were identified, including 114 up-regulated genes and 64 down-regulated genes. Enrichment analysis indicated that the DEGs were primarily associated with stress, autophagy, and metabolism. According to the WGCNA, the brown module has the highest correlation with clinical symptoms, containing 1141 DEGs. Combining with the identified ferroptosis-related DEGs, two hub genes of CDKN1A and BCAT2 were identified by multiple bioinformatics techniques of LASSO, SVM, and Random Forest. ROC curves demonstrated strong diagnostic values in CDKN1A (test set, AUC = 0.881; validation set, AUC = 0.705) and BCAT2 (test set, AUC = 0.808; validation set, AUC = 0.756). RT-qPCR confirmed that the mRNA expression levels of CDKN1A and BCAT2 in three MM cells (RPMI 8226, WT-U266, and LP-1) were both significantly higher than the control HMy2.CIR cell line (p < 0.05). ELISA quantification revealed significantly elevated relative expression of CDKN1A protein in the MM cohort compared to healthy controls (p < 0.01), but the protein expression of BCAT2 exhibited comparable levels (p > 0.05).

conclusionOur results suggest that CDKN1A and BCAT2 are potential ferroptosis-related biomarkers for MM. This may help understand the molecular mechanisms and therapeutic strategies of MM.

Indexed as

Biomarkers, TumorCyclin-Dependent Kinase Inhibitor p21FerroptosisGene Regulatory NetworksMultiple MyelomaComputational BiologyGene Expression ProfilingGene Expression Regulation, NeoplasticHumansBiomarkers, TumorCDKN1A protein, humanCyclin-Dependent Kinase Inhibitor p21BCAT2CDKN1Aferroptosismultiple myelomaWGCNA

Identifiers

PMID41457818
PMCPMC12745893

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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.