Evidence map›Paper›PMID 38058815›Full record

ArticleAmerican journal of cancer research2023

Risk model-guided identification of MTDH expression as a marker for ferroptosis induction therapy in head and neck squamous cell carcinoma.

Xueying Wang, Yuzhang Gao, Rui Miao, Lisha Li, Abiyasi Nanding, Yong Liu, Xin Zhang

Open access · greenAbstract read
In one paragraph

Article in American journal of cancer research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 27% 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

4 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
  2. Review
  3. ZNF683Nature communications · 2026
    Article
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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

7 authors at 3 institutions in 2 countries.

Xueying WangDepartment of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University No. 87 Xiangya Road, Changsha 410008, Hunan, The People's Republic of China.
Yuzhang GaoDepartment of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University No. 87 Xiangya Road, Changsha 410008, Hunan, The People's Republic of China.
Rui MiaoDepartment of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University No. 87 Xiangya Road, Changsha 410008, Hunan, The People's Republic of China.
Lisha LiCancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology Wuhan 430022, Hubei, The People's Republic of China.
Abiyasi NandingDepartment of Pathology, Harbin Medical University Cancer Hospital Harbin 150081, Heilongjiang, The People's Republic of China.
Yong LiuDepartment of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University No. 87 Xiangya Road, Changsha 410008, Hunan, The People's Republic of China.
Xin ZhangDepartment of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University No. 87 Xiangya Road, Changsha 410008, Hunan, The People's Republic of China.
Central South University · CNHarbin Medical University · CNWuhan Union Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Head and neck squamous cell carcinoma (HNSCC) are a prevalent malignancy with high mortality and morbidity rates. Therefore, in this study, we aimed to develop a novel risk score model by using a DNA methylation signature associated with ferroptosis to enhance the prognosis prediction of HNSCC. The transcriptome, methylome, and clinical data of HNSCC patients were collected from The Cancer Genome Atlas (TCGA) database. Additionally, data from a methylation dataset in the Gene Expression Omnibus (GEO) database were used for validation. The ferroptosis score (FS) in each patient was calculated using the transcriptome data, and the single-sample gene set enrichment analysis (ssGSEA) was performed to assess ferroptosis activity. Furthermore, a series of biochemical experiments including CCK8, colony formation, wound healing, and ROS detection were carried out to evaluate the influence of MTDH on the malignancy of HNSCC. Our results revealed that the FS was associated with patient prognosis, as the patients with high FS had a poor prognosis. The receiver operating characteristic (ROC) curve established based on the ferroptosis-associated DNA methylation signature, demonstrated the excellent predictive power of FS for the 1-, 3-, and 5-year survival of HNSCC. Importantly, this predictive model was successfully validated in the GEO dataset. The nomogram also demonstrated excellent accuracy and reliability, as determined by the calibration curves and the decision curve analysis (DCA) plot. Interestingly, the risk score model was found to be correlated with immune cell infiltration and immunotherapy-related biomarkers, suggesting its potential in predicting the immunotherapy response in HNSCC treatment. Moreover, we found that the expression of two risk score model component genes, SETD1B and MTDH, was significantly different between tumor and the adjacent tissues in patients with LSCC, which was also significantly correlated with patient prognosis. Further experimental validation showed that the upregulated expression of MTDH significantly inhibited ferroptosis through regulating GPX4 expression and enhanced the cytotoxicity of ferroptosis inducers in HNSCC cells. In conclusion, we have developed a risk score model by using a ferroptosis-related DNA methylation signature, which can be used as an alternative tool to predict the prognosis of patients with HNSCC. SETD1B and MTDH were identified as the pivotal genes in this model and might play important role in the progression of HNSCC.

Indexed as

DNA methylationFerroptosishead and neck squamous cell carcinoma (HNSCC)predictive modelprognosis

Identifiers

PMID38058815
PMCPMC10695774
OpenAlexW4389452812

What OpenQuestion holds

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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.