Evidence map›Paper›PMID 39896807›Full record

ArticleFrontiers in immunology2024

Disulfidptosis-related gene signatures as prognostic biomarkers and predictors of immunotherapy response in HNSCC.

Haotian Qin, Juan Xu, Yaohang Yue, Meiling Chen, Zheng Zhang, Panpan Xu, Yan Zheng, Hui Zeng, Jian Weng, Jun Yang and 1 more

Abstract read
In one paragraph

Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

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

17 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Haotian Qin *Department of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China.
Juan Xu *Department of Oncology, Chaohu Hospital of Anhui Medical University, Hefei, China.
Yaohang Yue *Department of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China.
Meiling ChenOperating Room, Peking University Shenzhen Hospital, Shenzhen, China.
Zheng ZhangStomatological Center, Peking University Shenzhen Hospital, Shenzhen, China.
Panpan XuDepartment of Otolaryngology Head and Neck Surgery, Chaohu Hospital of Anhui Medical University, Hefei, China.
Yan ZhengDepartment of Pathology, Chaohu Hospital of Anhui Medical University, Hefei, China.
Hui ZengDepartment of Orthopedics, Medical Innovation Technology Transformation Center of Shenzhen Second People's Hospital, Shenzhen Second People's Hospital, Shenzhen, Guangdong, China.
Jian WengDepartment of Bone and Joint Surgery, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China.
Jun YangDepartment of Radiology, Peking University Shenzhen Hospital, Shenzhen, China.
Fei YuDepartment of Spine Surgery, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Disulfidptosis is a newly discovered form of cell death associated with tumorigenesis, particularly under oxidative stress and metabolic disorder conditions. Currently, the biological mechanisms of disulfidptosis-related genes (DRGs) in head and neck squamous cell carcinoma (HNSCC) remain unclear. Methods: The study includes sections on methodologies, data sources, clinical data collection, subtype establishment, identification and analysis of differentially expressed genes, genetic variation, and the construction and validation of a DRG prognostic model. Various analyses are conducted, including the relationship between the risk scores model and clinicopathological features, immune status, immune checkpoints, tumor mutational burden (TMB), microsatellite instability (MSI), ESTIMATE, mRNAsi, and drug sensitivity. The study also covers single-cell analysis and DNA methylation analysis of DRGs, and the prediction of potential microRNA and long non-coding RNA target genes. Prognostic DRGs expression in HNSCC is validated through RT-qPCR and immunohistochemistry. The model's predictive capability is confirmed using external validation cohorts from GEO datasets and clinical tissue samples. The role of DSTN in HNSCC is further validated through gene knockout experiments. Results: We identified four valuable genes (SLC3A2, NUBPL, ACTB, DSTN) and constructed a prognostic model, along with identifying two DRG-related subtypes. Analysis of the DRG risk score revealed that the low-risk group had a better prognosis compared to the high-risk group. Significant correlations were found between the DRG risk score and clinical features, immunotherapy response, drug sensitivity, and genes related to RNA epigenetic modifications. Low-risk HNSCC patients were identified as potential beneficiaries of immune checkpoint inhibitor (ICI) therapy. A regulatory axis involving DSTN, hsa-miR-181c-5p, LUCAT1, and IGFL2-AS1 was constructed for HNSCC. RT-qPCR and IHC data further validated the upregulation of prognostic DRGs in HNSCC. The prognostic model demonstrated excellent predictive performance for the prognosis of HNSCC patients. Additionally, DSTN was significantly overexpressed in tumor cells; its knockdown inhibited tumor cell proliferation, migration, and invasion. Conclusion: The prognostic model effectively predicts HNSCC outcomes, with better prognosis in the low-risk group. DSTN upregulation promotes tumor growth, and its knockout inhibits proliferation, migration, and invasion.

Indexed as

Biomarkers, TumorHead and Neck NeoplasmsImmunotherapySquamous Cell Carcinoma of Head and NeckTranscriptomeDisulfidptosisFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMaleMiddle AgedPrognosisBiomarkers, Tumorbioinformatics analysisdisulfidptosishead and neck squamous cell carcinomaimmunotherapy responseprognostic signatures

Identifiers

PMID39896807
PMCPMC11782277

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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.