Evidence map›Paper›PMID 42526909›Full record

ArticleIET systems biology

Machine Learning Modelling, Single-Cell Landscape Profiling and Spatial Transcriptomics Provide New Insights Into SUMOylation in Head and Neck Squamous Cell Carcinoma.

Zhe Fang, Kai Mei, Jiaqi Liu, Wei Zhou, Tingjing Li, Hai Zhang, Chuangjie Cao

Abstract read
In one paragraph

Article in IET systems biology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Zhe FangDepartment of Oncology, The First Affiliated Hospital of Hengyang Medical School, University of South China, Hengyang, Hunan, China.ORCID https://orcid.org/0009-0001-0814-8435
Kai MeiDepartment of Oncology, The First Affiliated Hospital of Hengyang Medical School, University of South China, Hengyang, Hunan, China.
Jiaqi LiuDepartment of Oncology, The First Affiliated Hospital of Hengyang Medical School, University of South China, Hengyang, Hunan, China.
Wei ZhouSchool of Chinese Medicine, Hunan University of Chinese Medicine, Changsha, Hunan, China.
Tingjing LiDepartment of Oncology, The First Affiliated Hospital of Hengyang Medical School, University of South China, Hengyang, Hunan, China.
Hai ZhangDepartment of Pathology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan, China.
Chuangjie CaoDepartment of Pathology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

SUMOylation is implicated in the regulation of multiple malignancies. However, its potential roles in head and neck squamous cell carcinoma (HNSCC) remain insufficiently characterised. By integrating bulk RNA-seq, scRNA-seq and stRNA-seq datasets, we systematically interrogated the biological relevance of SUMOylation in HNSCC. Key markers from the signature were further validated using in vitro functional assays. A recognition model was established and validated using 692 HNSCC and 178 non-HNSCC samples. SROC analysis demonstrated robust performance across eight datasets (AUC = 0.92). Functional enrichment and scRNA-seq analyses indicated that SUMOylation may exert its effects in HNSCC primarily through cell-cycle regulation. Among the model features, SAE1 was markedly overexpressed in HNSCC (SMD = 1.07, 95% CI 0.56-1.59, p < 0.05). In vitro assays further confirmed that SAE1 enhanced proliferation, colony formation and migration in SAS and SCC-9 cells and validated its role in regulating cell cycle progression and apoptosis. We established a SUMOylation-related recognition model for HNSCC with consistently strong performance in multiple external validation cohorts. SAE1 emerges as a candidate molecular biomarker for HNSCC.

Indexed as

Head and Neck NeoplasmsMachine LearningSingle-Cell AnalysisSquamous Cell Carcinoma of Head and NeckSumoylationCell Line, TumorGene Expression Regulation, NeoplasticHumansSpatial Transcriptomicscell cyclehead and neck squamous cell carcinomaSAE1SUMOylation

Identifiers

PMID42526909
PMCPMC13420368

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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.