Evidence map›Paper›PMID 42098219›Full record

ArticleCommunications biology2026

Distinct single-cell cellular states and ecosystems linked to HPV status distinguish therapeutic vulnerability of head and neck squamous cell carcinoma.

Nihui Zhang, Zhizhou Xu, Guanghui Tian, Wanxin Deng, Jiankai Xu, Chenqing Huang, Qiang Chen, Jiale Cai, Xiaoyu Huang, Hong Wang and 3 more

Abstract read
In one paragraph

Article in Communications biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

13 authors.

Nihui Zhang *School of Intelligent Medicine and Technology (Big Data Research Center), Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou, China.
Zhizhou Xu *School of Intelligent Medicine and Technology (Big Data Research Center), Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou, China.
Guanghui Tian *School of Intelligent Medicine and Technology (Big Data Research Center), Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou, China.
Wanxin DengDepartment of Clinical Laboratory, Center for Laboratory Medicine, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, China.
Jiankai XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Chenqing HuangSchool of Intelligent Medicine and Technology (Big Data Research Center), Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou, China.
Qiang ChenSchool of Intelligent Medicine and Technology (Big Data Research Center), Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou, China.
Jiale CaiSchool of Intelligent Medicine and Technology (Big Data Research Center), Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou, China.
Xiaoyu HuangSchool of Intelligent Medicine and Technology (Big Data Research Center), Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou, China.
Hong WangSchool of Intelligent Medicine and Technology (Big Data Research Center), Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou, China.
Bo WangSchool of Intelligent Medicine and Technology (Big Data Research Center), Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou, China. wangqugans@163.com.ORCID http://orcid.org/0009-0009-4597-4750
Kongning LiSchool of Intelligent Medicine and Technology (Big Data Research Center), Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou, China. likongning@muhn.edu.cn.ORCID http://orcid.org/0000-0002-4928-6922
Dahua XuSchool of Intelligent Medicine and Technology (Big Data Research Center), Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou, China. xudahua1209@muhn.edu.cn.ORCID http://orcid.org/0000-0003-3373-5487

Funding

National Natural Science Foundation of China (National Science Foundation of China) 32160152National Natural Science Foundation of China (National Science Foundation of China) 32460161Natural Science Foundation of Hainan Province 825QN315
6 · The paper itself

Abstract

Human papillomavirus (HPV) infection plays a significant role in shaping the tumor microenvironment of head and neck squamous cell carcinoma (HNSCC). However, the heterogeneity of cellular states and ecosystems within the tumor microenvironment of HPV-infected HNSCC is still largely unknown. Using the EcoTyper framework, we perform an extensive evaluation of HPV-related cellular profiles and cellular ecotypes (CEs) in HNSCC. Single-cell RNA sequencing reveals 46 unique states across 12 principal cell types. Spatial transcriptomics confirm the spatial correlation of cellular states from the same ecotype. Moreover, prognostic and drug sensitivity analyses reveal the clinically relevant and therapeutic vulnerabilities of cellular status for patients with different HPV statuses. In conclusion, our findings provide insights into the different cellular organizations and microenvironments of HPV-related HNSCC, with potential implications for the development of biomarkers and precision therapies.

Indexed as

Head and Neck NeoplasmsHuman Papillomavirus VirusesPapillomavirus InfectionsSquamous Cell Carcinoma of Head and NeckTumor MicroenvironmentHumansSingle-Cell AnalysisSingle-Cell Gene Expression Analysis

Identifiers

PMID42098219
PMCPMC13369925

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.