Evidence map›Paper›PMID 40025504›Full record

ArticleJournal of translational medicine2025

High-dimensional deconstruction of HNSC reveals clinically distinct cellular states and ecosystems that are associated with prognosis and therapy response.

Lei Xiao, Zhe Shen, Zhaoyu Pan, Yuanzheng Qiu, Donghai Huang, Yong Liu, Chao Liu, Xin Zhang

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PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. 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

8 authors.

Lei XiaoDepartment of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China.
Zhe ShenDepartment of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China.
Zhaoyu PanDepartment of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China.
Yuanzheng QiuDepartment of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China.
Donghai HuangDepartment of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China.
Yong LiuDepartment of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China.
Chao LiuDepartment of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China. liuchaoent@csu.edu.cn.ORCID 0000-0003-2184-9102
Xin ZhangDepartment of Otolaryngology Head and Neck Surgery, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China. xinzhang@csu.edu.cn.

Funding

the National Natural Science Foundation of China 82103631the National Natural Science Foundation of China 82473442the Postgraduate Research Innovation Project of Hunan Province CX20230280the Youth Science Foundation of Xiangya Hospital No. 2020Q03
6 · The paper itself

Abstract

backgroundCharacterizing the variety of cell types in the tumor microenvironment (TME) and their organization into cellular communities is vital for elucidating the biological diversity of cancer and informing therapeutic strategies.

methodsHere, we employed a machine learning-based algorithm framework, EcoTyper, to analyze single-cell transcriptomes from 139 patients with head and neck squamous cell carcinoma (HNSC)and gene expression profiles from 983 additional HNSC patients, aiming to delineate the fundamental cell states and ecosystems integral to HNSC.

resultsA diverse landscape of 66 cell states and 9 ecosystems within the HNSC microenvironment was identified, revealing classical cell types while also expanding upon previous immune classifications. Survival analysis revealed that specific cell states and ecotypes (ecosystems) are associated with patient prognosis, underscoring their potential as indicators of clinical outcomes. Moreover, distinct cell states and ecotypes exhibited varying responses to immunotherapy and chemotherapy, with several showing promise as predictive biomarkers for treatment efficacy.

conclusionOur large-scale integrative transcriptome analysis provides high-resolution insights into the cellular states and ecosystems of HNSC, facilitating the discovery of novel biomarkers and supporting the development of precision therapies.

Indexed as

Carcinoma, Squamous CellEcosystemHead and Neck NeoplasmsGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMachine LearningPrognosisSquamous Cell Carcinoma of Head and NeckTranscriptomeTreatment OutcomeTumor Microenvironment

Identifiers

PMID40025504
PMCPMC11872339

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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.