Evidence map›Paper›PMID 39928204›Full record

ArticleDiscover oncology2025

Single-cell pseudotime and intercellular communication analysis reveals heterogeneity and immune microenvironment in oral cancer.

Hanjun Liu, Lian Xie, Xuemin Xing, Lili Hou, Jinfeng Zhang, Ling Yang

Abstract read
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Hanjun LiuDepartment of Rehabilitation, Chengdu Xinhua Hospital Affiliated to North Sichuan Medical College, Chengdu, China.
Lian XieDepartment of Nursing, Chengdu Xinhua Hospital Affiliated to North Sichuan Medical College, Chengdu, China.
Xuemin XingDepartment of Neurosurgery, Chengdu Xinhua Hospital Affiliated to North Sichuan Medical College, Chengdu, China.
Lili HouDepartment of Nursing, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jinfeng ZhangDepartment of Oral and Maxillofacial-Head and Neck Oncology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Ling YangDepartment of Nursing, Chengdu Xinhua Hospital Affiliated to North Sichuan Medical College, Chengdu, China. dalinglingerj66y77@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOral cancer is one of the most prevalent malignant neoplasms globally, with its microenvironment being extremely complicated and heterogeneous with regard to distribution of different types of cells, which creates a barrier against treatment. We integrated single-cell RNA sequencing, pseudotime analysis, and intercellular communication to identify subtypes, state transitions, and interactions in the development of oral cancer and their roles in tumor progression and immune response.

methodsPrincipal component analysis (PCA) followed by dimensionality reduction techniques (UMAP and t-SNE) revealed multiple populations in the single-cell data from oral cancer. Analysis of gene expression patterns associated individual genes with distinct principal components that described features of cell subtypes or states in the oral cancer microenvironment. We also conducted gene set enrichment analysis (GSEA) and cell-cell communication network analysis to investigate the important signaling pathways as well as potential cell-cell communications.

resultsGene expression patterns linked to oral cancer cell subtypes and states in this study included cell membrane, signal transduction and immune response in different biological processes. Pseudotime analysis showed differentiation trajectories and expression of essential differentiation genes were also altered. Cell-cell communication network analysis revealed that myeloid cells interacted heavily with myeloid cells and they also had strong interactions with endothelial cells. Analysis of the MIF signaling pathway network showed participation of various cell types in MIF signaling, suggesting its potential significance in the oral cancer microenvironment.

conclusionThe intercellular communication complexity of TME in oral cancer is reported here with the first-ever single cell analysis and data providing new perspective regarding the heterogeneity of oral cancer.

Indexed as

Immune microenvironmentIntercellular communicationOral cancerPseudotime analysisSingle-cell RNA sequencing

Identifiers

PMID39928204
PMCPMC11810869

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