Single-Cell Transcriptome Analysis Reveals Different Immune Signatures in HPV- and HPV + Driven Human Head and Neck Squamous Cell Carcinoma.
Alphapapillomavirus
/ genetics
Carcinogens
Carcinoma, Squamous Cell
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Head and Neck Neoplasms
/ genetics
Humans
Papillomaviridae
/ genetics
Papillomavirus Infections
Prognosis
Squamous Cell Carcinoma of Head and Neck
/ genetics
Transcriptome
Tumor Microenvironment
/ genetics
Journal
Journal of immunology research
ISSN: 2314-7156
Titre abrégé: J Immunol Res
Pays: Egypt
ID NLM: 101627166
Informations de publication
Date de publication:
2022
2022
Historique:
received:
31
05
2022
accepted:
16
08
2022
entrez:
26
9
2022
pubmed:
27
9
2022
medline:
28
9
2022
Statut:
epublish
Résumé
Head and neck squamous cell carcinoma (HNSCC) is a significant health problem and related to poor long-term outcomes, indicating more research to be done to deeply understand the underlying pathways. This current study aimed in the assessment of the viral- (especially human papilloma virus [HPV]) and carcinogen-driven head and neck squamous cell carcinoma (HNSCC) microenvironment based on single-cell sequencing analysis. Data were downloaded from GEO database (GSE139324), including 131224 cells from 18 HP- HNSCC patients and 8 HPV+ HNSCC patients. Following data normalization, all highly variable genes in single cells were identified, and batch correction was applied. Differentially expressed genes were identified using Wilcoxon rank sum test. A gene enrichment analysis was performed in each cell cluster using KEGG analysis. Single-cell pseudotime trajectories were constructed with MONOCLE (version 2.6.4). Cell-cell interactions were analyzed with CellChat R package. Additionally, cell-cell communication patterns in key signal pathways were compared in different tissue groups. A hidden Markov model (HMM) was used to predict gene expression states (on or off) throughout pseudotime. Five-year overall survival outcomes were compared in both HPV+ and HPV- subsets. 20,978 high-quality individual cells passed quality control. RNA-seq data were used from 522 HNSCC primary tumor samples. 1,137 differentially expressed genes between HPV+ and HPV- HNSCC patients were investigated. 96 differentially expressed genes were associated with overall survival and highly enriched in B cell associated biological process. Cell composition differed between types of samples. MHC-I, MHC-II, and MIF signaling pathways were found to be most relevant. Within these pathways, some cells were either signal receiver or signal sender, depending on sample type, respectively. Six genes were obtained, AREG and TGFBI (upregulation), CD27, CXCR3, MS4A1, and CD19 (downregulation), whose expression and HPV types were highly associated with worse overall survival. AREG and TGFBI were pDC marker genes, CXCR3 and CD27 were significantly expressed in T cell-related cells, while MS4A1 and CD19 were mainly expressed in B naïve cells. This study revealed dynamic changes in cell percentage and heterogeneity of cell subtypes of HNSCC. AREG, TGFBI, CD27, CXCR3, MS4A1, and CD19 were associated with worse overall survival in HPV-related HNSCC. Especially B-cell related pathways were revealed as particularly relevant in HPV-related HNSCC. These findings are a basis for the development of biomarkers and therapeutic targets in respective patients.
Sections du résumé
Background
UNASSIGNED
Head and neck squamous cell carcinoma (HNSCC) is a significant health problem and related to poor long-term outcomes, indicating more research to be done to deeply understand the underlying pathways.
Objective
UNASSIGNED
This current study aimed in the assessment of the viral- (especially human papilloma virus [HPV]) and carcinogen-driven head and neck squamous cell carcinoma (HNSCC) microenvironment based on single-cell sequencing analysis.
Methods
UNASSIGNED
Data were downloaded from GEO database (GSE139324), including 131224 cells from 18 HP- HNSCC patients and 8 HPV+ HNSCC patients. Following data normalization, all highly variable genes in single cells were identified, and batch correction was applied. Differentially expressed genes were identified using Wilcoxon rank sum test. A gene enrichment analysis was performed in each cell cluster using KEGG analysis. Single-cell pseudotime trajectories were constructed with MONOCLE (version 2.6.4). Cell-cell interactions were analyzed with CellChat R package. Additionally, cell-cell communication patterns in key signal pathways were compared in different tissue groups. A hidden Markov model (HMM) was used to predict gene expression states (on or off) throughout pseudotime. Five-year overall survival outcomes were compared in both HPV+ and HPV- subsets.
Results
UNASSIGNED
20,978 high-quality individual cells passed quality control. RNA-seq data were used from 522 HNSCC primary tumor samples. 1,137 differentially expressed genes between HPV+ and HPV- HNSCC patients were investigated. 96 differentially expressed genes were associated with overall survival and highly enriched in B cell associated biological process. Cell composition differed between types of samples. MHC-I, MHC-II, and MIF signaling pathways were found to be most relevant. Within these pathways, some cells were either signal receiver or signal sender, depending on sample type, respectively. Six genes were obtained, AREG and TGFBI (upregulation), CD27, CXCR3, MS4A1, and CD19 (downregulation), whose expression and HPV types were highly associated with worse overall survival. AREG and TGFBI were pDC marker genes, CXCR3 and CD27 were significantly expressed in T cell-related cells, while MS4A1 and CD19 were mainly expressed in B naïve cells.
Conclusions
UNASSIGNED
This study revealed dynamic changes in cell percentage and heterogeneity of cell subtypes of HNSCC. AREG, TGFBI, CD27, CXCR3, MS4A1, and CD19 were associated with worse overall survival in HPV-related HNSCC. Especially B-cell related pathways were revealed as particularly relevant in HPV-related HNSCC. These findings are a basis for the development of biomarkers and therapeutic targets in respective patients.
Identifiants
pubmed: 36157879
doi: 10.1155/2022/2079389
pmc: PMC9507777
doi:
Substances chimiques
Carcinogens
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2079389Informations de copyright
Copyright © 2022 Simin Li et al.
Déclaration de conflit d'intérêts
The authors have nothing to declare.
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