scholarly journals Single-Cell Deconvolution of Head and Neck Squamous Cell Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1230
Author(s):  
Zongtai Qi ◽  
Yating Liu ◽  
Michael Mints ◽  
Riley Mullins ◽  
Reilly Sample ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
T Cell ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Single Cell ◽  
Squamous Cell ◽  
Neck Squamous Cell Carcinoma ◽  
Cell Type ◽  
Cell Data

Complexities in cell-type composition have rightfully led to skepticism and caution in the interpretation of bulk transcriptomic analyses. Recent studies have shown that deconvolution algorithms can be utilized to computationally estimate cell-type proportions from the gene expression data of bulk blood samples, but their performance when applied to tumor tissues, including those from head and neck, remains poorly characterized. Here, we use single-cell data (~6000 single cells) collected from 21 head and neck squamous cell carcinoma (HNSCC) samples to generate cell-type-specific gene expression signatures. We leverage bulk RNA-seq data from >500 HNSCC samples profiled by The Cancer Genome Atlas (TCGA), and using single-cell data as a reference, apply two newly developed deconvolution algorithms (CIBERSORTx and MuSiC) to the bulk transcriptome data to quantitatively estimate cell-type proportions for each tumor in TCGA. We show that these two algorithms produce similar estimates of constituent/major cell-type proportions and that a high T-cell fraction correlates with improved survival. By further characterizing T-cell subpopulations, we identify that regulatory T-cells (Tregs) were the major contributor to this improved survival. Lastly, we assessed gene expression, specifically in the Treg population, and found that TNFRSF4 (Tumor Necrosis Factor Receptor Superfamily Member 4) was differentially expressed in the core Treg subpopulation. Moreover, higher TNFRSF4 expression was associated with greater survival, suggesting that TNFRSF4 could play a key role in mechanisms underlying the contribution of Treg in HNSCC outcomes.

Multi-omic single-cell analysis of antigen-presenting compartment reveals a unique functional signature for head and neck squamous cell carcinoma.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15179-e15179
Author(s):  
Brittany Barber ◽  
Martin Prlic ◽  
Florian Mair ◽  
Jami Erickson
Keyword(s):  
Squamous Cell Carcinoma ◽  
T Cell ◽  
Immune Responses ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Single Cell ◽  
Squamous Cell ◽  
Antigen Presenting Cells ◽  
Neck Squamous Cell Carcinoma ◽  
Antigen Presenting

e15179 Background: Immune studies in head and neck squamous cell carcinoma (HNSCC) are lacking. Studies in the past decade have highlighted the biological significance and the distinct functional properties of immune cell subsets that are resident in non-lymphoid tissues. While tissue-resident memory T cells (TRM) have been well characterized, much less is known about the human myeloid compartment in HNSCC, which includes professional antigen-presenting cells (APCs) such as dendritic cells (DCs) and macrophages, both of which are critical for shaping the local T cell response. This is particularly relevant in the context of anti-tumor immune responses, which are currently a major focus for therapeutic intervention in HNSCC by either checkpoint inhibitory blockade or adoptive T cell therapy. Methods: A combination of multi-omic single cell RNA sequencing (sc-RNAseq) and 30-parameter fluorescent flow cytometry were used to define the APC compartment in 7 human head and neck squamous cell carcinoma (HNSCC) samples and 4 normal gingival tissue samples as references. Importantly, we performed parallel profiling of the adaptive and innate T cell compartment to elucidate the relationship between APCs and local TRM cells that have been designated as critical players for immune responses in solid tumor tissue. Results: Several novel myeloid phenotypes and an altered composition of the APC compartment in HNSCC relative to normal gingival tissues. APCs expressing pro-inflammatory cytokines such as IL-1b and IL-6 showed reduced abundance, while previously unknown APC subsets defined by the expression of a unique chemokine profile were found to infiltrate HNSCC tissue. Furthermore, our multi-omic approach allowed for profiling of the protein surface phenotype in these transcript-defined clusters, opening up avenues for future therapeutic targeting of tumor-specific antigen-presenting cells. Conclusions: A novel myeloid phenotype and APC compartment were observed in HNSCC when compared to normal gingival tissues. A multi-omic assay identified tumor-specific APCs that may represent future therapeutic targets.

scholarly journals Bioinformatics analysis of DNMT1 expression and its role in head and neck squamous cell carcinoma prognosis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jili Cui ◽  
Lian Zheng ◽  
Yuanyuan Zhang ◽  
Miaomiao Xue
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Immune Cell ◽  
Neck Squamous Cell Carcinoma ◽  
Hub Genes ◽  
Significant Difference ◽  
Dnmt1 Expression

AbstractHead and neck squamous cell carcinoma (HNSCC) is the sixth most common type of malignancy in the world. DNA cytosine-5-methyltransferase 1 (DNMT1) play key roles in carcinogenesis and regulation of the immune micro-environment, but the gene expression and the role of DNMT1 in HNSCC is unknown. In this study, we utilized online tools and databases for pan-cancer and HNSCC analysis of DNMT1 expression and its association with clinical cancer characteristics. We also identified genes that positively and negatively correlated with DNMT1 expression and identified eight hub genes based on protein–protein interaction (PPI) network analysis. Enrichment analyses were performed to explore the biological functions related with of DNMT1. The Tumor Immune Estimation Resource (TIMER) database was performed to explore the relationship between DNMT1 expression and immune-cell infiltration. We demonstrated that DNMT1 gene expression was upregulated in HNSCC and associated with poor prognosis. Based on analysis of the eight hub genes, we determined that DNMT1 may be involved in cell cycle, proliferation and metabolic related pathways. We also found that significant difference of B cells infiltration based on TP 53 mutation. These findings suggest that DNMT1 related epigenetic alterations have close relationship with HNSCC progression, and DNMT1 could be a novel diagnostic biomarker and a promising therapeutic target for HNSCC.

scholarly journals Expression of placenta-specific 1 and its potential for eliciting anti-tumor helper T-cell responses in head and neck squamous cell carcinoma

2020 ◽  
Vol 10 (1) ◽  
pp. 1856545
Author(s):  
Ryusuke Hayashi ◽  
Toshihiro Nagato ◽  
Takumi Kumai ◽  
Kenzo Ohara ◽  
Mizuho Ohara ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
T Cell ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
T Cell Responses ◽  
Neck Squamous Cell Carcinoma ◽  
Helper T Cell ◽  
Cell Responses

scholarly journals Functional Genomics Screen with Pooled shRNA Library and Gene Expression Profiling with Extracts of Azadirachta indica Identify Potential Pathways for Therapeutic Targets in Head and Neck Squamous Cell Carcinoma

2018 ◽  
Author(s):  
Neeraja M Krishnan ◽  
Hiroto Katoh ◽  
Vinayak Palve ◽  
Manisha Pareek ◽  
Reiko Sato ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Cancer Cell ◽  
Squamous Cell ◽  
Azadirachta Indica ◽  
Neck Squamous Cell Carcinoma ◽  
Neem Extract ◽  
Infected Cells

AbstractTumor suppression by the extracts of Azadirachta indica (neem) works via anti-proliferation, cell cycle arrest, and apoptosis, demonstrated previously using cancer cell lines and live animal models. However, very little is known about the molecular targets and pathways that the neem extracts and the associated compounds act through. Here, we address this using a genome-wide functional pooled shRNA screen on head and neck squamous cell carcinoma cell line treated with crude neem leaf extracts, known for their anti-tumorigenic activity. By analyzing differences in global clonal sizes of the shRNA-infected cells cultured under no treatment and treatment with neem leaf extract conditions, assayed using next-generation sequencing, we found 225 genes affected the cancer cell growth in the shRNA-infected cells treated with neem extract. Pathway enrichment analyses of whole-genome gene expression data from cells temporally treated with neem extract revealed important roles played by the TGF-β pathway and HSF-1-related gene network. Our results indicate that neem extract simultaneously affects various important molecular signaling pathways in head and neck cancer cells, some of which may be therapeutic targets for this devastating tumor.

scholarly journals The Identification of Stemness-Related Genes in the Risk of Head and Neck Squamous Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Guanying Feng ◽  
Feifei Xue ◽  
Yingzheng He ◽  
Tianxiao Wang ◽  
Hua Yuan
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Network Analysis ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Risk Score ◽  
Squamous Cell ◽  
Neck Squamous Cell Carcinoma ◽  
Potential Biomarker ◽  
Score Model

ObjectivesThis study aimed to identify genes regulating cancer stemness of head and neck squamous cell carcinoma (HNSCC) and evaluate the ability of these genes to predict clinical outcomes.Materials and MethodsThe stemness index (mRNAsi) was obtained using a one-class logistic regression machine learning algorithm based on sequencing data of HNSCC patients. Stemness-related genes were identified by weighted gene co-expression network analysis and least absolute shrinkage and selection operator analysis (LASSO). The coefficient of LASSO was applied to construct a diagnostic risk score model. The Cancer Genome Atlas database, the Gene Expression Omnibus database, Oncomine database and the Human Protein Atlas database were used to validate the expression of key genes. Interaction network analysis was performed using String database and DisNor database. The Connectivity Map database was used to screen potential compounds. The expressions of stemness-related genes were validated using quantitative real‐time polymerase chain reaction (qRT‐PCR).ResultsTTK, KIF14, KIF18A and DLGAP5 were identified. Stemness-related genes were upregulated in HNSCC samples. The risk score model had a significant predictive ability. CDK inhibitor was the top hit of potential compounds.ConclusionStemness-related gene expression profiles may be a potential biomarker for HNSCC.

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