Single-Cell Deconvolution of Head and Neck Squamous Cell Carcinoma
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 b...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-03-01
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| Series: | Cancers |
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| Online Access: | https://www.mdpi.com/2072-6694/13/6/1230 |
| _version_ | 1797541666247147520 |
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| author | Zongtai Qi Yating Liu Michael Mints Riley Mullins Reilly Sample Travis Law Thomas Barrett Angela L. Mazul Ryan S. Jackson Stephen Y. Kang Patrik Pipkorn Anuraag S. Parikh Itay Tirosh Joseph Dougherty Sidharth V. Puram |
| author_facet | Zongtai Qi Yating Liu Michael Mints Riley Mullins Reilly Sample Travis Law Thomas Barrett Angela L. Mazul Ryan S. Jackson Stephen Y. Kang Patrik Pipkorn Anuraag S. Parikh Itay Tirosh Joseph Dougherty Sidharth V. Puram |
| author_sort | Zongtai Qi |
| collection | DOAJ |
| description | 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 (T<sub>regs</sub>) were the major contributor to this improved survival. Lastly, we assessed gene expression, specifically in the T<sub>reg</sub> population, and found that TNFRSF4 (Tumor Necrosis Factor Receptor Superfamily Member 4) was differentially expressed in the core T<sub>reg</sub> subpopulation. Moreover, higher TNFRSF4 expression was associated with greater survival, suggesting that TNFRSF4 could play a key role in mechanisms underlying the contribution of T<sub>reg</sub> in HNSCC outcomes. |
| first_indexed | 2024-03-10T13:20:12Z |
| format | Article |
| id | doaj.art-4b0dbd53478f4e76951ac7e0942b4dd1 |
| institution | Directory Open Access Journal |
| issn | 2072-6694 |
| language | English |
| last_indexed | 2024-03-10T13:20:12Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cancers |
| spelling | doaj.art-4b0dbd53478f4e76951ac7e0942b4dd12023-11-21T10:06:38ZengMDPI AGCancers2072-66942021-03-01136123010.3390/cancers13061230Single-Cell Deconvolution of Head and Neck Squamous Cell CarcinomaZongtai Qi0Yating Liu1Michael Mints2Riley Mullins3Reilly Sample4Travis Law5Thomas Barrett6Angela L. Mazul7Ryan S. Jackson8Stephen Y. Kang9Patrik Pipkorn10Anuraag S. Parikh11Itay Tirosh12Joseph Dougherty13Sidharth V. Puram14Department of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine, St. Louis, MO 63110, USADepartment of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USADepartment of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, IsraelDepartment of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine, St. Louis, MO 63110, USADepartment of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine, St. Louis, MO 63110, USADepartment of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine, St. Louis, MO 63110, USADepartment of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine, St. Louis, MO 63110, USADepartment of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine, St. Louis, MO 63110, USADepartment of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine, St. Louis, MO 63110, USADivision of Head and Neck Oncology, Department of Otolaryngology—Head and Neck Surgery, The James Cancer Hospital and Solove Research Institute, The Ohio State University, Columbus, OH 43210, USADepartment of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine, St. Louis, MO 63110, USADivision of Head and Neck Oncology, Department of Otolaryngology—Head and Neck Surgery, The James Cancer Hospital and Solove Research Institute, The Ohio State University, Columbus, OH 43210, USADepartment of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 7610001, IsraelDepartment of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine, St. Louis, MO 63110, USADepartment of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine, St. Louis, MO 63110, USAComplexities 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 (T<sub>regs</sub>) were the major contributor to this improved survival. Lastly, we assessed gene expression, specifically in the T<sub>reg</sub> population, and found that TNFRSF4 (Tumor Necrosis Factor Receptor Superfamily Member 4) was differentially expressed in the core T<sub>reg</sub> subpopulation. Moreover, higher TNFRSF4 expression was associated with greater survival, suggesting that TNFRSF4 could play a key role in mechanisms underlying the contribution of T<sub>reg</sub> in HNSCC outcomes.https://www.mdpi.com/2072-6694/13/6/1230head and neck squamous cell carcinomadeconvolutionsingle-cell RNA sequencingregulatory T-cells |
| spellingShingle | Zongtai Qi Yating Liu Michael Mints Riley Mullins Reilly Sample Travis Law Thomas Barrett Angela L. Mazul Ryan S. Jackson Stephen Y. Kang Patrik Pipkorn Anuraag S. Parikh Itay Tirosh Joseph Dougherty Sidharth V. Puram Single-Cell Deconvolution of Head and Neck Squamous Cell Carcinoma Cancers head and neck squamous cell carcinoma deconvolution single-cell RNA sequencing regulatory T-cells |
| title | Single-Cell Deconvolution of Head and Neck Squamous Cell Carcinoma |
| title_full | Single-Cell Deconvolution of Head and Neck Squamous Cell Carcinoma |
| title_fullStr | Single-Cell Deconvolution of Head and Neck Squamous Cell Carcinoma |
| title_full_unstemmed | Single-Cell Deconvolution of Head and Neck Squamous Cell Carcinoma |
| title_short | Single-Cell Deconvolution of Head and Neck Squamous Cell Carcinoma |
| title_sort | single cell deconvolution of head and neck squamous cell carcinoma |
| topic | head and neck squamous cell carcinoma deconvolution single-cell RNA sequencing regulatory T-cells |
| url | https://www.mdpi.com/2072-6694/13/6/1230 |
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