Single-cell RNA sequencing reveals TCR ⁺ macrophages in HPV-related head and neck squamous cell carcinoma

Abstract Tumor progression and the efficacy of immunotherapy are strongly influenced by the composition and abundance of immune cells in the tumor microenvironment. Due to the limitations of direct measurement methods, computational algorithms are often used to infer immune cell composition from bulk tumor transcriptome profiles. These estimated tumor immune infiltrate populations have been associated with genomic and transcriptomic changes in the tumors, providing insight into tumor–immune interactions. However, such investigations on large-scale public data remain challenging. To lower the barriers for the analysis of complex tumor–immune interactions, we significantly improved our previous web platform TIMER. Instead of just using one algorithm, TIMER2.0 (http://timer.cistrome.org/) provides more robust estimation of immune infiltration levels for The Cancer Genome Atlas (TCGA) or user-provided tumor profiles using six state-of-the-art algorithms. TIMER2.0 provides four modules for investigating the associations between immune infiltrates and genetic or clinical features, and four modules for exploring cancer-related associations in the TCGA cohorts. Each module can generate a functional heatmap table, enabling the user to easily identify significant associations in multiple cancer types simultaneously. Overall, the TIMER2.0 web server provides comprehensive analysis and visualization functions of tumor infiltrating immune cells.

Understanding global communications among cells requires accurate representation of cell-cell signaling links and effective systems-level analyses of those links. We construct a database of interactions among ligands, receptors and their cofactors that accurately represent known heteromeric molecular complexes. We then develop CellChat, a tool that is able to quantitatively infer and analyze intercellular communication networks from single-cell RNA-sequencing (scRNA-seq) data. CellChat predicts major signaling inputs and outputs for cells and how those cells and signals coordinate for functions using network analysis and pattern recognition approaches. Through manifold learning and quantitative contrasts, CellChat classifies signaling pathways and delineates conserved and context-specific pathways across different datasets. Applying CellChat to mouse and human skin datasets shows its ability to extract complex signaling patterns. Our versatile and easy-to-use toolkit CellChat and a web-based Explorer (http://www.cellchat.org/) will help discover novel intercellular communications and build cell-cell communication atlases in diverse tissues.

Most head and neck cancers are derived from the mucosal epithelium in the oral cavity, pharynx and larynx and are known collectively as head and neck squamous cell carcinoma (HNSCC). Oral cavity and larynx cancers are generally associated with tobacco consumption, alcohol abuse or both, whereas pharynx cancers are increasingly attributed to infection with human papillomavirus (HPV), primarily HPV-16. Thus, HNSCC can be separated into HPV-negative or HPV-positive HNSCC. Despite evidence of histological progression from cellular atypia through various degrees of dysplasia, ultimately leading to invasive HNSCC, most patients are diagnosed with late-stage HNSCC without a clinically evident antecedent premalignant lesion. Traditional staging of HNSCC using the tumour-node-metastasis system has been supplemented by the 2017 AJCC/UICC staging system, which incorporated additional information relevant to HPV-positive disease. The treatment approach is generally multimodal, consisting of surgery followed by chemotherapy plus radiation (chemoradiation or CRT) for oral cavity cancers and primary CRT for pharynx and larynx cancers. The EGFR monoclonal antibody cetuximab is generally used in combination with radiation in HPV-negative HNSCC where co-morbidities prevent the use of cytotoxic chemotherapy. The FDA approved the immune checkpoint inhibitors pembrolizumab and nivolumab for treatment of recurrent or metastatic HNSCC and pembrolizumab as primary treatment for unresectable disease. Elucidation of the molecular genetic landscape of HNSCC over the past decade has revealed new opportunities for therapeutic intervention. Ongoing efforts aim to integrate our understanding of HNSCC biology and immunobiology to identify predictive biomarkers that will enable delivery of the most effective, least toxic therapies.