JSON
Jimenez DG, Altunbulakli C, Swoboda S, Sobti A, Askmyr D, Ali A, Greiff L, Lindstedt M
Front Immunol 13 (-) 1087843 [2023-01-19; online 2023-01-19]
The incidence of human papillomavirus-positive (HPV+) tonsillar cancer has been sharply rising during the last decades. Myeloid cells represent an appropriate therapeutic target due to their proximity to virus-infected tumor cells, and their ability to orchestrate antigen-specific immunity, within the tonsil. However, the interrelationship of steady-state and inflammatory myeloid cell subsets, and their impact on patient survival remains unexplored. Here, we used single-cell RNA-sequencing to map the myeloid compartment in HPV+ tonsillar cancer. We observed an expansion of the myeloid compartment in HPV+ tonsillar cancer, accompanied by interferon-induced cellular responses both in dendritic cells (DCs) and monocyte-macrophages. Our analysis unveiled the existence of four DC lineages, two macrophage polarization processes, and their sequential maturation profiles. Within the DC lineages, we described a balance shift in the frequency of progenitor and mature cDC favoring the cDC1 lineage in detriment of cDC2s. Furthermore, we observed that all DC lineages apart from DC5s matured into a common activated DC transcriptional program involving upregulation of interferon-inducible genes. In turn, the monocyte-macrophage lineage was subjected to early monocyte polarization events, which give rise to either interferon-activated or CXCL-producing macrophages, the latter enriched in advanced tumor stages. We validated the existence of most of the single-cell RNA-seq clusters using 26-plex flow cytometry, and described a positive impact of cDC1 and interferon-activated DCs and macrophages on patient survival using gene signature scoring. The current study contributes to the understanding of myeloid ontogeny and dynamics in HPV-driven tonsillar cancer, and highlights myeloid biomarkers that can be used to assess patient prognosis.
Bioinformatics Support and Infrastructure [Collaborative]
Bioinformatics Support, Infrastructure and Training [Collaborative]
Clinical Genomics Lund [Service]
PubMed 36741389
DOI 10.3389/fimmu.2022.1087843
Crossref 10.3389/fimmu.2022.1087843