Introduction:
Immunotherapy has significantly advanced HNSCC treatment, however the response rate is only 15 – 20% due to factors in the TME formed by stroma, cancer and immune cells. Studying heterogeneous cell populations is greatly facilitated by the recent development of single-cell RNA sequencing, a technique that can be leveraged to investigate the transcriptomic composition of individual cells to determine their origin as well as current functional state.
Methods:
Fresh HNSCC specimens with matched blood from treatment-naïve patients were processed. Tumor tissue was dissociated manually and enzymatically. Cell suspensions were stained and sorted into CD45-positive and -negative cells. Subsequently, 3' single cell libraries were created on the 10x Genomics workflow and sequenced on a NextSeq500 (Illumina). Cells were aggregated, normalized and bioinformatic analysis was performed using Python (scampy).
Results:
80'214 single cells were generated from 15 patients with a median of 1105 genes each. Clustering analysis identified major cell types in the immune cell compartment – T cells, B cells and myeloid cells – as well as the stroma – fibroblasts and endothelial cells. The relative distribution of each cell type was compared across patients. Therapeutically important cell sub-states – e.g. activated regulatory T cells (Treg) and exhausted cytotoxic T cells – were identified. Cell maturation was modeled using pseudo-time analysis.
Conclusions:
The tumor microenvironment in HNSCC is characterized by an abundance of different cell types and even more granular cell states. Single cell RNA sequencing allows an unprecedented deep and broad look into the TME, helping to identify rare cell populations and new putative therapeutic targets.
