Background
Oral squamous cell carcinoma (OSCC) is a highly heterogeneous neoplasm where the identification of heterogeneity is a critical clinical need to improve treatment planning and prognosis prediction. Utilizing the Hyperion imaging system to carry out high-dimensional proteomics analysis on the heterogeneity of tumor samples, this study aims to detect and analyze the heterogeneity of OSCC without lymph node metastasis and explore potential contributing factors for poor prognosis of early-stage OSCC.
Conclusions
High-dimensional proteomics analyses using the Hyperion imaging system help identify and analyze the tumor microenvironment heterogeneity of OSCC. Our study now presents this valuable resource and explains the potential reasons behind early OSCC patients' poor prognosis.
Methods
We collected tumor tissue samples from four OSCC patients at the T1N0M0 stage, who presented with similar clinical manifestations. Patient formalin-fixed, paraffin-embedded (FFPE) tissue sections were prepared and stained using a panel of 26 immune or tumor-related antibodies. Different metal tags were assigned to each antibody. The stained cells were then detected and analyzed by the Hyperion imaging system.
Results
Tumor samples of four OSCC patients presenting with similar clinical characteristics at the T1N0M0 stage had different cell subtypes, including CD4+ T cells, CD8+ T cells, CD19+ B cells, CD11c+ dendritic cells, CD56+ natural killer cells, granulocytes, etc. More immunosuppressive cells were found in the sample of patient 1. We propose that differences in the tumor microenvironment of samples may contribute to different patients' prognosis in the future. Conclusions: High-dimensional proteomics analyses using the Hyperion imaging system help identify and analyze the tumor microenvironment heterogeneity of OSCC. Our study now presents this valuable resource and explains the potential reasons behind early OSCC patients' poor prognosis.