Immune landscape of papillary thyroid cancer and immunotherapeutic implications

Author:

Na Kwon Joong,Choi Hongyoon

Abstract

Although papillary thyroid cancer (PTC) is curable with excellent survival rate, patients with dedifferentiated PTC suffer the recurrence or death. As cancer immune escape plays a critical role in cancer progression, we aimed to investigate the relationship between differentiation and immune landscape of PTC and its implications for immunotherapy. Using The Cancer Genome Atlas data, we estimated the immune cell enrichment scores and overall immune infiltration, ImmuneScore, to characterize the immune landscape of PTC. Thyroid differentiation score (TDS) was calculated from 16 thyroid function genes. We demonstrated that ImmuneScore had a significant negative correlation with TDS, and BRAFV600E+ tumors showed significantly low TDS and high ImmuneScore. Enrichment scores of myeloid cells and B-cells were negatively correlated with TDS, while those of plasma cells were positively correlated with TDS. In addition, the association between TDS, ImmuneScore and immunosuppressive markers (CTLA-4, PD-L1, HLA-G) were evaluated according to BRAFV600E status. All immunosuppressive markers expression had a significant negative correlation with TDS, and they were significantly higher in BRAFV600E+ status. Subgroups were divided by median values of TDS and ImmuneScore, and immunosuppressive markers of these subgroups were compared. The immunosuppressive markers expression was the highest in high ImmuneScore and low TDS subgroup. Furthermore, ImmuneScore had a significant association with recurrence-free survival, irrespective of clinicopathologic factors including BRAFV600E status. These findings based on gene expression data illuminate the immune landscape of PTC and its association with TDS, immunosuppressive markers and recurrence. Our results would be extended to investigate immunotherapeutic approaches in PTC.

Publisher

Bioscientifica

Subject

Cancer Research,Endocrinology,Oncology,Endocrinology, Diabetes and Metabolism

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