Profiles of immune infiltration in ovarian cancer and their clinical significance: A gene expression-based study

Abstract

Objective: The effect of immune cell infiltration on the prognosis of ovarian cancer (OC) has not yet been intensively investigated. Methods: In the present study, by using a deconvolution algorithm (known as CIBERSORT) and clinical annotated expression profiles (GEO and TCGA), we comprehensively analyzed the tumor-infiltrating immune cells (TIICs) present in OC and their effect on the prognosis and progression of OC. Results: A fraction of 22 immune cell subpopulations was evaluated to determine the associations between each cell type and survival. Of the cell subpopulations investigated, follicular helper T cells, monocytes, and macrophages M0 and M1 significantly varied between normal ovarian surface epithelium and OC tumors. The proportion of CD8+ T cells and M0 macrophages was moderately correlated (Pearson correlation = 0.48) in the TCGA. Resting dendritic cells were higher in grade 1 cells after GEO datasets were pooled. Resting dendritic cells showed higher proportion in stage II than in stage III/IV tumors. In TCGA, a higher proportion of neutrophils cell implied poor prognosis compared with the lower. In GEO datasets, the high proportions of CD8 T cells, activated dendritic cells, and plasma cells indicated better survival time comparing with the lower. Conclusion: Collectively, our data suggest that subtle differences appear to exist in the cellular composition of the immune cell infiltrate in OC, and these differences are likely to be the important determinants of both prognosis and response to treatment.