Gene Expression Profiles Infer — The Landscape of Tumor-Infiltrating Immune Cells in Ovarian Cancer and their Clinical Significance

Background: Infiltration of immune cells associated with tumor clinical results affects different cancers. However, the composition and the clinical significance of tumor-infiltrated immune cells in epithelial ovarian cancer has not been completely investigated. Methods: The metagene deconvolution algorithm (Cell type Identification by Estimating Relative Subsets of known RNA Transcripts (CIBERSORT)) was used to analyze gene expression profiles in public databases (GEO and TCGA) to infer the composition of 22 immune cell subgroups in ovarian tumors. The proportions obtained in this study were used to investigate the association between each cell type and the clinical outcomes for ovarian cancer diagnosis and prognosis. Quantitative real-time polymerase chain reaction (qRT-PCR) was used for detecting the expression levels of related genes. Results: The profiles of immune cells infiltration were altered in malignant ovarian neoplastic tissue. Ovarian cancer tissues contained higher proportion of T follicular helper cells (Tfh) and macrophages (M0 and M1) rather than the normal ovarian tissue. Meanwhile, lower proportion of monocytes and neutrophils was also observed in ovarian cancer tissues compared with normal tissues. The qRT-PCR test confirmed the conclusion that the contents of CD80 (M1 cells) and CD4+ (Tfh cells) were high in the interstitium of ovarian cancer tissue, while the contents of CD21 (B cells) and CD66b (neutrophil) were low. Interestingly, immune cell infiltration was observed to be correlated with the change in clinical outcome. The activated mast cell subpopulation was associated with poor prognosis, while the subpopulation of resting dendritic cells was correlated with pathological grade of the ovarian cancer. Conclusions: Our bioanalysis revealed that the composition of tumor-infiltrating immune cells was closely related to the clinical outcome of ovarian cancer, which was also validated in clinical samples. These results provide a new strategic basis for the prognosis and treatment of ovarian cancer.