Construction of an Immune Cell Infiltration Score to Evaluate the Prognosis and Therapeutic Efficacy of Ovarian Cancer Patients - Liu, Jinhui; Wang, Yichun; Yuan, Shuning; Wei, Junting; Bai, Jianling (Frontiers in Immunology, 2021)
Background: Ovarian cancer (OC) is an immunogenetic disease which contains tumor-infiltrating lymphocytes (TILs) and immunotherapy has become a novel treatment for OC. With the development of NGS, profiles of gene expression and comprehensive landscape of immune cells can be applied to predict clinical outcome and response to immunotherapy. Methods: We obtained data from TCGA and GEO databases and applied two computational algorithms (CIBERSORT and ESTIMATE) for consensus clustering of immune cells. Patients were divided into two subtypes using on immune cell infiltration (ICI) levels. Then, differentially expressed genes (DEGs) associated with immune cell infiltration (ICI) level were identified. We also constructed ICI score after principle-component analysis (PCA) for dimension reduction. Results: Patients in ICI cluster B had better survival than in ICI cluster A. After construction of ICI score, we found high-ICI score had better clinical OS, as well as significantly higher tumor mutation burden (TMB). According to the expression of immune checkpoints, the results showed that patients in high ICI group showed high expression of CTLA4, PD1, PD-L1 and PD-L2 which implies that they might benefit from immunotherapy. Besides, patients in high ICI group showed higher sensitivity to two first-line chemotherapy drugs (Paclitaxel and Cisplatin). Conclusion: ICI score is an effective prognosis related biomarker for OC and can provide valuable information on the potential response to immunotherapy.