Background Ovarian cancer is one of the most lethal gynecological cancers,and is in the top five cancer types associated with death in women. Immune infiltration of ovarian cancer is a critical factor in determining patient's prognosis. In addition to immune infiltration, key mutations also have a greater impact on the development and prognosis of OV.Methods Using data from TCGA and GTEx database combined with WGCNA and ESTIMATE methods, genes related to OV occurrence and immune infiltration were identified. Lasso and multivariate Cox regression were applied to define a prognostic score (IGCI score) based on immune genes and clinical information. The IGCI score has been verified by K-M curves, ROC curves, C-index on test set. Based on mutation data from TCGA, we identified key mutations related to immune infiltration by Chi-squared tests and we also did survival analysis of these mutations.Results In this section, we found 46 genes related to disease occurrence and immune infiltration, IGCI score was established based on six factors: Age, White, Pharmaceutical, FGF7, CCR1 and CD14. In test set, IGCI score (C-index = 0.630) is significantly better than AJCC stage (C-index = 0.541, P < 0.05) and CIN25 (C-index = 0.571, P < 0.05). Chi-squared tests revealed that 6 mutations are significantly (P < 0.05) related to immune infiltration : BRCA1, ZNF462, VWF, RBAK, RB1, and ADGRV1. According to mutation survival analysis, we found another 5 key mutations significantly related to patient prognosis (P < 0.05): CSMD3, FLG2, HMCN1, TOP2A, TRRAP. RB1 and CSMD3 mutations had small p-value (P < 0.1) in both Chi-squared tests and survival analysis. Then we conducted a drug sensitivity analysis of key mutation and found when RB1 mutation occurs, the efficacy of six anti-tumor drugs has changed significantly (P < 0.05).Conclusion Based on immune-related genes and clinical information, we have established an ovarian cancer prognosis score that is superior to other methods. At the same time, RB1 and CSMD3 gene mutations are considered to be closely related to ovarian cancer immunity and prognosis.