AUTHOR=Li Xiushen , Liang Weizheng , Zhao Huanyi , Jin Zheng , Shi Guoqi , Xie Wanhua , Wang Hao , Wu Xueqing 

TITLE=Immune Cell Infiltration Landscape of Ovarian Cancer to Identify Prognosis and Immunotherapy-Related Genes to Aid Immunotherapy

JOURNAL=Frontiers in Cell and Developmental Biology

VOLUME=Volume 9 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2021.749157

DOI=10.3389/fcell.2021.749157

ISSN=2296-634X

ABSTRACT=Ovarian cancer (OC) is the second most common cause of death in gynecological cancer. Studies have shown that the efficacy of tumor immunotherapy is related to tumor immune cell infiltration (ICI). However, so far, the immune invasion information of tumor microenvironment (TME) in OC has not been elucidated. In this study, We organized the transcriptome data of OC in the TCGA and GEO databases, evaluated the patient’s TME invasion information, and constructed the ICI score to predict the clinical benefits of patients undergoing immunotherapy. Immune-related genes were further used to construct the prognostic model. We found ICI gene cluster C had the best prognosis, and the proportion of macrophage M1 and T cell follicular helper was the highest. This result was consistent with that of multivariate cox (multi-cox) analysis. The prognostic model constructed by immune-related genes had good predictive performance. By calculating TMB, we also found that there were multiple genes with statistically different mutation frequencies in the high and low ICI score groups. The model based on the ICI score may help to screen out patients who would benefit from immunotherapy. The immune-related genes screened may be used as biomarkers and therapeutic targets.