Abstract
Ovarian cancer (OC) is the second leading cause of death in gynecological cancer. Multiple study have shown that the efficacy of tumor immunotherapy is related to tumor immune cell infiltration (ICI). However, so far, the Immune infiltration landscape of tumor microenvironment (TME) in OC has not been elucidated. In this study, We organized the transcriptome data of OC in the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, evaluated the patient’s TME information, and constructed the ICI scores to predict the clinical benefits of patients undergoing immunotherapy. Immune-related genes were further used to construct the prognostic model. After clustering analysis of ICI genes, we found that patients in ICI gene cluster C had the best prognosis, and their tumor microenvironment had the highest proportion of macrophage M1 and T cell follicular helper cells. 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 estimating Tumor mutation burden (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.
Highlights
Ovarian cancer (OC) is one of the deadliest gynecological malignancies
The ratio of 22 immune cells in OC samples was calculated by executing the CIBERSORT algorithms (Supplementary Table S2)
According to the obtained 817 differentially expressed genes, the OC patients were divided into five gene subgroups by using the “ConsensuClusterPlus” R package based on the unsupervised clustering algorithm (Supplementary Figure S2, Figure 3A)
Summary
Ovarian cancer (OC) is one of the deadliest gynecological malignancies. Owing to the lack of specific symptoms and early detection methods, approximately three-quarters of patients are already in stage III/IV at the time of diagnosis (Cheng et al, 2021). Cancer immunotherapy, based on the mechanism of immune escape, was rated as Breakthrough of the Year by Science (Xiang et al, 2019). Tumor mutation burden (TMB), known as tumor mutational load, is an emerging feature of cancer, which represents the number of somatic mutations (per one million bases) (Zehir et al, 2017). The tumor microenvironment (TME), composed of a variety of immune and non-immune cell populations, plays an crucial role during tumor initiation and progression. The changes in the proportion of different immune cell populations and stromal cell populations in TME are related to the occurrence, metastasis, chemoresistance and progression of tumors (Turley et al, 2015). The overall landscape of immune cells and non-immune cells in the TME of OC is not yet clear
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