Landscape of Immune Microenvironment in Epithelial Ovarian Cancer and Establishing Risk Model by Machine Learning.

Shiyi Liu ,Wei Tan,Shu Xian,Min Hu,Li Zhang,Feiyan Wang ,Yanxiang Cheng ,Y Zheng ,Dongyong Yang ,Yanqing Wang ,Zhanfeng Deng ,Mali Wu ,Mengqin Yuan ,Jian‐Qing He ,Yu-Wei Zhang ,Zitao Wang ,Fangfang Dai ,Ronghui Zhu ,Yeqiang Liu

doi:10.1155/2021/5523749

Abstract

Background Epithelial ovarian cancer (EOC) is an extremely lethal gynecological malignancy and has the potential to benefit from the immune checkpoint blockade (ICB) therapy, whose efficacy highly depends on the complex tumor microenvironment (TME). Method and Result We comprehensively analyze the landscape of TME and its prognostic value through immune infiltration analysis, somatic mutation analysis, and survival analysis. The results showed that high infiltration of immune cells predicts favorable clinical outcomes in EOC. Then, the detailed TME landscape of the EOC had been investigated through “xCell” algorithm, Gene set variation analysis (GSVA), cytokines expression analysis, and correlation analysis. It is observed that EOC patients with high infiltrating immune cells have an antitumor phenotype and are highly correlated with immune checkpoints. We further found that dendritic cells (DCs) may play a dominant role in promoting the infiltration of immune cells into TME and forming an antitumor immune phenotype. Finally, we conducted machine-learning Lasso regression, support vector machines (SVMs), and random forest, identifying six DC-related prognostic genes (CXCL9, VSIG4, ALOX5AP, TGFBI, UBD, and CXCL11). And DC-related risk stratify model had been well established and validated. Conclusion High infiltration of immune cells predicted a better outcome and an antitumor phenotype in EOC, and the DCs might play a dominant role in the initiation of antitumor immune cells. The well-established risk model can be used for prognostic prediction in EOC.

Highlights

Ovarian cancer is the second leading cause of cancer death in adult women, and the epithelial ovarian cancer (EOC) is the most common histological subtype characterized by complex adjacent anatomical structures, high-degree malignancy, and heterogeneity [1, 2]. e surgical excision and chemotherapy are effective for Epithelial ovarian cancer (EOC) patients, but a large fraction of EOC patients will subsequently relapse and develop to chemoresistance, which seriously shortens the patients’ clinical survival [3].Nowadays, the immune checkpoint blockades (ICBs) have received wide attention and have emerged as efficient agents for tumor therapy
It has been proposed to be valuable in diagnosis and prognosis in a wide range of tumors, but the utility on EOC Journal of Oncology has not been investigated in detail [6]. e immune cells are a master component in tumor microenvironment (TME), composed of CD8+ cytotoxic T lymphocytes (CTLs), B cells, plasma cells, macrophages, and dendritic cells (DCs) [7,8,9]. e class II major histocompatibility complex- (MHC-I-) restricted CTLs implicated as critical components in antitumor immunity, contributing to tumor killing [10]
We found that the immune cells were highly infiltrated into TME in carcinogenesis and predict a better clinical outcome in EOC, which are consistent with the study by Hao et al [32], that the immune score can be used as a powerful predictive tool for both prognosis and chemotherapeutic sensitivity of EOC

Summary

Introduction

The immune checkpoint blockades (ICBs) have received wide attention and have emerged as efficient agents for tumor therapy. Epithelial ovarian cancer (EOC) is an extremely lethal gynecological malignancy and has the potential to benefit from the immune checkpoint blockade (ICB) therapy, whose efficacy highly depends on the complex tumor microenvironment (TME). E results showed that high infiltration of immune cells predicts favorable clinical outcomes in EOC. We further found that dendritic cells (DCs) may play a dominant role in promoting the infiltration of immune cells into TME and forming an antitumor immune phenotype. High infiltration of immune cells predicted a better outcome and an antitumor phenotype in EOC, and the DCs might play a dominant role in the initiation of antitumor immune cells. High infiltration of immune cells predicted a better outcome and an antitumor phenotype in EOC, and the DCs might play a dominant role in the initiation of antitumor immune cells. e well-established risk model can be used for prognostic prediction in EOC

Methods

Results

Discussion

Conclusion