Abstract
Objective: To understand the immune characteristics of the ovarian cancer (OC) microenvironment and explore the differences of immune-related molecules and cells to establish an effective risk model and identify the molecules that significantly affected the immune response of OC, to help guide the diagnosis.Methods: First, we calculate the TMEscore which reflects the immune microenvironment, and then analyze the molecular differences between patients with different immune characteristics, and determine the prognostic genes. Then, the risk model was established by least absolute shrinkage and selection operator (LASSO) analysis and combined with clinical data into a nomogram for diagnosis and prediction. Subsequently, the potential gene CLEC5A influencing the immune response of OC was identified from the prognostic genes by integrative immune-stromal analysis. The genomic alteration was explored based on copy number variant (CNV) and somatic mutation data.Results: TMEscore was a prognostic indicator of OC. The prognosis of patients with high TMEscore was better. The risk model based on immune characteristics was a reliable index to predict the prognosis of patients, and the nomogram could comprehensively evaluate the prognosis of patients. Besides, CLEC5A was closely related to the abundance of immune cells, immune response, and the expression of immune checkpoints in the OC microenvironment. OC cells with high expression of CLEC5A increased the polarization of M2 macrophages. CLEC5A expression was significantly associated with TTN and CDK12 mutations and affected the copy number of tumor progression and immune-related genes.Conclusion: The study of immune characteristics in the OC microenvironment and the risk model can reveal the factors affecting the prognosis and guide the clinical hierarchical treatment. CLEC5A can be used as a potential key gene affecting the immune microenvironment remodeling of OC, which provides a new perspective for improving the effect of OC immunotherapy.
Highlights
Ovarian cancer (OC) is a kind of malignant tumor with a poor prognosis, and its mortality rate ranks second in gynecological cancer mortality (Bray et al, 2018)
The RNA-seq expression profile data and clinical information of OC patients were downloaded from the International Cancer Genome Consortium (ICGC) OV-AU (Ovarian cancerAustralia) database,2 and samples were excluded for patients without survival information, which are used for subsequent validation
By integrating the expression data and clinical data (OS >1 month, precise pathological stage), 339 OC samples were obtained for the generation of the TMEscore (Figure 2A)
Summary
Ovarian cancer (OC) is a kind of malignant tumor with a poor prognosis, and its mortality rate ranks second in gynecological cancer mortality (Bray et al, 2018). The immune microenvironment of tumor tissue can reflect the response rate to immunotherapy and chemotherapy (Rosenberg et al, 2016; Jiang et al, 2018). The immune cell components in TME are the basis for determining tumor fate and the cells’ ability to invade and metastasize (Melaiu et al, 2019; Vitale et al, 2019; Xiao et al, 2019). Their composition and interactions within the TME are closely related to clinical outcomes in cancer patients. Understanding the differences of the immune microenvironment in OC may be an essential step in finding prognostic markers, stratifying patients before treatment, and prolonging life expectancy in OC patients
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