Three Genes Predict Prognosis in Microenvironment of Ovarian Cancer

Abstract

Ovarian cancer (OC) is the deadliest gynecological cancer in women. Immune cell infiltration has a critical role in regulating carcinogenesis and prognosis in OC. To identify prognostic genes relevant to the tumor microenvironment in OC, we investigated the association between OC and gene expression profiles. Results obtained with the ESTIMATE R tool showed that immune score and stromal score were correlated with lymphatic invasion, and high immune score predicted a favorable prognosis. A total of 342 common differentially expressed genes were identified according to the two scores; these genes were mainly involved in immune response, extracellular region, and serine-type endopeptidase activity. Three immune-related prognostic genes were selected by univariate and multivariate Cox regression analysis. We further established a prognostic model and validated the prognostic value of three hub genes in different databases; our results showed that this model could accurately predict survival and evaluate prognosis independent of clinical characteristics. Three hub genes have prognostic value in OC. TIMER analysis revealed that the three genes were correlated with different immune cells. Low levels of macrophage infiltration and high levels of CD4+ T cell infiltration were associated with favorable survival outcomes. Arm-level gain of GYPC was correlated with neutrophils and dendritic cells. These findings indicate that CXCR4, GYPC, and MMP12 modulate prognosis via effects on the infiltration of immune cells. Thus, these genes represent potential targets for immune therapy in OC.

Keywords: The Cancer Genome Atlas; immune score; ovarian cancer; overall survival; stromal score; tumor microenvironment.

FIGURE 1

Immune and stromal scores are correlated with ovarian cancer clinical characters and their overall survival. (A,B) Distribution of immune and stromal scores of ovarian cancer anatomic neoplasm subdivision. (C,D) Distribution of immune and stromal scores of ovarian cancer stage. (E,F) Distribution of immune and stromal scores of ovarian cancer grade. (G,H) Distribution of immune and stromal scores of ovarian cancer lymphatic invasion. (I,J) Distribution of immune and stromal scores of ovarian cancer sample type. (K) Kaplan–Meier (KM) overall survival (OS) curve for high and low immune score group. (L) KM survival curve showing the OS time of high and low stomal score group.

FIGURE 2

Different expression genes based on immune scores and stromal scores in ovarian cancer. (A) Heat maps demonstrated the different expression genes (DEGs) between high immune scores low immune scores. P < 0.05, fold change > 1.5. (B) Heat map of DEGs between high stromal scores and low stromal scores. P < 0.05, fold change > 1.5. Red module represents high-expression genes; low-expression genes are shown in blue. (C) Volcano plot illustrated the DEGs based on immune scores. (D) Volcano plot displayed the DEGs based on stromal scores. Red dots represent upregulated genes, green dots represent downregulated genes. (E) Venn diagrams displayed the commonly upregulated genes in immune and stromal groups. (F) Venn diagrams showed the commonly downregulated genes.

FIGURE 3

Function enrichment analysis of 342 intersection genes. Top 10 enriched GO terms of 342 common DEGs. Significantly GO terms were identified using DAVID functional annotation tool (https://david.ncifcrf.gov/). FDR smaller than 0.05 was used as the criteria for significantly enriched. Enriched GO terms included three categories: biological process, cellular component, and molecular function.

FIGURE 4

Establishment and evaluation prognostic model. (A–C) Survival rates were calculated between high and low gene expression groups. The red line represents the high gene expression group, and the blue line represents the low gene expression group. (A) CXCR4, (B) MMP12, (C) GYPC. (D–F) Distribution of risk score ranking, survival status, and three DEGs’ expression heat map. (G) Survival curves of patients in the high-risk group and low-risk group. (H) 3- and 5-year ROC curves. ROC, receiver operating characteristic; AUC, area under the curve. (I,J) Univariate and multiple regression analysis was performed to assess the relationship between age, grade, stage, lymphatic invasion, subdivision, and risk scores.

FIGURE 5

Evaluation of the association between three prognostic signatures, immune cells, and survival. Three prognostic signatures associated with immune cell infiltration. (A) CXCR4, (B) MMP12, (C) GYPC. (D,E) Association of three prognostic signature mutants with immune cell infiltration. (D) The arm level gain of GYPC was correlated with neutrophils and dendritic cells. (E) The SCNA level of MMP12 was not significant with immune infiltration. Association between CXCR4 mutants with immune cell infiltration was not detected by the SCNA module of timer. (F) Survival analysis of differentially immune cells. Low infiltration level of macrophage cells and high infiltration level of CD4+ T cells correlated with favorable survival outcomes. Statistical significance was defined by a P value: *** means 0 ≤ P value < 0.001, ** represents 0.001 ≤ P value < 0.01, * represents 0.01 ≤ P value < 0.05, means 0.05 ≤ P value < 0.1.