Integrated Analysis of Tumor‑Associated Macrophage Infiltration and Prognosis in Ovarian Cancer

Abstract BackgroundMost ovarian cancer patients with poor prognosis and immune microenvironment play a vital role in the progression of ovarian cancer. We aim to develop a tumor-associated macrophage related gene (TAMRGs) prognostic signature that can stratify and predict overall survival for ovarian cancer.MethodsWe acquired single cell and bulk transcriptome raw data of ovarian cancer from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The immune landscape was identified in primary and ascites of ovarian cancer. CIBERSORT deconvolution algorithm, Weighted gene co-expression network analysis (WGCNA), univariate cox analysis, LASSO algorithm, and multivariate cox analysis were performed for the identification of TAMRG and the development of prognostic signature.Results We identified inter-and intra-patient heterogeneity for immune infiltration cells at a single-cell resolution. Tumor infiltration macrophages showed immunosuppressive characteristics with an M2 phenotype. T cell CD4 memory activated, mast cell activated, neutrophils and macrophages M2 were negatively correlated with overall survival, while macrophages M1 was positively correlated. A total of 219 TAMRGs were identified and a novel 6-gene signature (TAP1, CD163, VSIG4, IGKV4-1, CD3E, and MS4A7) with superior prognostic independence was established.ConclusionsThe TAMRG-based signature is expected to be a promising target for prognosis and treatment response of ovarian cancer.