Abstract
BackgroundOvarian cancer (OV) is one of the most common malignant tumors of gynecology oncology. The lack of effective early diagnosis methods and treatment strategies result in a low five-year survival rate. Also, immunotherapy plays an important auxiliary role in the treatment of advanced OV patient, so it is of great significance to find out effective immune-related tumor markers for the diagnosis and treatment of OV.MethodsBased on the consensus clustering analysis of single-sample gene set enrichment analysis (ssGSEA) score transformed via The Cancer Genome Atlas (TCGA) mRNA profile, we obtained two groups with high and low levels of immune infiltration. Multiple machine learning methods were conducted to explore prognostic genes associated with immune infiltration. Simultaneously, the correlation between the expression of mark genes and immune cells components was explored.ResultsA prognostic classifier including 5 genes (CXCL11, S1PR4, TNFRSF17, FPR1 and DHRS95) was established and its robust efficacy for predicting overall survival was validated via 1129 OV samples. Some significant variations of copy number on gene loci were found between two risk groups and it showed that patients with fine chemosensitivity has lower risk score than patient with poor chemosensitivity (P = 0.013). The high and low-risk groups showed significantly different distribution (P < 0.001) of five immune cells (Monocytes, Macrophages M1, Macrophages M2, T cells CD4 menory and T cells CD8).ConclusionThe present study identified five prognostic genes associated with immune infiltration of OV, which may provide some potential clinical implications for OV treatment.
Highlights
Ovarian cancer (OV) is one of the most common malignant tumors of gynecology oncology
Determination of trait genes of immune infiltration for OV A total of 1129 OV samples obtained from training set (n = 365), validation set 1 (n = 93), validation set 2 (n = 291) and validation set 3 (n = 380) were extracted for further analysis (Table 1)
There are 1398 differentially expressed genes obtained via limma package between high and low immune infiltration groups (Fig. 3a)
Summary
Ovarian cancer (OV) is one of the most common malignant tumors of gynecology oncology. The lack of effective early diagnosis methods and treatment strategies result in a low five-year survival rate. Immunotherapy plays an important auxiliary role in the treatment of advanced OV patient, so it is of great significance to find out effective immune-related tumor markers for the diagnosis and treatment of OV. Ovarian cancer (OV), a highly malignant gynecologic tumour, is the leading cause of cancer-related mortality in women, and lack of specific symptoms at the early stage. TME is playing an increasingly important role in the beginning and development of OV as well as anti-tumour treatment [4].
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