Comprehensive analysis of prognostic gene signatures based on immune infiltration of ovarian cancer
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RESEARCH ARTICLE
Open Access
Comprehensive analysis of prognostic gene signatures based on immune infiltration of ovarian cancer Shibai Yan1, Juntao Fang2, Yongcai Chen3, Yong Xie3, Siyou Zhang3, Xiaohui Zhu4* and Feng Fang3*
Abstract Background: 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. 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. Methods: Based 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. Results: A 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). Conclusion: The present study identified five prognostic genes associated with immune infiltration of OV, which may provide some potential clinical implications for OV treatment. Keywords: Ovarian cancer (OV), Single-sample gene set enrichment analysis (ssGSEA), Immune infiltration, Prognosis
Background 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. Despite aggressive frontline treated with surgery and adjuvant chemotherapy, the overall survival rate of * Correspondence: [email protected]; [email protected] 4 Department of Pharmacology, College of Pharmacy, Shenzhen Technology University, Shenzhen 518118, Guangdong, China 3 Department of Obstetrics and Gynecology, The First People’s Hospital of Foshan, 81 Lingnan North Avenue, Foshan 528000, Guangdong, China Full list of author information is available at the end of the article
5 years is still about 30% for most women diagnosed with advanced stages III/IV disease [1–3]. Tumour microenvironment (TME) is the primary or metastatic niche, in which tumour cells cooperate with the host stroma, such as various immune cells, endothelial cells, fibroblasts and metabolites. Recently, TME is playing an increasingly important role in the beg
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