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Development and validation of an immune-related prognostic signature in cervical cancer

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Abstract Background Cervical cancer is the fourth most frequently gynecological malignancy across the world. Immunotherapies have proved to improve prognosis of cervical cancer. However, few studies on immune-related prognostic signature had been reported in cervical cancer. Methods Raw data and clinical information of cervical cancer samples were download from TCGA and UCSC Xena website. Immunophenoscore of immune infiltration cells in cervical cancer samples was calculated through ssGSEA method using GSVA package. WGCNA, Cox regression analysis, LASSO analysis and GSEA analysis were performed to classify cervical cancer prognosis and explore the biological signaling pathway. Results There were 8 immune infiltration cells associated with prognosis of cervical cancer. Through WGCNA, 153 genes from 402 immune-related genes were significantly correlated with prognosis of cervical cancer. A 15-gene signature demonstrated powerful predictive ability in prognosis of cervical cancer. GSEA analysis showed multiple signaling pathways containing PD-L1 expression and PD-1 checkpoint pathway differences between high risk and low risk groups. Furthermore, the 15-gene signature was associated with multiple immune cells and immune infiltration in tumor microenvironment. Conclusion The 15-gene signature is an effective potential prognostic classifier in the immunotherapies and surveillance of cervical cancer.
Title: Development and validation of an immune-related prognostic signature in cervical cancer
Description:
Abstract Background Cervical cancer is the fourth most frequently gynecological malignancy across the world.
Immunotherapies have proved to improve prognosis of cervical cancer.
However, few studies on immune-related prognostic signature had been reported in cervical cancer.
Methods Raw data and clinical information of cervical cancer samples were download from TCGA and UCSC Xena website.
Immunophenoscore of immune infiltration cells in cervical cancer samples was calculated through ssGSEA method using GSVA package.
WGCNA, Cox regression analysis, LASSO analysis and GSEA analysis were performed to classify cervical cancer prognosis and explore the biological signaling pathway.
Results There were 8 immune infiltration cells associated with prognosis of cervical cancer.
Through WGCNA, 153 genes from 402 immune-related genes were significantly correlated with prognosis of cervical cancer.
A 15-gene signature demonstrated powerful predictive ability in prognosis of cervical cancer.
GSEA analysis showed multiple signaling pathways containing PD-L1 expression and PD-1 checkpoint pathway differences between high risk and low risk groups.
Furthermore, the 15-gene signature was associated with multiple immune cells and immune infiltration in tumor microenvironment.
Conclusion The 15-gene signature is an effective potential prognostic classifier in the immunotherapies and surveillance of cervical cancer.

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