A panel of seven immune-related genes can serve as a good predictive biomarker for cervical squamous cell carcinoma - Dai, Junshang; Pan, Yuwen; Chen, Yili; Yao, Shuzhong (Frontiers in Genetics, 2022)
Objective: Cervical cancer is one of the most common gynecological malignancies. The interaction between tumor microenvironment and immune infiltration is closely related to the progression of cervical squamous cell carcinoma (CSCC) and patients’ prognosis. Herein, a panel of immune-related genes was established for making a more accurate prognostic prediction. Methods: The transcriptome information of CSCC tissues and normal cervix samples was obtained from TCGA-CSCC and GTEx and defined differentially expressed genes (DEGs) from it. Immune-related genes (IRGs) were retrieved from the ImmPort database. After removing the transcriptome data not mentioned in GSE44001 from the GEO database, IR-DEGs were preliminarily identified. The TCGA-CSCC samples were divided into training set and internal validation set (3:1) randomly. Univariate Cox analysis, LASSO regression analysis and multivariate Cox analysis were used in turn to construct the immune-related signature to predict the overall survival (overall survival) and disease-free survival (DFS) of CSCC patients. Afterwards, external validation was performed in GSE44001 cohort, and initial clinical validation was performed by qRT-PCR in samples from our clinical center. Function enrichment analysis and immune infiltration analysis were performed, as well as a nomogram was drawn based on the signature. Results: A prognostic prediction signature consisting of 7 IR-DEGs was established. The high expression of NRP1, IGF2R, SERPINA3, TNF and the low expression of ICOS, DES, HCK suggested that CSCC patients had shorter OS (POS<0.001) and DFS (PDFS<0.001). AUC values of 1-, 3-, 5- year OS were 0.800, 0.831 and 0.809, respectively. The nomogram also showed good predictability. Functional enrichment analysis and immune infiltration analysis indicated that patients in high-risk group had lower immune infiltration, weaker immune function, and were more likely to benefit from immune checkpoint inhibitor therapy. Conclusion: The signature we constructed can be used as an independent prediction factor of CSCC patients’ prognosis, and the nomogram base on it has similar prediction performance. In all, the immune-related signature can provide strong support for prediction of prognosis and response to immunotherapy through stratify CSCC patients into subgroups.