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Cytl1 is a Key Target for Chemoradiotherapy Resistance in Locally Advanced Cervical Cancer: Based on Bioinformatics Analysis


 Background

Locally advanced cervical cancer (LACC), FIGO stage equal or more than IB1 is treated with chemotherapy and external beam radiotherapy followed by brachytherapy. However, treatment failure and distant metastasis still remain a major problem. Bioinformatics analysis was used to comprehensively evaluate the intrinsic resistance to treatment in LACC. We selected cytokine-like protein 1 (Cytl1), a novel cytokine, for validation by immunochemistry assays (IHC).

Materials and methods

The Gene Expression Omnibus (GEO) and the cancer genome atlas (TCGA) were analyzed to identify significant prognostic differentially expressed genes (DEGs). The CIBERSORT and ESTIMATE algorithms was performed to validate the genetic risk score model. A total of 113 tissues were evaluated by IHC. Kaplan-Meier curves and the log-rank test were applied for survival analysis.

Results

One thousand and twenty-one genes, consisting of 663 upregulated and 358 downregulated genes, were screened out in the GSE56363 cohort. KEGG and GO pathway enrichment methods was used to analyze the abundant DEGs to find the common characteristics. A genetic risk score model which formed by fifteen genes was established from GSE56363 and validated in the TCGA discovery set. We performed the CIBERSORT and ESTIMATE algorithms to find the difference of immune related signature between the high- and low-risk group to quantify the prognostic value of the fifteen-gene risk model. Among the 22 immune cell types, CD8 T cells, resting CD4 T cells, resting mast cells, activated mast cells, monocytes, neutrophil granulocyte were significantly different between high- and low-risk group. Immune-checkpoints (LAG3 and PDCD1) were highly expressed, and associated with poor prognosis in LACC. IHC demonstrated that cytl1 overexpression was positively associated with poor overall survival (P = 0.01). Cytl1 expression was closely correlated with CD8+T cell low-expression in LACC (r = 0.889, P = 0.066).

Conclusion

This study identified a novel fifteen-gene signature biomarker for predicting the treatment effect of LACC. Moreover, the current results demonstrated that cytl1was overexpressed and associated with poor prognosis in LACC. Cytl1 may be a potential prognostic marker and novel therapeutic target for LACC.