Abstract
Cervical cancer and endometrial cancer remain serious threats to women’s health. Even though some patients can be treated with surgery plus chemoradiotherapy as a conventional option, the overall efficacy is deemed unsatisfactory. As such, the development for new treatment approaches is truly necessary. In recent years, immunotherapy has been widely used in clinical practice and it is an area of great interest that researchers are keeping attention on. However, a thorough immune-related genes (IRGs) study for cervical cancer and endometrial cancer is still lacking. We therefore aim to make a comprehensive evaluation of IRGs through bioinformatics and large databases, and also investigate the relationship between the two types of cancer. We reviewed the transcriptome RNAs of IRGs and clinical data based on the TCGA database. Survival-associated IRGs in cervical/endometrial cancer were identified using univariable and multivariable Cox proportional-hazard regression analysis for developing an IRG signature model to evaluate the risk of patients. In the end, this model was validated based on the enrichment analyses through GO, KEGG, and GSEA pathways, Kaplan-Meier survival curve, ROC curves, and immune cell infiltration. Our results showed that out of 25/23 survival-associated IRGs for cervical/endometrial cancer, 13/12 warranted further examination by multivariate Cox proportional-hazard regression analysis and were selected to develop an IRGs signature model. As a result, enrichment analyses for high-risk groups indicated main enriched pathways were associated with tumor development and progression, and statistical differences were found between high-risk and low-risk groups as shown by Kaplan-Meier survival curve. This model could be used as an independent measure for risk assessment and was considered relevant to immune cell infiltration, but it had nothing to do with clinicopathological characteristics. In summary, based on comprehensive analysis, we obtained the IRGs signature model in cervical cancer (LTA, TFRC, TYK2, DLL4, CSK, JUND, NFATC4, SBDS, FLT1, IL17RD, IL3RA, SDC1, PLAU) and endometrial cancer (LTA, PSMC4, KAL1, TNF, SBDS, HDGF, LTB, HTR3E, NR2F1, NR3C1, PGR, CBLC), which can effectively evaluate the prognosis and risk of patients and provide justification in immunology for further researches.
Highlights
Cervical cancer is the fourth most commonly occurring cancer in women worldwide (Yang et al, 2019), for which a major cause is chronic infection with high-risk human papillomavirus (HPV) types (HPV types 16 and 18) (Cohen et al, 2019)
Based on the results derived from the R software, we found that there were 3192 differentially expressed genes in cervical cancer, including 1833 upregulated and 1359 downregulated; and 5665 differentially expressed genes in endometrial cancer, including 3316 upregulated and 2349 downregulated
Based on univariate and multivariate Cox regression analyses, we found the risk score resulted from the immune-related genes (IRGs) signature model could be considered an independent statistical measure to evaluate the overall survival (OS) in patients with cervical cancer (P < 0.001) (Figures 7A,B)
Summary
Cervical cancer is the fourth most commonly occurring cancer in women worldwide (Yang et al, 2019), for which a major cause is chronic infection with high-risk HPV types (HPV types 16 and 18) (Cohen et al, 2019). This condition is considered the leading cause of death and disability for women, progress has been made for diagnostic methods and treatment in recent years in the context of improved test panels that provide detailed screening around the world. Immunotherapy has been increasingly used in clinical settings (Crusz and Miller, 2020) and has becomes one of the important areas of cancer research
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