Identification and Validation of LYZ and CCL19 as Prognostic Genes in the Cervical Cancer Micro-Environment

Abstract

Backgrounds: Cervical cancer was a primary epithelial malignant tumor in the cervix, which was one of the most common malignant tumor in gynecology. We aimed to investigate the relation of tumor microenvironment and the prognosis of cervical cancer patients. Methods: We conducted an extensive bioinformatics analysis aims to study the correlation between stromal/immune cells and the prognosis of cervical cancer. In order to investigate the associations between genes and overall survival (OS) of cervical cancer. We performed large-scale data analysis through a global gene expression profile. We analyzed the expression profile of cervical cancer using the Cancer Genome Atlas (TCGA) database. An immune score and stromal score depending on the estimation algorithm which can quantify the stromal or immune components of cervical cancer was obtained. Based on that, we divided the cervical cancer patients in the TCGA database into high- and low-score groups, and then the identified different expression genes (DEGs) that expression associated with cervical cancer patient’s prognosis was identified. After that, we generated protein-protein interaction (PPI) networks and interrelationship analyses of the immune system by performing functional enrichment analysis. Results: Our study showed that these 363 genes were primarily associated with immune/inflammatory responses. Meanwhile, Gene Expression Omnibus (GEO) confirmed that 9 genes (CX3CL1, SCML4, LYZ, FGD2, SLAMF6, GIMAP7, CCL19, SELP and POU2AF1) were significantly associated with cervical cancer prognosis. Conclusions: We have made a list of genes related to tumor microenvironment which would be potential biomarkers for the prognosis of cervical cancer patients.

Keywords

• cervical cancer
• os
• immune micro-environment
• bioinformatics analysis