Cervical cancer is the third leading cause of cancer death among women in less-developed regions. Because of the poor survivorship of patients with advanced disease, finding new biomarkers for prognostic prediction is of great importance. In the current study, mRNA datasets (GSE9750 and GSE63514) were retrieved from Gene Expression Omnibus and was used to identify differentially expressed genes. The underlying molecular mechanisms associated with high-mobility group box 1 protein (HMGB1) were investigated using bioinformatics analysis. Immunohistochemical analysis of HMGB1 was performed on 239 cases of cervical cancer samples to investigate its possible correlation with clinicopathological characteristics and outcomes. A preliminary validation has been made to explore the possible correlation factors with HMGB1 that promote migration of cervical cancer cells. Bioinformatics analysis showed that adherens junction was significant for both P-value and enrichment scores, which was consistent with the clinical study. The underlying molecular mechanisms might be the interaction among HMGB1, RAC1, and CDC42. HMGB1 expression was significantly associated with tumor size, parametrial infiltration, the depth of cervical stromal invasion, and FIGO stage (P=0.003, 0.019, 0.013, and 0.003, respectively). FIGO stage, lymph mode metastasis, and HMGB1 expression were independent predictors of a poorer prognosis of patients with cervical cancer. Knockdown of HMGB1 inhibits migration of Siha and C33A cells in vitro Western blot and quantitative real-time PCR (qRT-PCR) showed that the expression of RAC1 and CDC42 was positively correlated with HMGB1. HMGB1 is a useful prognostic indicator and a potential biomarker of cervical cancer. RAC1 and CDC42 may be involved in the progression of cervical cancer migration induced by HMGB1.
Keywords: HMGB1; bioinformatics analysis; cervical cancer; prognosis.
© 2019 The Author(s).