Identification of APEX2 as an oncogene in liver cancer

Abstract

BACKGROUND DNA damage is one of the critical contributors to the occurrence and development of some cancers. APEX1 and APEX2 are the most important molecules in the DNA damage, and APEX1 has been identified as a diagnostic and prognostic biomarker in liver hepatocellular carcinoma (LIHC). However, the expression of APEX2 and its functional mechanisms in LIHC are still unclear. AIM To examine the expression of APEX2 and the potential mechanism network in LIHC. METHODS We conducted a pan-cancer analysis of the expression of APEX1 and APEX2 using the interactive TIMER tool. GEO datasets, including GSE14520, GSE22058, and GSE64041, were used to compare the APEX2 expression level in tumor tissues and adjacent non-tumor tissues. Then, we calculated the 5-year survival rate according to the web-based Kaplan-Meier analysis. We included the TCGA liver cancer database in GSEA analysis based on the high and low APEX2 expression, showing the potential mechanisms of APEX2 in LIHC. After that, we conducted Pearson correlation analysis using GEPIA2. Next, we performed quantitative polymerase chain reaction (qPCR) assay to examine the APEX2 levels in normal liver cell line LO2 and several liver cancer cell lines, including HepG2, Huh7, SMMC7721, and HCCLM3. APEX2 in HCCLM3 cells was knocked down using small interfering RNA. The role of APEX2 in cell viability was confirmed using CCK-8. Dual-luciferase reporter assay was performed to examine the promoter activity of CCNB1 and MYC . RESULTS APEX1 and APEX2 are both highly expressed in the tumor tissues of BLCA, BRCA, CHOL, COAD, ESCA, HNSC, LIHC, LUAD, LUSC, READ, and STAD. APEX2 overexpression in LIHC was validated using GSE14520, GSE22058, and GSE64041 datasets. The survival analysis showed that LIHC patients with high expression of APEX2 had a lower overall survival rate, even in the AJCC T1 patients. High level of APEX2 could indicate a lower overall survival rate in patients with or without viral hepatitis. The GSEA analysis identified that kinetochore and spindle microtubules are the two main cellular components of APEX2 in GO Ontology. APEX2 was also positively associated with molecular function regulation of chromosome segregation and DNA replication. The results of KEGG analysis indicated that APEX2 expression was positively correlated with cell cycle pathway and pro-oncogenic MYC signaling. Pearson correlation analysis showed that APEX2 had a significant positive correlation with CCNB1 and MYC. APEX2 level was higher in liver cancer cell lines than in normal liver LO2 cells. Small interfering RNA could knock down the APEX2 expression in HCCLM3 cells. Knockdown of APEX2 resulted in a decrease in the viability of HCCLM3 cells as well as the expression and promoter activity of CCNB1 and MYC . CONCLUSION APEX2 i...

A zinc finger protein gene signature enables bladder cancer treatment stratification

“…Our findings on APEX2 are supported by evidence that this ZNF protein serves as a synthetic lethal target in BRCA1- and BRCA2-deficient colonic and ovarian cancer cell lines [ 28 ]. In contrast, APEX2 overexpression has been reported in liver cancer [ 29 ] and myeloma [ 30 ]. Jensen et al recently explored the expression of APEX2 in multiple cancers and indicated that this gene possesses tissue-specific characteristics [ 31 ].…”

Nanoparticle-Encapsulated Camptothecin: Epigenetic Modulation in DNA Repair Mechanisms in Colon Cancer Cells

“…It can bind to Receptor for Advanced Glycation End products (RAGE) or Toll-like receptors (TLRs), which eventually activates the nuclear transcription factor κB (NF-κB) signal transduction pathway, and upregulates various apoptotic factors to cause cell death [ 31 , 33 ]. Meanwhile, APEX1 -encoded DNA-(apurinic or apyrimidinic site) lyase has been shown to be highly expressed in a variety of tumors, including liver [ 34 ], colorectal [ 35 ], gastric [ 36 ], and non-small-cell lung cancer [ 37 ]. Gene expression profiling demonstrated that increased APE1 correlated with glioblastoma recurrence in patients [ 38 ].…”

Biological Function and Clinical Value of VPS13A in Pan-Cancer Based on Bioinformatics Analysis

“…The larger the R, the higher the correlation was. 21 In addition, the "Gene_Corr" module of TIMER2 was used to input VPS13A-related genes, and purity adjusted Spearman rank correlation test was selected to perform gene correlation analysis on VPS13A and the selected genes, and heat maps and scatter maps with partial correlation (COR) and p values in different tumors were obtained. The larger R was, the higher the correlation was.…”