APEX1 Expression as a Potential Diagnostic Biomarker of Clear Cell Renal Cell Carcinoma and Hepatobiliary Carcinomas

Kim, Ji-Myung; Yeo, Min‐Kyung; Lim, Jae Sung; Song, In-Sang; Chun, Kwangsik; Kim, Kyung‐Hee

doi:10.3390/jcm8081151

Cited by 13 publications

(22 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The common overexpression of APEX1 and APEX2 in cancer types suggested that they could be potential biomarkers for cancer screening (Figure 1 ). The overexpression of APEX2 in liver cancer was also validated based on other external data (Figure 2 ), which is consistent with the previous reports of APEX1[ 6 ]. To confirm the clinical value of APEX2 in liver cancer, this study also evaluated the relationship between APEX2 expression and survival time.…”

Section: Discussionsupporting

confidence: 91%

“…Also, APEX1 was reported to be associated with some cancer types, including the cancers of colon, stomach, liver, kidney, and breast, as well as osteosarcoma[ 4 - 8 , 33 ]. Recent studies showed that APEX1 is an efficient biomarker for the diagnosis and prognosis of liver cancer[ 6 , 8 , 34 ]. However, the role of APEX2 in cancer is still poorly understood.…”

Section: Discussionmentioning

confidence: 99%

“…Apyrimidinic endodeoxyribonuclease contains two members, namely, APEX1 and APEX2[ 3 ]. Having been widely reported in the pathogenesis of many cancers, especially in liver cancer[ 4 - 8 ], APEX1 was recently identified as a new diagnostic and prognostic biomarker for liver hepatocellular carcinoma (LIHC)[ 6 , 8 ]. However, the role of APEX2 in LIHC remains poorly understood.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Identification of APEX2 as an oncogene in liver cancer

Ru¹,

Zhu²,

Hu³

et al. 2020

WJCC

View full text Add to dashboard Cite

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...

show abstract

Section: Discussionsupporting

confidence: 91%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Identification of APEX2 as an oncogene in liver cancer

Ru¹,

Zhu²,

Hu³

et al. 2020

WJCC

View full text Add to dashboard Cite

show abstract

“…2,39 In the past few decades, great progress has been made from a non-specific immune approach to targeted therapy (against VEGF, PDGF) and now to novel immunotherapy with immune-checkpoint inhibitors. 40 In recent years, the potential of snoRNA as biomarkers has been graduated recognized. Although APEX1 has been reported diagnosis value of ccRCC, its clinical practical prospective was still a long way.…”

Section: Discussionmentioning

confidence: 99%

“…Although APEX1 has been reported diagnosis value of ccRCC, its clinical practical prospective was still a long way. 40 In recent years, the potential of snoRNA as biomarkers has been graduated recognized. 15,16,41 For example, SNORA42 was identified as a novel diagnostic, predictive biomarker and prospective therapeutic targets for CRC patients.…”

Section: Discussionmentioning

confidence: 99%

Expression signature of six‐snoRNA serves as novel non‐invasive biomarker for diagnosis and prognosis prediction of renal clear cell carcinoma

Zhao

Yan

et al. 2020

J Cellular Molecular Medi

View full text Add to dashboard Cite

Increasing evidence has verified that small nucleolar RNAs (snoRNAs) play significant roles in tumorigenesis and exhibit prognostic value in clinical practice. In the study, we analysed the expression profile and clinical relevance of snoRNAs from TCGA database including 530 ccRCC (clear cell renal cell carcinoma) and 72 control cases. By using univariate and multivariate Cox analysis, we established a six-snoRNA signature and divided patients into high-risk or low-risk groups. We found patients in highrisk group had significantly shorter overall survival and recurrence-free survival than those in low-risk group in test series, validation series and entire series by Kaplan-Meier analysis. We also confirmed this signature had a great accuracy and specificity in 64 clinical tissue cases and 50 serum samples. Then, depending on receiver operating characteristic curve analysis we found the six-snoRNA signature was an superior indicator better than conventional clinical factors (AUC = 0.732). Furthermore, combining the signature with TNM stage or Fuhrman grade were the optimal indicators (AUC = 0.792; AUC = 0.800) and processed the clinical applied value for ccRCC. Finally, we found the SNORA70B and its hose gene USP34 might directly regulate Wnt signalling pathway to promote tumorigenesis in ccRCC. In general, our study established a six-snoRNA signature as an independent and superior diagnosis and prognosis indicator for ccRCC. K E Y W O R D S biomarker, clear cell renal cell carcinoma, overall survival, prognostic, recurrence-free survival, snoRNAs S U PP O RTI N G I N FO R M ATI O N Additional supporting information may be found online in the Supporting Information section. How to cite this article: Zhao Y, Yan Y, Ma R, et al. Expression signature of six-snoRNA serves as novel non-invasive biomarker for diagnosis and prognosis prediction of renal clear cell carcinoma.

show abstract