NCAPG Is a Promising Therapeutic Target Across Different Tumor Types

Xiao, Cuicui; Gong, Jiao; Jie, Yusheng; Cao, Jing; Chen, Zhongcheng; Li, Rong; Chong, Yutian; Hu, Bo; Zhang, Qi

doi:10.3389/fphar.2020.00387

Cited by 35 publications

(35 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…NCAPG has also been identified as a key gene in triple-negative breast cancer 61 as well as hepatocellular carcinoma 62 . Furthermore, it was reported that high expression of NCAPG is associated with poor prognosis of various tumor types, and its overexpression may play an important role in the regulation of tumor-related pathways in tumor growth 63 .…”

Section: Discussionmentioning

confidence: 99%

Screening and predicted value of potential biomarkers for breast cancer using bioinformatics analysis

Zeng

Shi

et al. 2021

Sci Rep

View full text Add to dashboard Cite

Breast cancer is the most common cancer and the leading cause of cancer-related deaths in women. Increasing molecular targets have been discovered for breast cancer prognosis and therapy. However, there is still an urgent need to identify new biomarkers. Therefore, we evaluated biomarkers that may aid the diagnosis and treatment of breast cancer. We searched three mRNA microarray datasets (GSE134359, GSE31448 and GSE42568) and identified differentially expressed genes (DEGs) by comparing tumor and non-tumor tissues using GEO2R. Functional and pathway enrichment analyses of the DEGs were performed using the DAVID database. The protein–protein interaction (PPI) network was plotted with STRING and visualized using Cytoscape. Module analysis of the PPI network was done using MCODE. The associations between the identified genes and overall survival (OS) were analyzed using an online Kaplan–Meier tool. The redundancy analysis was conducted by DepMap. Finally, we verified the screened HUB gene at the protein level. A total of 268 DEGs were identified, which were mostly enriched in cell division, cell proliferation, and signal transduction. The PPI network comprised 236 nodes and 2132 edges. Two significant modules were identified in the PPI network. Elevated expression of the genes Discs large-associated protein 5 (DLGAP5), aurora kinase A (AURKA), ubiquitin-conjugating enzyme E2 C (UBE2C), ribonucleotide reductase regulatory subunit M2(RRM2), kinesin family member 23(KIF23), kinesin family member 11(KIF11), non-structural maintenance of chromosome condensin 1 complex subunit G (NCAPG), ZW10 interactor (ZWINT), and denticleless E3 ubiquitin protein ligase homolog(DTL) are associated with poor OS of breast cancer patients. The enriched functions and pathways included cell cycle, oocyte meiosis and the p53 signaling pathway. The DEGs in breast cancer have the potential to become useful targets for the diagnosis and treatment of breast cancer.

show abstract

Section: Discussionmentioning

confidence: 99%

Screening and predicted value of potential biomarkers for breast cancer using bioinformatics analysis

Zeng

Shi

et al. 2021

Sci Rep

View full text Add to dashboard Cite

show abstract

“…NCAPG is the regulatory subunit of the condensin complex, which is required for the conversion of interphase chromatin into a condensed chromosome. NCAPG is highly expressed in a variety of tumors, serving as a promising therapeutic target [ 57 ]. CCNB2 is essential for the control of the cell cycle at the G2-M transition.…”

Section: Discussionmentioning

confidence: 99%

HEDGEHOG/GLI Modulates the PRR11-SKA2 Bidirectional Transcription Unit in Lung Squamous Cell Carcinomas

Sun

Zhang

et al. 2021

Genes

View full text Add to dashboard Cite

We previously demonstrated that proline-rich protein 11 (PRR11) and spindle and kinetochore associated 2 (SKA2) constituted a head-to-head gene pair driven by a prototypical bidirectional promoter. This gene pair synergistically promoted the development of non-small cell lung cancer. However, the signaling pathways leading to the ectopic expression of this gene pair remains obscure. In the present study, we first analyzed the lung squamous cell carcinoma (LSCC) relevant RNA sequencing data from The Cancer Genome Atlas (TCGA) database using the correlation analysis of gene expression and gene set enrichment analysis (GSEA), which revealed that the PRR11-SKA2 correlated gene list highly resembled the Hedgehog (Hh) pathway activation-related gene set. Subsequently, GLI1/2 inhibitor GANT-61 or GLI1/2-siRNA inhibited the Hh pathway of LSCC cells, concomitantly decreasing the expression levels of PRR11 and SKA2. Furthermore, the mRNA expression profile of LSCC cells treated with GANT-61 was detected using RNA sequencing, displaying 397 differentially expressed genes (203 upregulated genes and 194 downregulated genes). Out of them, one gene set, including BIRC5, NCAPG, CCNB2, and BUB1, was involved in cell division and interacted with both PRR11 and SKA2. These genes were verified as the downregulated genes via RT-PCR and their high expression significantly correlated with the shorter overall survival of LSCC patients. Taken together, our results indicate that GLI1/2 mediates the expression of the PRR11-SKA2-centric gene set that serves as an unfavorable prognostic indicator for LSCC patients, potentializing new combinatorial diagnostic and therapeutic strategies in LSCC.

show abstract

“…NCAPG overexpression has been detected in cancers including melanoma, lung cancer, prostate cancer, and HCC, suggesting that this gene plays an important oncogenic role. 27 - 29 WDHD1 is a DNA-binding protein that interacts with DNA via an HMG domain, 30 controlling mitosis, DNA damage responses, and DNA repair. 31 In prior research, WDHD1 has been closely linked to malignancies including ESCC, lung cancer, and cervical cancer.…”

Section: Discussionmentioning

confidence: 99%

Identification of Key Modules and Hub Genes Involved in Esophageal Squamous Cell Carcinoma Tumorigenesis Using WCGNA

Chen

Zhang

et al. 2020

Cancer Control

View full text Add to dashboard Cite

Introduction: The mechanistic basis for the development of esophageal squamous cell carcinoma (ESCC) remains poorly understood. The goal of the present study was thus to characterize mRNA and long noncoding RNA (lncRNA) expression profiles associated with ESCC in order to identify key hub genes associated with the pathogenesis of this cancer. Materials and Methods: The GSE26866 and GSE45670 datasets from the Gene Expression Omnibus (GEO) database were used to conduct a weighted gene co-expression network analysis (WGCNA), after which Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted. Cytoscape was additionally used to construct lncRNA-mRNA networks, after which hub genes were identified and validated through the assessment of TCGA datasets and clinical samples. Results: Two gene modules were found to be closely linked to ESCC tumorigenesis. These genes were enriched in cell cycle, MAPK signaling, JAK-STAT signaling, pyrimidine metabolism, arachidonic acid metabolism, and P53 signaling pathway activity, all of which are directly linked with the development of cancer. In total, we identified and validated 9 hub genes associated with ESCC (DDX18, DNMT1, NCAPG, WDHD1, PRR11, VOPP1, ZKSCAN5, LC35C2, and PHACTR2). Conclusion: In summary, we identified key gene modules and hub genes associated with ESCC development, and we constructed a lncRNA-mRNA network pertaining to this cancer type. These results provide a foundation for future research regarding the mechanistic basis of ESCC.

show abstract

NCAPG Is a Promising Therapeutic Target Across Different Tumor Types

Cited by 35 publications

References 25 publications

Screening and predicted value of potential biomarkers for breast cancer using bioinformatics analysis

Screening and predicted value of potential biomarkers for breast cancer using bioinformatics analysis

HEDGEHOG/GLI Modulates the PRR11-SKA2 Bidirectional Transcription Unit in Lung Squamous Cell Carcinomas

Identification of Key Modules and Hub Genes Involved in Esophageal Squamous Cell Carcinoma Tumorigenesis Using WCGNA

Contact Info

Product

Resources

About