Mutation and Copy Number Alterations Analysis of KIF23 in Glioma

Zhao, Zheng; Wang, Zheng; Bao, Zhaoshi; Gao, Weizhen; Zhang, Yuan-Da; Ruan, Cijie; Lv, Tao; Wang, Yong; Sun, Lihua

doi:10.3389/fgene.2021.646929

Cited by 6 publications

(4 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The best explanation is that diffuse astrocytic and oligodendroglial tumors are classified by the presence of isocitrate dehydrogenase 1 or 2 (IDH1/2) mutation in the 2016 World Health Organization (WHO) classification of central nervous system (CNS) tumors for the impact of specific gene mutations on the progression and patient outcome of glioma [ 64 ]. In addition, Zhao et al found that after the copy number of KIF23 alterations, its expression level is increased, which in turn leads to tumorigenesis and the development of gliomas [ 65 ]. Our experimental results showed that the TRIM family molecules are genetically altered in gliomas.…”

Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of the prognostic and immunological signature of eight Tripartitemotif (TRIM) family molecules in human gliomas

Liang

Zou

et al. 2023

Aging

View full text Add to dashboard Cite

Background: TRIM family molecules have been identified as being involved in the tumor progression of various cancer types. Increasingly, experimental evidence indicates that some of TRIM family molecules are implicated in glioma tumorigenesis. However, the diverse genomic changes, prognostic values and immunological landscapes of TRIM family of molecules have yet to be fully determined in glioma. Methods: In our study, employing the comprehensive bioinformatics tools, we evaluated the unique functions of 8 TRIM members including TRIM5/17/21/22/24/28/34/47 in gliomas. Results: The expression levels of 7 TRIM members (TRIM5/21/22/24/28/34/47) were higher in glioma as well as its diverse cancer subtypes than in normal tissues, whereas the expression level of TRIM17 was the opposite, lower in the former than in the latter. In addition, survival analysis revealed that the high expression profiles of TRIM5/21/22/24/28/34/47 were associated with poor overall survival (OS), disease-specific survival (DSS) and progress-free interval (PFI) in glioma patients, whereas TRIM17 displayed adverse outcomes. Moreover, the 8 TRIM molecules expression as well as methylation profiles remarkably correlated with different WHO grades. And genetic alterations, including mutations and copy number alterations (CNAs), in the TRIM family were correlated with longer OS, DSS and progress-free survival (PFS) in glioma patients. Furthermore, through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis results of these 8 molecules and their related genes, we found that these molecules may change the immune infiltration of the tumor microenvironment and regulate the expression of immune checkpoint molecules (ICMs), affecting the occurrence and development of gliomas. The correlation analyses between the 8 TRIM molecules and TMB (tumor mutational burden)/MSI (microsatellite instability)/ICMs discovered that as the expression level of TRIM5/21/22/24/28/34/47 increased, the TMB score also increased significantly, while TRIM17 showed an opposite outcome. Further, a 6-gene signature (TRIM 5/17/21/28/34/47) for predicting overall survival (OS) in gliomas was built by using the least absolute shrinkage and selection operator (LASSO) regression, and the survival and time-dependent ROC analyses all were found to perform well in testing and validation cohorts. Results of multivariate COX regression analysis showed that TRIM5/28 are both expected to become independent risk predictors to guide clinical treatment. Conclusion: In general, the results indicate that TRIM5/17/21/22/24/28/34/47 might exert a crucial influence on gliomas tumorigenesis and might be putative prognostic markers and therapeutic targets for glioma patients.

show abstract

Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of the prognostic and immunological signature of eight Tripartitemotif (TRIM) family molecules in human gliomas

Liang

Zou

et al. 2023

Aging

View full text Add to dashboard Cite

show abstract

“…KIF23 was first found in 1992, which was a plus-end-directed motor enzyme. 30 Studies have suggested KIF23 as a potential biomarker in several tumors. 31 KIF23 promoted gastric carcinogenesis by activating Wnt/β-Catenin signaling.…”

Section: Discussionmentioning

confidence: 99%

Systematic Pan-Cancer Analysis of KIF23 and a Prediction Model Based on KIF23 in Clear Cell Renal Cell Carcinoma (ccRCC)

Bai¹,

Cao²,

Yan³

et al. 2021

PGPM

View full text Add to dashboard Cite

Purpose This study aims to carry out a pan-cancer analysis of kinesin family member 23 (KIF23) and construct a predictive model for the prognosis of clear cell renal cell carcinoma (ccRCC) patients. Methods We evaluated the differential expression of KIF23 in pan-cancer by The Cancer Genome Atlas (TCGA) and Oncomine database. Then, the correlation between KIF23 with prognosis, clinical grade, stage, immune subtype, tumor mutation burden (TMB), microsatellite instability (MSI) and immune microenvironment was explored by TCGA, an integrated repository portal for tumor-immune system interactions (TISIDB) and cBioPortal. Subsequently, we screened out ferroptosis-related genes (FRGs) related to KIF23 and constructed a risk score model. Univariate Cox analysis was used to determine independent prognostic factors for ccRCC overall survival (OS), and a nomogram was established. Furthermore, gene set enrichment analysis (GSEA) was applied to study the biological functions and pathways of KIF23. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was carried out to evaluate the expression of KIF23. Results KIF23 was highly expressed in most tumors. Further, KIF23 was strongly correlated with prognosis, clinical grade, stage, immune subtype, TMB, MSI and immune microenvironment in different tumors. We found that KIF23 was significantly associated with all aspects of ccRCC. Then, 8 FRGs were identified to construct a risk score model together with KIF23. And a prognostic nomogram prediction model of OS was established. After GSEA analysis, cell cycle, condensed chromosome and other physiological processes were screened out. Finally, qRT-PCR verified the high expression of KIF23 in ccRCC cell lines than normal kidney cell line. Conclusion KIF23 may act as a pivotal part in occurrence and progression of different tumors. In ccRCC, KIF23 can be a great prognostic biomarker, and the nomogram based on KIF23 may contribute to better treatment plans for ccRCC patients.

show abstract

“…By serving as a bridge between recycling vesicles and the microtubule network through its connection with STX4 and SNAP25, it controls the recycling of the plasma membrane. including gastric, esophageal, liver, colorectal, pancreatic, 57,59,60 cervical, prostate, ovarian, bladder, 60,61 lung, gliomas, 62 lymphoma, melanoma, and in BC. 60,63 KIF23 promotes cancer cell proliferation via direct competitive interaction with the membrane recruitment protein 1 (Amer1), blocking the association of this protein with the adenomatous polyposis coli (APC), thereby relocating Amer1 from the membrane and cytoplasm to the nucleus and attenuating its ability to negatively regulate Wnt/β-catenin signaling, thus activating this signaling pathway.…”

Section: Cenpfmentioning

confidence: 99%

Identification of prognostic biomarkers of invasive ductal carcinoma by an integrated bioinformatics approach

Marrugo-Padilla,

Márquez-Lázaro,

Álviz-Amador

2023

F1000Res

View full text Add to dashboard Cite

Background: Invasive ductal carcinoma (IDC) is the most common type of breast cancer (BC) worldwide. Nowadays, due to its heterogeneity and high capacity for metastasis, it is necessary to discover novel diagnostic and prognostic biomarkers. Therefore, this study aimed to identify novel candidate prognostic genes for IDC using an integrated bioinformatics approach. Methods: Three expression profile data sets were obtained from GEO (GSE29044, GSE3229, and GSE21422), from which differentially expressed genes (DEGs) were extracted for comparative transcriptome analysis of experimental groups (IDC versus control). Next, STRING was utilized to construct a protein interaction network with the shared DEGs, and MCODE and cytoHubba were used to identify the hub genes, which were then characterized using functional enrichment analysis in DAVID and KEGG. Finally, using the Kaplan-Meier tracer database, we determined the correlation between the expression of hub genes and overall survival in BC. Results: We identified seven hub genes (Kinesin-like protein KIF23 [KIF23], abnormal spindle-like microcephaly [ASPM]-associated protein [ASPMAP], Aurora kinase A [AURKA], Rac GTPase-activating protein 1 [RACGAP1], centromere protein F [CENPF], hyaluronan-mediated motility receptor [HMMR], and protein regulator of cytokinesis 1 [PRC1]), which were abundant in microtubule binding and tubulin binding, pathways linked to fundamental cellular structures including the mitotic spindle, spindle, microtubule, and spindle pole. The role of these genes in the pathophysiology of IDC is not yet well characterized; however, they have been associated with other common types of BC, modulating pathways such as Wnt/β-catenin, the epithelial-to-mesenchymal transition (EMT) process, chromosomal instability (CIN), PI3K/AKT/mTOR, and BRCA1 and BRCA2, playing an important role in its progression and being associated with a poor prognosis, thus representing a way to improve our understanding of the process of tumorigenesis and the underlying molecular events of IDC. Conclusions: Genes identified may lead to the discovery of new prognostic targets for IDC.

show abstract

Mutation and Copy Number Alterations Analysis of KIF23 in Glioma

Cited by 6 publications

References 29 publications

Comprehensive analysis of the prognostic and immunological signature of eight Tripartitemotif (TRIM) family molecules in human gliomas

Comprehensive analysis of the prognostic and immunological signature of eight Tripartitemotif (TRIM) family molecules in human gliomas

Systematic Pan-Cancer Analysis of KIF23 and a Prediction Model Based on KIF23 in Clear Cell Renal Cell Carcinoma (ccRCC)

Identification of prognostic biomarkers of invasive ductal carcinoma by an integrated bioinformatics approach

Contact Info

Product

Resources

About