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

Pharmacogenomics and Personalized Medicine Pub Date : 2021-12-30 eCollection Date: 2021-01-01 DOI:10.2147/PGPM.S337695
Xiaojie Bai, Yuanfei Cao, Xin Yan, Kurerban Tuoheti, Guowei Du, Zhao Chen, Huahui Wu, Linfa Guo, Tongzu Liu
{"title":"Systematic Pan-Cancer Analysis of KIF23 and a Prediction Model Based on KIF23 in Clear Cell Renal Cell Carcinoma (ccRCC).","authors":"Xiaojie Bai,&nbsp;Yuanfei Cao,&nbsp;Xin Yan,&nbsp;Kurerban Tuoheti,&nbsp;Guowei Du,&nbsp;Zhao Chen,&nbsp;Huahui Wu,&nbsp;Linfa Guo,&nbsp;Tongzu Liu","doi":"10.2147/PGPM.S337695","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":509088,"journal":{"name":"Pharmacogenomics and Personalized Medicine","volume":" ","pages":"1717-1729"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/f9/a6/pgpm-14-1717.PMC8725058.pdf","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pharmacogenomics and Personalized Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/PGPM.S337695","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

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.

Abstract Image

Abstract Image

Abstract Image

KIF23在透明细胞肾细胞癌(ccRCC)中的泛癌系统分析及基于KIF23的预测模型
目的:本研究旨在对kinesin家族成员23 (KIF23)进行泛癌分析,构建透明细胞肾细胞癌(ccRCC)患者预后的预测模型。方法:利用癌症基因组图谱(Cancer Genome Atlas, TCGA)和Oncomine数据库对KIF23在泛癌组织中的差异表达进行评估。然后,通过TCGA、肿瘤-免疫系统相互作用集成知识库门户网站(TISIDB)和cBioPortal,探讨KIF23与预后、临床分级、分期、免疫亚型、肿瘤突变负担(TMB)、微卫星不稳定性(MSI)和免疫微环境的相关性。随后,我们筛选了与KIF23相关的铁凋亡相关基因(FRGs),并构建了风险评分模型。采用单因素Cox分析确定影响ccRCC总生存期(OS)的独立预后因素,并建立nomogram。此外,利用基因集富集分析(GSEA)对KIF23的生物学功能和通路进行了研究。最后采用实时定量聚合酶链反应(qRT-PCR)检测KIF23的表达。结果:KIF23在大多数肿瘤中高表达。KIF23与不同肿瘤的预后、临床分级、分期、免疫亚型、TMB、MSI和免疫微环境密切相关。我们发现KIF23与ccRCC的各个方面都显著相关。然后,识别8个frg,与KIF23一起构建风险评分模型。并建立了OS的预后nomogram预测模型。经GSEA分析,筛选出细胞周期、浓缩染色体等生理过程。最后,qRT-PCR验证了KIF23在ccRCC细胞系中的高表达,高于正常肾细胞系。结论:KIF23可能在不同肿瘤的发生发展中起关键作用。在ccRCC中,KIF23可能是一个重要的预后生物标志物,基于KIF23的nomographic可能有助于为ccRCC患者提供更好的治疗方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书