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KIF20A 低表达抑制细胞增殖,提高化疗敏感性,并与 HCC 的较好预后相关。

Low expression of KIF20A suppresses cell proliferation, promotes chemosensitivity and is associated with better prognosis in HCC.

机构信息

Department of General Surgery, Shanghai General Hospital Affiliated to Shanghai Jiaotong University, Shanghai, China.

出版信息

Aging (Albany NY). 2021 Sep 6;13(18):22148-22163. doi: 10.18632/aging.203494.

Abstract

This study analysed the microarray datasets from Gene Expression Omnibus (GEO) database, and aimed to identify novel potential hub genes associated with the progression of HCC via bioinformatics analysis and experimental validation. The common differentially expressed genes (DEGs) from five GEO datasets were screened using GEO2R tool. The expression and survival analysis of hub genes in HCC were performed using Gene Expression Profiling Interactive Analysis, UALCAN and Kaplan-Meier plotter tools. functional assays were used to determine the caspase-3, -9, cell proliferation and chemo-sensitivity of HCC cells. A total of 177 common DEGs were identified between normal liver and HCC tissues among these datasets. Functional enrichment and PPI network analysis identified 22 hub genes from the common DEGs. The mRNA expression of 22 hub genes was all significantly up-regulated in HCC tissues compared to that in normal liver tissues. Further survival analysis showed that 10 hub genes predicted poor prognosis of patients with HCC. More importantly, the functional studies demonstrated that KIF20A knockdown suppressed the HCC cell proliferation and promoted the chemosensitivity of HCC cells to cisplatin and sorafenib. In conclusion, the present study identified a total of 177 common DEGs among 5 GEO microarray datasets and found that 10 hub genes could predict the poor prognosis of patients with HCC using the comprehensive bioinformatics analysis. Furthermore, KIF20A silence suppressed cell proliferation and enhanced chemosensitivity in HCC cells. Further studies may be required to determine the mechanistic role of these hub genes in HCC progression.

摘要

本研究通过生物信息学分析和实验验证,分析了基因表达综合数据库(GEO)中的微阵列数据集,旨在鉴定与 HCC 进展相关的新的潜在枢纽基因。使用 GEO2R 工具筛选了五个 GEO 数据集的常见差异表达基因(DEGs)。使用基因表达谱交互分析、UALCAN 和 Kaplan-Meier 绘图仪工具对 HCC 中枢纽基因的表达和生存进行分析。功能测定用于确定 HCC 细胞中的 caspase-3、-9、细胞增殖和化疗敏感性。在这些数据集中,在正常肝组织和 HCC 组织之间确定了 177 个常见的 DEGs。功能富集和 PPI 网络分析从常见的 DEGs 中确定了 22 个枢纽基因。与正常肝组织相比,22 个枢纽基因在 HCC 组织中的 mRNA 表达均显著上调。进一步的生存分析表明,10 个枢纽基因预测 HCC 患者预后不良。更重要的是,功能研究表明,KIF20A 敲低抑制 HCC 细胞增殖并增强 HCC 细胞对顺铂和索拉非尼的化疗敏感性。总之,本研究通过综合生物信息学分析,在 5 个 GEO 微阵列数据集中确定了 177 个常见的 DEGs,并发现 10 个枢纽基因可以预测 HCC 患者的预后不良。此外,KIF20A 沉默抑制 HCC 细胞增殖并增强 HCC 细胞的化疗敏感性。可能需要进一步研究以确定这些枢纽基因在 HCC 进展中的机制作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bb0d/8507281/e84d07cd9a8d/aging-13-203494-g001.jpg

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