Multi-omics prognostic signatures of IPO11 mRNA expression and clinical outcomes in colorectal cancer using bioinformatics approaches.

IF 4.7 3区 医学 Q1 MEDICAL INFORMATICS
Health Information Science and Systems Pub Date : 2023-11-27 eCollection Date: 2023-12-01 DOI:10.1007/s13755-023-00259-2
Mohammed Othman Aljahdali, Mohammad Habibur Rahman Molla
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引用次数: 0

Abstract

The most prevalent malignant illness of the gastrointestinal system, colorectal cancer, is the third most prevalent cancer in males and the second most prevalent cancer in women. Importin-11 is a protein that acts as a regulator of cancer cell proliferation in colorectal tumours by conveying β-catenin to the cell nucleus. However, the IPO11 gene was found to encode a protein called Importin-11, which functions as a nucleus importer for the cell. As a result, preventing β-catenin from entering the nucleus requires blocking Importin-11. As a result, we conducted a multi-omics investigation to assess IPO11 gene potential as a therapeutic biomarker for human colorectal cancer (CC). Oncomine, GEPIA2, immunohisto-chemistry, and UALCAN databases were used to analyses the mRNA expression profiles of IPO11 in CC. The investigation has yielded clear evidence of the increase of IPO11 expression in CC subtypes, as indicated by the data acquired. Analysing CC research from the cBioPortal database, the study discovered three new missense mutations in the importin-11 protein sequence at a frequency of 0.00-1.50% copy number changes. Additionally, the Kaplan-Meier plots demonstrated a strong connection concerning IPO11 downregulation and a poorer CC patient survival rate. The co-expressed gene profile of IPO11 was likewise associated with the onset of CC. IPO11 co-expressed gene profile was also linked to CC development. Moreover, the correlation analysis using bc-GenExMiner and the UCSC Xena server identified KIF2A as the most positively co-expressed gene. The study found that KIF2A and its co-expressed genes were involved in a wide variety of cancer progression pathways using the Enrichr database. Cumulatively, this result will not only provide new information about the expression of IPO11 associated with CC progression and patient survival, but could also serve as a therapeutic biomarker for treating CC in a significant and worthwhile manner.

Supplementary information: The online version contains supplementary material available at 10.1007/s13755-023-00259-2.

利用生物信息学方法研究IPO11 mRNA表达的多组学预后特征和结直肠癌的临床结果。
结肠直肠癌是最常见的胃肠道恶性疾病,在男性中排名第三,在女性中排名第二。Importin-11是一种通过向细胞核传递β-连环蛋白来调节结直肠肿瘤中癌细胞增殖的蛋白。然而,IPO11基因被发现编码一种叫做Importin-11的蛋白质,它的功能是作为细胞核的入口。因此,阻止β-catenin进入细胞核需要阻断Importin-11。因此,我们进行了多组学研究,以评估IPO11基因作为人类结直肠癌(CC)治疗性生物标志物的潜力。使用Oncomine、GEPIA2、免疫组织化学和UALCAN数据库分析了IPO11在CC中的mRNA表达谱,研究结果表明,IPO11在CC亚型中的表达明显增加。通过分析来自cbiopportal数据库的CC研究,该研究在importin-11蛋白序列中发现了三个新的错义突变,其拷贝数变化频率为0.00% -1.50%。此外,Kaplan-Meier图显示了IPO11下调与较差的CC患者生存率之间的密切联系。IPO11共表达基因谱同样与CC的发病有关,IPO11共表达基因谱也与CC的发展有关。此外,使用bc-GenExMiner和UCSC Xena服务器进行相关性分析,发现KIF2A是最阳性的共表达基因。利用enrichment数据库,该研究发现KIF2A及其共表达基因参与了多种癌症进展途径。总的来说,这一结果不仅将提供与CC进展和患者生存相关的IPO11表达的新信息,而且还可以作为治疗CC的重要和有价值的治疗性生物标志物。补充信息:在线版本包含补充资料,下载地址:10.1007/s13755-023-00259-2。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
11.30
自引率
5.00%
发文量
30
期刊介绍: Health Information Science and Systems is a multidisciplinary journal that integrates artificial intelligence/computer science/information technology with health science and services, embracing information science research coupled with topics related to the modeling, design, development, integration and management of health information systems, smart health, artificial intelligence in medicine, and computer aided diagnosis, medical expert systems. The scope includes: i.) smart health, artificial Intelligence in medicine, computer aided diagnosis, medical image processing, medical expert systems ii.) medical big data, medical/health/biomedicine information resources such as patient medical records, devices and equipments, software and tools to capture, store, retrieve, process, analyze, optimize the use of information in the health domain, iii.) data management, data mining, and knowledge discovery, all of which play a key role in decision making, management of public health, examination of standards, privacy and security issues, iv.) development of new architectures and applications for health information systems.
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