Gao Shuang, Zhang Lei, Sun Guoping
Department of Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230001, Anhui, China.
Ward 4 of the Department of Oncology, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, 230001, Anhui, China.
Discov Oncol. 2024 Nov 19;15(1):681. doi: 10.1007/s12672-024-01516-w.
GNL2, a nuclear protein, is involved in ribosome production and cell cycle regulation. However, its expression and function in different types of tumors are not well understood. Comprehensive studies across multiple cancer types are needed to assess the potential of GNL2 as a diagnostic, prognostic, and immunological marker.
mRNA expression data, copy number alteration threshold data, masked copy number segmentation data, and DNA methylation 450 K data from The Cancer Genome Atlas (TCGA) pan-cancer cohort were obtained from the Firehose database. Additional data, including miRNA, The Cancer Proteome Atlas (TCPA), mutation data, and clinical information, were sourced from the University of California Santa Cruz (UCSC) Xena database. The cBioPortal database facilitates the examination of GNL2 mutation frequency, location, and 3D structure in the TCGA database. Gene Expression Omnibus (GEO) data verified the transcriptome level expression in the TCGA cohort. Protein expression levels were analyzed via the Human Protein Atlas (HPA) database and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database. Gene set enrichment analysis (GSEA) was employed to investigate the biological role of GNL2 across cancers. Multiple immune infiltration algorithms from the TIMER2.0 database were utilized to examine the correlation between GNL2 expression and the tumor immune microenvironment. The transcriptome-wide immune infiltration results were validated using 72 single-cell datasets from the Tumor Immune Single-cell Hub (TISCH) database. Pan-cancer survival maps were constructed, and GNL2 expression in different molecular subtypes across cancers was examined. The relationship between GNL2 and drug resistance was investigated using data from CellMiner, GDSC, and CTRP. The Comparative Toxicogenomics Database (CTD) was used to identify chemicals affecting GNL2 expression.
GNL2 is located primarily in the nucleus, and its expression is regulated mainly through somatic copy number alteration (SCNA) and aberrant DNA methylation, according to TCGA data. Database analysis and immunohistochemical results from clinical samples revealed high GNL2 expression in most tumors, which was correlated with diagnostic significance. High GNL2 expression often indicates a poor prognosis with pan-cancer prognostic value. Gene set enrichment analysis (GSEA) suggested that GNL2 is involved in tumor development through cell proliferation-related pathways. GNL2 expression is correlated with the expression of immune-related genes and the infiltration levels of multiple immune cells. The relationships between GNL2 and various drugs and chemicals were examined, revealing its influence on drug sensitivity and identifying five chemicals countering GNL2-mediated pro-cancer effects.
Comprehensive bioinformatics analysis of GNL2 in pan-cancer tissues, combined with experimental validation, elucidated the pan-cancer expression pattern of GNL2, determined its diagnostic and prognostic value, and explored the biological functions of GNL2. GNL2 may be involved in the regulation of cell cycle progression and remodeling of the tumor microenvironment and is associated with poor prognosis as a risk factor in most tumors. The potential of GNL2-based cancer therapies is emphasized, assisting in predicting the response to chemotherapy.
GNL2是一种核蛋白,参与核糖体生成和细胞周期调控。然而,其在不同类型肿瘤中的表达和功能尚未完全明确。需要对多种癌症类型进行全面研究,以评估GNL2作为诊断、预后和免疫标志物的潜力。
从Firehose数据库获取来自癌症基因组图谱(TCGA)泛癌队列的mRNA表达数据、拷贝数改变阈值数据、掩码拷贝数分割数据和DNA甲基化450K数据。其他数据,包括miRNA、癌症蛋白质组图谱(TCPA)、突变数据和临床信息,来自加利福尼亚大学圣克鲁兹分校(UCSC)的Xena数据库。cBioPortal数据库有助于检查TCGA数据库中GNL2的突变频率、位置和三维结构。基因表达综合数据库(GEO)数据验证了TCGA队列中的转录组水平表达。通过人类蛋白质图谱(HPA)数据库和临床蛋白质组肿瘤分析联盟(CPTAC)数据库分析蛋白质表达水平。采用基因集富集分析(GSEA)研究GNL2在各种癌症中的生物学作用。利用TIMER2.0数据库中的多种免疫浸润算法检查GNL2表达与肿瘤免疫微环境之间的相关性。使用来自肿瘤免疫单细胞中心(TISCH)数据库的72个单细胞数据集验证全转录组范围的免疫浸润结果。构建泛癌生存图谱,并检查GNL2在不同癌症分子亚型中的表达。利用来自CellMiner、GDSC和CTRP的数据研究GNL2与耐药性之间的关系。使用比较毒理基因组学数据库(CTD)识别影响GNL2表达的化学物质。
根据TCGA数据,GNL2主要位于细胞核中,其表达主要通过体细胞拷贝数改变(SCNA)和异常DNA甲基化进行调节。临床样本的数据库分析和免疫组化结果显示,大多数肿瘤中GNL2表达较高,这与诊断意义相关。GNL2高表达通常表明预后不良,具有泛癌预后价值。基因集富集分析(GSEA)表明,GNL2通过细胞增殖相关途径参与肿瘤发展。GNL2表达与免疫相关基因的表达以及多种免疫细胞的浸润水平相关。研究了GNL2与各种药物和化学物质之间的关系,揭示了其对药物敏感性的影响,并确定了五种对抗GNL2介导的促癌作用的化学物质。
对泛癌组织中的GNL2进行全面的生物信息学分析,并结合实验验证,阐明了GNL2的泛癌表达模式,确定了其诊断和预后价值,并探索了GNL2的生物学功能。GNL2可能参与细胞周期进程的调节和肿瘤微环境的重塑,并且在大多数肿瘤中作为危险因素与预后不良相关。强调了基于GNL2的癌症治疗的潜力,有助于预测对化疗的反应。