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肾细胞癌预后基因的生物信息学鉴定及潜在相互作用分析

Bioinformatics identification of prognostic genes and potential interaction analysis in renal cell carcinoma.

作者信息

Yuan Yimin, Wang Jingzi, Huang Liqu, Guo Yunfei

机构信息

Department of Urology, Children's Hospital of Nanjing Medical University, Nanjing, China.

出版信息

Transl Cancer Res. 2023 Apr 28;12(4):774-783. doi: 10.21037/tcr-22-2242. Epub 2023 Mar 29.

Abstract

BACKGROUND

Renal cell carcinoma (RCC) is one of the ten most prevalent cancers in the world and its incidence has been rising over the past decade. However, effective biomarkers to predict the prognosis of patients remains absent, and the exact molecular mechanism of the disease remains unclear. Therefore, the identification of key genes and their biological pathways are of great significance to identify the differential expressed genes associated with the prognosis for patients with RCC, and to further explore their potential protein-protein interactions (PPIs) in tumorigenesis.

METHODS

The gene expression microarray data for GSE15641 and GSE40435 were extracted from the Gene Expression Omnibus (GEO) database, including 150 primary tumors and their matched adjacent non-tumor tissues. Afterwards, gene expression for fold changes (FCs) and P value for tumor and non-tumor tissues were analyzed using online tool GEO2R. Gene expression with logFCs of greater than two combined with P value of lower than 0.01 were considered as candidate targets for treatment of RCC. The survival analysis of candidate genes was performed by online software OncoLnc. The PPI network was implemented with Search Tool for the Retrieval of Interacting Genes (STRING).

RESULTS

In total, there were 625 differentially expressed genes (DEGs) in GSE15641, including 415 increased and 210 decreased genes. A total of 343 DEGs were identified in the GSE40435 with 101 upregulated and 242 downregulated genes, the 20 genes with highest FC in high or low expression in each database were summarized. Five candidate genes were overlapped genes in the two GEO datasets. However, aldolase, fructose-bisphosphate B (ALDOB) was found to be the only gene affecting the prognosis. A number of critical genes were identified behind the mechanism, of which they interacted with ALDOB. Among them, phosphofructokinase, platelet (), phosphofructokinase, muscle (), pyruvate kinase L/R (), and fructose-bisphosphatase 1 () showed a better prognosis, whereas only glyceraldehyde-3-phosphate dehydrogenase () rendered a bleak outcome.

CONCLUSIONS

Five genes were found to be overlappingly expressed in the top 20 greatest FC in two human GEO datasets. This is of great value in the treatment and prognosis of RCC.

摘要

背景

肾细胞癌(RCC)是全球十大最常见癌症之一,在过去十年中其发病率一直在上升。然而,目前仍缺乏有效的生物标志物来预测患者的预后,该疾病的确切分子机制仍不清楚。因此,鉴定关键基因及其生物学途径对于识别与RCC患者预后相关的差异表达基因,并进一步探索它们在肿瘤发生过程中潜在的蛋白质 - 蛋白质相互作用(PPI)具有重要意义。

方法

从基因表达综合数据库(GEO)中提取GSE15641和GSE40435的基因表达微阵列数据,包括150个原发性肿瘤及其匹配的相邻非肿瘤组织。之后,使用在线工具GEO2R分析肿瘤组织和非肿瘤组织的基因表达倍数变化(FC)和P值。将logFC大于2且P值低于0.01的基因表达视为RCC治疗的候选靶点。通过在线软件OncoLnc对候选基因进行生存分析。使用STRING(蛋白质相互作用检索工具)构建PPI网络。

结果

在GSE15641中总共鉴定出625个差异表达基因(DEG),其中415个基因表达上调,210个基因表达下调。在GSE40435中总共鉴定出343个DEG,其中101个基因上调,242个基因下调,总结了每个数据库中高表达或低表达时FC最高的20个基因。在两个GEO数据集中有5个候选基因是重叠基因。然而,发现果糖二磷酸醛缩酶B(ALDOB)是唯一影响预后的基因。在该机制背后鉴定出了许多关键基因,它们与ALDOB相互作用。其中,血小板磷酸果糖激酶()、肌肉磷酸果糖激酶()、丙酮酸激酶L/R()和果糖二磷酸酶1()显示出较好的预后,而只有甘油醛 - 3 - 磷酸脱氢酶()预后不佳。

结论

在两个人类GEO数据集中,发现有5个基因在FC最高的前20个基因中重叠表达。这对RCC的治疗和预后具有重要价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be10/10174992/56e735e82d82/tcr-12-04-774-f1.jpg

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