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利用TCGA和GEO数据集评估FGFR1作为卵巢癌诊断生物标志物的价值。

Evaluation of FGFR1 as a diagnostic biomarker for ovarian cancer using TCGA and GEO datasets.

作者信息

Xiao Huiting, Wang Kun, Li Dan, Wang Ke, Yu Min

机构信息

Department of Gynecologic Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.

Department of Urologic Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.

出版信息

PeerJ. 2021 Feb 3;9:e10817. doi: 10.7717/peerj.10817. eCollection 2021.

Abstract

BACKGROUND

Malignant ovarian cancer is associated with the highest mortality of all gynecological tumors. Designing therapeutic targets that are specific to OC tissue is important for optimizing OC therapies. This study aims to identify different expression patterns of genes related to FGFR1 and the usefulness of FGFR1 as diagnostic biomarker for OC.

METHODS

We collected data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. In the TCGA cohort we analyzed clinical information according to patient characteristics, including age, stage, grade, longest dimension of the tumor and the presence of a residual tumor. GEO data served as a validation set. We obtained data on differentially expressed genes (DEGs) from the two microarray datasets. We then used gene set enrichment analysis (GSEA) to analyze the DEG data in order to identify enriched pathways related to FGFR1.

RESULTS

Differential expression analysis revealed that FGFR1 was significantly downregulated in OC specimens. 303 patients were included in the TCGA cohort. The GEO dataset confirmed these findings using information on 75 Asian patients. The GSE105437 and GSE12470 database highlighted the significant diagnostic value of FGFR1 in identifying OC (AUC = 1,  = 0.0009 and AUC = 0.8256,  = 0.0015 respectively).

CONCLUSIONS

Our study examined existing TCGA and GEO datasets for novel factors associated with OC and identified FGFR1 as a potential diagnostic factor. Further investigation is warranted to characterize the role played by FGFR1 in OC.

摘要

背景

恶性卵巢癌在所有妇科肿瘤中死亡率最高。设计针对卵巢癌(OC)组织的治疗靶点对于优化OC治疗至关重要。本研究旨在确定与FGFR1相关基因的不同表达模式以及FGFR1作为OC诊断生物标志物的效用。

方法

我们从癌症基因组图谱(TCGA)和基因表达综合数据库(GEO)收集数据。在TCGA队列中,我们根据患者特征分析临床信息,包括年龄、分期、分级、肿瘤最长径以及残留肿瘤的存在情况。GEO数据用作验证集。我们从两个微阵列数据集中获取差异表达基因(DEG)的数据。然后我们使用基因集富集分析(GSEA)来分析DEG数据,以确定与FGFR1相关的富集通路。

结果

差异表达分析显示,FGFR1在OC标本中显著下调。TCGA队列纳入了303例患者。GEO数据集使用75例亚洲患者的信息证实了这些发现。GSE105437和GSE12470数据库突出了FGFR1在识别OC方面的显著诊断价值(AUC分别为1,P = 0.0009和AUC = 0.8256,P = 0.0015)。

结论

我们的研究检查了现有的TCGA和GEO数据集,以寻找与OC相关的新因素,并确定FGFR1为潜在的诊断因素。有必要进一步研究以表征FGFR1在OC中所起的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4d8/7866899/c77f7dd0fda6/peerj-09-10817-g001.jpg

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