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

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

doi:10.7717/peerj.10817

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

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

Authors

Huiting Xiao^#¹, Kun Wang^#², Dan Li¹, Ke Wang¹, Min Yu¹

Affiliations

¹ 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.
² 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.

^# Contributed equally.

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, p = 0.0009 and AUC = 0.8256, p = 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.

Keywords: FGFR1; Ovarian cancer; RNA-sequencing; Targeted treatment.

Grants and funding

This work was supported by the National Natural Science Foundation of China (NO. 81602299), Tianjin Health and Family Planning Commission Foundation of Science and Technology (NO. 16KG129) and National Natural Science Foundation of China (NO. 81602245). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.