An Iron Metabolism-Related SLC22A17 for the Prognostic Value of Gastric Cancer

Jianming Wei; Xibo Gao; Yulan Qin; Tong Liu; Yani Kang

doi:10.2147/OTT.S287811

An Iron Metabolism-Related SLC22A17 for the Prognostic Value of Gastric Cancer

Onco Targets Ther. 2020 Dec 14:13:12763-12775. doi: 10.2147/OTT.S287811. eCollection 2020.

Authors

Jianming Wei^#¹, Xibo Gao^#², Yulan Qin³, Tong Liu¹, Yani Kang³

Affiliations

¹ Department of General Surgery, Tianjin Medical University General Hospital, Tianjin 300052, People's Republic of China.
² Department of Dermatology, Tianjin Children's Hospital, Tianjin 300074, People's Republic of China.
³ School of Biomedical Engineering, Bio-ID Center, Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China.

^# Contributed equally.

Abstract

Purpose: Gastric cancer (GC) is a type of malignant cancer with a poor prognosis. The iron's metabolism plays an important role in the process of GC. The aim of this study was to evaluate the effectiveness of SLC22A17, associated with iron metabolism, in predicting the prognosis of GC patients.

Materials and methods: We analyzed genes related to iron metabolism of gastric cancer mRNA-seq data from TCGA database. We identified an iron metabolism-related SLC22A17 as an independent prognostic factor using univariate and multivariate Cox regression analysis.

Results: Further research showed that SLC22A17 was related with many pathways involved in the process of gastric cancer, and the expression was associated with diverse cancer-infiltrating immune cells. The expression of SLC22A17 was associated with T (Topography).

Conclusion: We validated that SLC22A17 associated with iron metabolism could serve as a prognostic biomarker for GC patients.

Keywords: SLC22A17; gastric cancer; iron metabolism; prognostic marker.

Grants and funding

This study was supported by the Natural Science Foundation of Shanghai (19ZR1476100), National Infrastructures for Translational Medicine (Shanghai) (TMSK-2020-109), Interdisciplinary Program of Medical Engineering Cross Fund (YG2019GD02, YG2019QNB23, YG2019QNA49 and YG2019QNA52) and Laboratory Innovative Research Program of Shanghai Jiao Tong University (JCZXSJB2019002).