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In Silico Analysis for Sphingolipid Metabolism-Related Genes in Human Kidney Clear Cell Carcinoma Using The Cancer Genome Atlas.

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Author(s)
박지영권택규박종욱김신
Alternative Author(s)
Kwon, Taeg KyuPark, Jong WookKim, Shin
Publication Year
2020
Keyword
Clear cell renal cell carcinomaSphingolipid metabolismThe Cancer Genome Atlas
Abstract
The sphingolipid rheostat concept states that the cellular fate is largely determined by various sphingolipid metabolites and the associated signaling pathways. Aberrant regulation of the sphingolipid metabolism-related components is closely associated with cancer survival and death, including aspects like cancer development, proliferation, progression, and response to anticancer drugs. In the present study, we investigated the expression and prognostic significance of the sphingolipid metabolism-related genes in clear cell renal cell carcinoma (ccRCC), the most common pathological subtype of kidney cancer, using an RNA-sequencing dataset of The Cancer Genome Atlas Kidney Clear Cell Carcinoma (TCGA KIRC) cohort. Expression levels of various sphingolipid metabolism-related genes were significantly altered in ccRCC tissues compared with those of normal solid tissues. Notably, the expression of B4GALNT1, BNIP3, DEGS1, GAL3ST1, S1PR4, SLC26A10, SMPDL3A, and SPHK1 was significantly upregulated, whereas the expression of B4GALT6, HPGD, LPAR1, SFTPB, ST6GALNAC5, and UGT8 was significantly downregulated in ccRCC tissues. Notably, among these significantly-altered sphingolipid metabolism-related genes, the Kaplan-Meier survival analyses showed that high expression levels of B4GALNT1, SLC26A10, and SPHK1 were associated with a poor prognosis of patients with ccRCC, whereas high expression levels of BNIP3, HPGD, and SMPDL3A were associated with a better prognosis. Taken together, our study suggests that B4GALNT1, SLC26A10, SPHK1, BNIP3, HPGD, and SMPDL3A may be novel prognostic biomarkers and targets for a therapeutic strategy to improve the treatment of ccRCC.
Department
Dept. of Immunology (면역학)
Citation
Woo-Jae Park. (2020). In Silico Analysis for Sphingolipid Metabolism-Related Genes in Human Kidney Clear Cell Carcinoma Using The Cancer Genome Atlas.. Keimyung Medical Journal, 39(1), 14-22. doi: 10.46308/kmj.2020.00101
Type
Jounral
DOI
10.46308/kmj.2020.00101
URI
http://kumel.medlib.dsmc.or.kr/handle/2015.oak/42802
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