Abstract：Abstract: Through bioinformatics analysis of miRNA and gene expression chip data of papillary renal cell carcinoma (PRCC), the prognostic biomarkers of PRCC were studied in combination with clinical data. Firstly, PRCC miRNA-seq data downloaded from The Cancer Genome Atlas (TCGA) database was used to screen out differentially expressed miRNAs and analyze their correlation with patient survival. Then, univariate Cox, LASSO and multivariate Cox regression were used to analyze miRNAs that can independently affect the prognosis of PRCC. Finally, the target genes of selected miRNAs were predicted, and the correlation between the expression of these target genes and PRCC was verified by using the PRCC gene expression chip data downloaded from Gene Expression Omnibus (GEO) database. Survival analysis showed that up-regulated ex-pression of mir-1293 and mir-937 in PRCC tissue samples may be closely related to the prognostic survival of PRCC patients. The mechanism analysis suggested that high expression of mir-1293 in PRCC tissue may down-regulate the expression of tumor suppressors CLMN and DCN, and high expression of mir-937 may promote the occurrence and development of PRCC by inhibiting the expression of ST6GAL1, ATP6V1A and VAV3, leading to poor prognosis. These results suggest that upregulation of mir-1293 and mir-937 may be biological indicators of adverse prognosis of PRCC and help determine the prognosis of patients.
引用本文:
王松松, 黄慧珍, 林 凡, 苏陈颖, 李晓冉, 林 梦, 林晓晖. 基于miRNA的乳头状肾细胞癌预后指标的生物信息学研究[J]. 生命科学研究, 2022, 26(2): 151-157.
WANG Song-song, HUANG Hui-zhen, LIN Fan, SU Chen-ying, LI Xiao-ran, LIN Meng, LIN Xiao-hui. Bioinformatics Study of Prognostic Indicators of Papillary Renal Cell Carcinoma Based on miRNAs. Life Science Research, 2022, 26(2): 151-157.
