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NlE Qianru^ab ,ZHAO Haidong^a, YANG Xiaoli^a

(a. College of Public Health ,b. Scientifie Research Center, Guilin Medical University, Guilin 541199, China)

Objective Based on the cancer genome atlas (TCGA), the miRNAs prognostic risk seoring model ofAbstractrenal cancer was construeted to evaluate the potential clinical value of miRNAs and its target genes as molecularmarkers for renal cancer prognosis. Methods Based on TCGA miRNAs and mRNA datasets, the prognostie riskscoring model of renal cancer miRNAs was constructed and verified by single-factor, Lasso and multi-factor Coxregression analysis. CO and KEGG enrichment analyses of target genes were performed to predict the relatedfunetions of miRNAs in prognostic risk scoring model of renal cancer. The expressions of miRNAs and their target genes in the prognostic risk seoring model of renal cancer were verified in clinical samples. Results Based on theT'CGA database, 94 differential expression miRNAs and 1 226 mRNAs were identified in the transeriptome data ofrenal cancer samples compared with pericarcinomatous tissue. 7 miRNAs were sereened by independent prognosticanalysis and a prognostic risk scoring model of renal cancer was constructed, GO and KEGG enrichment analysesshowed that the fumetions of the '7 miRNAs were related to the PI3K-Akt signaling pathway, calcium ion signalingpathway and MAPK signaling pathway. The results of qPCR verification in renal cancer tissues samples showed thatthe expression patterns of 5 miRNAs and 8 target genes of miRNAs in clinical samples were consistent with the trendin 'TCGA database. lmunohistochemistry results showed that HPGD was low expressed in renal cancer. ConclusionThe miRNAs prognostic model constructed in this study can elfectively sereen for miRNAs related to the prognosis ofrenal cancer, The study of these miRNAs is of great significanee for the mechanism of renal cell carcinoma occurrenceand development, as well as the prognosis of renal cell cancer.

Keywords: renal cancer; miRNAs; target gene ; prognostic risk scoring model

DOI:10.19296/j.cnki.1008-2409.2024-02-016

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