Abstract 2297P
Background
Upper tract urothelial carcinoma (UTUC) accounts for 5%-10% of all urothelial malignancies. And the incidence of UTUC in China is much higher than that in European and American countries, accounting for about 31%. Approximately two-thirds of patients have invasive disease at diagnosis. However, little research has been done on UTUCs.
Methods
To better understand the pathogenesis of UTUC and provide references for its diagnosis and treatment, we conducted a Weighted Correlation Network Analysis (WGCNA) involving the RNA sequencing data of 27 UTUC patients. Multiple linear regression models were used to explore the association between gene modules and clinical indicators. We then imported related modules into Cytoscape. to screen hub genes. Additionally, we performed RNA differential expression analysis, exon mutation analysis, and looked at mutations in hub genes. Enrichment analysis was then conducted based on differentially expressed genes to discover potential pathways regulating UTUC. Finally, bladder cancer data in TCGA database was used to verify the hub genes.
Results
We classified the genes into 31 modules by unsupervised clustering, with 4 modules (FDR<0.05) significantly associated with tumor infiltration. Then 9 potential biomarkers, including MSRB3, HSPB2, SCRG1, SYNPO2, FXYD1, PLXNA4, CD163, IFFO1, and FPR3, were discovered by importing these 4 modules into Cytoscape software. Differential expression analysis showed that except for the FPR3 gene, the remaining 8 genes were under expressed in UTUC. This has also been verified in public databases. Meanwhile, SNP mutation occurred in MSRB3, SYNPO2, and PLXNA4 genes. Functional enrichment analysis revealed that differentially expressed genes regulate UTUC through pathways such as cell adhesion, transmembrane receptor protein kinase activity, cGMP-PKG signaling pathway, p53 signaling pathway, and cardiomyocyte adrenergic signaling pathway.
Conclusions
Although these 9 genes are new and significant genes in UTUC, they have been proved in public databases. Our results not only promote our understanding of the relationship between the transcriptome and clinical data in UTUC but will also guide the development of targeted molecular therapy for UTUC.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Medical Device Regulatory Research and Evaluation Center.
Funding
Medical Device Regulatory Research and Evaluation Center.
Disclosure
All authors have declared no conflicts of interest.
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