The two mRNA microarray datasets from the Gene Expression Omnibus (GEO) collection were used to find significant DEGs among PRCC and normal kidney tubules in this investigation. Microarray technology has been widely utilized to search for genetic variations at the genetic level over the last several years, which has allowed us to uncover specific genes, including DEGs and activities associated with PRCC tumorigenesis and development. Bioinformatics is a technology that combines computational analysis and molecular biology, providing a clear direction for the study of genes. Microarray technology is an efficient, large-scale genetic data acquisition technology that allows the simultaneous study of the relationships between many thousands of gene expression levels and diseases and can provide insights into the mechanism of tumors. In-depth studies on the prevalence and spread of renal papillary cancer, as well as the development of useful biological molecular indicators, will assist lead advances in the diagnosis and treatment of PRCC, thanks to the current advancement of medical science. To create better screening and therapeutic options, it is critical to know the specific molecular mechanisms involved in the tumorigenesis, multiplication, and recurring of PRCC. Biological molecular markers for PRCC are presently unavailable. Nevertheless, certain individuals are more likely to develop metastasis and recurrence following the surgery, culminating in a very bad outlook. Surgery remains the first option of treatment options due to a lack of efficient diagnostic tools in the early stages of PRCC, a lack of knowledge of the molecular mechanism of PRCC, and PRCC’s low susceptibility to radiotherapy and chemotherapy. The grade of PRCC was better than ccRCC, and their 5-year overall survival rate is much greater. The majority of kidney cancer charities have been concentrated on pure cell renal cell carcinoma (ccRCC). Patients with type I have a better prognosis than type II. The prognoses of type I (basophilic) and type II (eosinophilic) PRCC are totally different. The second most prevalent subtype of kidney cancer is papillary renal cell carcinoma (PRCC), which accounts for 15%-20% of RCC. In 2018, over 175,000 RCC individuals died throughout the world, while about 400,000 reported cases were diagnosed. Kidney carcinoma (RCC) affects the urinary tract. EGF might be a predictive biomarker for PRCC and therefore should be investigated as a novel treatment strategy. We revealed important genes and proposed biological pathways that may be implicated in the formation of PRCC. The higher expression group of EGF was associated with poor outcome in patients with PRCC. The CytoHubba plug-in-based analysis identified the 10 hub genes ( ALB, KNG1, C3, CXCL12, EGF, TIMP1, VCAN, PLG, LAMC1, and CASR) from the original PPI network. Renal growth, external exosome, binding of heparin, and metabolic processes were all substantially associated with DEGs. From the selected datasets, a total of 240 common DEGs were identified in the PRCC, including 50 upregulated genes and 190 downregulated regulated genes. The hub genes were subjected to a Kaplan-Meier analysis to identify their correlations with survival rates. Using the Cytoscape technology, a protein-protein interaction (PPI) network that associated with DEGs was created, and the hub genes were identified using the Cytoscape plug-in CytoHubba. The STRING database was utilized to construct the PPI network of DEGs. The online tool DAVID and ClusterProfiler package in R software were used to analyze Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway dominance, respectively. We used the R package limma to identify the differentially expressed genes (DEGs). ![]() We searched the Gene Expression Omnibus (GEO) datasets to obtain the GSE11151 and GSE15641 gene expression profiles of PRCC. This research was aimed at uncovering the possible biomarkers and the underlying principles in PRCC using a bioinformatics method. Due to a lack of knowledge of the disease process, papillary renal cell carcinoma (PRCC) has a dismal outlook.
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