Markers for Papillary Renal Cell Carcinoma

Renal cell carcinoma (RCC) is the most common kidney cancer and originates from epithelial cells of the renal tubular system. One and the second most common type of RCC is papillary renal cell carcinoma (pRCC), which accounts for 10 to 15 percent of carcinomas. There are two subtypes, type I and type II, with type I having a better prognosis. Most studies of kidney cancer show that pRCC patients usually have a lower tumor stage and grade and have longer overall survival. However, the molecular mechanism of pRCC is not clear, and the preferred treatment method is surgery.

The Cancer Genome Atlas (TCGA) project aims to use high-throughput genome analysis technology to improve cancer diagnosis and treatment. In a recent study published in the Journal of Oncology, researchers now examined key genes associated with the occurrence and development of pRCC using TCGA data. To do so, they used differential gene enrichment analysis, a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, protein-protein interaction (PPI) networks, and survival analysis.

Using high-throughput genome analysis to improve cancer diagnosis and treatment

The aim of this study was to identify differentially expressed genes (DEGs) in papillary renal cell carcinoma (pRCC) by analyzing transcriptome data from TCGA. DEGs were identified using edgeR software in the R language and various clustering and classification algorithms. The DAVID database was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. In addition, the STRING database was used for protein-protein interaction analysis and selection of the top 10 hub genes. Survival analysis was performed for the hub genes using the Kaplan-Meier method and log-rank values. The study also collected 60 paired pRCC samples and normal kidney samples and performed quantitative RT-PCR to validate the expressions of the hub genes. Statistical analysis was performed using SPSS and GraphPad Prism. The relationship between hub gene expression, patient characteristics and prognosis was analyzed using Pearson's chi-square test and Cox proportional hazard model.

Main findings: BDKRB1, NMUR2, PMCH and SAA1 decrease the survival rate

The results showed that the differentially expressed genes were enriched in excretion, ion transport, and calcium ion binding. The top 10 genes in the PPI network were BDKRB2, NMUR2, NMU, BDKRB1, LPAR5, KNG1, LPAR3, SAA1, MCHR1, and PMCH. Moreover, the expression levels of BDKRB1, NMUR2, PMCH, and SAA1 were associated with poorer survival of pRCC patients and were significantly higher in pRCC tissues than in normal adjacent tissues. The expression of these hub genes also correlated positively with tumor stage, lymph node metastasis. The same applies to histopathological grade of pRCC patients, but not to patient sex or age. Survival analysis showed that high levels of BDKRB1, NMUR2, PMCH, and SAA1 were associated with poor prognosis for pRCC patients.

The authors conclude:

BDKRB1, NMUR2, PMCH, and SAA1 may contribute to the occurrence and development of papillary renal cell carcinoma. This identification of specific biological functions that may be involved in the mechanism of pRCC development provides new clues and directions for efforts to develop future treatments for papillary renal cell carcinoma.

Summing up

  • 1,992 differentially expressed genes (DEGs) were found in the study, including 1,142 up-regulated genes and 850 down-regulated genes.

  • The DEGs were analyzed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG).

  • The study also created a protein-protein interaction (PPI) network using the DEGs. The researchers found several node genes, including BDKRB1, NMUR2, PMCH, and also SAA1, that are critical for pRCC development.

  • BDKRB1 is a known tumor suppressor gene. In contrast, KNG1 showed no significant effect on survival and LPAR3 was downregulated in pRCC.