Abstract
Micro-abstract: Using the publicly available datasets, we have investigated the list of critical pathways and the genes which appear to be clinically highly significant in case of renal cell carcinoma. ARHGAP6, TGM4, CD248, SLC13A3, EPO, PARD6A, CLCA2, UBE2S, ERAL1, FGFR1, MRVI1, DYNC1I2, CDCA7 are among the top ranked genes which appeared highly significant in terms of patient survival.Clinical practice points: Using the publicly available datasets, we have investigated the gene expression profiling for renal cell carcinoma. In the previous work, it has been focused on selected genes and pathways. Here, we have investigated the list of critical pathways and the genes which appear to be clinically highly significant in case of renal cell carcinoma. ARHGAP6, TGM4, CD248, SLC13A3, EPO, PARD6A, CLCA2, UBE2S, ERAL1, FGFR1, MRVI1, DYNC1I2, CDCA7 are among the top ranked genes which appeared highly significant in terms of patient survival. These genes leads to potential alteration in PI3K-Akt, Foxo, endocytosis, MAPK, tight junction, cytokine-cytokine receptor interaction pathways. Our work will help in diagnosing the renal cell carcinoma patients because here, we have presented the differentially expressed genes, their inferred pathways, and the clinical impact of the selective genes. Since, our finding is from overall perspective including clinical relevance so this study will help in future for diagnostic also.Background: Cancer is among the highly complex disease and renal cell carcinoma is the sixth-leading cause of cancer death. In order to understand complex diseases such as cancer, diabetes and kidney diseases, high-throughput data are generated at large scale and it has helped in the research and diagnostic advancement. However, to unravel the meaningful information from such large datasets for comprehensive and minute understanding of cell phenotypes and disease pathophysiology remains a trivial challenge and also the molecular events leading to disease onset and progression are not well understood. Methods: With this goal, we have collected gene expression datasets from publicly available dataset which are for two different stages (I and II) for renal cell carcinoma.Results and conclusion: In this work, we have applied computational approach to unravel the differentially expressed genes, their networks for the enriched pathways. Based on our results, we conclude that among the most dominantly altered pathways for renal cell carcinoma, are PI3K-Akt, Foxo, endocytosis, MAPK, Tight junction, cytokine-cytokine receptor interaction pathways and the major source of alteration for these pathways are MAP3K13, CHAF1A, FDX1, ARHGAP26, ITGBL1, C10orf118, MTO1, LAMP2, STAMBP, DLC1, NSMAF, YY1, TPGS2, SCARB2, PRSS23, SYNJ1, CNPPD1, PPP2R5E. In terms of clinical significance, there are large number of differentially expressed genes which appears to be playing critical roles in survival.
Identification and Classification of Differentially Expressed Genes in Renal Cell Carcinoma by Expression Profiling on a Global Human 31,500-Element cDNA Array
