Abstract:
Clear cell renal cell carcinoma (ccRCC) is the most predominant sub type of
Renal cell carcinoma and accounts for about 75-80% of all kidney malignancies. Although
extensive studies have been carried out for identifying the therapeutic targets
of ccRCC. Yet, patients that undergo targeted therapies eventually exhibit continued
disease progression or are resistant to the approved targeted drugs. Therefore,
there is an urge to discover novel biomarkers and therapeutic targets for ccRCC. The
integration of powerful approaches like meta-analysis of microarrays and next generation
sequencing provides an opportunity to get better insights into pathogenesis
of ccRCC and to predict more reliable potential biomarkers and therapeutic targets
for ccRCC . The unavailability of a stand-alone Graphical user Interface(GUI) for
meta-analysis of microarrays limits the research of a biologist having little knowledge
over programming and linux commands. Identifying molecular biomarkers and therapeutic
target and designing an interactive interface for meta-analysis of microarrays
has been at the forefront of current study. In order to achieve the goals and objectives
of the study, an interface was designed for meta-analysis of microarrays and
meta-analysis using the developed interface and miRNA-seq data analysis have been
performed. The data analysis has revealed SLC25A3, HNRNP, ZPR1, ABCF1, CBX3,
ELOB, STARD7,RPS24, CFL1, SMNDC1 and EIF4G2 as significant differentially
expressed genes for disease. The effect of differential expression of ZPR1, ABCF1,
CBX3, STARD7 and SMNDC1 genes in ccRCC patients is not stated in the literature
therefore these genes can be considered as novel discovery. The genes CBX3 and
SMNDC1 already serves as therapeutic targets for different carcinomas. Hence, these
two genes could be taken as therapeutic targets for ccRCC. Rational drug designing
should be performed while considering CBX3 and SMNDC1 as targets to pave a path
towards improved and effective therapy for ccRCC
