Abstract
Microarrays can simultaneously measure the expression level of thousands of genes within a particular mRNA sample, which permits description of genome-wide expression changes in health and disease. Systematic observe of gene expression profiling allows the establishment of new taxonomy of disease, so here differential gene expression analysis of Papillary thyroid cancer (PTC) from microarray profile, was executed with various computational applications like RStudio Bioconductor Package, DAVID, KEGG mapper, miRNet, which explains the expression level (132 up, 260 down) based on log2 ratio, functional annotations, enriched metabolic pathways and highly linked miRNAs (has-mir-335p, has-mir-335-5p, has-mir-26b-5p) respectively for the resulted significant genes (P value < 0.05) in the progression of PTC. The revealed information regarding thousands of genes of papillary thyroid cancer will be a better dataset for the genetic study of thyroid cancer and also summarize the genomic concept for papillary thyroid carcinoma which might be successfully interpret in future research vicinity.
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