Introduction: Prostate cancer (PC) is a major public health problem among men population, and the third-leading cause of death. A large number of factors have been associated with the patient survival including cancer stage at the time of diagnosis. Due to the false positive results in panelPSA., therefore, identification of specific biomarkers for early PC diagnosis is demanded
Methods: . This survey aims to identify the specific biomarkers in PC for designing a diagnosis panel by in silico analysis.
Rna-seq data of 15 different cancers was extracted from Cancer Genome Atlas. Differentially expressed genes (DEGs) were identified among these cancer types. Then, the genes were recognized only in prostate sample across normal one. The DEGs were also identified among PC and 14 cancers. Subsequently, the up-regulated genes were merged.
Results: We found 246 genes were up-regulated in PC than 14 cancer types. Subsequently, these genes were analysed in prostate cancer samples across normal one. Twenty-four genes were identified specifically in PC. Following the data selection by means of >100 copy number, six highly transcribed genes were identified as specific biomarkers in PC.It is interesting that most of these genes were long non-coding RNA that include AP006748.1,AF35931401,ARLNC1,
GPC5-AS1,PCA3,SCHLAP1
Conclusion: We already found that PCA3 is a common in the existed panel. These six genes in PC can be introduced as new diagnosis biomarkers that may be applied as a potential specific panel
Keywords: In silico, Prostate Cancer,Biomarker, Diagnosis Panel.