An in-silico Approach for Recognition of Long non-coding RNA-Associated Competing Endogenous RNA Axes in Prostate Cancer - Taheri, Mohammad; Safarzadeh, Arash; Ghafouri-Fard, Soudeh; Baniahmad, Aria (Urology Journal, 2024)
Purpose: Prostate cancer is among the most central sources of cancer-related mortalities. In order to find novel candidates for therapeutic strategies in this kind of cancer, we developed an in-silico method for identification of competing endogenous RNA network. Methods: According to the microarray data analyses between prostate tumor and normal specimens, we attained 1312 differentially expressed (DE)mRNAs, including 778 down-regulated DEmRNAs (such as CXCL13 and BMP5) and 584 up-regulated DEmRNAs (such as OR51E2 and LUZP2), 39 DElncRNAs, including 10 down-regulated DElncRNAs (such as UBXN10-AS1 and FENDRR) and 29 up-regulated DElncRNAs (such as PCA3 and LINC00992) and 10 DEmiRNAs, including 2 down-regulated DEmiRNAs (such as MIR675 and MIR1908) and 8 up-regulated DEmiRNAs (such as MIR6773 and MIR4683). Results: We constructed the ceRNA network between these transcripts. We also evaluated the related signaling pathways and the significance of these RNAs in prediction of survival of patients with prostate cancer. Conclusion: This study provides novel candidates for construction of specific treatment routes for prostate cancer.