Abstract
Prostate cancer (PCa) is the most frequently diagnosed malignant neoplasm in men. Despite the high incidence, the underlying pathogenic mechanisms of PCa are still largely unknown, which limits the therapeutic options and leads to poor prognosis. Herein, based on the expression profiles from The Cancer Genome Atlas (TCGA) database, we investigated the interactions between long noncoding RNA (lncRNA) and mRNA by constructing a competing endogenous RNA network. Several competing endogenous RNAs could participate in the tumorigenesis of PCa. Six lncRNA signatures were identified as potential candidates associated with stage progression by the Kolmogorov-Smirnov test. In addition, 32 signatures from the coexpression network had potential diagnostic value for PCa lymphatic metastasis using machine learning algorithms. By targeting the coexpression network, the antifungal compound econazole was screened out for PCa treatment. Econazole could induce growth restraint, arrest the cell cycle, lead to apoptosis, inhibit migration, invasion, and adhesion in PC3 and DU145 cell lines, and inhibit the growth of prostate xenografts in nude mice. This systematic characterization of lncRNAs, microRNAs, and mRNAs in the risk of metastasis and progression of PCa will aid in the identification of candidate prognostic biomarkers and potential therapeutic drugs.
Highlights
Prostate cancer (PCa) is the most frequently diagnosed malignant neoplasm and second leading cause of death in men worldwide [1]
The PCa-associated dysregulated competing endogenous RNAs (ceRNAs) network was developed by utilizing sample-matched miRNA, long noncoding RNA (lncRNA), and mRNA expression profiles in combination with the miRNA regulatory network based on the ceRNA hypothesis
XIST/ miR 372/DUSP2 in the ceRNA network was speculated to participate in the epithelial-mesenchymal transition (EMT) process
Summary
Prostate cancer (PCa) is the most frequently diagnosed malignant neoplasm and second leading cause of death in men worldwide [1]. Tumor metastasis is responsible for the majority of deaths [2]. Lymph node metastasis (LNM) is the most important risk factor for treatment in early-stage PCa [3]. The underlying pathogenic mechanisms of PCa are still largely unknown, which limits prognosis and therapy. The identification of new potential biomarkers and therapeutic targets for the progression of PCa would help overcome these serious clinical challenges and improve alternative therapies. Noncoding RNAs (ncRNAs) have become recognized as important molecules in many types of cancer. They are potential biomarkers and can reveal uncharacterized aspects of tumor etiology. Relevant lncRNAs include PCAT1, PCAT5, PCA3, PCGEM1, MALAT1, PRNCR1, CTBP1-AS, TRPM2, and Oxidative Medicine and Cellular Longevity
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