Screening and identification of epithelial-to-mesenchymal transition-related circRNA and miRNA in prostate cancer

Yan, Zhijian; Xiao, Yiming; Chen, Yiyan; Luo, Guangcheng

doi:10.1016/j.prp.2019.152784

Cited by 35 publications

(27 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Shan et al [85] identified consistent expression between microarray and RT-qPCR analyses in four of five selected circRNAs using 90 PCa and paired non-cancerous tissue samples. Yan et al [86] reported that three of four selected circRNAs in PCa cells analyzed by RT-qPCR showed consistent high-throughput sequencing results. Qui et al [87] found an upregulation of circCASP8AP2 in hepatocellular carcinoma compared to adjacent normal tissue by sequencing, but in RT-qPCR analyses, this circRNA was downregulated.…”

Section: Discussionmentioning

confidence: 96%

Circular RNAs and Their Linear Transcripts as Diagnostic and Prognostic Tissue Biomarkers in Prostate Cancer after Prostatectomy in Combination with Clinicopathological Factors

Rochow

Jung

Weickmann

et al. 2020

IJMS

View full text Add to dashboard Cite

As new biomarkers, circular RNAs (circRNAs) have been largely unexplored in prostate cancer (PCa). Using an integrative approach, we aimed to evaluate the potential of circRNAs and their linear transcripts (linRNAs) to act as (i) diagnostic biomarkers for differentiation between normal and tumor tissue and (ii) prognostic biomarkers for the prediction of biochemical recurrence (BCR) after radical prostatectomy. In a first step, eight circRNAs (circATXN10, circCRIM1, circCSNK1G3, circGUCY1A2, circLPP, circNEAT1, circRHOBTB3, and circSTIL) were identified as differentially expressed via a genome-wide circRNA-based microarray analysis of six PCa samples. Additional bioinformatics and literature data were applied for this selection process. In total, 115 malignant PCa and 79 adjacent normal tissue samples were examined using robust RT-qPCR assays specifically established for the circRNAs and their linear counterparts. Their diagnostic and prognostic potential was evaluated using receiver operating characteristic curves, Cox regressions, decision curve analyses, and C-statistic calculations of prognostic indices. The combination of circATXN10 and linSTIL showed a high discriminative ability between malignant and adjacent normal tissue PCa. The combination of linGUCY1A2, linNEAT1, and linSTIL proved to be the best predictive RNA-signature for BCR. The combination of this RNA signature with five established reference models based on only clinicopathological factors resulted in an improved predictive accuracy for BCR in these models. This is an encouraging study for PCa to evaluate circRNAs and their linRNAs in an integrative approach, and the results showed their clinical potential in combination with standard clinicopathological variables.

show abstract

Section: Discussionmentioning

confidence: 96%

Circular RNAs and Their Linear Transcripts as Diagnostic and Prognostic Tissue Biomarkers in Prostate Cancer after Prostatectomy in Combination with Clinicopathological Factors

Rochow

Jung

Weickmann

et al. 2020

IJMS

View full text Add to dashboard Cite

show abstract

“…Then, GO function (BP, CC, and MF) analysis of DEMs and DEGs demonstrated the majority of miRNAs and genes were involved in some processes and pathways, such as cell communication, and signal transduction in BP [42,43], extracellular space, and nucleus in CC [44,45], transcription factor activity, extracellular matrix structural constituent in MF [46,47], which is consistent with the previous studies on tumors. Biological pathway analysis of DEGs and DEMs showed the majority of genes and miRNAs were participated in in regulating epithelial-tomesenchymal transition [48], PI3K-Akt signaling pathway [49], mTOR pathway [50], EGF receptor pathway [51], VEGF and VEGFR network [52], IFN-gamma pathway [53], PDGF receptor network [54], and ErbB receptor signaling network [55]. Previous studies had shown these pathways played vital roles in PCa progression.…”

Section: Discussionmentioning

confidence: 99%

Identification of a novel six autophagy-related genes signature for the prognostic and a miRNA-related autophagy predictor for anti-PD-1 therapy responses in prostate cancer

Quan

Yue

et al. 2021

Preprint

View full text Add to dashboard Cite

Background: Autophagy is a highly conserved homeostatic process in the human body that is responsible for the elimination of aggregated proteins and damaged organelles. Several autophagy-related genes (ARGs) contribute to the process of tumorigenesis and metastasis of prostate cancer (PCa). Also, miRNAs have been proven to modulate autophagy by targeting some ARGs. However, their potential role in PCa still remains unclear.Methods: An univariate Cox proportional regression model was used to identify 17 ARGs associated with the overall survival (OS) of PCa. Then, a multivariate Cox proportional regression model was used to construct a 6 autophagy-related prognostic genes signature. Patients were divided into low-risk group and high-risk group using the median risk score as a cutoff value. High-risk patients had shorter OS than low-risk patients. Furthermore, the signature was validated by ROC curves. Regarding mRNA and miRNA, 12 differentially expressed miRNAs (DEMs) and 1073 differentially expressed genes (DEGs) were detected via the GEO database. We found that miR-205, one of the DEMs, was negatively regulated the expression of ARG (NKX2-3). Based on STRING analysis results, we found that the NKX2-3 was moderately related to the part of genes among the 6 autophagy-related genes prognostic signature. Further, NKX 2-3 was significantly correlated with OS and some clinical parameters of PCa by cBioProtal. By gene set enrichment analysis (GSEA). Lastly, we demonstrated that the association between NKX2-3 and tumor mutation burden (TMB) and PDCD1 (programmed cell death 1) of PCa.Results: We identified that the six ARGs expression patterns are independent predictors of OS in PCa patients. Furthermore, our results suggest that ARGs and miRNAs are inter-related. MiR-205 was negatively regulated the expression of ARG (NKX2-3). Further analysis demonstrated that NKX2-3 may be a potential biomarker for predicting the efficacy of anti-PD-1 therapy in PCa.Conclusions: The current study may offer a novel autophagy-related prognostic signature and may identify a promising miRNA-ARG pathway for predicting the efficacy of anti-PD-1 therapy in PCa.

show abstract

“…The circRNAs identified in this study have not been reported previously. Therefore, we performed a literature review of circRNAs in PCa in the PubMed database, identifying 13 studies ( Xia et al, 2018 ; Shen et al, 2019 ; Song et al, 2019 ; Wang et al, 2019 ; Wu et al, 2019 ; Hu and Guo, 2020 ; Kong et al, 2020 ; Li T. et al, 2020 ; Ou et al, 2020 ; Shan et al, 2020 ; Yan et al, 2020 ; Zheng et al, 2020a , b ) of 18 circRNA–miRNA interactions. The miRNAs identified in this study have previously been shown to play important roles in PCa.…”

Section: Discussionmentioning

confidence: 99%

Identification of Prostate Cancer-Related Circular RNA Through Bioinformatics Analysis

Lin

Chen

et al. 2020

Front. Genet.

View full text Add to dashboard Cite

Background: Prostate cancer (PCa) is one of the most common malignant tumors worldwide. Accumulating evidence has suggested that circular RNAs (circRNAs) are involved in the development and progression of various cancers, and they show great potential as novel biomarkers. However, the underlying mechanisms and specific functions of most circRNAs in PCa remain unknown. Here, we aimed to identify circRNAs with potential roles in PCa from the PCa expression profile. Methods: We used data downloaded from the Gene Expression Omnibus to identify circRNAs that were differentially expressed between PCa samples and adjacent nontumor samples. Relative expression levels of identified circRNAs were validated by quantitative real-time PCR. Micro (mi)RNA response elements were predicted by the CircInteractome database, and miRNA target genes were predicted by miRDB, miRTarBase, and TargetScan databases. Gene ontology (GO) enrichment analysis and pathway analysis revealed the potential biological and functional roles of these target genes. A circRNA-miRNA-mRNA interaction network was constructed by Cytoscape. The interaction between circRNAs and miRNAs in PCa was thoroughly reviewed in the PubMed. Finally, the mRNA expression of these genes was validated by the Cancer Genome Atlas (TCGA) and Gene Expression Profiling Interactive Analysis (GEPIA) databases. The expression of proteins encoded by these genes was further validated by the Human protein Atlas (HPA) database. Results: A total of 60 circRNAs that were differentially expressed between PCa and healthy samples were screened, of which 15 were annotated. Three circRNAs (hsa_circ_0024353, hsa_circ_0085494, hsa_circ_0031408) certified the criteria were studied. The results of quantitative real-time PCR demonstrated that the expression of hsa_circ_0024353 was significantly downregulated in PC-3 cells when compared with RWPE-1 cells, while the expression of hsa_circ_0031408 and hsa_circ_0085494 was significantly upregulated in PC-3 cells when compared with RWPE-1 cells. GO and Kyoto Encyclopedia of Genes and Genomes analyses found that target genes were mainly enriched in metabolic processes and pathways involving phosphoinositide 3-kinase-Akt signaling, hypoxia-inducible factor-1 signaling, p53 signaling, and the cell cycle. A total of 11 miRNA target genes showing differential expression between

show abstract

Screening and identification of epithelial-to-mesenchymal transition-related circRNA and miRNA in prostate cancer

Cited by 35 publications

References 44 publications

Circular RNAs and Their Linear Transcripts as Diagnostic and Prognostic Tissue Biomarkers in Prostate Cancer after Prostatectomy in Combination with Clinicopathological Factors

Circular RNAs and Their Linear Transcripts as Diagnostic and Prognostic Tissue Biomarkers in Prostate Cancer after Prostatectomy in Combination with Clinicopathological Factors

Identification of a novel six autophagy-related genes signature for the prognostic and a miRNA-related autophagy predictor for anti-PD-1 therapy responses in prostate cancer

Identification of Prostate Cancer-Related Circular RNA Through Bioinformatics Analysis

Contact Info

Product

Resources

About