Characterization and validation of long noncoding RNAs as new candidates in prostate cancer

EVADR ceRNA transcript variants upregulate WNT and PI3K signaling pathways in SW480 and HCT116 cells by sponging miR-7 and miR-29b

Long noncoding RNAs are cancer regulators and EVADR-lncRNA is highly upregulated in colorectal cancer (CRC). Accordingly, we aimed to functionally characterize the EVADR in CRC-originated cells. Firstly, during the amplification of EVADR full-length cDNA (named EVADR-v1), a novel/shorter variant (EVADR-v2) was discovered. Then, RT-qPCR analysis confirmed that EVADR is upregulated in tumors, consistent with RNA-seq analysis. Interestingly, bioinformatics analysis and dual-luciferase assay verified that EVADR sponges miR-7 and miR-29b. When both EVADR-v1/-v2 variants were overexpressed in SW480/HCT116 cells, miR-7 and miR-29b target genes (involved in the WNT/PI3K signaling) were upregulated. Furthermore, EVADR-v1/-v2 overexpression resulted in elevated PI3K activity (verified by western blotting and RT-qPCR) and upregulation of WNT signaling (confirmed by western blotting, TopFlash assay, and RT-qPCR). Consistently, overexpression of EVADR-v1/-v2 variants was followed by increased cell cycle progression, viability and migration as well as reduced early/late apoptotic rate, and Bax/Bcl2 ratio of the CRC cells, detected by the cell cycle analysis, MTT, wound-healing, Annexin-V/PI, and RT-qPCR methods, respectively. Overall, we introduced two oncogenic transcript variants for EVADR that by sponging miR-7/miR-29b, upregulate WNT and PI3K signaling. Given the crucial role of these pathways in CRC, EVADR may present potential therapy use.

Metagenomic analysis of viral genes integrated in whole genome sequencing data of Thai patients with Brugada syndrome

Brugada syndrome (BS) is an autosomal dominant inheritance cardiac arrhythmia disorder associated with sudden death in young adults. Thailand has the highest prevalence of BS worldwide, and over 60% of patients with BS still have unclear disease etiology. Here, we performeda new viral metagenome analysis pipeline called VIRIN and validated it with whole genome sequencing (WGS) data of HeLa cell lines and hepatocellular carcinoma. Then the VIRIN pipelinewas applied to identify viral integration positions from unmapped WGS data of Thai males, including 100 BS patients (case) and 100 controls. Even though the sample preparation had noviral enrichment step, we can identify several virus genes from our analysis pipeline. The predominance of human endogenous retrovirus K (HERV-K) viruses was found in both cases andcontrols by blastn and blastx analysis. This study is the first report on the full-length HERV-Kassembled genomes in the Thai population. Furthermore, the HERV-K integration breakpointpositions were validated and compared between the case and control datasets. Interestingly,Brugada cases contained HERV-K integration breakpoints at promoters five times more oftenthan controls. Overall, the highlight of this study is the BS-specific HERV-K breakpoint positionsthat were found at the gene coding region "NBPF11" (n = 9), "NBPF12" (n = 8) and longnon-coding RNA (lncRNA) "PCAT14" (n = 4) region. The genes and the lncRNA have been reported to be associated with congenital heart and arterial diseases. These findings provide another aspect of the BS etiology associated with viral genome integrations within the humangenome.

The long non-sacoding RNA TMEM147-AS1/miR-133b/ZNF587 axis regulates the Warburg effect and promotes prostatic carcinoma invasion and proliferation

BACKGROUND

The Warburg effect is a characteristic tumor cell behavior regarded as one of the cancer hallmarks and promotes tumor progression by promoting glucose uptake and lactate production. Long non-coding RNAs (lncRNAs) had been reported to emerge as a vital function in cancer development. The present research is designed to investigate the underlying molecular mechanism of lncRNA TMEM147 antisense RNA 1 (TMEM147-AS1) on aerobic glycolysis in prostatic carcinoma.

METHODS

lncRNA TMEM147-AS1, miR-133b and ZNF587 levels in prostatic carcinoma tissues and cells were detected by a polymerase chain reaction or western blot assays. Cell viability or invasion was determined by Edu (i.e. 5-ethynyl-2'-deoxyuridine), MTT (i.e. 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide) or transwell assays. Hematoxylin and eosin and immunohistochemical staining were applied for histopathological examination. Tumor xenograft model was employed to investigate tumor growth in vivo. The combinative relationship between TMEM147-AS1 or ZNF587 and miR-133b was confirmed by a luciferase reporter assay.

RESULTS

TMEM147-AS1 and ZNF587 were up-regulated in prostatic carcinoma tissues and cells. Knockdown of TMEM147-AS1 or ZNF587 within prostate cancer cells significantly restrained cell viability, invasion and aerobic glycolysis in vitro and suppressed the neoplasia of prostatic carcinoma in vivo. miR-133b was directly targeted in both TMEM147-AS1 and ZNF587. Overexpression of miR-133b restrained prostate cancer cell viability, invasion and aerobic glycolysis. TMEM147-AS1 competitively targeted miR-133b, therefore counteracting miR-133b-mediated repression on ZNF587.

CONCLUSIONS

TMEM147-AS1 plays a tumor-promoting action in prostatic carcinoma aerobic glycolysis via affecting the miR-133b/ZNF587 axis, therefore regulating prostatic carcinoma cells invasion and proliferation. These outcomes implied that TMEM147-AS1 could be an effective treatment strategy for further study of prostatic carcinoma.

opplncRNA: A MATLAB Package for Comprehensive Pathway Analysis of lncRNA-miRNA-mRNA in Humans

The discovery of new lncRNAs (long noncoding RNAs) and their regulatory pathways has always been a hotspot in the field of ceRNA (competing endogenous RNA). Herein, we report opplncRNA (Omics Pilot Platform of lncRNA), a novel and rapid tool for investigating lncRNA-miRNA-mRNA interactions based on the architecture of MATLAB AppDesigner. opplncRNA is useful to analyze the regulatory interaction networks of lncRNA with a friendly GUI (graphical user interface). There are three lncRNA databases (ENCORI, LncBase, and miRcode) about lncRNA-miRNA interactions that have been integrated into opplncRNA, as well as seven miRNA databases (miRcode, ENCORI, TarBase, miRTarBase, miRDB, miRanda, and miRecords) about miRNA-mRNA interactions as also. opplncRNA can read expression data from any profile techniques, such as microarray or RNA-seq. Then, the relationships between lncRNA-miRNA and miRNA-mRNA can be directly calculated through the profile data of lncRNA, miRNA, and mRNA by the threshold of correlation coefficients. Integrated databases can be used to filter calculation outcomes to obtain more reliable pathways. Moreover, opplncRNA has the functionality of directly demonstrating 3 layers network from lncRNA to mRNA in command line form.

Multivariate competing endogenous RNA network characterization for cancer MicroRNA biomarker discovery: a novel bioinformatics model with application to prostate cancer metastasis

Background

MicroRNAs (miRNAs) are post-transcriptional regulators with potential as biomarkers for cancer management. Data-driven competing endogenous RNA (ceRNA) network modeling is an effective way to decipher the complex interplay between miRNAs and spongers. However, there are currently no general rules for ceRNA network-based biomarker prioritization.

Methods and results

In this study, a novel bioinformatics model was developed by integrating gene expression with multivariate miRNA-target data for ceRNA network-based biomarker discovery. Compared with traditional methods, the structural vulnerability in the human long non-coding RNA (lncRNA)–miRNA–messenger RNAs (mRNA) network was comprehensively analyzed, and the single-line regulatory or competing mode among miRNAs, lncRNAs, and mRNAs was characterized and quantified as statistical evidence for miRNA biomarker identification. The application of this model to prostate cancer (PCa) metastasis identified a total of 12 miRNAs as putative biomarkers from the metastatic PCa-specific lncRNA–miRNA–mRNA network and nine of them have been previously reported as biomarkers for PCa metastasis. The receiver operating characteristic curve and cell line qRT-PCR experiments demonstrated the power of miR-26b-5p, miR-130a-3p, and miR-363-3p as novel candidates for predicting PCa metastasis. Moreover, PCa-associated pathways such as prostate cancer signaling, ERK/MAPK signaling, and TGF-β signaling were significantly enriched by targets of identified miRNAs, indicating the underlying mechanisms of miRNAs in PCa carcinogenesis.

Conclusions

A novel ceRNA-based bioinformatics model was proposed and applied to screen candidate miRNA biomarkers for PCa metastasis. Functional validations using human samples and clinical data will be performed for future translational studies on the identified miRNAs.