The Evolutionarily Conserved Cassette Exon 7b Drives ERG's Oncogenic Properties

Long Non-Coding RNAs as Novel Biomarkers in the Clinical Management of Papillary Renal Cell Carcinoma Patients: A Promise or a Pledge?

Papillary renal cell carcinoma (pRCC) represents the second most common subtype of renal cell carcinoma, following clear cell carcinoma and accounting for 10–15% of cases. For around 20 years, pRCCs have been classified according to their mere histopathologic appearance, unsupported by genetic and molecular evidence, with an unmet need for clinically relevant classification. Moreover, patients with non-clear cell renal cell carcinomas have been seldom included in large clinical trials; therefore, the therapeutic landscape is less defined than in the clear cell subtype. However, in the last decades, the evolving comprehension of pRCC molecular features has led to a growing use of target therapy and to better oncological outcomes. Nonetheless, a reliable molecular biomarker able to detect the aggressiveness of pRCC is not yet available in clinical practice. As a result, the pRCC correct prognosis remains cumbersome, and new biomarkers able to stratify patients upon risk of recurrence are strongly needed. Non-coding RNAs (ncRNAs) are functional elements which play critical roles in gene expression, at the epigenetic, transcriptional, and post-transcriptional levels. In the last decade, ncRNAs have gained importance as possible biomarkers for several types of diseases, especially in the cancer universe. In this review, we analyzed the role of long non-coding RNAs (lncRNAs) in the prognosis of pRCC, with a particular focus on their networking. In fact, in the competing endogenous RNA hypothesis, lncRNAs can bind miRNAs, resulting in the modulation of the mRNA levels targeted by the sponged miRNA, leading to additional regulation of the target gene expression and increasing complexity in the biological processes.

In situ expression of ERG protein in the context of tumor heterogeneity identifies prostate cancer patients with inferior prognosis

Prognostic biomarkers for prostate cancer are needed to improve prediction of disease course and guide treatment decisions. However, biomarker development is complicated by the common multifocality and heterogeneity of the disease. We aimed to determine the prognostic value of candidate biomarkers transcriptional regulator ERG and related ETS family genes, while considering tumor heterogeneity. In a multisampled, prospective, and treatment‐naïve radical prostatectomy cohort from one tertiary center (2010–2012, median follow‐up 8.1 years), we analyzed ERG protein (480 patients; 2047 tissue cores), and RNA of several ETS genes in a subcohort (165 patients; 778 fresh‐frozen tissue samples). Intra‐ and interfocal heterogeneity was identified in 29% and 33% (ERG protein) and 39% and 27% (ETS RNA) of patients, respectively. ERG protein and ETS RNA was identified exclusively in a nonindex tumor in 31% and 32% of patients, respectively. ERG protein demonstrated independent prognostic value in predicting biochemical (P = 0.04) and clinical recurrence (P = 0.004) and appeared to have greatest prognostic value for patients with Grade Groups 4–5. In conclusion, when heterogeneity is considered, ERG protein is a robust prognostic biomarker for prostate cancer.

Targeting the ERG oncogene with splice-switching oligonucleotides as a novel therapeutic strategy in prostate cancer

BACKGROUND

The ERG oncogene, a member of the ETS family of transcription factor encoding genes, is a genetic driver of prostate cancer. It is activated through a fusion with the androgen-responsive TMPRSS2 promoter in 50% of cases. There is therefore significant interest in developing novel therapeutic agents that target ERG. We have taken an antisense approach and designed morpholino-based oligonucleotides that target ERG by inducing skipping of its constitutive exon 4.

METHODS

We designed antisense morpholino oligonucleotides (splice-switching oligonucleotides, SSOs) that target both the 5' and 3' splice sites of ERG's exon 4. We tested their efficacy in terms of inducing exon 4 skipping in two ERG-positive cell lines, VCaP prostate cancer cells and MG63 osteosarcoma cells. We measured their effect on cell proliferation, migration and apoptosis. We also tested their effect on xenograft tumour growth in mice and on ERG protein expression in a human prostate cancer radical prostatectomy sample ex vivo.

RESULTS

In VCaP cells, both SSOs were effective at inducing exon 4 skipping, which resulted in a reduction of overall ERG protein levels up to 96 h following a single transfection. SSO-induced ERG reduction decreased cell proliferation, cell migration and significantly increased apoptosis. We observed a concomitant reduction in protein levels for cyclin D1, c-Myc and the Wnt signalling pathway member β-catenin as well as a marker of activated Wnt signalling, p-LRP6. We tested the 3' splice site SSO in MG63 xenografts in mice and observed a reduction in tumour growth. We also demonstrated that the 3' splice site SSO caused a reduction in ERG expression in a patient-derived prostate tumour tissue cultured ex vivo.

CONCLUSIONS

We have successfully designed and tested morpholino-based SSOs that cause a marked reduction in ERG expression, resulting in decreased cell proliferation, a reduced migratory phenotype and increased apoptosis. Our initial tests on mouse xenografts and a human prostate cancer radical prostatectomy specimen indicate that SSOs can be effective for oncogene targeting in vivo. As such, this study encourages further in vivo therapeutic studies using SSOs targeting the ERG oncogene.

Long non-coding RNA PVT1 encapsulated in bone marrow mesenchymal stem cell-derived exosomes promotes osteosarcoma growth and metastasis by stabilizing ERG and sponging miR-183-5p

Exosomes secreted by bone marrow mesenchymal stem cells (BMSCs) promote osteosarcoma cell proliferation and migration, while the underlying mechanism remains unknown. Since the long non-coding RNA PVT1 has been reported to be upregulated in osteosarcoma cells and contributes to its growth and metastasis, we aim to investigate whether BMSC-derived exosomes promote osteosarcoma growth and metastasis via transporting PVT1 into osteosarcoma cells. The PVT1 expression in BMSC-derived exosomes was markedly higher than that in osteosarcoma cell-derived exosomes. The co-culturing of BMSC-derived exosomes and osteosarcoma cells (Saos-2, MG-63, and MNNG/HOS cell lines) significantly raised PVT1 expression of osteosarcoma cells. The direct binding between PVT1 and the oncogenic protein ERG was confirmed using RNA immunoprecipitation and RNA pull-down assays, and the transported PVT1 promotes osteosarcoma cell proliferation and migration via inhibiting degradation and ubiquitination of ERG. PVT1 also increased ERG expression through sponging miR-183-5p. In summary, our findings indicated that BMSC-derived exosomes encapsulate PVTl and transport it into osteosarcoma cells, and the transported PVT1 promotes tumor growth and metastasis by inhibiting ubiquitination and promoting expression of ERG in osteosarcoma cells. These data provide a novel insight into the mechanism of BMSC-derived exosomes in affecting osteosarcoma progression.

Fusion transcripts: Unexploited vulnerabilities in cancer?

Gene fusions are an important class of mutations in several cancer types and include genomic rearrangements that fuse regulatory or coding elements from two different genes. Analysis of the genetics of cancers harboring fusion oncogenes and the proteins they encode have enhanced cancer diagnosis and in some cases patient treatment. However, the effect of the complex structure of fusion genes on the biogenesis of the resulting chimeric transcripts they express is not well studied. There are two potential RNA‐related vulnerabilities inherent to fusion‐driven cancers: (a) the processing of the fusion precursor messenger RNA (pre‐mRNA) to the mature mRNA and (b) the mature mRNA. In this study, we discuss the effects that the genetic organization of fusion oncogenes has on the generation of translatable mature RNAs and the diversity of fusion transcripts expressed in different cancer subtypes, which can fundamentally influence both tumorigenesis and treatment. We also discuss functional genomic approaches that can be utilized to identify proteins that mediate the processing of fusion pre‐mRNAs. Furthermore, we assert that an enhanced understanding of fusion transcript biogenesis and the diversity of the chimeric RNAs present in fusion‐driven cancers will increase the likelihood of successful application of RNA‐based therapies in this class of tumors.

This article is categorized under:

RNA Processing > RNA Editing and Modification

RNA Processing > Splicing Regulation/Alternative Splicing

RNA in Disease and Development > RNA in Disease

Comprehensive analysis of competing endogenous RNA network and 3-mRNA signature predicting survival in papillary renal cell cancer

Long non-coding RNAs (lncRNAs) can act as competing endogenous RNAs (ceRNAs) to exert significant roles in regulating the expression of mRNAs by sequestering and binding miRNAs. To elucidate the functional roles and regulatory mechanism of lncRNAs in papillary renal cell cancer (pRCC), we conducted a comprehensive analysis of ceRNA network and constructed a mRNA signature to predict prognosis of pRCC.We collected mRNAs and lncRNAs expression profiles of 289 pRCC samples and 32 normal renal tissues, and miRNA expression profiles of 292 pRCC samples and 34 normal samples from The Cancer Genome Atlas (TCGA) database. Differential expressions of RNAs were evaluated by the "edgeR" package in R. Functional enrichment analysis of DEmRNA was performed by DAVID 6.8 and KEGG, while PPI network of top 200 DEmRNAs was conducted using the STRING database. The univariate and multivariate Cox regression were conducted to figure out the candidate DEmRNAs with predictive values in prognosis. Receiver operator characteristic (ROC) curve estimation was performed to achieve the area under the curve (AUC) of the ROC curve to judge mRNA-associated prognosic model. A ceRNA network was established relying on the basis of combination of lncRNA-miRNA interactions and miRNA-mRNA interactions.A total of 1928 DEmRNAs, 981 DElncRNAs, and 52 DEmiRNAs were identified at significance level of |log2Fold Change |>2 and adjusted P-value < .01. A 3-mRNA signatures consisting of ERG, RRM2, and EGF was constructed to predict survival in pRCC. Moreover, a pRCC-associated ceRNA network was constructed, with 57 lncRNAs, 11 miRNAs, and 28 mRNAs.Our study illustrated the regulatory mechanism of ceRNA network in papillary renal cancer. The identified mRNA signatures could be used to predict survival of pRCC.