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Long non-coding RNAs (lncRNAs) are emerging as new players in the cancer paradigm demonstrating potential roles in both oncogenic and tumor suppressive pathways. These novel genes are frequently aberrantly expressed in a variety of human cancers, however the biological functions of the vast majority remain unknown. Recently, evidence has begun to accumulate describing the molecular mechanisms by which these RNA species function, providing insight into the functional roles they may play in tumorigenesis. In this review, we highlight the emerging functional role of lncRNAs in human cancer.

Molecular stratification can improve the management of advanced cancers, but requires relevant tumor samples. Metastatic urothelial carcinoma (mUC) is poised to benefit given a recent expansion of treatment options and its high genomic heterogeneity. We profile minimally-invasive plasma circulating tumor DNA (ctDNA) samples from 104 mUC patients, and compare to same-patient tumor tissue obtained during invasive surgery. Patient ctDNA abundance is independently prognostic for overall survival in patients initiating first-line systemic therapy. Importantly, ctDNA analysis reproduces the somatic driver genome as described from tissue-based cohorts. Furthermore, mutation concordance between ctDNA and matched tumor tissue is 83.4%, enabling benchmarking of proposed clinical biomarkers. While 90% of mutations are identified across serial ctDNA samples, concordance for serial tumor tissue is significantly lower. Overall, our exploratory analysis demonstrates that genomic profiling of ctDNA in mUC is reliable and practical, and mitigates against disease undersampling inherent to studying archival primary tumor foci. We urge the incorporation of cell-free DNA profiling into molecularly-guided clinical trials for mUC. In metastatic urothelial carcinoma, it has not been established whether circulating tumor DNA (ctDNA) can replace archival primary tissue to assess mutations and biomarkers. Here, the authors show high mutation concordance between ctDNA and tumour tissue, with high consistency in serial samples.

Systemic metabolic alterations associated with increased consumption of saturated fat and obesity are linked with increased risk of prostate cancer progression and mortality, but the molecular underpinnings of this association are poorly understood. Here, we demonstrate in a murine prostate cancer model, that high-fat diet (HFD) enhances the MYC transcriptional program through metabolic alterations that favour histone H4K20 hypomethylation at the promoter regions of MYC regulated genes, leading to increased cellular proliferation and tumour burden. Saturated fat intake (SFI) is also associated with an enhanced MYC transcriptional signature in prostate cancer patients. The SFI-induced MYC signature independently predicts prostate cancer progression and death. Finally, switching from a high-fat to a low-fat diet, attenuates the MYC transcriptional program in mice. Our findings suggest that in primary prostate cancer, dietary SFI contributes to tumour progression by mimicking MYC over expression, setting the stage for therapeutic approaches involving changes to the diet. Prostate cancer progression may be enhanced by a high-fat diet. Here the authors show that a diet high in saturated fats enhance the MYC-driven transcriptional program, a feature that independently predicts prostate cancer progression and death.

Once thought to be a part of the 'dark matter' of the genome, long non-coding RNAs (lncRNAs) are emerging as an integral functional component of the mammalian transcriptome. LncRNAs are a novel class of mRNA-like transcripts which, despite no known protein-coding potential, demonstrate a wide range of structural and functional roles in cellular biology. However, the magnitude of the contribution of lncRNA expression to normal human tissues and cancers has not been investigated in a comprehensive manner. In this study, we compiled 272 human serial analysis of gene expression (SAGE) libraries to delineate lncRNA transcription patterns across a broad spectrum of normal human tissues and cancers. Using a novel lncRNA discovery pipeline we parsed over 24 million SAGE tags and report lncRNA expression profiles across a panel of 26 different normal human tissues and 19 human cancers. Our findings show extensive, tissue-specific lncRNA expression in normal tissues and highly aberrant lncRNA expression in human cancers. Here, we present a first generation atlas for lncRNA profiling in cancer.

Frogs play important ecological roles, and several species are important model organisms for scientific research. The globally distributed Ranidae (true frogs) are the largest frog family, and have substantial evolutionary distance from the model laboratory Xenopus frog species. Unfortunately, there are currently no genomic resources for the former, important group of amphibians. More widely applicable amphibian genomic data is urgently needed as more than two-thirds of known species are currently threatened or are undergoing population declines. We report a 5.8 Gbp (NG50 = 69 kbp) genome assembly of a representative North American bullfrog ( Rana [Lithobates] catesbeiana ). The genome contains over 22,000 predicted protein-coding genes and 6,223 candidate long noncoding RNAs (lncRNAs). RNA-Seq experiments show thyroid hormone causes widespread transcriptional change among protein-coding and putative lncRNA genes. This initial bullfrog draft genome will serve as a key resource with broad utility including amphibian research, developmental biology, and environmental research. The globally-distributed Ranidae (true frogs) are the largest frog family. Here, Hammond et al. present a draft genome of the North American bullfrog, Rana ( Lithobates ) catesbeiana , as a foundation for future understanding of true frog genetics as amphibian species face difficult environmental challenges.

Background Muscle-invasive bladder cancer (MIBC) is a heterogeneous disease, and gene expression profiling has identified several molecular subtypes with distinct biological and clinicopathological characteristics. While MIBC subtyping has primarily been based on messenger RNA (mRNA), long non-coding RNAs (lncRNAs) may provide additional resolution. Methods LncRNA expression was quantified from microarray data of a MIBC cohort treated with neoadjuvant chemotherapy (NAC) and radical cystectomy (RC) ( n  = 223). Unsupervised consensus clustering of highly variant lncRNAs identified a four-cluster solution, which was characterized using a panel of MIBC biomarkers, regulon activity profiles, gene signatures, and survival analysis. The four-cluster solution was confirmed in The Cancer Genome Atlas (TCGA) cohort ( n  = 405). A single-sample genomic classifier (GC) was trained using ridge-penalized logistic regression and validated in two independent cohorts ( n  = 255 and n  = 94). Results NAC and TCGA cohorts both contained an lncRNA cluster (LC3) with favorable prognosis that was enriched with tumors of the luminal-papillary (LP) subtype. In both cohorts, patients with LP tumors in LC3 (LPL-C3) were younger and had organ-confined, node-negative disease. The LPL-C3 tumors had enhanced FGFR3, SHH, and wild-type p53 pathway activity. In the TCGA cohort, LPL-C3 tumors were enriched for FGFR3 mutations and depleted for TP53 and RB1 mutations. A GC trained to identify these LPL-C3 patients showed robust performance in two validation cohorts. Conclusions Using lncRNA expression profiles, we identified a biologically distinct subgroup of luminal-papillary MIBC with a favorable prognosis. These data suggest that lncRNAs provide additional information for higher-resolution subtyping, potentially improving precision patient management.

Improved and cheaper molecular diagnostics allow the shift from “one size fits all” therapies to personalised treatments targeting the individual tumor. However, the wealth of potential targets based on comprehensive sequencing remains a yet unsolved challenge that prevents its routine use in clinical practice. Thus, we designed a workflow that selects the most promising treatment targets based on multi-omics sequencing and in silico drug prediction. In this study we demonstrate the workflow with focus on bladder cancer (BLCA), as there are, to date, no reliable diagnostics available to predict the potential benefit of a therapeutic approach. Within the TCGA-BLCA cohort, our workflow identified a panel of 21 genes and 72 drugs that suggested personalized treatment for 95% of patients—including five genes not yet reported as prognostic markers for clinical testing in BLCA. The automated predictions were complemented by manually curated data, thus allowing for accurate sensitivity- or resistance-directed drug response predictions. We discuss potential improvements of drug-gene interaction databases on the basis of pitfalls that were identified during manual curation.

Background Alternative polyadenylation (APA) results in messenger RNA molecules with different 3′ untranslated regions (3’ UTRs), affecting the molecules’ stability, localization, and translation. APA is pervasive and implicated in cancer. Earlier reports on APA focused on 3’ UTR length modifications and commonly characterized APA events as 3’ UTR shortening or lengthening. However, such characterization oversimplifies the processing of 3′ ends of transcripts and fails to adequately describe the various scenarios we observe. Results We built a cloud-based targeted de novo transcript assembly and analysis pipeline that incorporates our previously developed cleavage site prediction tool, KLEAT. We applied this pipeline to elucidate the APA profiles of 114 genes in 9939 tumor and 729 tissue normal samples from The Cancer Genome Atlas (TCGA). The full set of 10,668 RNA-Seq samples from 33 cancer types has not been utilized by previous APA studies. By comparing the frequencies of predicted cleavage sites between normal and tumor sample groups, we identified 77 events (i.e. gene-cancer type pairs) of tumor-specific APA regulation in 13 cancer types; for 15 genes, such regulation is recurrent across multiple cancers. Our results also support a previous report showing the 3’ UTR shortening of FGF2 in multiple cancers. However, over half of the events we identified display complex changes to 3’ UTR length that resist simple classification like shortening or lengthening. Conclusions Recurrent tumor-specific regulation of APA is widespread in cancer. However, the regulation pattern that we observed in TCGA RNA-seq data cannot be described as straightforward 3’ UTR shortening or lengthening. Continued investigation into this complex, nuanced regulatory landscape will provide further insight into its role in tumor formation and development.

The GUSTO clinical trial (Gene expression subtypes of Urothelial carcinoma: Stratified Treatment and Oncological outcomes) uses molecular subtypes to guide neoadjuvant therapies in participants with muscle‐invasive bladder cancer (MIBC). Before commencing the GUSTO trial, we needed to determine the reliability of a commercial subtyping platform (Decipher Bladder; Veracyte) when performed in an external trial laboratory as this has not been done previously. Here, we report our pre‐trial verification of the TCGA molecular subtyping model using gene expression profiling. Formalin‐fixed paraffin‐embedded tissue blocks of MIBC were used for gene expression subtyping by gene expression microarrays. Intra‐ and inter‐laboratory technical reproducibilities, together with quality control of laboratory and bioinformatics processes, were assessed. Eighteen samples underwent analysis. RNA of sufficient quality and quantity was successfully extracted from all samples. All subtypes were represented in the cohort. Each sample was subtyped twice in our laboratory and once in a separate reference laboratory. No clinically significant discordance in subtype occurred between intra‐ or inter‐laboratory replicates. Examination of sample histopathology showed variability of morphological appearances within and between subtypes. Overall, these results show that molecular subtyping by gene expression profiling is reproducible, robust and suitable for use in the GUSTO clinical trial.

Background Long non-coding RNAs (lncRNAs) are emerging as molecules that significantly impact many cellular processes and have been associated with almost every human cancer. Compared to protein-coding genes, lncRNA genes are often associated with transposable elements, particularly with endogenous retroviral elements (ERVs). ERVs can have potentially deleterious effects on genome structure and function, so these elements are typically silenced in normal somatic tissues, albeit with varying efficiency. The aberrant regulation of ERVs associated with lncRNAs (ERV-lncRNAs), coupled with the diverse range of lncRNA functions, creates significant potential for ERV-lncRNAs to impact cancer biology. Methods We used RNA-seq analysis to identify and profile the expression of a novel lncRNA in six large cohorts, including over 7,500 samples from The Cancer Genome Atlas (TCGA). Results We identified the tumor-specific expression of a novel lncRNA that we have named Endogenous retroViral-associated ADenocarcinoma RNA or ‘ EVADR ’, by analyzing RNA-seq data derived from colorectal tumors and matched normal control tissues. Subsequent analysis of TCGA RNA-seq data revealed the striking association of EVADR with adenocarcinomas, which are tumors of glandular origin. Moderate to high levels of EVADR were detected in 25 to 53% of colon, rectal, lung, pancreas and stomach adenocarcinomas (mean = 30 to 144 FPKM), and EVADR expression correlated with decreased patient survival (Cox regression; hazard ratio = 1.47, 95% confidence interval = 1.06 to 2.04, P  = 0.02). In tumor sites of non-glandular origin, EVADR expression was detectable at only very low levels and in less than 10% of patients. For EVADR , a MER48 ERV element provides an active promoter to drive its transcription. Genome-wide, MER48 insertions are associated with nine lncRNAs, but none of the MER48-associated lncRNAs other than EVADR were consistently expressed in adenocarcinomas, demonstrating the specific activation of EVADR . The sequence and structure of the EVADR locus is highly conserved among Old World monkeys and apes but not New World monkeys or prosimians, where the MER48 insertion is absent. Conservation of the EVADR locus suggests a functional role for this novel lncRNA in humans and our closest primate relatives. Conclusions Our results describe the specific activation of a highly conserved ERV-lncRNA in numerous cancers of glandular origin, a finding with diagnostic, prognostic and therapeutic implications.