Circular stable intronic RNAs possess distinct biological features and are deregulated in bladder cancer.

Until recently, intronic lariats were regarded as short-lasting splicing byproducts with no apparent function; however, increasing evidence of stable derivatives suggests regulatory roles. Yet little is known about their characteristics, functions, distribution, and expression in healthy and tumor tissue. Here, we profiled and characterized circular stable intronic sequence RNAs (sisRNAs) using total RNA-Seq data from bladder cancer (BC; n = 457, UROMOL cohort), healthy tissue (n = 46), and fractionated cell lines (n = 5). We found that the recently-discovered full-length intronic circles and the stable lariats formed distinct subclasses, with a surprisingly high intronic circle fraction in BC (∼45%) compared to healthy tissues (0-20%). The stable lariats and their host introns were characterized by small transcript sizes, highly conserved BP regions, enriched BP motifs, and localization in multiple cell fractions. Additionally, circular sisRNAs showed tissue-specific expression patterns. We found nine circular sisRNAs as differentially expressed across early-stage BC patients with different prognoses, and sisHNRNPK expression correlated with progression-free survival. In conclusion, we identify distinguishing biological features of circular sisRNAs and point to specific candidates (incl. sisHNRNPK, sisWDR13 and sisMBNL1) that were highly expressed, had evolutionary conserved sequences, or had clinical correlations, which may facilitate future studies and further insights into their functional roles.

Error Characterization and Statistical Modeling Improves Circulating Tumor DNA Detection by Droplet Digital PCR.

BACKGROUND: Droplet digital PCR (ddPCR) is a widely used and sensitive application for circulating tumor DNA (ctDNA) detection. As ctDNA is often found in low abundance, methods to separate low-signal readouts from noise are necessary. We aimed to characterize the ddPCR-generated noise and, informed by this, create a sensitive and specific ctDNA caller. METHODS: We built 2 novel complimentary ctDNA calling methods: dynamic limit of blank and concentration and assay-specific tumor load estimator (CASTLE). Both methods are informed by empirically established assay-specific noise profiles. Here, we characterized noise for 70 mutation-detecting ddPCR assays by applying each assay to 95 nonmutated samples. Using these profiles, the performance of the 2 new methods was assessed in a total of 9447 negative/positive reference samples and in 1311 real-life plasma samples from colorectal cancer patients. Lastly, performances were compared to 7 literature-established calling methods. RESULTS: For many assays, noise increased proportionally with the DNA input amount. Assays targeting transition base changes were more error-prone than transversion-targeting assays. Both our calling methods successfully accounted for the additional noise in transition assays and showed consistently high performance regardless of DNA input amount. Calling methods that were not noise-informed performed less well than noise-informed methods. CASTLE was the only calling method providing a statistical estimate of the noise-corrected mutation level and call certainty. CONCLUSIONS: Accurate error modeling is necessary for sensitive and specific ctDNA detection by ddPCR. Accounting for DNA input amounts ensures specific detection regardless of the sample-specific DNA concentration. Our results demonstrate CASTLE as a powerful tool for ctDNA calling using ddPCR.

RHCG and TCAF1 promoter hypermethylation predicts biochemical recurrence in prostate cancer patients treated by radical prostatectomy.

PURPOSE: The lack of biomarkers that can distinguish aggressive from indolent prostate cancer has caused substantial overtreatment of clinically insignificant disease. Here, by genome-wide DNA methylome profiling, we sought to identify new biomarkers to improve the accuracy of prostate cancer diagnosis and prognosis. EXPERIMENTAL DESIGN: Eight novel candidate markers, COL4A6, CYBA, TCAF1 (FAM115A), HLF, LINC01341 (LOC149134), LRRC4, PROM1, and RHCG, were selected from Illumina Infinium HumanMethylation450 BeadChip analysis of 21 tumor (T) and 21 non-malignant (NM) prostate specimens. Diagnostic potential was further investigated by methylation-specific qPCR analysis of 80 NM vs. 228 T tissue samples. Prognostic potential was assessed by Kaplan-Meier, uni- and multivariate Cox regression analysis in 203 Danish radical prostatectomy (RP) patients (cohort 1), and validated in an independent cohort of 286 RP patients from Switzerland and the U.S. (cohort 2). RESULTS: Hypermethylation of the 8 candidates was highly cancer-specific (area under the curves: 0.79-1.00). Furthermore, high methylation of the 2-gene panel RHCG-TCAF1 was predictive of biochemical recurrence (BCR) in cohort 1, independent of the established clinicopathological parameters Gleason score, pathological tumor stage, and pre-operative PSA (HR (95% confidence interval (CI)): 2.09 (1.26 - 3.46); P = 0.004), and this was successfully validated in cohort 2 (HR (95% CI): 1.81 (1.05 - 3.12); P = 0.032). CONCLUSION: Methylation of the RHCG-TCAF1 panel adds significant independent prognostic value to established prognostic parameters for prostate cancer and thus may help to guide treatment decisions in the future. Further investigation in large independent cohorts is necessary before translation into clinical utility.

SNHG16 is regulated by the Wnt pathway in colorectal cancer and affects genes involved in lipid metabolism.

It is well established that lncRNAs are aberrantly expressed in cancer where they have been shown to act as oncogenes or tumor suppressors. RNA profiling of 314 colorectal adenomas/adenocarcinomas and 292 adjacent normal colon mucosa samples using RNA-sequencing demonstrated that the snoRNA host gene 16 (SNHG16) is significantly up-regulated in adenomas and all stages of CRC. SNHG16 expression was positively correlated to the expression of Wnt-regulated transcription factors, including ASCL2, ETS2, and c-Myc. In vitro abrogation of Wnt signaling in CRC cells reduced the expression of SNHG16 indicating that SNHG16 is regulated by the Wnt pathway. Silencing of SNHG16 resulted in reduced viability, increased apoptotic cell death and impaired cell migration. The SNHG16 silencing particularly affected expression of genes involved in lipid metabolism. A connection between SNHG16 and genes involved in lipid metabolism was also observed in clinical tumors. Argonaute CrossLinking and ImmunoPrecipitation (AGO-CLIP) demonstrated that SNHG16 heavily binds AGO and has 27 AGO/miRNA target sites along its length, indicating that SNHG16 may act as a competing endogenous RNA (ceRNA) "sponging" miRNAs off their cognate targets. Most interestingly, half of the miRNA families with high confidence targets on SNHG16 also target the 3'UTR of Stearoyl-CoA Desaturase (SCD). SCD is involved in lipid metabolism and is down-regulated upon SNHG16 silencing. In conclusion, up-regulation of SNHG16 is a frequent event in CRC, likely caused by deregulated Wnt signaling. In vitro analyses demonstrate that SNHG16 may play an oncogenic role in CRC and that it affects genes involved in lipid metabolism, possible through ceRNA related mechanisms.

PINCAGE: probabilistic integration of cancer genomics data for perturbed gene identification and sample classification.

MOTIVATION: Cancer development and progression is driven by a complex pattern of genomic and epigenomic perturbations. Both types of perturbations can affect gene expression levels and disease outcome. Integrative analysis of cancer genomics data may therefore improve detection of perturbed genes and prediction of disease state. As different data types are usually dependent, analysis based on independence assumptions will make inefficient use of the data and potentially lead to false conclusions. MODEL: Here, we present PINCAGE (Probabilistic INtegration of CAncer GEnomics data), a method that uses probabilistic integration of cancer genomics data for combined evaluation of RNA-seq gene expression and 450k array DNA methylation measurements of promoters as well as gene bodies. It models the dependence between expression and methylation using modular graphical models, which also allows future inclusion of additional data types. RESULTS: We apply our approach to a Breast Invasive Carcinoma dataset from The Cancer Genome Atlas consortium, which includes 82 adjacent normal and 730 cancer samples. We identify new biomarker candidates of breast cancer development (PTF1A, RABIF, RAG1AP1, TIMM17A, LOC148145) and progression (SERPINE3, ZNF706). PINCAGE discriminates better between normal and tumour tissue and between progressing and non-progressing tumours in comparison with established methods that assume independence between tested data types, especially when using evidence from multiple genes. Our method can be applied to any type of cancer or, more generally, to any genomic disease for which sufficient amount of molecular data is available. AVAILABILITY AND IMPLEMENTATION: R scripts available at http://moma.ki.au.dk/prj/pincage/ CONTACT: : michal.switnicki@clin.au.dk or jakob.skou@clin.au.dk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Analysis of circulating tumour DNA to monitor disease burden following colorectal cancer surgery.

OBJECTIVE: To develop an affordable and robust pipeline for selection of patient-specific somatic structural variants (SSVs) being informative about radicality of the primary resection, response to adjuvant therapy, incipient recurrence and response to treatment performed in relation to diagnosis of recurrence. DESIGN: We have established efficient procedures for identification of SSVs by next-generation sequencing and subsequent quantification of 3-6 SSVs in plasma. The consequence of intratumour heterogeneity on our approach was assessed. The level of circulating tumour DNA (ctDNA) was quantified in 151 serial plasma samples from six relapsing and five non-relapsing colorectal cancer (CRC) patients by droplet digital PCR, and correlated to clinical findings. RESULTS: Up to six personalised assays were designed for each patient. Our approach enabled efficient temporal assessment of disease status, response to surgical and oncological intervention, and early detection of incipient recurrence. Our approach provided 2-15 (mean 10) months' lead time on detection of metastatic recurrence compared to conventional follow-up. The sensitivity and specificity of the SSVs in terms of detecting postsurgery relapse were 100%. CONCLUSIONS: We show that assessment of ctDNA is a non-invasive, exquisitely specific and highly sensitive approach for monitoring disease load, which has the potential to provide clinically relevant lead times compared with conventional methods. Furthermore, we provide a low-coverage protocol optimised for identifying SSVs with excellent correlation between SSVs identified in tumours and matched metastases. Application of ctDNA analysis has the potential to change clinical practice in the management of CRC.

The lncRNA MIR31HG regulates p16(INK4A) expression to modulate senescence.

Oncogene-induced senescence (OIS) can occur in response to oncogenic insults and is considered an important tumour suppressor mechanism. Here we identify the lncRNA MIR31HG as upregulated in OIS and find that knockdown of MIR31HG promotes a strong p16(INK4A)-dependent senescence phenotype. Under normal conditions, MIR31HG is found in both nucleus and cytoplasm, but following B-RAF expression MIR31HG is located mainly in the cytoplasm. We show that MIR31HG interacts with both INK4A and MIR31HG genomic regions and with Polycomb group (PcG) proteins, and that MIR31HG is required for PcG-mediated repression of the INK4A locus. We further identify a functional enhancer, located between MIR31HG and INK4A, which becomes activated during OIS and interacts with the MIR31HG promoter. Data from melanoma patients show a negative correlation between MIR31HG and p16(INK4A) expression levels, suggesting a role for this transcript in cancer. Hence, our data provide a new lncRNA-mediated regulatory mechanism for the tumour suppressor p16(INK4A).

Cellular disposal of miR23b by RAB27-dependent exosome release is linked to acquisition of metastatic properties.

Exosomes are small secreted vesicles that can transfer their content to recipient cells. In cancer, exosome secretion has been implicated in tumor growth and metastatic spread. In this study, we explored the possibility that exosomal pathways might discard tumor-suppressor miRNA that restricts metastatic progression. Secreted miRNA characterized from isogenic bladder carcinoma cell lines with differing metastatic potential were uncoupled from binding to target transcripts or the AGO2-miRISC complex. In metastatic cells, we observed a relative increase in secretion of miRNA with tumor-suppressor functions, including miR23b, miR224, and miR921. Ectopic expression of miR23b inhibited invasion, anoikis, angiogenesis, and pulmonary metastasis. Silencing of the exocytotic RAB family members RAB27A or RAB27B halted miR23b and miR921 secretion and reduced cellular invasion. Clinically, elevated levels of RAB27B expression were linked to poor prognosis in two independent cohorts of patients with bladder cancer. Moreover, highly exocytosed miRNA from metastatic cells, such as miR23b, were reduced in lymph node metastases compared with patient-matched primary tumors and were correlated with increments in miRNA-targeted RNA. Taken together, our results suggested that exosome-mediated secretion of tumor-suppressor miRNA is selected during tumor progression as a mechanism to coordinate activation of a metastatic cascade.

Locating protein-coding sequences under selection for additional, overlapping functions in 29 mammalian genomes.

The degeneracy of the genetic code allows protein-coding DNA and RNA sequences to simultaneously encode additional, overlapping functional elements. A sequence in which both protein-coding and additional overlapping functions have evolved under purifying selection should show increased evolutionary conservation compared to typical protein-coding genes--especially at synonymous sites. In this study, we use genome alignments of 29 placental mammals to systematically locate short regions within human ORFs that show conspicuously low estimated rates of synonymous substitution across these species. The 29-species alignment provides statistical power to locate more than 10,000 such regions with resolution down to nine-codon windows, which are found within more than a quarter of all human protein-coding genes and contain ∼2% of their synonymous sites. We collect numerous lines of evidence that the observed synonymous constraint in these regions reflects selection on overlapping functional elements including splicing regulatory elements, dual-coding genes, RNA secondary structures, microRNA target sites, and developmental enhancers. Our results show that overlapping functional elements are common in mammalian genes, despite the vast genomic landscape.

Posttranscriptional crossregulation between Drosha and DGCR8.

The Drosha-DGCR8 complex, also known as Microprocessor, is essential for microRNA (miRNA) maturation. Drosha functions as the catalytic subunit, while DGCR8 (also known as Pasha) recognizes the RNA substrate. Although the action mechanism of this complex has been intensively studied, it remains unclear how Drosha and DGCR8 are regulated and if these proteins have any additional role(s) apart from miRNA processing. Here, we report that Drosha and DGCR8 regulate each other posttranscriptionally. The Drosha-DGCR8 complex cleaves the hairpin structures embedded in the DGCR8 mRNA and thereby destabilizes the mRNA. We further find that DGCR8 stabilizes the Drosha protein via protein-protein interaction. This crossregulation between Drosha and DGCR8 may contribute to the homeostatic control of miRNA biogenesis. Furthermore, microarray analyses suggest that a number of mRNAs may be downregulated in a Microprocessor-dependent, miRNA-independent manner. Our study reveals a previously unsuspected function of Microprocessor in mRNA stability control.

Discovery of functional elements in 12 Drosophila genomes using evolutionary signatures.

Sequencing of multiple related species followed by comparative genomics analysis constitutes a powerful approach for the systematic understanding of any genome. Here, we use the genomes of 12 Drosophila species for the de novo discovery of functional elements in the fly. Each type of functional element shows characteristic patterns of change, or 'evolutionary signatures', dictated by its precise selective constraints. Such signatures enable recognition of new protein-coding genes and exons, spurious and incorrect gene annotations, and numerous unusual gene structures, including abundant stop-codon readthrough. Similarly, we predict non-protein-coding RNA genes and structures, and new microRNA (miRNA) genes. We provide evidence of miRNA processing and functionality from both hairpin arms and both DNA strands. We identify several classes of pre- and post-transcriptional regulatory motifs, and predict individual motif instances with high confidence. We also study how discovery power scales with the divergence and number of species compared, and we provide general guidelines for comparative studies.

Structured RNAs in the ENCODE selected regions of the human genome.

Functional RNA structures play an important role both in the context of noncoding RNA transcripts as well as regulatory elements in mRNAs. Here we present a computational study to detect functional RNA structures within the ENCODE regions of the human genome. Since structural RNAs in general lack characteristic signals in primary sequence, comparative approaches evaluating evolutionary conservation of structures are most promising. We have used three recently introduced programs based on either phylogenetic-stochastic context-free grammar (EvoFold) or energy directed folding (RNAz and AlifoldZ), yielding several thousand candidate structures (corresponding to approximately 2.7% of the ENCODE regions). EvoFold has its highest sensitivity in highly conserved and relatively AU-rich regions, while RNAz favors slightly GC-rich regions, resulting in a relatively small overlap between methods. Comparison with the GENCODE annotation points to functional RNAs in all genomic contexts, with a slightly increased density in 3'-UTRs. While we estimate a significant false discovery rate of approximately 50%-70% many of the predictions can be further substantiated by additional criteria: 248 loci are predicted by both RNAz and EvoFold, and an additional 239 RNAz or EvoFold predictions are supported by the (more stringent) AlifoldZ algorithm. Five hundred seventy RNAz structure predictions fall into regions that show signs of selection pressure also on the sequence level (i.e., conserved elements). More than 700 predictions overlap with noncoding transcripts detected by oligonucleotide tiling arrays. One hundred seventy-five selected candidates were tested by RT-PCR in six tissues, and expression could be verified in 43 cases (24.6%).

Forces shaping the fastest evolving regions in the human genome.

Comparative genomics allow us to search the human genome for segments that were extensively changed in the last approximately 5 million years since divergence from our common ancestor with chimpanzee, but are highly conserved in other species and thus are likely to be functional. We found 202 genomic elements that are highly conserved in vertebrates but show evidence of significantly accelerated substitution rates in human. These are mostly in non-coding DNA, often near genes associated with transcription and DNA binding. Resequencing confirmed that the five most accelerated elements are dramatically changed in human but not in other primates, with seven times more substitutions in human than in chimp. The accelerated elements, and in particular the top five, show a strong bias for adenine and thymine to guanine and cytosine nucleotide changes and are disproportionately located in high recombination and high guanine and cytosine content environments near telomeres, suggesting either biased gene conversion or isochore selection. In addition, there is some evidence of directional selection in the regions containing the two most accelerated regions. A combination of evolutionary forces has contributed to accelerated evolution of the fastest evolving elements in the human genome.

An RNA gene expressed during cortical development evolved rapidly in humans.

The developmental and evolutionary mechanisms behind the emergence of human-specific brain features remain largely unknown. However, the recent ability to compare our genome to that of our closest relative, the chimpanzee, provides new avenues to link genetic and phenotypic changes in the evolution of the human brain. We devised a ranking of regions in the human genome that show significant evolutionary acceleration. Here we report that the most dramatic of these 'human accelerated regions', HAR1, is part of a novel RNA gene (HAR1F) that is expressed specifically in Cajal-Retzius neurons in the developing human neocortex from 7 to 19 gestational weeks, a crucial period for cortical neuron specification and migration. HAR1F is co-expressed with reelin, a product of Cajal-Retzius neurons that is of fundamental importance in specifying the six-layer structure of the human cortex. HAR1 and the other human accelerated regions provide new candidates in the search for uniquely human biology.

Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes.

We have conducted a comprehensive search for conserved elements in vertebrate genomes, using genome-wide multiple alignments of five vertebrate species (human, mouse, rat, chicken, and Fugu rubripes). Parallel searches have been performed with multiple alignments of four insect species (three species of Drosophila and Anopheles gambiae), two species of Caenorhabditis, and seven species of Saccharomyces. Conserved elements were identified with a computer program called phastCons, which is based on a two-state phylogenetic hidden Markov model (phylo-HMM). PhastCons works by fitting a phylo-HMM to the data by maximum likelihood, subject to constraints designed to calibrate the model across species groups, and then predicting conserved elements based on this model. The predicted elements cover roughly 3%-8% of the human genome (depending on the details of the calibration procedure) and substantially higher fractions of the more compact Drosophila melanogaster (37%-53%), Caenorhabditis elegans (18%-37%), and Saccharaomyces cerevisiae (47%-68%) genomes. From yeasts to vertebrates, in order of increasing genome size and general biological complexity, increasing fractions of conserved bases are found to lie outside of the exons of known protein-coding genes. In all groups, the most highly conserved elements (HCEs), by log-odds score, are hundreds or thousands of bases long. These elements share certain properties with ultraconserved elements, but they tend to be longer and less perfectly conserved, and they overlap genes of somewhat different functional categories. In vertebrates, HCEs are associated with the 3' UTRs of regulatory genes, stable gene deserts, and megabase-sized regions rich in moderately conserved noncoding sequences. Noncoding HCEs also show strong statistical evidence of an enrichment for RNA secondary structure.