Characterization and clustering of kinase isoform expression in metastatic melanoma.

Mutations to the human kinome are known to play causal roles in cancer. The kinome regulates numerous cell processes including growth, proliferation, differentiation, and apoptosis. In addition to aberrant expression, aberrant alternative splicing of cancer-driver genes is receiving increased attention as it could lead to loss or gain of functional domains, altering a kinase's downstream impact. The present study quantifies changes in gene expression and isoform ratios in the kinome of metastatic melanoma cells relative to primary tumors. We contrast 538 total kinases and 3,040 known kinase isoforms between 103 primary tumor and 367 metastatic samples from The Cancer Genome Atlas (TCGA). We find strong evidence of differential expression (DE) at the gene level in 123 kinases (23%). Additionally, of the 468 kinases with alternative isoforms, 60 (13%) had significant difference in isoform ratios (DIR). Notably, DE and DIR have little correlation; for instance, although DE highlights enrichment in receptor tyrosine kinases (RTKs), DIR identifies altered splicing in non-receptor tyrosine kinases (nRTKs). Using exon junction mapping, we identify five examples of splicing events favored in metastatic samples. We demonstrate differential apoptosis and protein localization between SLK isoforms in metastatic melanoma. We cluster isoform expression data and identify subgroups that correlate with genomic subtypes and anatomic tumor locations. Notably, distinct DE and DIR patterns separate samples with BRAF hotspot mutations and (N/K/H)RAS hotspot mutations, the latter of which lacks effective kinase inhibitor treatments. DE in RAS mutants concentrates in CMGC kinases (a group including cell cycle and splicing regulators) rather than RTKs as in BRAF mutants. Furthermore, isoforms in the RAS kinase subgroup show enrichment for cancer-related processes such as angiogenesis and cell migration. Our results reveal a new approach to therapeutic target identification and demonstrate how different mutational subtypes may respond differently to treatments highlighting possible new driver events in cancer.

A novel role for nucleolin in splice site selection.

Latent 5' splice sites, not normally used, are highly abundant in human introns, but are activated under stress and in cancer, generating thousands of nonsense mRNAs. A previously proposed mechanism to suppress latent splicing was shown to be independent of NMD, with a pivotal role for initiator-tRNA independent of protein translation. To further elucidate this mechanism, we searched for nuclear proteins directly bound to initiator-tRNA. Starting with UV-crosslinking, we identified nucleolin (NCL) interacting directly and specifically with initiator-tRNA in the nucleus, but not in the cytoplasm. Next, we show the association of ini-tRNA and NCL with pre-mRNA. We further show that recovery of suppression of latent splicing by initiator-tRNA complementation is NCL dependent. Finally, upon nucleolin knockdown we show activation of latent splicing in hundreds of coding transcripts having important cellular functions. We thus propose nucleolin, a component of the endogenous spliceosome, through its direct binding to initiator-tRNA and its effect on latent splicing, as the first protein of a nuclear quality control mechanism regulating splice site selection to protect cells from latent splicing that can generate defective mRNAs.

Differential gene expression identifies a transcriptional regulatory network involving ER-alpha and PITX1 in invasive epithelial ovarian cancer.

BACKGROUND: The heterogeneous subtypes and stages of epithelial ovarian cancer (EOC) differ in their biological features, invasiveness, and response to chemotherapy, but the transcriptional regulators causing their differences remain nebulous. METHODS: In this study, we compared high-grade serous ovarian cancers (HGSOCs) to low malignant potential or serous borderline tumors (SBTs). Our aim was to discover new regulatory factors causing distinct biological properties of HGSOCs and SBTs. RESULTS: In a discovery dataset, we identified 11 differentially expressed genes (DEGs) between SBTs and HGSOCs. Their expression correctly classified 95% of 267 validation samples. Two of the DEGs, TMEM30B and TSPAN1, were significantly associated with worse overall survival in patients with HGSOC. We also identified 17 DEGs that distinguished stage II vs. III HGSOC. In these two DEG promoter sets, we identified significant enrichment of predicted transcription factor binding sites, including those of RARA, FOXF1, BHLHE41, and PITX1. Using published ChIP-seq data acquired from multiple non-ovarian cell types, we showed additional regulatory factors, including AP2-gamma/TFAP2C, FOXA1, and BHLHE40, bound at the majority of DEG promoters. Several of the factors are known to cooperate with and predict the presence of nuclear hormone receptor estrogen receptor alpha (ER-alpha). We experimentally confirmed ER-alpha and PITX1 presence at the DEGs by performing ChIP-seq analysis using the ovarian cancer cell line PEO4. Finally, RNA-seq analysis identified recurrent gene fusion events in our EOC tumor set. Some of these fusions were significantly associated with survival in HGSOC patients; however, the fusion genes are not regulated by the transcription factors identified for the DEGs. CONCLUSIONS: These data implicate an estrogen-responsive regulatory network in the differential gene expression between ovarian cancer subtypes and stages, which includes PITX1. Importantly, the transcription factors associated with our DEG promoters are known to form the MegaTrans complex in breast cancer. This is the first study to implicate the MegaTrans complex in contributing to the distinct biological trajectories of malignant and indolent ovarian cancer subtypes.

CAGI experiments: Modeling sequence variant impact on gene splicing using predictions from computational tools.

Improving predictions of phenotypic consequences for genomic variants is part of ongoing efforts in the scientific community to gain meaningful insights into genomic function. Within the framework of the critical assessment of genome interpretation experiments, we participated in the Vex-seq challenge, which required predicting the change in the percent spliced in measure (ΔΨ) for 58 exons caused by more than 1,000 genomic variants. Experimentally determined through the Vex-seq assay, the Ψ quantifies the fraction of reads that include an exon of interest. Predicting the change in Ψ associated with specific genomic variants implies determining the sequence changes relevant for splicing regulators, such as splicing enhancers and silencers. Here we took advantage of two computational tools, SplicePort and SPANR, that incorporate relevant sequence features in their models of splice sites and exon-inclusion level, respectively. Specifically, we used the SplicePort and SPANR outputs to build mathematical models of the experimental data obtained for the variants in the training set, which we then used to predict the ΔΨ associated with the mutations in the test set. We show that the sequence changes captured by these computational tools provide a reasonable foundation for modeling the impact on splicing associated with genomic variants.

Assessing predictions of the impact of variants on splicing in CAGI5.

Precision medicine and sequence-based clinical diagnostics seek to predict disease risk or to identify causative variants from sequencing data. The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype-phenotype prediction challenges; participants build models, undergo assessment, and share key findings. In the past, few CAGI challenges have addressed the impact of sequence variants on splicing. In CAGI5, two challenges (Vex-seq and MaPSY) involved prediction of the effect of variants, primarily single-nucleotide changes, on splicing. Although there are significant differences between these two challenges, both involved prediction of results from high-throughput exon inclusion assays. Here, we discuss the methods used to predict the impact of these variants on splicing, their performance, strengths, and weaknesses, and prospects for predicting the impact of sequence variation on splicing and disease phenotypes.

Significant associations between driver gene mutations and DNA methylation alterations across many cancer types.

Recent evidence shows that mutations in several driver genes can cause aberrant methylation patterns, a hallmark of cancer. In light of these findings, we hypothesized that the landscapes of tumor genomes and epigenomes are tightly interconnected. We measured this relationship using principal component analyses and methylation-mutation associations applied at the nucleotide level and with respect to genome-wide trends. We found that a few mutated driver genes were associated with genome-wide patterns of aberrant hypomethylation or CpG island hypermethylation in specific cancer types. In addition, we identified associations between 737 mutated driver genes and site-specific methylation changes. Moreover, using these mutation-methylation associations, we were able to distinguish between two uterine and two thyroid cancer subtypes. The driver gene mutation-associated methylation differences between the thyroid cancer subtypes were linked to differential gene expression in JAK-STAT signaling, NADPH oxidation, and other cancer-related pathways. These results establish that driver gene mutations are associated with methylation alterations capable of shaping regulatory network functions. In addition, the methodology presented here can be used to subdivide tumors into more homogeneous subsets corresponding to underlying molecular characteristics, which could improve treatment efficacy.

Whole-genome sequencing identifies a recurrent functional synonymous mutation in melanoma.

Synonymous mutations, which do not alter the protein sequence, have been shown to affect protein function [Sauna ZE, Kimchi-Sarfaty C (2011) Nat Rev Genet 12(10):683-691]. However, synonymous mutations are rarely investigated in the cancer genomics field. We used whole-genome and -exome sequencing to identify somatic mutations in 29 melanoma samples. Validation of one synonymous somatic mutation in BCL2L12 in 285 samples identified 12 cases that harbored the recurrent F17F mutation. This mutation led to increased BCL2L12 mRNA and protein levels because of differential targeting of WT and mutant BCL2L12 by hsa-miR-671-5p. Protein made from mutant BCL2L12 transcript bound p53, inhibited UV-induced apoptosis more efficiently than WT BCL2L12, and reduced endogenous p53 target gene transcription. This report shows selection of a recurrent somatic synonymous mutation in cancer. Our data indicate that silent alterations have a role to play in human cancer, emphasizing the importance of their investigation in future cancer genome studies.

Ascertaining regions affected by GC-biased gene conversion through weak-to-strong mutational hotspots.

A major objective for evolutionary biology is to identify regions affected by positive selection. High dN/dS values for proteins and accelerated lineage-specific substitution rates for non-coding regions are considered classic signatures of positive selection. However, these could also be the result of non-adaptive phenomena, such as GC-biased gene conversion (gBGC), which favors the fixation of strong (C/G) over weak (A/T) nucleotides. Recent estimates indicate that gBGC affected up to 20% of regions with signatures of positive selection. Here we evaluate the impact of gBGC through its molecular signature of weak-to-strong mutational hotspots. We implemented specific modifications to the test proposed by Tang and Lewontin (1999) for identifying regions of differential variability and applied it to regions previously investigated for the influence of gBGC. While we found significant agreement with previous reports, our results suggest a smaller influence of gBGC than previously estimated, warranting further development of methods for its detection.

Homotypic clusters of transcription factor binding sites are a key component of human promoters and enhancers.

Clustering of multiple transcription factor binding sites (TFBSs) for the same transcription factor (TF) is a common feature of cis-regulatory modules in invertebrate animals, but the occurrence of such homotypic clusters of TFBSs (HCTs) in the human genome has remained largely unknown. To explore whether HCTs are also common in human and other vertebrates, we used known binding motifs for vertebrate TFs and a hidden Markov model-based approach to detect HCTs in the human, mouse, chicken, and fugu genomes, and examined their association with cis-regulatory modules. We found that evolutionarily conserved HCTs occupy nearly 2% of the human genome, with experimental evidence for individual TFs supporting their binding to predicted HCTs. More than half of the promoters of human genes contain HCTs, with a distribution around the transcription start site in agreement with the experimental data from the ENCODE project. In addition, almost half of the 487 experimentally validated developmental enhancers contain them as well--a number more than 25-fold larger than expected by chance. We also found evidence of negative selection acting on TFBSs within HCTs, as the conservation of TFBSs is stronger than the conservation of sequences separating them. The important role of HCTs as components of developmental enhancers is additionally supported by a strong correlation between HCTs and the binding of the enhancer-associated coactivator protein Ep300 (also known as p300). Experimental validation of HCT-containing elements in both zebrafish and mouse suggest that HCTs could be used to predict both the presence of enhancers and their tissue specificity, and are thus a feature that can be effectively used in deciphering the gene regulatory code. In conclusion, our results indicate that HCTs are a pervasive feature of human cis-regulatory modules and suggest that they play an important role in gene regulation in the human and other vertebrate genomes.

Genome-wide detection of a TFIID localization element from an initial human disease mutation.

Eukaryotic core promoters are often characterized by the presence of consensus motifs such as the TATA box or initiator elements, which attract and direct the transcriptional machinery to the transcription start site. However, many human promoters have none of the known core promoter motifs, suggesting that undiscovered promoter motifs exist in the genome. We previously identified a mutation in the human Ankyrin-1 (ANK-1) promoter that causes the disease ankyrin-deficient Hereditary Spherocytosis (HS). Although the ANK-1 promoter is CpG rich, no discernable basal promoter elements had been identified. We showed that the HS mutation disrupted the binding of the transcription factor TFIID, the major component of the pre-initiation complex. We hypothesized that the mutation identified a candidate promoter element with a more widespread role in gene regulation. We examined 17,181 human promoters for the experimentally validated binding site, called the TFIID localization sequence (DLS) and found three times as many promoters containing DLS than TATA motifs. Mutational analyses of DLS sequences confirmed their functional significance, as did the addition of a DLS site to a minimal Sp1 promoter. Our results demonstrate that novel promoter elements can be identified on a genome-wide scale through observations of regulatory disruptions that cause human disease.

DiRE: identifying distant regulatory elements of co-expressed genes.

Regulation of gene expression in eukaryotic genomes is established through a complex cooperative activity of proximal promoters and distant regulatory elements (REs) such as enhancers, repressors and silencers. We have developed a web server named DiRE, based on the Enhancer Identification (EI) method, for predicting distant regulatory elements in higher eukaryotic genomes, namely for determining their chromosomal location and functional characteristics. The server uses gene co-expression data, comparative genomics and profiles of transcription factor binding sites (TFBSs) to determine TFBS-association signatures that can be used for discriminating specific regulatory functions. DiRE's unique feature is its ability to detect REs outside of proximal promoter regions, as it takes advantage of the full gene locus to conduct the search. DiRE can predict common REs for any set of input genes for which the user has prior knowledge of co-expression, co-function or other biologically meaningful grouping. The server predicts function-specific REs consisting of clusters of specifically-associated TFBSs and it also scores the association of individual transcription factors (TFs) with the biological function shared by the group of input genes. Its integration with the Array2BIO server allows users to start their analysis with raw microarray expression data. The DiRE web server is freely available at http://dire.dcode.org.

Do transposable elements really contribute to proteomes?

Recent studies indicate that the initial classification of transposable elements (TEs) as 'useless', 'selfish' or 'junk' pieces of DNA is not an accurate one. TEs seem to have complex regulatory functions and contribute to the coding regions of many genes. Because this contribution had been documented only at transcript level, we searched for evidence that would also support the translation of TE cassettes. Our findings suggest that the proportion of proteins with TE-encoded fragments (approximately 0.1%), although probably underestimated, is much less than what the data at transcript level suggest (approximately 4%). In all cases, the TE cassettes are derived from old TEs, consistent with the idea that incorporation (exaptation) of TE fragments into functional proteins requires long evolutionary periods. We therefore argue that functional proteins are unlikely to contain TE cassettes derived from young TEs, the role of which is probably limited to regulatory functions.

Transposable Elements: Classification, Identification, and Their Use As a Tool For Comparative Genomics.

Most genomes are populated by hundreds of thousands of sequences originated from mobile elements. On the one hand, these sequences present a real challenge in the process of genome analysis and annotation. On the other hand, they are very interesting biological subjects involved in many cellular processes. Here we present an overview of transposable elements biodiversity, and we discuss different approaches to transposable elements detection and analyses.

CpG island methylator phenotype in adenocarcinomas from the digestive tract: Methods, conclusions, and controversies.

Over the last two decades, cancer-related alterations in DNA methylation that regulate transcription have been reported for a variety of tumors of the gastrointestinal tract. Due to its relevance for translational research, great emphasis has been placed on the analysis and molecular characterization of the CpG island methylator phenotype (CIMP), defined as widespread hypermethylation of CpG islands in clinically distinct subsets of cancer patients. Here, we present an overview of previous work in this field and also explore some open questions using cross-platform data for esophageal, gastric, and colorectal adenocarcinomas from The Cancer Genome Atlas. We provide a data-driven, pan-gastrointestinal stratification of individual samples based on CIMP status and we investigate correlations with oncogenic alterations, including somatic mutations and epigenetic silencing of tumor suppressor genes. Besides known events in CIMP such as BRAF V600E mutation, CDKN2A silencing or MLH1 inactivation, we discuss the potential role of emerging actors such as Wnt pathway deregulation through truncating mutations in RNF43 and epigenetic silencing of WIF1. Our results highlight the existence of molecular similarities that are superimposed over a larger backbone of tissue-specific features and can be exploited to reduce heterogeneity of response in clinical trials.

Transposable elements as a significant source of transcription regulating signals.

Transposable elements (TEs) are major components of eukaryotic genomes, contributing about 50% to the size of mammalian genomes. TEs serve as recombination hot spots and may acquire specific cellular functions, such as controlling protein translation and gene transcription. The latter is the subject of the analysis presented. We scanned TE sequences located in promoter regions of all annotated genes in the human genome for their content in potential transcription regulating signals. All investigated signals are likely to be over-represented in at least one TE class, which shows that TEs have an important potential to contribute to pre-transcriptional gene regulation, especially by moving transcriptional signals within the genome and thus potentially leading to new gene expression patterns. We also found that some TE classes are more likely than others to carry transcription regulating signals, which can explain why they have different retention rates in regions neighboring genes.

Mastering seeds for genomic size nucleotide BLAST searches.

One of the most common activities in bioinformatics is the search for similar sequences. These searches are usually carried out with the help of programs from the NCBI BLAST family. As the majority of searches are routinely performed with default parameters, a question that should be addressed is how reliable the results obtained using the default parameter values are, i.e. what fraction of potential matches have been retrieved by these searches. Our primary focus is on the initial hit parameter, also known as the seed or word, used by the NCBI BLASTn, MegaBLAST and other similar programs in searches for similar nucleotide sequences. We show that the use of default values for the initial hit parameter can have a big negative impact on the proportion of potentially similar sequences that are retrieved. We also show how the hit probability of different seeds varies with the minimum length and similarity of sequences desired to be retrieved and describe methods that help in determining appropriate seeds. The experimental results described in this paper illustrate situations in which these methods are most applicable and also show the relationship between the various BLAST parameters.

A Case of IL-7R Deficiency Caused by a Novel Synonymous Mutation and Implications for Mutation Screening in SCID Diagnosis.

Reported synonymous substitutions are generally non-pathogenic, and rare pathogenic synonymous variants may be disregarded unless there is a high index of suspicion. In a case of IL7 receptor deficiency severe combined immunodeficiency (SCID), the relevance of a non-reported synonymous variant was only suspected through the use of additional in silico computational tools, which focused on the impact of mutations on gene splicing. The pathogenic nature of the variant was confirmed using experimental validation of the effect on mRNA splicing and IL7 pathway function. This case reinforces the need to use additional experimental methods to establish the functional impact of specific mutations, in particular for cases such as SCID where prompt diagnosis can greatly impact on diagnosis, treatment, and survival.

The functional relevance of somatic synonymous mutations in melanoma and other cancers.

Recent technological advances in sequencing have flooded the field of cancer research with knowledge about somatic mutations for many different cancer types. Most cancer genomics studies focus on mutations that alter the amino acid sequence, ignoring the potential impact of synonymous mutations. However, accumulating experimental evidence has demonstrated clear consequences for gene function, leading to a widespread recognition of the functional role of synonymous mutations and their causal connection to various diseases. Here, we review the evidence supporting the direct impact of synonymous mutations on gene function via gene splicing; mRNA stability, folding, and translation; protein folding; and miRNA-based regulation of expression. These results highlight the functional contribution of synonymous mutations to oncogenesis and the need to further investigate their detection and prioritization for experimental assessment.

Pan-cancer stratification of solid human epithelial tumors and cancer cell lines reveals commonalities and tissue-specific features of the CpG island methylator phenotype.

BACKGROUND: The term CpG island methylator phenotype (CIMP) has been used to describe widespread DNA hypermethylation at CpG-rich genomic regions affecting clinically distinct subsets of cancer patients. Even though there have been numerous studies of CIMP in individual cancer types, a uniform analysis across tissues is still lacking. RESULTS: We analyze genome-wide patterns of CpG island hypermethylation in 5,253 solid epithelial tumors from 15 cancer types from TCGA and 23 cancer cell lines from ENCODE. We identify differentially methylated loci that define CIMP+ and CIMP- samples, and we use unsupervised clustering to provide a robust molecular stratification of tumor methylomes for 12 cancer types and all cancer cell lines. With a minimal set of 89 discriminative loci, we demonstrate accurate pan-cancer separation of the 12 CIMP+/- subpopulations, based on their average levels of methylation. Tumor samples in different CIMP subclasses show distinctive correlations with gene expression profiles and recurrence of somatic mutations, copy number variations, and epigenetic silencing. Enrichment analyses indicate shared canonical pathways and upstream regulators for CIMP-targeted regions across cancer types. Furthermore, genomic alterations showing consistent associations with CIMP+/- status include genes involved in DNA repair, chromatin remodeling genes, and several histone methyltransferases. Associations of CIMP status with specific clinical features, including overall survival in several cancer types, highlight the importance of the CIMP+/- designation for individual tumor evaluation and personalized medicine. CONCLUSIONS: We present a comprehensive computational study of CIMP that reveals pan-cancer commonalities and tissue-specific differences underlying concurrent hypermethylation of CpG islands across tumors. Our stratification of solid tumors and cancer cell lines based on CIMP status is data-driven and agnostic to tumor type by design, which protects against known biases that have hindered classic methods previously used to define CIMP. The results that we provide can be used to refine existing molecular subtypes of cancer into more homogeneously behaving subgroups, potentially leading to more uniform responses in clinical trials.

Bidirectional promoters as important drivers for the emergence of species-specific transcripts.

The diversification of gene functions has been largely attributed to the process of gene duplication. Novel examples of genes originating from previously untranscribed regions have been recently described without regard to a unifying functional mechanism for their emergence. Here we propose a model mechanism that could generate a large number of lineage-specific novel transcripts in vertebrates through the activation of bidirectional transcription from unidirectional promoters. We examined this model in silico using human transcriptomic and genomic data and identified evidence consistent with the emergence of more than 1,000 primate-specific transcripts. These are transcripts with low coding potential and virtually no functional annotation. They initiate at less than 1 kb upstream of an oppositely transcribed conserved protein coding gene, in agreement with the generally accepted definition of bidirectional promoters. We found that the genomic regions upstream of ancestral promoters, where the novel transcripts in our dataset reside, are characterized by preferential accumulation of transposable elements. This enhances the sequence diversity of regions located upstream of ancestral promoters, further highlighting their evolutionary importance for the emergence of transcriptional novelties. By applying a newly developed test for positive selection to transposable element-derived fragments in our set of novel transcripts, we found evidence of adaptive evolution in the human lineage in nearly 3% of the novel transcripts in our dataset. These findings indicate that at least some novel transcripts could become functionally relevant, and thus highlight the evolutionary importance of promoters, through their capacity for bidirectional transcription, for the emergence of novel genes.