Identification of differentially regulated splice variants and novel exons in glial brain tumors using exon expression arrays

Transcriptomics for Clinical and Experimental Biology Research: Hang on a Seq

Sequencing the human genome empowers translational medicine, facilitating transcriptome-wide molecular diagnosis, pathway biology, and drug repositioning. Initially, microarrays are used to study the bulk transcriptome; but now short-read RNA sequencing (RNA-seq) predominates. Positioned as a superior technology, that makes the discovery of novel transcripts routine, most RNA-seq analyses are in fact modeled on the known transcriptome. Limitations of the RNA-seq methodology have emerged, while the design of, and the analysis strategies applied to, arrays have matured. An equitable comparison between these technologies is provided, highlighting advantages that modern arrays hold over RNA-seq. Array protocols more accurately quantify constitutively expressed protein coding genes across tissue replicates, and are more reliable for studying lower expressed genes. Arrays reveal long noncoding RNAs (lncRNA) are neither sparsely nor lower expressed than protein coding genes. Heterogeneous coverage of constitutively expressed genes observed with RNA-seq, undermines the validity and reproducibility of pathway analyses. The factors driving these observations, many of which are relevant to long-read or single-cell sequencing are discussed. As proposed herein, a reappreciation of bulk transcriptomic methods is required, including wider use of the modern high-density array data-to urgently revise existing anatomical RNA reference atlases and assist with more accurate study of lncRNAs.

Integration of TE Induces Cancer Specific Alternative Splicing Events

Alternative splicing of messenger RNA (mRNA) precursors contributes to genetic diversity by generating structurally and functionally distinct transcripts. In a disease state, alternative splicing promotes incidence and development of several cancer types through regulation of cancer-related biological processes. Transposable elements (TEs), having the genetic ability to jump to other regions of the genome, can bring about alternative splicing events in cancer. TEs can integrate into the genome, mostly in the intronic regions, and induce cancer-specific alternative splicing by adjusting various mechanisms, such as exonization, providing splicing donor/acceptor sites, alternative regulatory sequences or stop codons, and driving exon disruption or epigenetic regulation. Moreover, TEs can produce microRNAs (miRNAs) that control the proportion of transcripts by repressing translation or stimulating the degradation of transcripts at the post-transcriptional level. Notably, TE insertion creates a cancer-friendly environment by controlling the overall process of gene expression before and after transcription in cancer cells. This review emphasizes the correlative interaction between alternative splicing by TE integration and cancer-associated biological processes, suggesting a macroscopic mechanism controlling alternative splicing by TE insertion in cancer.

A Quality Control Mechanism of Splice Site Selection Abrogated under Stress and in Cancer

Simple Summary

Splicing and alternative splicing play a major role in regulating gene expression, and mis-regulation of splicing can lead to several diseases, including cancer. The aim of this review is to summarize the current knowledge of a quality control mechanism of splice site selection termed Suppression of Splicing (SOS), proposed to protect cells from splicing at the numerous intronic unused 5′ splice sites, and emphasize its relevance to cancer. This relevance stems from the finding that SOS is abrogated under stress and in cancer resulting in the expression of thousands of aberrant nonsense mRNAs that may be toxic to cells. These findings highlight the unexplored potential of such aberrant isoforms as novel targets for cancer diagnosis and therapies.

Abstract

Latent 5’ splice sites, highly abundant in human introns, are not normally used. This led to the proposal of a quality control mechanism, Suppression of Splicing (SOS), which protects cells from splicing at the numerous intronic latent sites, and whose activation can generate nonsense mRNAs. SOS was shown to be independent of Nonsense-Mediated mRNA Decay (NMD). Efforts to decipher the SOS mechanism revealed a pivotal role for initiator-tRNA, independent of protein translation. Recently, nucleolin (a multifunctional protein) was found to directly and specifically bind the initiator-tRNA in the nucleus and was shown to be a protein component of SOS, enabling an updated model of the SOS mechanism. Importantly, SOS is abrogated under stress and in cancer (e.g., in breast cancer cells and gliomas), generating thousands of nonsense mRNAs due to activation of latent splicing. The resulting affected human genes cover a variety of functional groups, including genes involved in cell proliferation and differentiation. Furthermore, in oligodendroglioma, the extent of activation of latent splicing increases with the severity of the cancer. Interesting examples are genes expressing aberrant nonsense mRNAs in both breast cancer and glioma, due to latent splicing activation. These findings highlight the unexplored potential of such aberrant isoforms as novel targets for cancer diagnosis and therapies.

SON drives oncogenic RNA splicing in glioblastoma by regulating PTBP1/PTBP2 switching and RBFOX2 activity

While dysregulation of RNA splicing has been recognized as an emerging target for cancer therapy, the functional significance of RNA splicing and individual splicing factors in brain tumors is poorly understood. Here, we identify SON as a master regulator that activates PTBP1-mediated oncogenic splicing while suppressing RBFOX2-mediated non-oncogenic neuronal splicing in glioblastoma multiforme (GBM). SON is overexpressed in GBM patients and SON knockdown causes failure in intron removal from the PTBP1 transcript, resulting in PTBP1 downregulation and inhibition of its downstream oncogenic splicing. Furthermore, SON forms a complex with hnRNP A2B1 and antagonizes RBFOX2, which leads to skipping of RBFOX2-targeted cassette exons, including the PTBP2 neuronal exon. SON knockdown inhibits proliferation and clonogenicity of GBM cells in vitro and significantly suppresses tumor growth in orthotopic xenografts in vivo. Collectively, our study reveals that SON-mediated RNA splicing is a GBM vulnerability, implicating SON as a potential therapeutic target in brain tumors.

Creation and validation of models to predict response to primary treatment in serous ovarian cancer

Nearly a third of patients with high-grade serous ovarian cancer (HGSC) do not respond to initial therapy and have an overall poor prognosis. However, there are no validated tools that accurately predict which patients will not respond. Our objective is to create and validate accurate models of prediction for treatment response in HGSC. This is a retrospective case–control study that integrates comprehensive clinical and genomic data from 88 patients with HGSC from a single institution. Responders were those patients with a progression-free survival of at least 6 months after treatment. Only patients with complete clinical information and frozen specimen at surgery were included. Gene, miRNA, exon, and long non-coding RNA (lncRNA) expression, gene copy number, genomic variation, and fusion-gene determination were extracted from RNA-sequencing data. DNA methylation analysis was performed. Initial selection of informative variables was performed with univariate ANOVA with cross-validation. Significant variables (p < 0.05) were included in multivariate lasso regression prediction models. Initial models included only one variable. Variables were then combined to create complex models. Model performance was measured with area under the curve (AUC). Validation of all models was performed using TCGA HGSC database. By integrating clinical and genomic variables, we achieved prediction performances of over 95% in AUC. Most performances in the validation set did not differ from the training set. Models with DNA methylation or lncRNA underperformed in the validation set. Integrating comprehensive clinical and genomic data from patients with HGSC results in accurate and robust prediction models of treatment response.

The aberrant splicing of BAF45d links splicing regulation and transcription in glioblastoma

Background

Glioblastoma, the most aggressive primary brain tumor, is genetically heterogeneous. Alternative splicing (AS) plays a key role in numerous pathologies, including cancer. The objectives of our study were to determine whether aberrant AS could play a role in the malignant phenotype of glioma and to understand the mechanism underlying its aberrant regulation.

Methods

We obtained surgical samples from patients with glioblastoma who underwent 5-aminolevulinic fluorescence-guided surgery. Biopsies were taken from the tumor center as well as from adjacent normal-appearing tissue. We used a global splicing array to identify candidate genes aberrantly spliced in these glioblastoma samples. Mechanistic and functional studies were performed to elucidate the role of our top candidate splice variant, BAF45d, in glioblastoma.

Results

BAF45d is part of the switch/sucrose nonfermentable complex and plays a key role in the development of the CNS. The BAF45d/6A isoform is present in 85% of over 200 glioma samples that have been analyzed and contributes to the malignant glioma phenotype through the maintenance of an undifferentiated cellular state. We demonstrate that BAF45d splicing is mediated by polypyrimidine tract-binding protein 1 (PTBP1) and that BAF45d regulates PTBP1, uncovering a reciprocal interplay between RNA splicing regulation and transcription.

Conclusions

Our data indicate that AS is a mechanism that contributes to the malignant phenotype of glioblastoma. Understanding the consequences of this biological process will uncover new therapeutic targets for this devastating disease.

Construction of lncRNA-mediated ceRNA network to reveal clinically relevant lncRNA biomarkers in glioblastomas

Cross-talk between competing endogenous RNAs (ceRNAs) play key roles in tumor development. In this study, we performed exon-level expression profiling on 26 glioblastomas (GBMs) and 6 controls to identify long non-coding RNAs (lncRNAs) of GBM initiation and progression using lncRNA-mediated ceRNA network (LMCN). The mRNA and lncRNA expression data, as well as miRNA-target interactions were firstly collected. Then, we used hypergeometric test to detect the lncRNA-mRNA interactions, followed by the construction of LMCN based on Pearson correlation coefficient. With the goal of investigation of the network organization, degree distribution of LMCN was performed. Next, the synergistic, competing lncRNA modules were identified using jActiveModule plug-in of Cytoscape. Moreover, we implemented the pathway analysis for its mRNAs in the module to explore the functions of significant lncRNAs. Using the criteria of degrees >50, 8 hub genes were identified, including EPB41L4A-AS1, ZRANB2-AS2, XIST, HOTAIR, TRAF3IP2-AS1, TPT1-AS1, PVT1 and DLG1-AS1. Furthermore, 1 synergistic, competitive module was identified. In this module, lncRNAs XIST and PVT1 were also the hubs in the synergistic, competing lncRNA module. Functional annotation demonstrated that 5 pathways were identified, including cytokine-cytokine receptor interaction, neuroactive ligand-receptor interaction, and mTOR signaling pathway. We have successfully identified several hubs (such as XIST and PVT1) and significant pathways (for instance, cytokine-cytokine receptor interaction, and neuroactive ligand-receptor interactions) for GBM via establishing the LMCN. These findings might offer potential biomarkers to early diagnose, and predict GBM prognosis in the future.

PATZ1 is a new prognostic marker of glioblastoma associated with the stem-like phenotype and enriched in the proneural subtype

Glioblastoma (GBM), the most malignant of the brain tumors, has been classified on the basis of molecular signature into four subtypes: classical, mesenchymal, proneural and neural, among which the mesenchymal and proneural subtypes have the shortest and longest survival, respectively. Here we show that the transcription factor PATZ1 gene is upregulated in gliomas compared to normal brain and, among GBMs, is particularly enriched in the proneural subtype and co-localize with stemness markers. Accordingly, in GBM-derived glioma-initiating stem cells (GSCs) PATZ1 is overexpressed compared to differentiated tumor cells and its expression significantly correlates with the characteristic stem cell capacity to grow as neurospheres in vitro. Interestingly, survival analysis demonstrated that PATZ1 lower levels informed poor prognosis in GBM and, specifically, in the proneural subgroup, suggesting it may serve a role as diagnostic and prognostic biomarker for intra-subtype heterogeneity of proneural GBM. We also show that PATZ1 suppresses the expression of the mesenchyme-inducer CXCR4, and that PATZ1 and CXCR4 are inversely correlated in GSC and proneural GBM. Overall these findings support a central role of PATZ1 in regulating malignancy of GBM.

iGEMS: an integrated model for identification of alternative exon usage events

DNA microarrays and RNAseq are complementary methods for studying RNA molecules. Current computational methods to determine alternative exon usage (AEU) using such data require impractical visual inspection and still yield high false-positive rates. Integrated Gene and Exon Model of Splicing (iGEMS) adapts a gene-level residuals model with a gene size adjusted false discovery rate and exon-level analysis to circumvent these limitations. iGEMS was applied to two new DNA microarray datasets, including the high coverage Human Transcriptome Arrays 2.0 and performance was validated using RT-qPCR. First, AEU was studied in adipocytes treated with (n = 9) or without (n = 8) the anti-diabetes drug, rosiglitazone. iGEMS identified 555 genes with AEU, and robust verification by RT-qPCR (∼90%). Second, in a three-way human tissue comparison (muscle, adipose and blood, n = 41) iGEMS identified 4421 genes with at least one AEU event, with excellent RT-qPCR verification (95%, n = 22). Importantly, iGEMS identified a variety of AEU events, including 3′UTR extension, as well as exon inclusion/exclusion impacting on protein kinase and extracellular matrix domains. In conclusion, iGEMS is a robust method for identification of AEU while the variety of exon usage between human tissues is 5–10 times more prevalent than reported by the Genotype-Tissue Expression consortium using RNA sequencing.

Novel long non-coding RNAs are specific diagnostic and prognostic markers for prostate cancer

Current prostate cancer (PCa) biomarkers such as PSA are not optimal in distinguishing cancer from benign prostate diseases and predicting disease outcome. To discover additional biomarkers, we investigated PCa-specific expression of novel unannotated transcripts. Using the unique probe design of Affymetrix Human Exon Arrays, we identified 334 candidates (EPCATs), of which 15 were validated by RT-PCR. Combined into a diagnostic panel, 11 EPCATs classified 80% of PCa samples correctly, while maintaining 100% specificity. High specificity was confirmed by in situ hybridization for EPCAT4R966 and EPCAT2F176 (SChLAP1) on extensive tissue microarrays. Besides being diagnostic, EPCAT2F176 and EPCAT4R966 showed significant association with pT-stage and were present in PIN lesions. We also found EPCAT2F176 and EPCAT2R709 to be associated with development of metastases and PCa-related death, and EPCAT2F176 to be enriched in lymph node metastases. Functional significance of expression of 9 EPCATs was investigated by siRNA transfection, revealing that knockdown of 5 different EPCATs impaired growth of LNCaP and 22RV1 PCa cells. Only the minority of EPCATs appear to be controlled by androgen receptor or ERG. Although the underlying transcriptional regulation is not fully understood, the novel PCa-associated transcripts are new diagnostic and prognostic markers with functional relevance to prostate cancer growth.

Aberrant RNA splicing in cancer; expression changes and driver mutations of splicing factor genes

Alternative splicing is a widespread process contributing to structural transcript variation and proteome diversity. In cancer, the splicing process is commonly disrupted, resulting in both functional and non-functional end-products. Cancer-specific splicing events are known to contribute to disease progression; however, the dysregulated splicing patterns found on a genome-wide scale have until recently been less well-studied. In this review, we provide an overview of aberrant RNA splicing and its regulation in cancer. We then focus on the executors of the splicing process. Based on a comprehensive catalog of splicing factor encoding genes and analyses of available gene expression and somatic mutation data, we identify cancer-associated patterns of dysregulation. Splicing factor genes are shown to be significantly differentially expressed between cancer and corresponding normal samples, and to have reduced inter-individual expression variation in cancer. Furthermore, we identify enrichment of predicted cancer-critical genes among the splicing factors. In addition to previously described oncogenic splicing factor genes, we propose 24 novel cancer-critical splicing factors predicted from somatic mutations.

RNA splicing regulated by RBFOX1 is essential for cardiac function in zebrafish

Alternative splicing is one of the major mechanisms through which the proteomic and functional diversity of eukaryotes is achieved. However, the complex nature of the splicing machinery, its associated splicing regulators and the functional implications of alternatively spliced transcripts are only poorly understood. Here, we investigated the functional role of the splicing regulator rbfox1 in vivo using the zebrafish as a model system. We found that loss of rbfox1 led to progressive cardiac contractile dysfunction and heart failure. By using deep-transcriptome sequencing and quantitative real-time PCR, we show that depletion of rbfox1 in zebrafish results in an altered isoform expression of several crucial target genes, such as actn3a and hug. This study underlines that tightly regulated splicing is necessary for unconstrained cardiac function and renders the splicing regulator rbfox1 an interesting target for investigation in human heart failure and cardiomyopathy.

Summary: The zebrafish splicing regulator rbfox1 is necessary for tightly regulated splicing and unconstrained cardiac function, making it an interesting candidate for targeting during human cardiomyopathy.

Algorithms for differential splicing detection using exon arrays: a comparative assessment

Background

The analysis of differential splicing (DS) is crucial for understanding physiological processes in cells and organs. In particular, aberrant transcripts are known to be involved in various diseases including cancer. A widely used technique for studying DS are exon arrays. Over the last decade a variety of algorithms for the detection of DS events from exon arrays has been developed. However, no comprehensive, comparative evaluation including sensitivity to the most important data features has been conducted so far. To this end, we created multiple data sets based on simulated data to assess strengths and weaknesses of seven published methods as well as a newly developed method, KLAS. Additionally, we evaluated all methods on two cancer data sets that comprised RT-PCR validated results.

Results

Our studies indicated ARH as the most robust methods when integrating the results over all scenarios and data sets. Nevertheless, special cases or requirements favor other methods. While FIRMA was highly sensitive according to experimental data, SplicingCompass, MIDAS and ANOSVA showed high specificity throughout the scenarios. On experimental data ARH, FIRMA, MIDAS, and KLAS performed best.

Conclusions

Each method shows different characteristics regarding sensitivity, specificity, interference to certain data settings and robustness over multiple data sets. While some methods can be considered as generally good choices over all data sets and scenarios, other methods show heterogeneous prediction quality on the different data sets. The adequate method has to be chosen carefully and with a defined study aim in mind.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1322-x) contains supplementary material, which is available to authorized users.

The future of high-grade glioma: Where we are and where are we going

High-grade glioma (HGG) are optimally treated with maximum safe surgery, followed by radiotherapy (RT) and/or systemic chemotherapy (CT). Recently, the treatment of newly diagnosed anaplastic glioma (AG) has changed, particularly in patients with 1p19q codeleted tumors. Results of trials currenlty ongoing are likely to determine the best standard of care for patients with noncodeleted AG tumors. Trials in AG illustrate the importance of molecular characterization, which are germane to both prognosis and treatment. In contrast, efforts to improve the current standard of care of newly diagnosed glioblastoma (GB) with, for example, the addition of bevacizumab (BEV), have been largely disappointing and furthermore molecular characterization has not changed therapy except in elderly patients. Novel approaches, such as vaccine-based immunotherapy, for newly diagnosed GB are currently being pursued in multiple clinical trials. Recurrent disease, an event inevitable in nearly all patients with HGG, continues to be a challenge. Both recurrent GB and AG are managed in similar manner and when feasible re-resection is often suggested notwithstanding limited data to suggest benefit from repeat surgery. Occassional patients may be candidates for re-irradiation but again there is a paucity of data to commend this therapy and only a minority of selected patients are eligible for this approach. Consequently systemic therapy continues to be the most often utilized treatment in recurrent HGG. Choice of therapy, however, varies and revolves around re-challenge with temozolomide (TMZ), use of a nitrosourea (most often lomustine; CCNU) or BEV, the most frequently used angiogenic inhibitor. Nevertheless, no clear standard recommendation regarding the prefered agent or combination of agents is avaliable. Prognosis after progression of a HGG remains poor, with an unmet need to improve therapy.

Computational identification of epigenetically regulated lncRNAs and their associated genes based on integrating genomic data

Long non-coding RNAs (lncRNAs) are new players in various biological processes. However, understanding of lncRNAs is still in its infancy. Here, we proposed an integrative method to identify epigenetically regulated lncRNAs and their associated genes. By combining RNA-seq data and ChIP-seq data for histone H3 trimethylated at lysine 4 (H3K4me3) and H3K27me3, we identified 699 H3K4me3-regulated and 235 H3K27me3-regulated lncRNAs, each with an average of 238 and 307 associated genes, respectively. By analyzing Polycomb repressive complex 2 (PRC2) binding maps, we observed that the negatively related genes of most epigenetically regulated lncRNAs were enriched for PRC2-binding genes. In addition, through enrichment analysis, we inferred some lncRNAs with aberrant epigenetic modifications in glioblastoma and Alzheimer's disease. Together, we describe a method for the analysis of lncRNAs and demonstrate how integration of multi-omics data can improve understanding of lncRNAs.

Identification of differential splicing genes in gliomas using exon expression profiling

Diffuse gliomas are the most common type of malignant primary brain tumor, and their initiation and/or progression are often associated with alternative splicing. They produce an enormous economic burden on society and greatly impair the quality of life of those affected. The aim of the current study was to explore the differentially expressed genes (DEGs) observed in glioblastoma (GBM) and oligodendroglioma (OD) at the splicing level, and to analyze their functions in order to identify the underlying molecular mechanisms of gliomas. The exon‑level expression profile data GSE9385 was downloaded from the Gene Expression Omnibus database, and included 26 GBM samples, 22 OD samples and 6 control brain samples. The differentially expressed exon‑level probes were analyzed using the microarray detection of alternative splicing algorithm combined with the splicing index method, and the corresponding DEGs were identified. Next, a Gene Ontology enrichment analysis of the DEGs was performed. Additionally, the protein‑protein interaction (PPI) networks were constructed based on the depth‑first search algorithm. A total of 300 DEGs were identified to be shared by GBM and OD, including 97 upregulated and 203 downregulated DEGs. Furthermore, screening with a defined threshold identified 6 genes that were highly expressed in GBM, including AFF2, CACNA2D3 and ARPP21, while the 6 highly expressed genes in OD notably included CNTN2. The TP53 and HIST1H3A genes were the hub nodes in the PPI network of DEGs from GBM, while CNTN2 was linked to the highest degree in the OD PPI network. The present study provides a comprehensive bioinformatics analysis of DEGs in GBM and OD, which may provide a basis for understanding the initiation and/or progression of glioma development.

The role of mRNA splicing in prostate cancer

Alternative splicing (AS) is a crucial step in gene expression. It is subject to intricate regulation, and its deregulation in cancer can lead to a wide array of neoplastic phenotypes. A large body of evidence implicates splice isoforms in most if not all hallmarks of cancer, including growth, apoptosis, invasion and metastasis, angiogenesis, and metabolism. AS has important clinical implications since it can be manipulated therapeutically to treat cancer and represents a mechanism of resistance to therapy. In prostate cancer (PCa) AS also plays a prominent role and this review will summarize the current knowledge of alternatively spliced genes with important functional consequences. We will highlight accumulating evidence on AS of the components of the two critical pathways in PCa: androgen receptor (AR) and phosphoinositide 3-kinase (PI3K). These observations together with data on dysregulation of splice factors in PCa suggest that AR and PI3K pathways may be interconnected with previously unappreciated splicing regulatory networks. In addition, we will discuss several lines of evidence implicating splicing regulation in the development of the castration resistance.

Lineage-specific splicing of a brain-enriched alternative exon promotes glioblastoma progression

Tissue-specific alternative splicing is critical for the emergence of tissue identity during development, yet the role of this process in malignant transformation is undefined. Tissue-specific splicing involves evolutionarily conserved, alternative exons that represent only a minority of the total alternative exons identified. Many of these conserved exons have functional features that influence signaling pathways to profound biological effect. Here, we determined that lineage-specific splicing of a brain-enriched cassette exon in the membrane-binding tumor suppressor annexin A7 (ANXA7) diminishes endosomal targeting of the EGFR oncoprotein, consequently enhancing EGFR signaling during brain tumor progression. ANXA7 exon splicing was mediated by the ribonucleoprotein PTBP1, which is normally repressed during neuronal development. PTBP1 was highly expressed in glioblastomas due to loss of a brain-enriched microRNA (miR-124) and to PTBP1 amplification. The alternative ANXA7 splicing trait was present in precursor cells, suggesting that glioblastoma cells inherit the trait from a potential tumor-initiating ancestor and that these cells exploit this trait through accumulation of mutations that enhance EGFR signaling. Our data illustrate that lineage-specific splicing of a tissue-regulated alternative exon in a constituent of an oncogenic pathway eliminates tumor suppressor functions and promotes glioblastoma progression. This paradigm may offer a general model as to how tissue-specific regulatory mechanisms can reprogram normal developmental processes into oncogenic ones.

Cloning of a novel insulin-regulated ghrelin transcript in prostate cancer

Ghrelin is a multifunctional hormone, with roles in stimulating appetite and regulating energy balance, insulin secretion and glucose homoeostasis. The ghrelin gene locus (GHRL) is highly complex and gives rise to a range of novel transcripts derived from alternative first exons and internally spliced exons. The wild-type transcript encodes a 117 amino acid preprohormone that is processed to yield the 28 amino acid peptide ghrelin. Here, we identified insulin-responsive transcription corresponding to cryptic exons in intron 2 of the human ghrelin gene. A transcript, termed in2c-ghrelin (intron 2-cryptic), was cloned from the testis and the LNCaP prostate cancer cell line. This transcript may encode an 83 amino acid preproghrelin isoform that codes for ghrelin, but not obestatin. It is expressed in a limited number of normal tissues and in tumours of the prostate, testis, breast and ovary. Finally, we confirmed that in2c-ghrelin transcript expression, as well as the recently described in1-ghrelin transcript, is significantly upregulated by insulin in cultured prostate cancer cells. Metabolic syndrome and hyperinsulinaemia have been associated with prostate cancer risk and progression. This may be particularly significant after androgen deprivation therapy for prostate cancer, which induces hyperinsulinaemia, and this could contribute to castrate-resistant prostate cancer growth. We have previously demonstrated that ghrelin stimulates prostate cancer cell line proliferation in vitro. This study is the first description of insulin regulation of a ghrelin transcript in cancer and should provide further impetus for studies into the expression, regulation and function of ghrelin gene products.

Detection of Alternatively Spliced or Processed RNAs in Cancer Using Oligonucleotide Microarray

Deregulation of gene expression plays a pivotal role in tumorigenesis, so the ability to detect RNA alterations is of great value in cancer diagnosis and management. DNA microarrays have been used to measure changes in mRNA or microRNA level, but less often the change of RNA isoforms. Here we appraise the utilization of microarray in detecting alternatively processed RNAs, which have alternative splice forms, retained introns, or altered 3' untranslated regions. We cover the methodology and focus on cancer studies. Recent development in parallel or deep sequencing used in transcriptome analysis is also discussed.

Intrinsic molecular subtypes of glioma are prognostic and predict benefit from adjuvant procarbazine, lomustine, and vincristine chemotherapy in combination with other prognostic factors in anaplastic oligodendroglial brain tumors: a report from EORTC study 26951

PURPOSE

Intrinsic glioma subtypes (IGSs) are molecularly similar tumors that can be identified based on unsupervised gene expression analysis. Here, we have evaluated the clinical relevance of these subtypes within European Organisation for Research and Treatment of Cancer (EORTC) 26951, a randomized phase III clinical trial investigating adjuvant procarbazine, lomustine, and vincristine (PCV) chemotherapy in anaplastic oligodendroglial tumors. Our study includes gene expression profiles of formalin-fixed, paraffin-embedded (FFPE) clinical trial samples.

PATIENTS AND METHODS

Gene expression profiling was performed in 140 samples, 47 fresh frozen samples and 93 FFPE samples, on HU133_Plus_2.0 and HuEx_1.0_st arrays, respectively.

RESULTS

All previously identified six IGSs are present in EORTC 26951. This confirms that different molecular subtypes are present within a well-defined histologic subtype. Intrinsic subtypes are highly prognostic for overall survival (OS) and progression-free survival (PFS). They are prognostic for PFS independent of clinical (age, performance status, and tumor location), molecular (1p/19q loss of heterozygosity [LOH], IDH1 mutation, and MGMT methylation), and histologic parameters. Combining known molecular (1p/19q LOH, IDH1) prognostic parameters with intrinsic subtypes improves outcome prediction (proportion of explained variation, 30% v 23% for each individual group of factors). Specific genetic changes (IDH1, 1p/19q LOH, and EGFR amplification) segregate into different subtypes. We identified one subtype, IGS-9 (characterized by a high percentage of 1p/19q LOH and IDH1 mutations), that especially benefits from PCV chemotherapy. Median OS in this subtype was 5.5 years after radiotherapy (RT) alone versus 12.8 years after RT/PCV (P = .0349; hazard ratio, 2.18; 95% CI, 1.06 to 4.50).

CONCLUSION

Intrinsic subtypes are highly prognostic in EORTC 26951 and improve outcome prediction when combined with other prognostic factors. Tumors assigned to IGS-9 benefit from adjuvant PCV.

PTBP1-dependent regulation of USP5 alternative RNA splicing plays a role in glioblastoma tumorigenesis

Aberrant RNA splicing is thought to play a key role in tumorigenesis. The assessment of its specific contributions is limited by the complexity of information derived from genome-wide array-based approaches. We describe how performing splicing factor-specific comparisons using both tumor and cell line data sets may more readily identify physiologically relevant tumor-specific splicing events. Affymetrix exon array data derived from glioblastoma (GBM) tumor samples with defined polypyrimidine tract-binding protein 1 (PTBP1) levels were compared with data from U251 GBM cells with and without PTBP1 knockdown. This comparison yielded overlapping gene sets that comprised only a minor fraction of each data set. The identification of a novel GBM-specific splicing event involving the USP5 gene led us to further examine its role in tumorigenesis. In GBM, USP5 generates a shorter isoform 2 through recognition of a 5' splice site within exon 15. Production of the USP5 isoform 2 was strongly correlated with PTBP1 expression in GBM tumor samples and cell lines. Splicing regulation was consistent with the presence of an intronic PTBP1 binding site and could be modulated through antisense targeting of the isoform 2 splice site to force expression of isoform 1 in GBM cells. The forced expression of USP5 isoform 1 in two GBM cell lines inhibited cell growth and migration, implying an important role for USP5 splicing in gliomagenesis. These results support a role for aberrant RNA splicing in tumorigenesis and suggest that changes in relatively few genes may be sufficient to drive the process.

Genome-wide activation of latent donor splice sites in stress and disease

Sequences that conform to the 5′ splice site (5′SS) consensus are highly abundant in mammalian introns. Most of these sequences are preceded by at least one in-frame stop codon; thus, their use for splicing would result in pre-maturely terminated aberrant mRNAs. In normally grown cells, such intronic 5′SSs appear not to be selected for splicing. However, under heat shock conditions aberrant splicing involving such latent 5′SSs occurred in a number of specific gene transcripts. Using a splicing-sensitive microarray, we show here that stress-induced (e.g. heat shock) activation of latent splicing is widespread across the human transcriptome, thus highlighting the possibility that latent splicing may underlie certain diseases. Consistent with this notion, our analyses of data from the Gene Expression Omnibus (GEO) revealed widespread activation of latent splicing in cells grown under hypoxia and in certain cancers such as breast cancer and gliomas. These changes were found in thousands of transcripts representing a wide variety of functional groups; among them are genes involved in cell proliferation and differentiation. The GEO analysis also revealed a set of gene transcripts in oligodendroglioma, in which the level of activation of latent splicing increased with the severity of the disease.

Subgroup-specific alternative splicing in medulloblastoma

Medulloblastoma comprises four distinct molecular variants: WNT, SHH, Group 3, and Group 4. We analyzed alternative splicing usage in 14 normal cerebellar samples and 103 medulloblastomas of known subgroup. Medulloblastoma samples have a statistically significant increase in alternative splicing as compared to normal fetal cerebella (2.3-times; P < 6.47E-8). Splicing patterns are distinct and specific between molecular subgroups. Unsupervised hierarchical clustering of alternative splicing events accurately assigns medulloblastomas to their correct subgroup. Subgroup-specific splicing and alternative promoter usage was most prevalent in Group 3 (19.4%) and SHH (16.2%) medulloblastomas, while observed less frequently in WNT (3.2%), and Group 4 (9.3%) tumors. Functional annotation of alternatively spliced genes reveals overrepresentation of genes important for neuronal development. Alternative splicing events in medulloblastoma may be regulated in part by the correlative expression of antisense transcripts, suggesting a possible mechanism affecting subgroup-specific alternative splicing. Our results identify additional candidate markers for medulloblastoma subgroup affiliation, further support the existence of distinct subgroups of the disease, and demonstrate an additional level of transcriptional heterogeneity between medulloblastoma subgroups.

BEAT: Bioinformatics Exon Array Tool to store, analyze and visualize Affymetrix GeneChip Human Exon Array data from disease experiments

BACKGROUND

It is known from recent studies that more than 90% of human multi-exon genes are subject to Alternative Splicing (AS), a key molecular mechanism in which multiple transcripts may be generated from a single gene. It is widely recognized that a breakdown in AS mechanisms plays an important role in cellular differentiation and pathologies. Polymerase Chain Reactions, microarrays and sequencing technologies have been applied to the study of transcript diversity arising from alternative expression. Last generation Affymetrix GeneChip Human Exon 1.0 ST Arrays offer a more detailed view of the gene expression profile providing information on the AS patterns. The exon array technology, with more than five million data points, can detect approximately one million exons, and it allows performing analyses at both gene and exon level. In this paper we describe BEAT, an integrated user-friendly bioinformatics framework to store, analyze and visualize exon arrays datasets. It combines a data warehouse approach with some rigorous statistical methods for assessing the AS of genes involved in diseases. Meta statistics are proposed as a novel approach to explore the analysis results. BEAT is available at http://beat.ba.itb.cnr.it.

RESULTS

BEAT is a web tool which allows uploading and analyzing exon array datasets using standard statistical methods and an easy-to-use graphical web front-end. BEAT has been tested on a dataset with 173 samples and tuned using new datasets of exon array experiments from 28 colorectal cancer and 26 renal cell cancer samples produced at the Medical Genetics Unit of IRCCS Casa Sollievo della Sofferenza.To highlight all possible AS events, alternative names, accession Ids, Gene Ontology terms and biochemical pathways annotations are integrated with exon and gene level expression plots. The user can customize the results choosing custom thresholds for the statistical parameters and exploiting the available clinical data of the samples for a multivariate AS analysis.

CONCLUSIONS

Despite exon array chips being widely used for transcriptomics studies, there is a lack of analysis tools offering advanced statistical features and requiring no programming knowledge. BEAT provides a user-friendly platform for a comprehensive study of AS events in human diseases, displaying the analysis results with easily interpretable and interactive tables and graphics.

Gene expression profiles of gliomas in formalin-fixed paraffin-embedded material

BACKGROUND

We have recently demonstrated that expression profiling is a more accurate and objective method to classify gliomas than histology. Similar to most expression profiling studies, our experiments were performed using fresh frozen (FF) glioma samples whereas most archival samples are fixed in formalin and embedded in paraffin (FFPE). Identification of the same, expression-based intrinsic subtypes in FFPE-stored samples would enable validation of the prognostic value of these subtypes on these archival samples. In this study, we have therefore determined whether the intrinsic subtypes identified using FF material can be reproduced in FFPE-stored samples.

METHODS

We have performed expression profiling on 55 paired FF-FFPE glioma samples using HU133 plus 2.0 arrays (FF) and Exon 1.0 ST arrays (FFPE). The median time in paraffin of the FFPE samples was 14.1 years (range 6.6-26.4 years).

RESULTS

In general, the correlation between FF and FFPE expression in a single sample was poor. We then selected the most variable probe sets per gene (n=17,583), and of these, the 5000 most variable probe sets on FFPE expression profiles. This unsupervised selection resulted in a better concordance (R(2)=0.54) between expression of FF and FFPE samples. Importantly, this probe set selection resulted in a correct assignment of 87% of FFPE samples into one of seven intrinsic subtypes identified using FF samples. Assignment to the same molecular cluster as the paired FF tissue was not correlated to time in paraffin.

CONCLUSION

We are the first to examine a large cohort of paired FF and FFPE samples. We show that expression data from FFPE material can be used to assign samples to intrinsic molecular subtypes identified using FF material. This assignment allows the use of archival material, including material derived from large-randomised clinical trials, to determine the predictive and/or prognostic value of 'intrinsic glioma subtypes' on Exon arrays. This would enable clinicians to provide patients with an objective and accurate diagnosis and prognosis, and a personalised treatment strategy.

Comparative analysis of human protein-coding and noncoding RNAs between brain and 10 mixed cell lines by RNA-Seq

In their expression process, different genes can generate diverse functional products, including various protein-coding or noncoding RNAs. Here, we investigated the protein-coding capacities and the expression levels of their isoforms for human known genes, the conservation and disease association of long noncoding RNAs (ncRNAs) with two transcriptome sequencing datasets from human brain tissues and 10 mixed cell lines. Comparative analysis revealed that about two-thirds of the genes expressed between brain and cell lines are the same, but less than one-third of their isoforms are identical. Besides those genes specially expressed in brain and cell lines, about 66% of genes expressed in common encoded different isoforms. Moreover, most genes dominantly expressed one isoform and some genes only generated protein-coding (or noncoding) RNAs in one sample but not in another. We found 282 human genes could encode both protein-coding and noncoding RNAs through alternative splicing in the two samples. We also identified more than 1,000 long ncRNAs, and most of those long ncRNAs contain conserved elements across either 46 vertebrates or 33 placental mammals or 10 primates. Further analysis showed that some long ncRNAs differentially expressed in human breast cancer or lung cancer, several of those differentially expressed long ncRNAs were validated by RT-PCR. In addition, those validated differentially expressed long ncRNAs were found significantly correlated with certain breast cancer or lung cancer related genes, indicating the important biological relevance between long ncRNAs and human cancers. Our findings reveal that the differences of gene expression profile between samples mainly result from the expressed gene isoforms, and highlight the importance of studying genes at the isoform level for completely illustrating the intricate transcriptome.

Splicing programs and cancer

Numerous studies report splicing alterations in a multitude of cancers by using gene-by-gene analysis. However, understanding of the role of alternative splicing in cancer is now reaching a new level, thanks to the use of novel technologies allowing the analysis of splicing at a large-scale level. Genome-wide analyses of alternative splicing indicate that splicing alterations can affect the products of gene networks involved in key cellular programs. In addition, many splicing variants identified as being misregulated in cancer are expressed in normal tissues. These observations suggest that splicing programs contribute to specific cellular programs that are altered during cancer initiation and progression. Supporting this model, recent studies have identified splicing factors controlling cancer-associated splicing programs. The characterization of splicing programs and their regulation by splicing factors will allow a better understanding of the genetic mechanisms involved in cancer initiation and progression and the development of new therapeutic targets.

Tumor-specific usage of alternative transcription start sites in colorectal cancer identified by genome-wide exon array analysis

BACKGROUND

Approximately half of all human genes use alternative transcription start sites (TSSs) to control mRNA levels and broaden the transcriptional output in healthy tissues. Aberrant expression patterns promoting carcinogenesis, however, may arise from alternative promoter usage.

RESULTS

By profiling 108 colorectal samples using exon arrays, we identified nine genes (TCF12, OSBPL1A, TRAK1, ANK3, CHEK1, UGP2, LMO7, ACSL5, and SCIN) showing tumor-specific alternative TSS usage in both adenoma and cancer samples relative to normal mucosa. Analysis of independent exon array data sets corroborated these findings. Additionally, we confirmed the observed patterns for selected mRNAs using quantitative real-time reverse-transcription PCR. Interestingly, for some of the genes, the tumor-specific TSS usage was not restricted to colorectal cancer. A comprehensive survey of the nine genes in lung, bladder, liver, prostate, gastric, and brain cancer revealed significantly altered mRNA isoform ratios for CHEK1, OSBPL1A, and TCF12 in a subset of these cancer types.To identify the mechanism responsible for the shift in alternative TSS usage, we antagonized the Wnt-signaling pathway in DLD1 and Ls174T colorectal cancer cell lines, which remarkably led to a shift in the preferred TSS for both OSBPL1A and TRAK1. This indicated a regulatory role of the Wnt pathway in selecting TSS, possibly also involving TP53 and SOX9, as their transcription binding sites were enriched in the promoters of the tumor preferred isoforms together with their mRNA levels being increased in tumor samples. Finally, to evaluate the prognostic impact of the altered TSS usage, immunohistochemistry was used to show deregulation of the total protein levels of both TCF12 and OSBPL1A, corresponding to the mRNA levels observed. Furthermore, the level of nuclear TCF12 had a significant correlation to progression free survival in a cohort of 248 stage II colorectal cancer samples.

CONCLUSIONS

Alternative TSS usage in colorectal adenoma and cancer samples has been shown for nine genes, and OSBPL1A and TRAK1 were found to be regulated in vitro by Wnt signaling. TCF12 protein expression was upregulated in cancer samples and correlated with progression free survival.

Identification of transcriptional regulatory networks specific to pilocytic astrocytoma

Background

Pilocytic Astrocytomas (PAs) are common low-grade central nervous system malignancies for which few recurrent and specific genetic alterations have been identified. In an effort to better understand the molecular biology underlying the pathogenesis of these pediatric brain tumors, we performed higher-order transcriptional network analysis of a large gene expression dataset to identify gene regulatory pathways that are specific to this tumor type, relative to other, more aggressive glial or histologically distinct brain tumours.

Methods

RNA derived from frozen human PA tumours was subjected to microarray-based gene expression profiling, using Affymetrix U133Plus2 GeneChip microarrays. This data set was compared to similar data sets previously generated from non-malignant human brain tissue and other brain tumour types, after appropriate normalization.

Results

In this study, we examined gene expression in 66 PA tumors compared to 15 non-malignant cortical brain tissues, and identified 792 genes that demonstrated consistent differential expression between independent sets of PA and non-malignant specimens. From this entire 792 gene set, we used the previously described PAP tool to assemble a core transcriptional regulatory network composed of 6 transcription factor genes (TFs) and 24 target genes, for a total of 55 interactions. A similar analysis of oligodendroglioma and glioblastoma multiforme (GBM) gene expression data sets identified distinct, but overlapping, networks. Most importantly, comparison of each of the brain tumor type-specific networks revealed a network unique to PA that included repressed expression of ONECUT2, a gene frequently methylated in other tumor types, and 13 other uniquely predicted TF-gene interactions.

Conclusions

These results suggest specific transcriptional pathways that may operate to create the unique molecular phenotype of PA and thus opportunities for corresponding targeted therapeutic intervention. Moreover, this study also demonstrates how integration of gene expression data with TF-gene and TF-TF interaction data is a powerful approach to generating testable hypotheses to better understand cell-type specific genetic programs relevant to cancer.

Absence of common somatic alterations in genes on 1p and 19q in oligodendrogliomas

A common and histologically well defined subtype of glioma are the oligodendroglial brain tumors. Approximately 70% of all oligodendrogliomas have a combined loss of the entire 1p and 19q chromosomal arms. This remarkably high frequency suggests that the remaining arms harbor yet to be identified tumor suppressor genes. Identification of these causal genetic changes in oligodendrogliomas is important because they form direct targets for treatment. In this study we therefore performed targeted resequencing of all exons, microRNAs, splice sites and promoter regions residing on 1p and 19q on 7 oligodendrogliomas and 4 matched controls. Only one missense mutation was identified in a single sample in the ARHGEF16 gene. This mutation lies within- and disrupts the conserved PDZ binding domain. No similar ARHGEF16 mutations or deletions were found in a larger set of oligodendrogliomas. The absence of common somatic changes within genes located on 1p and 19q in three out of four samples indicates that no additional "second hit" is required to drive oncogenic transformation on either chromosomal arm.

Whole field tendencies in transcranial magnetic stimulation: A systematic review with data and text mining

BACKGROUND

Transcranial magnetic stimulation (TMS) has played an important role in the fields of psychiatry, neurology and neuroscience, since its emergence in the mid-1980s; and several high quality reviews have been produced since then. Most high quality reviews serve as powerful tools in the evaluation of predefined tendencies, but they cannot actually uncover new trends within the literature. However, special statistical procedures to 'mine' the literature have been developed which aid in achieving such a goal.

OBJECTIVES

This paper aims to uncover patterns within the literature on TMS as a whole, as well as specific trends in the recent literature on TMS for the treatment of depression.

METHODS

Data mining and text mining.

RESULTS

Currently there are 7299 publications, which can be clustered in four essential themes. Considering the frequency of the core psychiatric concepts within the indexed literature, the main results are: depression is present in 13.5% of the publications; Parkinson's disease in 2.94%; schizophrenia in 2.76%; bipolar disorder in 0.158%; and anxiety disorder in 0.142% of all the publications indexed in PubMed. Several other perspectives are discussed in the article.

Lex-SVM: exploring the potential of exon expression profiling for disease classification

Exon expression profiling technologies, including exon arrays and RNA-Seq, measure the abundance of every exon in a gene. Compared with gene expression profiling technologies like 3' array, exon expression profiling technologies could detect alterations in both transcription and alternative splicing, therefore they are expected to be more sensitive in diagnosis. However, exon expression profiling also brings higher dimension, more redundancy, and significant correlation among features. Ignoring the correlation structure among exons of a gene, a popular classification method like L1-SVM selects exons individually from each gene and thus is vulnerable to noise. To overcome this limitation, we present in this paper a new variant of SVM named Lex-SVM to incorporate correlation structure among exons and known splicing patterns to promote classification performance. Specifically, we construct a new norm, ex-norm, including our prior knowledge on exon correlation structure to regularize the coefficients of a linear SVM. Lex-SVM can be solved efficiently using standard linear programming techniques. The advantage of Lex-SVM is that it can select features group-wisely, force features in a subgroup to take equal weihts and exclude the features that contradict the majority in the subgroup. Experimental results suggest that on exon expression profile, Lex-SVM is more accurate than existing methods. Lex-SVM also generates a more compact model and selects genes more consistently in cross-validation. Unlike L1-SVM selecting only one exon in a gene, Lex-SVM assigns equal weights to as many exons in a gene as possible, lending itself easier for further interpretation.

Tumor profiling: development of prognostic and predictive factors to guide brain tumor treatment

Primary brain tumors are a heterogeneous group of malignancies with highly variable outcomes, and diagnosis is largely based on the histological appearance of the tumors. However, the diversity of primary brain tumors has made prognostic determinations based purely on clinicopathologic variables difficult. There is an increasing body of data suggesting a significant amount of molecular diversity accounts for the heterogeneity of clinical observations, such as response to treatment and time to progression. The last decade has witnessed an explosive advance in our knowledge of the molecular genetics of brain tumors, due in large part to the availability of high-throughput profiling techniques and to the completion of the human genome sequencing project. The large amount of data generated by these efforts has enabled the identification of prognostic and predictive factors and helping to identify pathways which are driving tumor growth. Identification of biomarkers will enable better patient stratification and individualization of treatment.

Exon array analysis reveals neuroblastoma tumors have distinct alternative splicing patterns according to stage and MYCN amplification status

BACKGROUND

Neuroblastoma (NB) tumors are well known for their pronounced clinical and molecular heterogeneity. The global gene expression and DNA copy number alterations have been shown to have profound differences in tumors of low or high stage and those with or without MYCN amplification. RNA splicing is an important regulatory mechanism of gene expression, and differential RNA splicing may be associated with the clinical behavior of a tumor.

METHODS

In this study, we used exon array profiling to investigate global alternative splicing pattern of 47 neuroblastoma samples in stage 1 and stage 4 with normal or amplified MYCN copy number (stage 1-, 4- and 4+). The ratio of exon-level expression to gene-level expression was used to detect alternative splicing events, while the gene-level expression was applied to characterize whole gene expression change.

RESULTS

Principal component analysis (PCA) demonstrated distinct splicing pattern in three groups of samples. Pairwise comparison identified genes with splicing changes and/or whole gene expression changes in high stage tumors. In stage 4- compared with stage 1- tumors, alternatively spliced candidate genes had little overlap with genes showing whole gene expression changes, and most of them were involved in different biological processes. In contrast, a larger number of genes exhibited either exon-level splicing, gene-level expression or both changes in stage 4+ versus stage 1- tumors. Those biological processes involved in stage 4- tumors were disrupted to a greater extent by both splicing and transcription regulations in stage 4+ tumors.

CONCLUSIONS

Our results demonstrated a significant role of alternative splicing in high stage neuroblastoma, and suggested a MYCN-associated splicing regulation pathway in stage 4+ tumors. The identification of differentially spliced genes and pathways in neuroblastoma tumors of different stages and molecular subtypes may be important to the understanding of cancer biology and the discovery of diagnostic markers or therapeutic targets in neuroblastoma.

Melanoma spheroids grown under neural crest cell conditions are highly plastic migratory/invasive tumor cells endowed with immunomodulator function

Background

The aggressiveness of melanoma tumors is likely to rely on their well-recognized heterogeneity and plasticity. Melanoma comprises multi-subpopulations of cancer cells some of which may possess stem cell-like properties. Although useful, the sphere-formation assay to identify stem cell-like or tumor initiating cell subpopulations in melanoma has been challenged, and it is unclear if this model can predict a functional phenotype associated with aggressive tumor cells.

Methodology/Principal Findings

We analyzed the molecular and functional phenotypes of melanoma spheroids formed in neural crest cell medium. Whether from metastatic or advanced primary tumors, spheroid cells expressed melanoma-associated markers. They displayed higher capacity to differentiate along mesenchymal lineages and enhanced expression of SOX2, NANOG, KLF4, and/or OCT4 transcription factors, but not enhanced self-renewal or tumorigenicity when compared to their adherent counterparts. Gene expression profiling attributed a neural crest cell signature to these spheroids and indicated that a migratory/invasive and immune-function modulating program could be associated with these cells. In vitro assays confirmed that spheroids display enhanced migratory/invasive capacities. In immune activation assays, spheroid cells elicited a poorer allogenic response from immune cells and inhibited mitogen-dependent T cells activation and proliferation more efficiently than their adherent counterparts. Our findings reveal a novel immune-modulator function of melanoma spheroids and suggest specific roles for spheroids in invasion and in evasion of antitumor immunity.

Conclusion/Significance

The association of a more plastic, invasive and evasive, thus a more aggressive tumor phenotype with melanoma spheroids reveals a previously unrecognized aspect of tumor cells expanded as spheroid cultures. While of limited efficiency for melanoma initiating cell identification, our melanoma spheroid model predicted aggressive phenotype and suggested that aggressiveness and heterogeneity of melanoma tumors can be supported by subpopulations other than cancer stem cells. Therefore, it could be constructive to investigate melanoma aggressiveness, relevant to patients and clinical transferability.

Identification of Tat-SF1 cellular targets by exon array analysis reveals dual roles in transcription and splicing

Tat specific factor 1 (Tat-SF1) interacts with components of both the transcription and splicing machineries and has been classified as a transcription-splicing factor. Although its function as an HIV-1 dependency factor has been investigated, relatively little is known about the cellular functions of Tat-SF1. To identify target genes of Tat-SF1, we utilized a combination of RNAi and exon-specific microarrays. These arrays, which survey genome-wide changes in transcript and individual exon levels, revealed 450 genes with transcript level changes upon Tat-SF1 depletion. Strikingly, 98% of these target genes were down-regulated upon depletion, indicating that Tat-SF1 generally activates gene expression. We also identified 89 genes that showed differential exon level changes after Tat-SF1 depletion. The 89 genes showed evidence of many different types of alternative exon use consistent with the regulation of transcription initiation sites and RNA processing. Minimal overlap between genes with transcript-level and exon-level changes suggests that Tat-SF1 does not functionally couple transcription and splicing. Biological processes significantly enriched with transcript- and exon-level targets include the cell cycle and nucleic acid metabolism; the insulin signaling pathway was enriched with Tat-SF1 transcript-level targets but not exon-level targets. Additionally, a hexamer, ATGCCG, was over-represented in the promoter region of genes showing changes in transcription initiation upon Tat-SF1 depletion. This may represent a novel motif that Tat-SF1 recognizes during transcription. Together, these findings suggest that Tat-SF1 functions independently in transcription and splicing of cellular genes.

The use of global profiling in biomarker development for gliomas

The diffuse gliomas are a heterogeneous group of malignancies with highly variable outcomes and diagnosis is largely based on the histological appearance of the tumors. Tumor classification according to cello type and grade provides some prognostic information. However, the diversity of gliomas, within tumor type and grade categories, has made prognostic determinations based purely on clinicopathologic variables difficult. There is an increasing body of data suggesting a significant amount of molecular diversity accounts for the heterogeneity of clinical observations, such as response to treatment and time to progression. The last decade has witnessed an explosive advance in our knowledge of the molecular genetics of brain tumors, due in large part to the availability of high-throughput profiling techniques, including new sequencing methodologies as well as multidimensional profiling by the Cancer Genome Atlas project. The large amount of data generated by these efforts has enabled the identification of prognostic and predictive factors and helping to identify pathways that are driving tumor growth. Identification of biomarkers, especially when coupled to clinical trials of newer targeted therapies, will enable better patient stratification and individualization of treatment.

Genome-wide analysis of alternative splicing in medulloblastoma identifies splicing patterns characteristic of normal cerebellar development

Alternative splicing is an important mechanism for the generation of protein diversity at a post-transcriptional level. Modifications in the splicing patterns of several genes have been shown to contribute to the malignant transformation of different tissue types. In this study, we used the Affymetrix Exon arrays to investigate patterns of differential splicing between pediatric medulloblastomas and normal cerebellum on a genome-wide scale. Of the 1,262 genes identified as potentially generating tumor-associated splice forms, we selected 14 examples of differential splicing of known cassette exons and successfully validated 11 of them by reverse transcriptase PCR. The pattern of differential splicing of three validated events was characteristic for the molecular subset of sonic hedgehog (Shh)-driven medulloblastomas, suggesting that their unique gene signature includes the expression of distinctive transcript variants. Generally, we observed that tumor and normal fetal cerebellar samples shared significantly lower exon inclusion rates than normal adult cerebellum. We investigated whether tumor-associated splice forms were expressed in primary cultures of Shh-dependent mouse cerebellar granule cell precursors (GCP) and found that Shh caused a decrease in the cassette exon inclusion rate of five of the seven tested genes. Furthermore, we observed a significant increase in exon inclusion between postnatal days 7 and 14 of mouse cerebellar development, at the time when GCPs mature into postmitotic neurons. We conclude that inappropriate splicing frequently occurs in human medulloblastomas and may be linked to the activation of developmental signaling pathways and a failure of cerebellar precursor cells to differentiate.

Adjunctive dexamethasone affects the expression of genes related to inflammation, neurogenesis and apoptosis in infant rat pneumococcal meningitis

Streptococcus pneumoniae is the most common pathogen causing non-epidemic bacterial meningitis worldwide. The immune response and inflammatory processes contribute to the pathophysiology. Hence, the anti-inflammatory dexamethasone is advocated as adjuvant treatment although its clinical efficacy remains a question at issue. In experimental models of pneumococcal meningitis, dexamethasone increased neuronal damage in the dentate gyrus. Here, we investigated expressional changes in the hippocampus and cortex at 72 h after infection when dexamethasone was given to infant rats with pneumococcal meningitis. Nursing Wistar rats were intracisternally infected with Streptococcus pneumoniae to induce experimental meningitis or were sham-infected with pyrogen-free saline. Besides antibiotics, animals were either treated with dexamethasone or saline. Expressional changes were assessed by the use of GeneChip® Rat Exon 1.0 ST Arrays and quantitative real-time PCR. Protein levels of brain-derived neurotrophic factor, cytokines and chemokines were evaluated in immunoassays using Luminex xMAP® technology. In infected animals, 213 and 264 genes were significantly regulated by dexamethasone in the hippocampus and cortex respectively. Separately for the cortex and the hippocampus, Gene Ontology analysis identified clusters of biological processes which were assigned to the predefined categories "inflammation", "growth", "apoptosis" and others. Dexamethasone affected the expression of genes and protein levels of chemokines reflecting diminished activation of microglia. Dexamethasone-induced changes of genes related to apoptosis suggest the downregulation of the Akt-survival pathway and the induction of caspase-independent apoptosis. Signalling of pro-neurogenic pathways such as transforming growth factor pathway was reduced by dexamethasone resulting in a lack of pro-survival triggers. The anti-inflammatory properties of dexamethasone were observed on gene and protein level in experimental pneumococcal meningitis. Further dexamethasone-induced expressional changes reflect an increase of pro-apoptotic signals and a decrease of pro-neurogenic processes. The findings may help to identify potential mechanisms leading to apoptosis by dexamethasone in experimental pneumococcal meningitis.

Insights into global mechanisms and disease by gene expression profiling

Transcriptomics has played an essential role as proof of concept in the development of experimental and bioinformatics approaches for the generation and analysis of Omics data. We are giving an introduction on how large-scale technologies for gene expression profiling, especially microarrays, have changed the view from studying single molecular events to a systems level view of global mechanisms in a cell, the biological processes, and their pathological mutations. The main platforms available for gene expression profiling (from microarrays to RNA-seq) are presented and the general concepts that need to be taken into account for proper data analysis in order to extract objective and general conclusions from transcriptomics experiments are introduced. We also describe the available main bioinformatics resources used for this purpose.

Improvements to previous algorithms to predict gene structure and isoform concentrations using Affymetrix Exon arrays

BACKGROUND

Exon arrays provide a way to measure the expression of different isoforms of genes in an organism. Most of the procedures to deal with these arrays are focused on gene expression or on exon expression. Although the only biological analytes that can be properly assigned a concentration are transcripts, there are very few algorithms that focus on them. The reason is that previously developed summarization methods do not work well if applied to transcripts. In addition, gene structure prediction, i.e., the correspondence between probes and novel isoforms, is a field which is still unexplored.

RESULTS

We have modified and adapted a previous algorithm to take advantage of the special characteristics of the Affymetrix exon arrays. The structure and concentration of transcripts -some of them possibly unknown- in microarray experiments were predicted using this algorithm. Simulations showed that the suggested modifications improved both specificity (SP) and sensitivity (ST) of the predictions. The algorithm was also applied to different real datasets showing its effectiveness and the concordance with PCR validated results.

CONCLUSIONS

The proposed algorithm shows a substantial improvement in the performance over the previous version. This improvement is mainly due to the exploitation of the redundancy of the Affymetrix exon arrays. An R-Package of SPACE with the updated algorithms have been developed and is freely available.

The CASPR2 cell adhesion molecule functions as a tumor suppressor gene in glioma

Genomic translocations have been implicated in cancer. In this study, we performed a screen for genetic translocations in gliomas based on exon-level expression profiles. We identified a translocation in the contactin-associated protein-like 2 (CASPR2) gene, encoding a cell adhesion molecule. CASPR2 mRNA was fused to an expressed sequence tag that likely is part of the nuclear receptor coactivator 1 gene. Despite high mRNA expression levels, no CASPR2 fusion protein was detected. In a set of 25 glioblastomas and 22 oligodendrogliomas, mutation analysis identified two additional samples with genetic alterations in the CASPR2 gene and all three identified genetic alterations are likely to reduce CASPR2 protein expression levels. Methylation of the CASPR2 gene was also observed in gliomas and glioma cell lines. CASPR2-overexpressing cells showed decreased proliferation rates, likely because of an increase in apoptosis. Moreover, high CASPR2 mRNA expression level is positively correlated with survival and is an independent prognostic factor. These results indicate that CASPR2 acts as a tumor suppressor gene in glioma.

Integrated genomic profiling identifies candidate genes implicated in glioma-genesis and a novel LEO1-SLC12A1 fusion gene

We performed genotyping and exon-level expression profiling on 21 glioblastomas (GBMs) and 19 oligodendrogliomas (ODs) to identify genes involved in glioma initiation and/or progression. Low-copy number amplifications (2.5 < n < 7) and high-copy number amplifications (n > 7) were more frequently observed in GBMs; ODs generally have more heterozygous deletions per tumor. Four high-copy amplicons were identified in more than one sample and resulted in overexpression of the known oncogenes EGFR, MDM2, and CDK4. In the fourth amplicon, RBBP5, a member of the RB pathway, may act as a novel oncogene in GBMs. Not all hCNAs contain known genes, which may suggest that other transcriptional and/or regulatory elements are the target for amplification. Regions with most frequent allelic loss, both in ODs and GBMs, resulted in a reduced expression of known tumor suppressor genes. We identified a homozygous deletion spanning the Pragmin gene in one sample, but direct sequencing of all coding exons in 20 other glioma samples failed to detect additional genetic changes. Finally, we screened for fusion genes by identifying aberrant 5'-3' expression of genes that lie over regions of a copy number change. A fusion gene between exon 11 of LEO1 and exon 10 of SLC12A1 was identified. Our data show that integrated genomic profiling can identify genes involved in tumor initiation, and/or progression and can be used as an approach to identify novel fusion genes.

Development of a novel splice array platform and its application in the identification of alternative splice variants in lung cancer

Background

Microarrays strategies, which allow for the characterization of thousands of alternative splice forms in a single test, can be applied to identify differential alternative splicing events. In this study, a novel splice array approach was developed, including the design of a high-density oligonucleotide array, a labeling procedure, and an algorithm to identify splice events.

Results

The array consisted of exon probes and thermodynamically balanced junction probes. Suboptimal probes were tagged and considered in the final analysis. An unbiased labeling protocol was developed using random primers. The algorithm used to distinguish changes in expression from changes in splicing was calibrated using internal non-spliced control sequences. The performance of this splice array was validated with artificial constructs for CDC6, VEGF, and PCBP4 isoforms. The platform was then applied to the analysis of differential splice forms in lung cancer samples compared to matched normal lung tissue. Overexpression of splice isoforms was identified for genes encoding CEACAM1, FHL-1, MLPH, and SUSD2. None of these splicing isoforms had been previously associated with lung cancer.

Conclusions

This methodology enables the detection of alternative splicing events in complex biological samples, providing a powerful tool to identify novel diagnostic and prognostic biomarkers for cancer and other pathologies.

A comparison of massively parallel nucleotide sequencing with oligonucleotide microarrays for global transcription profiling

Background

RNA-Seq exploits the rapid generation of gigabases of sequence data by Massively Parallel Nucleotide Sequencing, allowing for the mapping and digital quantification of whole transcriptomes. Whilst previous comparisons between RNA-Seq and microarrays have been performed at the level of gene expression, in this study we adopt a more fine-grained approach. Using RNA samples from a normal human breast epithelial cell line (MCF-10a) and a breast cancer cell line (MCF-7), we present a comprehensive comparison between RNA-Seq data generated on the Applied Biosystems SOLiD platform and data from Affymetrix Exon 1.0ST arrays. The use of Exon arrays makes it possible to assess the performance of RNA-Seq in two key areas: detection of expression at the granularity of individual exons, and discovery of transcription outside annotated loci.

Results

We found a high degree of correspondence between the two platforms in terms of exon-level fold changes and detection. For example, over 80% of exons detected as expressed in RNA-Seq were also detected on the Exon array, and 91% of exons flagged as changing from Absent to Present on at least one platform had fold-changes in the same direction. The greatest detection correspondence was seen when the read count threshold at which to flag exons Absent in the SOLiD data was set to t<1 suggesting that the background error rate is extremely low in RNA-Seq. We also found RNA-Seq more sensitive to detecting differentially expressed exons than the Exon array, reflecting the wider dynamic range achievable on the SOLiD platform. In addition, we find significant evidence of novel protein coding regions outside known exons, 93% of which map to Exon array probesets, and are able to infer the presence of thousands of novel transcripts through the detection of previously unreported exon-exon junctions.

Conclusions

By focusing on exon-level expression, we present the most fine-grained comparison between RNA-Seq and microarrays to date. Overall, our study demonstrates that data from a SOLiD RNA-Seq experiment are sufficient to generate results comparable to those produced from Affymetrix Exon arrays, even using only a single replicate from each platform, and when presented with a large genome.

Astrocytes derived from trisomic human embryonic stem cells express markers of astrocytic cancer cells and premalignant stem-like progenitors

BACKGROUND

Trisomic variants of human embryonic stem cells (hESCs) arise spontaneously in culture. Although trisomic hESCs share many properties with diploid hESCs, they also exhibit features of cancer stem cells. Since most hESC-based therapies will utilize differentiated derivatives, it is imperative to investigate the potential of trisomic hESCs to undergo malignant transformation during differentiation prior to their use in the clinical setting.

METHODS

Diploid and trisomic hESCs were differentiated into astrocytic progenitors cells (APCs), RNA extracted and hybridized to human exon-specific microarrays. Global gene expression profiles of diploid and trisomic APCs were compared to that of an astrocytoma cell line and glioblastoma samples, analyzed by others, using the same microarray platform.

RESULTS

Bioinformatic analysis of microarray data indicates that differentiated trisomic APCs exhibit global expression profiles with similarities to the malignant astrocytoma cell line. An analogous trend is observed in comparison to glioblastoma samples indicating that trisomic APCs express markers of astrocytic cancer cells. The analysis also allowed identification of transcripts predicted to be differentially expressed in brain tumor stem cells. These data indicate that in vitro differentiation of trisomic hESCs along astrocytic pathways give rise to cells exhibiting properties of premalignant astrocytic stem/progenitor cells.

CONCLUSIONS

Given their occult nature, opportunities to study premalignant stem/progenitor cells in human have been few. The ability to propagate and direct the differentiation of aneuploid hESCs provides a powerful in vitro system for investigating biological properties of human cells exhibiting features of premalignant stem cells. This in vitro culture system can be used to elucidate changes in gene expression occurring enroute to malignant transformation and to identify molecular markers of cancer stem/progenitor cells. These markers are invaluable for diagnostic purposes and may be novel targets for therapeutic intervention.