Entropy Measures Quantify Global Splicing Disorders in Cancer

Most mammalian genes are able to express several splice variants in a phenomenon known as alternative splicing. Serious alterations of alternative splicing occur in cancer tissues, leading to expression of multiple aberrant splice forms. Most studies of alternative splicing defects have focused on the identification of cancer-specific splice variants as potential therapeutic targets. Here, we examine instead the bulk of non-specific transcript isoforms and analyze their level of disorder using a measure of uncertainty called Shannon's entropy. We compare isoform expression entropy in normal and cancer tissues from the same anatomical site for different classes of transcript variations: alternative splicing, polyadenylation, and transcription initiation. Whereas alternative initiation and polyadenylation show no significant gain or loss of entropy between normal and cancer tissues, alternative splicing shows highly significant entropy gains for 13 of the 27 cancers studied. This entropy gain is characterized by a flattening in the expression profile of normal isoforms and is correlated to the level of estimated cellular proliferation in the cancer tissue. Interestingly, the genes that present the highest entropy gain are enriched in splicing factors. We provide here the first quantitative estimate of splicing disruption in cancer. The expression of normal splice variants is widely and significantly disrupted in at least half of the cancers studied. We postulate that such splicing disorders may develop in part from splicing alteration in key splice factors, which in turn significantly impact multiple target genes

Transcriptome instability in colorectal cancer identified by exon microarray analyses: Associations with splicing factor expression levels and patient survival

Background Colorectal cancer (CRC) is a heterogeneous disease that, on the molecular level, can be characterized by inherent genomic instabilities; chromosome instability and microsatellite instability. In the present study we analyze genome-wide disruption of pre-mRNA splicing, and propose transcriptome instability as a characteristic that is analogous to genomic instability on the transcriptome level. Methods Exon microarray profiles from two independent series including a total of 160 CRCs were investigated for their relative amounts of exon usage differences. Each exon in each sample was assigned an alternative splicing score calculated by the FIRMA algorithm. Amounts of deviating exon usage per sample were derived from exons with extreme splicing scores. Results There was great heterogeneity within both series in terms of sample-wise amounts of deviating exon usage. This was strongly associated with the expression levels of approximately half of 280 splicing factors (54% and 48% of splicing factors were significantly correlated to deviating exon usage amounts in the two series). Samples with high or low amounts of deviating exon usage, associated with overall transcriptome instability, were almost completely separated into their respective groups by hierarchical clustering analysis of splicing factor expression levels in both sample series. Samples showing a preferential tendency towards deviating exon skipping or inclusion were associated with skewed transcriptome instability. There were significant associations between transcriptome instability and reduced patient survival in both sample series. In the test series, patients with skewed transcriptome instability showed the strongest prognostic association (P = 0.001), while a combination of the two characteristics showed the strongest association with poor survival in the validation series (P = 0.03). Conclusions We have described transcriptome instability as a characteristic of CRC. This transcriptome instability has associations with splicing factor expression levels and poor patient survival

Targeting the spliceosome for cutaneous squamous cell carcinoma therapy:a role for c-MYC and wild-type p53 in determining the degree of tumour selectivity

This study was supported by DEBRA International and funded by DEBRA Austria (Saville-Proby 1). I.M.L and M.K.S were supported by an ERC Advanced Investigator Award (250170, Principal Investigator I.M.L.). C.M.P. and I.M.L. were supported by a Cancer Research UK Programme Grant (A13044)

Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation

High-throughput mRNA sequencing (RNA-Seq) promises simultaneous transcript discovery and abundance estimation. However, this would require algorithms that are not restricted by prior gene annotations and that account for alternative transcription and splicing. Here we introduce such algorithms in an open-source software program called Cufflinks. To test Cufflinks, we sequenced and analyzed >430 million paired 75-bp RNA-Seq reads from a mouse myoblast cell line over a differentiation time series. We detected 13,692 known transcripts and 3,724 previously unannotated ones, 62% of which are supported by independent expression data or by homologous genes in other species. Over the time series, 330 genes showed complete switches in the dominant transcription start site (TSS) or splice isoform, and we observed more subtle shifts in 1,304 other genes. These results suggest that Cufflinks can illuminate the substantial regulatory flexibility and complexity in even this well-studied model of muscle development and that it can improve transcriptome-based genome annotation

Detección de interacciones genéticas asociadas a enfermedades complejas. Aplicación al cáncer de vejiga

El proyecto en el que he participado se engloba dentro del Estudio Español de Cáncer de Vejiga/EPICURO, que comenzó en 1997 con el propósito de avanzar en el conocimiento de este cáncer respecto a las causas genéticas y ambientales, prevención, prognosis y tratamiento, y que aglutina esfuerzos de distintos grupos de nvestigación. El proyecto está coordinado por Núria Malats, jefa del Grupo de Epidemiología Genética y Molecular del CNIO (Centro Nacional de Investigaciones Oncológicas) y es uno de los mayores estudios sobre cáncer de vejiga que se han realizado. Sus objetivos principales son: (a) analizar el riesgo al cáncer de vejiga en relación a factores de susceptibilidad genética, tabaco, ocupación, exposiciones ambientales, dieta, drogas e historial médico; y (b) identi car marcadores moleculares que permitan pronosticar el cáncer de vejiga

Use of Large, Immunosignature Databases to Pose New Questions About Infection and Health Status

abstract: Immunosignature is a technology that retrieves information from the immune system. The technology is based on microarrays with peptides chosen from random sequence space. My thesis focuses on improving the Immunosignature platform and using Immunosignatures to improve diagnosis for diseases. I first contributed to the optimization of the immunosignature platform by introducing scoring metrics to select optimal parameters, considering performance as well as practicality. Next, I primarily worked on identifying a signature shared across various pathogens that can distinguish them from the healthy population. I further retrieved consensus epitopes from the disease common signature and proposed that most pathogens could share the signature by studying the enrichment of the common signature in the pathogen proteomes. Following this, I worked on studying cancer samples from different stages and correlated the immune response with whether the epitope presented by tumor is similar to the pathogen proteome. An effective immune response is defined as an antibody titer increasing followed by decrease, suggesting elimination of the epitope. I found that an effective immune response usually correlates with epitopes that are more similar to pathogens. This suggests that the immune system might occupy a limited space and can be effective against only certain epitopes that have similarity with pathogens. I then participated in the attempt to solve the antibiotic resistance problem by developing a classification algorithm that can distinguish bacterial versus viral infection. This algorithm outperforms other currently available classification methods. Finally, I worked on the concept of deriving a single number to represent all the data on the immunosignature platform. This is in resemblance to the concept of temperature, which is an approximate measurement of whether an individual is healthy. The measure of Immune Entropy was found to work best as a single measurement to describe the immune system information derived from the immunosignature. Entropy is relatively invariant in healthy population, but shows significant differences when comparing healthy donors with patients either infected with a pathogen or have cancer.Dissertation/ThesisDoctoral Dissertation Molecular and Cellular Biology 201

Papel y regulación de las nuevas variantes de splicing sst5TMD4 e In1-ghrelina en cáncer de mama

El cáncer, en sus múltiples formas, es uno de los mayores retos a los que se enfrenta la sociedad actual. Una de las mayores limitaciones en la investigación del cáncer es la gran heterogeneidad existente entre las diferentes patologías tumorales e incluso entre pacientes con un mismo tipo de cáncer. A pesar de esto, estudios recientes han definido un conjunto de características comunes compartidas por los diferentes tipos de cáncer entre los que se encuentran la alteración del splicing alternativo. En concreto, el splicing alternativo es un mecanismo molecular por el que los organismos eucariotas pueden aumentar exponencialmente la cantidad de transcritos diferentes partiendo de un mismo genoma, a través de la reorganización de los diferentes elementos (exones e intrones) que componen los genes. Entre las diferentes patologías tumorales, llama especialmente la atención el cáncer de mama ya que constituye uno de los tipos de cáncer más importante en términos de incidencia tumoral pero también en términos de mortalidad [1]. Este tipo de cáncer también se caracteriza por una desregulación de los procesos de splicing alternativo y, por lo tanto, por un perfil alterado de ciertas variantes de splicing. Así, nuestro grupo de investigación ha identificado la presencia de determinadas variantes de splicing de los ejes neuroendocrinos constituidos por las hormonas somatostatina (SST), cortistatina (CORT) y ghrelina y sus receptores (ssts y GHSRs), especialmente la variante de splicing In1-ghrelina y el receptor truncado sst5TMD4, en este tipo de patologías. En concreto, la variante de splicing del receptor 5 de SST denominada sst5TMD4 codifica un receptor truncado de 4 dominios transmembrana (TMDs) que está sobreexpresado en diversos tipos tumorales (tumores hipofisarios y neuroendocrinos, así como en cáncer de tiroides y de mama), mientras que su expresión en tejidos sanos es muy reducida o nula. Además, la expresión del sst5TMD4 en estas patologías se asocia con una mayor malignidad tumoral, con una menor respuesta al tratamiento con análogos de SST y con un peor pronóstico clínico. Por otro lado, la In1-ghrelina, descubierta recientemente por nuestro grupo y que se genera gracias a un proceso de retención intrónica, presenta importantes implicaciones patológicas en tumores hipofisarios, neuroendocrinos y de mama donde se ha encontrado sobreexpresada y asociada a procesos de malignización tumoral. Sin embargo, los mecanismos moleculares implicados en la regulación de la expresión de sst5TMD4 e In1-ghrelina, así como el papel preciso y las implicaciones clínicas de estas variantes de splicing en cáncer de mama no se han explorado aún con suficiente detalle. Por este motivo, el objetivo principal de esta Tesis Doctoral era profundizar en el conocimiento de los sistemas y/o mecanismos de regulación que determinan la expresión diferencial de las variantes de splicing sst5TMD4 e In1-ghrelina, así como el papel y las implicaciones clínicas que ambas variantes juegan en la fisiopatología del cáncer de mama. Para alcanzar este objetivo general se planteó el estudio de estas variantes de splicing desde una perspectiva multidisciplinar que incluyera estudios sobre muestras humanas, modelos preclínicos de ratón, líneas celulares y aproximaciones moleculares in vitro e in silico

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

New insights into alternative splicing using microarray technology

Tese de doutoramento, Ciências Biomédicas (Ciências Morfológicas), Universidade de Lisboa, Faculdade de Medicina, 2010Disponível no documentoFundação para a Ciência e a Tecnologia (SFRH/ BD/22825/2005