DISSECTION OF THE MOLECULAR PATHWAYS INVOLVED IN PANCREATIC CANCER INITIATION AND PROGRESSION WITH A NOVEL IN VIVO APPROACH

We have seen great advances in our knowledge of the genetic regulation of various cancers in recent years, thanks in large part to large-scale genome sequencing efforts. As we catalogue and characterize the genomic aberrations associated with cancers with increasing detail and accuracy, we are faced with the challenge of having to cull bystanders from biologically active drivers and establish relevant disease context in which these drivers are rate-limiting. To address this challenge, we have adapted a loss-of-function screening approach to function in the context of an intact tumor microenvironment using patient-derived xenografts that more faithfully recapitulate the human disease compared to established cell lines. Due to the relevant genetic heterogeneity between human tumors with the same clinico-pathological indications, we have integrated independent screening approaches in a flexible platform for the interrogation of patient-derived samples as well as genetically-defined mouse models in exactly the same experimental conditions. The goal of this platform is to identify context-specific genetic vulnerabilities and translate these findings into drug discovery opportunities. As proof of concept for this approach, we describe the development of an in vivo loss-of-function screen to systematically interrogate epigenetic dependencies in pancreatic ductal adenocarcinoma (PDAC). In addition to the well-known genetic alterations (Kras, TP53, CDKN2A/p16, SMAD4), some epigenetic mechanisms demonstrated to play a central role in PDAC evolution and progression. The screening system utilizes tumor cells isolated from low-passage PDAC xenografted tissue and a lentiviral library of pooled shRNAs targeting 236 potentially \u201ddruggable\u201d epigenetic regulators. The custom-designed shRNA library (10 shRNAs per gene) was engineered with unique molecular barcodes that allow quantitation of each clone by massively parallel sequencing. Hairpins are clustered according to their depletion or enrichment in comparison to a control population before transplantation. To date, we have completed a total of 5 in vivo screens using diverse PDAC target cell models that have informed on novel epigenetic dependencies. So far, the main limitation for the systematic exploitation of in vivo loss-of-function screens to identify specific patient vulnerabilities come from the limited number of human cells contributing to tumor establishment in a transplantation setting. The frequency of these tumors initiating cells (TICs) is commonly estimated by time-consuming limiting dilution assays and may consistently vary between different tumor origins. With this in mind, we have integrated in our platform a system based on scrambled barcoded libraries that allows to directly assess the required coverage of screening libraries in each model and adjust the shRNA screens for this factor. Our coverage study demonstrated to be a powerful tool to identify the minimal number of cells/barcode required to sustain a complex library in transplantation assay and at the same time a step forward to personalize the in vivo screening patient by patient. We optimized a comprehensive data analytics pipeline and developed a high-throughput validation scheme to triage "hits" that emerge from each screen. The most potent "hits" have been enrolled in both functional and clinico-pathological validation studies to determine the highest priority targets for this devastating disease. Significantly, different components of the COMPASS histone H3 Lys4 (H3K4) methyltransferase complexes were identified as candidates in our screens. COMPASS and COMPASS-like complexes are characterized by unique subunits composition, whose identities provide insight into the different biological functions of these complexes. The methyltransferase unit of the COMPASS complexes is directly involved into the methylation of Lys4 on histone H3, a commonly accepted sign of open-chromatin and active transcription. Chromosomal translocations involving MLL gene are frequent events characterizing the Mixed Lineage Leukemia. In this disease, it has been shown that fusion events with a variety of different partners compromise the MLL methyltransferase activity. However, multiple members of the MLL family could be deregulated via different oncogenic mechanisms in PDAC, as the genetic alteration in MLL2 (amplification) and MLL3 (mutation) suggested. Our platform represents an ideal starting point to understand the COMPASS functionalities. So, a deeper understanding of genes and pathways regulated by each MLL subunit in the context of PDAC is critical to better elucidate the molecular dynamics of this disease and identify additional key points of vulnerability. Our study identified the core different subunits of the COMPASS complexes (WDR5-ASH2L-RBBP5) as broad relevant players in sustain PDAC progression, while the dependency on the MLL subunits appears to be more context-dependent and potentially consequent to specific genetic alterations. Mechanistically, WDR5 functions to sustain proper execution of DNA replication in PDAC cells, as previously suggested by replication stress studies involving MLL1, a critical ATR substrate, and c-Myc, also found to interact with WDR5. By showing that ATR inhibition mimicked the effects of WDR5 suppression, we open up the possibility of testing inhibitors currently in development for activity in this disease. These findings are proposing a new layer of complexities in trapping the COMPASS complexes during tumor development and unmasking unexplored directions for new therapeutical opportunities

Landscape of gene fusions in epithelial cancers: seq and ye shall find

Abstract Enabled by high-throughput sequencing approaches, epithelial cancers across a range of tissue types are seen to harbor gene fusions as integral to their landscape of somatic aberrations. Although many gene fusions are found at high frequency in several rare solid cancers, apart from fusions involving the ETS family of transcription factors which have been seen in approximately 50 % of prostate cancers, several other common solid cancers have been shown to harbor recurrent gene fusions at low frequencies. On the other hand, many gene fusions involving oncogenes, such as those encoding ALK, RAF or FGFR kinase families, have been detected across multiple different epithelial carcinomas. Tumor-specific gene fusions can serve as diagnostic biomarkers or help define molecular subtypes of tumors; for example, gene fusions involving oncogenes such as ERG, ETV1, TFE3, NUT, POU5F1, NFIB, PLAG1, and PAX8 are diagnostically useful. Tumors with fusions involving therapeutically targetable genes such as ALK, RET, BRAF, RAF1, FGFR1–4, and NOTCH1–3 have immediate implications for precision medicine across tissue types. Thus, ongoing cancer genomic and transcriptomic analyses for clinical sequencing need to delineate the landscape of gene fusions. Prioritization of potential oncogenic “drivers” from “passenger” fusions, and functional characterization of potentially actionable gene fusions across diverse tissue types, will help translate these findings into clinical applications. Here, we review recent advances in gene fusion discovery and the prospects for medicine.http://deepblue.lib.umich.edu/bitstream/2027.42/116210/1/13073_2015_Article_252.pd

Priorización de genes y búsqueda de dianas terapéuticas por medio de herramientas informáticas y técnicas de aprendizaje automatizado en cáncer de mama

Programa Oficial de Doutoramento en Tecnoloxías da Información e as Comunicacións. 5032V01Tese por compendio de publicacións[Resumen] El cáncer de mama (CM) es la principal causa de muerte relacionada a neoplasias en mujeres y es el tipo de cáncer más diagnosticado a nivel mundial. CM es una enfermedad heterogénea en donde están envueltos diversos factores como alteraciones genómicas, desregulación de la expresión de proteínas, alteración de cascadas genéticas, desregulación hormonal, determinantes ambientales y etnicidad. A pesar de los grandes avances tecnológicos y científicos en los últimos años, la comprensión de los procesos moleculares, la identificación de nuevas dianas terapéuticas y la predicción de proteínas envueltas inmunoterapia, metástasis, y unión al ARN es indispensable para el desarrollo de fármacos y la aplicación de la medicina de precisión en la práctica clínica. La tesis aquí propuesta plantea el desarrollo de una estrategia consenso altamente eficiente en el reconocimiento de genes y proteínas asociadas al CM; la validación oncológica de dichos genes y proteínas priorizadas mediante la estrategia OncoOmics que consistió en el análisis de bases de datos experimentales de alta relevancia a nivel mundial; la identificación de mutaciones oncogénicas y fármacos indispensables para el desarrollo y aplicación de la medicina de precisión; y la predicción de proteínas de CM asociadas a inmunoterapia, metástasis y unión al ARN mediante diversas herramientas informáticas y métodos de inteligencia artificial. Todos los resultados se publicaron en revistas internacionales de importante factor de impacto.Abstract] Breast cancer (BC) is the leading cause of cancer-related death among women and the most commonly diagnosed cancer worldwide. BC is a heterogeneous disease where genomic alterations, protein expression deregulation, signaling pathway alterations, hormone disruption, ethnicity and environmental determinants are involved. Despite the technological and scientific advances in recent years, an understanding of molecular processes, the identification of new therapeutic targets and the prediction of proteins involved in immunotherapy, metastasis, and RNA binding is essential for drug development and application of precision medicine in clinical practice. The current thesis proposes the development of a high efficient consensus strategy in the recognition of genes and proteins associated with BC; the oncological validation of these prioritized genes and proteins using the OncoOmics strategy, which consisted of the analysis of outstanding experimental databases; the identification of oncogenic mutations and essential drugs for the development and application of precision medicine; and the prediction of BC proteins associated with immunotherapy, metastasis and RNA-binding using bioinformatics tools and artificial intelligence methods. All results were published in international journals with a significant impact factor.[Resumo] O cancro de mama (CM) é a principal causa de morte relacionada con enfermidades malignas en mulleres e é o tipo de cancro máis diagnosticado a nivel mundial. A CM é unha enfermidade heteroxénea onde interveñen varios factores, como alteracións xenómicas, desregulación da expresión proteica, alteración de cascadas xenéticas, desregulación hormonal, determinantes ambientais e etnia. A pesar dos grandes avances tecnolóxicos e científicos dos últimos anos, a comprensión dos procesos moleculares, a identificación de novas dianas terapéuticas e a predición de proteínas implicadas na inmunoterapia, metástase e unión ao ARN é fundamental para o desenvolvemento de fármacos e aplicación da medicina de precisión na práctica clínica. Esta tese propón o desenvolvemento dunha estratexia de consenso altamente eficiente no recoñecemento de xenes e proteínas asociadas a CM; a validación oncolóxica destes xenes e proteínas prioritarias mediante a estratexia OncoOmics, que consistiu na análise de bases de datos experimentais altamente relevantes en todo o mundo; a identificación de mutacións oncogénicas e fármacos esenciais para o desenvolvemento e aplicación da medicina de precisión; e a predición de proteínas CM asociadas á inmunoterapia, metástase e unión ao ARN usando diversas ferramentas informáticas e métodos de intelixencia artificial. Todos os resultados publicáronse en revistas internacionais cun importante factor de impacto

Discovering cancer-associated transcripts by RNA sequencing

High-throughput sequencing of poly-adenylated RNA (RNA-Seq) in human cancers shows remarkable potential to identify uncharacterized aspects of tumor biology, including gene fusions with therapeutic significance and disease markers such as long non-coding RNA (lncRNA) species. However, the analysis of RNA-Seq data places unprecedented demands upon computational infrastructures and algorithms, requiring novel bioinformatics approaches. To meet these demands, we present two new open-source software packages - ChimeraScan and AssemblyLine - designed to detect gene fusion events and novel lncRNAs, respectively. RNA-Seq studies utilizing ChimeraScan led to discoveries of new families of recurrent gene fusions in breast cancers and solitary fibrous tumors. Further, ChimeraScan was one of the key components of the repertoire of computational tools utilized in data analysis for MI-ONCOSEQ, a clinical sequencing initiative to identify potentially informative and actionable mutations in cancer patients’ tumors. AssemblyLine, by contrast, reassembles RNA sequencing data into full-length transcripts ab initio. In head-to-head analyses AssemblyLine compared favorably to existing ab initio approaches and unveiled abundant novel lncRNAs, including antisense and intronic lncRNAs disregarded by previous studies. Moreover, we used AssemblyLine to define the prostate cancer transcriptome from a large patient cohort and discovered myriad lncRNAs, including 121 prostate cancer-associated transcripts (PCATs) that could potentially serve as novel disease markers. Functional studies of two PCATs - PCAT-1 and SChLAP1 - revealed cancer-promoting roles for these lncRNAs. PCAT1, a lncRNA expressed from chromosome 8q24, promotes cell proliferation and represses the tumor suppressor BRCA2. SChLAP1, located in a chromosome 2q31 ‘gene desert’, independently predicts poor patient outcomes, including metastasis and cancer-specific mortality. Mechanistically, SChLAP1 antagonizes the genome-wide localization and regulatory functions of the SWI/SNF chromatin-modifying complex. Collectively, this work demonstrates the utility of ChimeraScan and AssemblyLine as open-source bioinformatics tools. Our applications of ChimeraScan and AssemblyLine led to the discovery of new classes of recurrent and clinically informative gene fusions, and established a prominent role for lncRNAs in coordinating aggressive prostate cancer, respectively. We expect that the methods and findings described herein will establish a precedent for RNA-Seq-based studies in cancer biology and assist the research community at large in making similar discoveries.PHDBioinformaticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120814/1/mkiyer_1.pd

A compendium of mutational cancer driver genes

A fundamental goal in cancer research is to understand the mechanisms of cell transformation. This is key to developing more efficient cancer detection methods and therapeutic approaches. One milestone towards this objective is the identification of all the genes with mutations capable of driving tumours. Since the 1970s, the list of cancer genes has been growing steadily. Because cancer driver genes are under positive selection in tumorigenesis, their observed patterns of somatic mutations across tumours in a cohort deviate from those expected from neutral mutagenesis. These deviations, which constitute signals of positive selection, may be detected by carefully designed bioinformatics methods, which have become the state of the art in the identification of driver genes. A systematic approach combining several of these signals could lead to a compendium of mutational cancer genes. In this Review, we present the Integrative OncoGenomics (IntOGen) pipeline, an implementation of such an approach to obtain the compendium of mutational cancer drivers. Its application to somatic mutations of more than 28,000 tumours of 66 cancer types reveals 568 cancer genes and points towards their mechanisms of tumorigenesis. The application of this approach to the ever-growing datasets of somatic tumour mutations will support the continuous refinement of our knowledge of the genetic basis of cancer