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Abstract Aim Chemoresistance is a major cause of treatment failure in colorectal cancer (CRC) therapy. In this study, the impact of the IGF2BP family of RNA-binding proteins on CRC chemoresistance was investigated using in silico, in vitro, and in vivo approaches. Methods Gene expression data from a well-characterized cohort and publicly available cross-linking immunoprecipitation sequencing (CLIP-Seq) data were collected. Resistance to chemotherapeutics was assessed in patient-derived xenografts (PDXs) and patient-derived organoids (PDOs). Functional studies were performed in 2D and 3D cell culture models, including proliferation, spheroid growth, and mitochondrial respiration analyses. Results We identified IGF2BP2 as the most abundant IGF2BP in primary and metastastatic CRC, correlating with tumor stage in patient samples and tumor growth in PDXs. IGF2BP2 expression in primary tumor tissue was significantly associated with resistance to selumetinib, gefitinib, and regorafenib in PDOs and to 5-fluorouracil and oxaliplatin in PDX in vivo. IGF2BP2 knockout (KO) HCT116 cells were more susceptible to regorafenib in 2D and to oxaliplatin, selumitinib, and nintedanib in 3D cell culture. Further, a bioinformatic analysis using CLIP data suggested stabilization of target transcripts in primary and metastatic tumors. Measurement of oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) revealed a decreased basal OCR and an increase in glycolytic ATP production rate in IGF2BP2 KO. In addition, real-time reverse transcriptase polymerase chain reaction (qPCR) analysis confirmed decreased expression of genes of the respiratory chain complex I, complex IV, and the outer mitochondrial membrane in IGF2BP2 KO cells. Conclusions IGF2BP2 correlates with CRC tumor growth in vivo and promotes chemoresistance by altering mitochondrial respiratory chain metabolism. As a druggable target, IGF2BP2 could be used in future CRC therapy to overcome CRC chemoresistance.

Abstract Our lives (and deaths) have by now been dominated for two years by COVID-19, a pandemic that has caused hundreds of millions of disease cases, millions of deaths, trillions in economic costs, and major restrictions on our freedom. Here we suggest a novel tool for controlling the COVID-19 pandemic. The key element is a method for a population-scale PCR-based testing, applied on a systematic and repeated basis. For this we have developed a low cost, highly sensitive virus-genome-based test. Using Germany as an example, we demonstrate by using a mathematical model, how useful this strategy could have been in controlling the pandemic. We show using real-world examples how this might be implemented on a mass scale and discuss the feasibility of this approach.

Abstract Background Artificial intelligence (AI) has the potential to transform our healthcare systems significantly. New AI technologies based on machine learning approaches should play a key role in clinical decision-making in the future. However, their implementation in health care settings remains limited, mostly due to a lack of robust validation procedures. There is a need to develop reliable assessment frameworks for the clinical validation of AI. We present here an approach for assessing AI for predicting treatment response in triple-negative breast cancer (TNBC), using real-world data and molecular -omics data from clinical data warehouses and biobanks. Methods The European “ITFoC (Information Technology for the Future Of Cancer)” consortium designed a framework for the clinical validation of AI technologies for predicting treatment response in oncology. Results This framework is based on seven key steps specifying: (1) the intended use of AI, (2) the target population, (3) the timing of AI evaluation, (4) the datasets used for evaluation, (5) the procedures used for ensuring data safety (including data quality, privacy and security), (6) the metrics used for measuring performance, and (7) the procedures used to ensure that the AI is explainable. This framework forms the basis of a validation platform that we are building for the “ITFoC Challenge”. This community-wide competition will make it possible to assess and compare AI algorithms for predicting the response to TNBC treatments with external real-world datasets. Conclusions The predictive performance and safety of AI technologies must be assessed in a robust, unbiased and transparent manner before their implementation in healthcare settings. We believe that the consideration of the ITFoC consortium will contribute to the safe transfer and implementation of AI in clinical settings, in the context of precision oncology and personalized care.

Summary: Secondary infections contribute significantly to covid-19 mortality but driving factors remain poorly understood. Autopsies of 20 covid-19 cases and 14 controls from the first pandemic wave complemented with microbial cultivation and RNA-seq from lung tissues enabled description of major organ pathologies and specification of secondary infections. Lethal covid-19 segregated into two main death causes with either dominant diffuse alveolar damage (DAD) or secondary pneumonias. The lung microbiome in covid-19 showed a reduced biodiversity and increased prototypical bacterial and fungal pathogens in cases of secondary pneumonias. RNA-seq distinctly mirrored death causes and stratified DAD cases into subgroups with differing cellular compositions identifying myeloid cells, macrophages and complement C1q as strong separating factors suggesting a pathophysiological link. Together with a prominent induction of inhibitory immune-checkpoints our study highlights profound alterations of the lung immunity in covid-19 wherein a reduced antimicrobial defense likely drives development of secondary infections on top of SARS-CoV-2 infection.

Abstract Background For large international research consortia, such as those funded by the European Union’s Horizon 2020 programme or the Innovative Medicines Initiative, good data coordination practices and tools are essential for the successful collection, organization and analysis of the resulting data. Research consortia are attempting ever more ambitious science to better understand disease, by leveraging technologies such as whole genome sequencing, proteomics, patient-derived biological models and computer-based systems biology simulations. Results The IMI eTRIKS consortium is charged with the task of developing an integrated knowledge management platform capable of supporting the complexity of the data generated by such research programmes. In this paper, using the example of the OncoTrack consortium, we describe a typical use case in translational medicine. The tranSMART knowledge management platform was implemented to support data from observational clinical cohorts, drug response data from cell culture models and drug response data from mouse xenograft tumour models. The high dimensional (omics) data from the molecular analyses of the corresponding biological materials were linked to these collections, so that users could browse and analyse these to derive candidate biomarkers. Conclusions In all these steps, data mapping, linking and preparation are handled automatically by the tranSMART integration platform. Therefore, researchers without specialist data handling skills can focus directly on the scientific questions, without spending undue effort on processing the data and data integration, which are otherwise a burden and the most time-consuming part of translational research data analysis.

Abstract Background Non-small cell lung cancer (NSCLC) is the most common cause of cancer-related deaths worldwide and is primarily treated with radiation, surgery, and platinum-based drugs like cisplatin and carboplatin. The major challenge in the treatment of NSCLC patients is intrinsic or acquired resistance to chemotherapy. Molecular markers predicting the outcome of the patients are urgently needed. Methods Here, we employed patient-derived xenografts (PDXs) to detect predictive methylation biomarkers for platin-based therapies. We used MeDIP-Seq to generate genome-wide DNA methylation profiles of 22 PDXs, their parental primary NSCLC, and their corresponding normal tissues and complemented the data with gene expression analyses of the same tissues. Candidate biomarkers were validated with quantitative methylation-specific PCRs (qMSP) in an independent cohort. Results Comprehensive analyses revealed that differential methylation patterns are highly similar, enriched in PDXs and lung tumor-specific when comparing differences in methylation between PDXs versus primary NSCLC. We identified a set of 40 candidate regions with methylation correlated to carboplatin response and corresponding inverse gene expression pattern even before therapy. This analysis led to the identification of a promoter CpG island methylation of LDL receptor-related protein 12 (LRP12) associated with increased resistance to carboplatin. Validation in an independent patient cohort (n = 35) confirmed that LRP12 methylation status is predictive for therapeutic response of NSCLC patients to platin therapy with a sensitivity of 80% and a specificity of 84% (p

Abstract Existing methods for paired antibody heavy- and light-chain repertoire sequencing rely on specialized equipment and are limited by their commercial availability and high costs. Here, we report a novel simple and cost-effective emulsion-based single-cell paired antibody repertoire sequencing method that employs only basic laboratory equipment. We performed a proof-of-concept using mixed mouse hybridoma cells and we also showed that our method can be used for discovery of novel antigen-specific monoclonal antibodies by sequencing human CD19+ B cell IgM and IgG repertoires isolated from peripheral whole blood before and seven days after Td (Tetanus toxoid/Diphtheria toxoid) booster immunization. We anticipate broad applicability of our method for providing insights into adaptive immune responses associated with various diseases, vaccinations, and cancer immunotherapies.

Summary: Colon cancer is a heterogeneous tumor driven by a subpopulation of cancer stem cells (CSCs). To study CSCs in colon cancer, we used limiting dilution spheroid and serial xenotransplantation assays to functionally define the frequency of CSCs in a panel of patient-derived cancer organoids. These studies demonstrated cancer organoids to be enriched for CSCs, which varied in frequency between tumors. Whole-transcriptome analysis identified WNT and Hedgehog signaling components to be enhanced in CSC-enriched tumors and in aldehyde dehydrogenase (ALDH)-positive CSCs. Canonical GLI-dependent Hedgehog signaling is a negative regulator of WNT signaling in normal intestine and intestinal tumors. Here, we show that Hedgehog signaling in colon CSCs is autocrine SHH-dependent, non-canonical PTCH1 dependent, and GLI independent. In addition, using small-molecule inhibitors and RNAi against SHH-palmitoylating Hedgehog acyltransferase (HHAT), we demonstrate that non-canonical Hedgehog signaling is a positive regulator of WNT signaling and required for colon CSC survival. : Colon cancer is a heterogeneous tumor driven by a subpopulation(s) of therapy-resistant cancer stem cells (CSCs). Regan et al. use 3D culture models to demonstrate that CSC survival is regulated by non-canonical, SHH-dependent, PTCH1-dependent Hedgehog signaling, which acts as a positive regulator of WNT signaling to block CSC differentiation. Keywords: WNT pathway, non-canonical Hedgehog signaling, cancer stem cell, colon cancer, cancer organoid, PTCH1, HHAT, SHH

The heterogeneity of colorectal cancer has important clinical and therapeutic implications. Here the authors analysed the responses of a large biobank of organoids and xenografts derived from colorectal patients to a panel of clinically relevant therapeutic agents to identify genes signatures associated with drug response.

Despite the increasing use of humanized mouse models to study new approaches of graft-versus-host disease (GVHD) prevention, the pathogenesis of xenogeneic GVHD (xGVHD) in these models remains misunderstood. The aim of this study is to describe this pathogenesis in NOD/LtSz-PrkdcscidIL2rγtm1Wjl (NSG) mice infused with human PBMCs and to assess the impact of the expression of HLA-A0201 by NSG mice cells (NSG-HLA-A2/HHD mice) on xGVHD and graft-versus-leukemia (GvL) effects, by taking advantage of next-generation technologies. We found that T cells recovered from NSG mice after transplantation had upregulated expression of genes involved in cell proliferation, as well as in TCR, co-stimulatory, IL-2/STAT5, mTOR and Aurora kinase A pathways. T cells had mainly an effector memory or an effector phenotype and exhibited a Th1/Tc1-skewed differentiation. TCRβ repertoire diversity was markedly lower both in the spleen and lungs (a xGVHD target organ) than at infusion. There was no correlation between the frequencies of specific clonotypes at baseline and in transplanted mice. Finally, expression of HLA-A0201 by NSG mice led to more severe xGVHD and enhanced GvL effects toward HLA-A2+ leukemic cells. Altogether our data demonstrate that the pathogenesis of xGVHD shares important features with human GVHD and that NSG-HLA-A2/HHD mice could serve as better model to study GVHD and GvL effects.

We investigated to which extent polymorphisms of an individual affect the proteomic network. Consomic mouse strains (CS) were used to study the trans-effect of the cis-variant (polymorphic) proteins of the strain PWD/Ph on the proteins of the host strain C57BL/6J. The cardiac proteome of ten CSs was analyzed by 2-DE and MS. Cis-variant PWD proteins altered a high number of C57BL/6J proteins, but the number of trans-variant proteins differed considerably between different CSs. Cardiac hypertrophy was induced in CSs. We found that high variability of the proteome, as induced by polymorphisms in CS14, acts protective against the complex disease.

Combined transcriptome and whole genome sequencing of the same ultra-low input sample down to single cells is a rapidly evolving approach for the analysis of rare cells. Besides stem cells, rare cells originating from tissues like tumor or biopsies, circulating tumor cells and cells from early embryonic development are under investigation. Herein we describe a universal method applicable for the analysis of minute amounts of sample material (150 to 200 cells) derived from sub-colony structures from human embryonic stem cells. The protocol comprises the combined isolation and separate amplification of poly(A) mRNA and whole genome DNA followed by next generation sequencing. Here we present a detailed description of the method developed and an overview of the results obtained for RNA and whole genome sequencing of human embryonic stem cells, sequencing data is available in the Gene Expression Omnibus (GEO) database under accession number GSE69471.

Congenital Cytomegalovirus infection (cCMV) is the leading infection in determining permanent long-term impairments (LTI), and its pathogenesis is largely unknown due to the complex interplay between viral, maternal, placental, and child factors. The cellular activity, considered to be the result of the response to exogenous and endogenous factors, is captured by the determination of gene expression profiles. In this study, we determined whole blood transcriptomes in relation to cCMV, CMV viral load and LTI development at 6 years of age by using RNA isolated from neonatal dried blood spots (DBS) stored at room temperature for 8 years. As DBS were assumed to mainly reflect the neonatal immune system, particular attention was given to the immune pathways using the global test. Additionally, differential expression of individual genes was performed using the voom/limma function packages. We demonstrated feasibility of RNA sequencing from archived neonatal DBS of children with cCMV, and non-infected controls, in relation to LTI and CMV viral load. Despite the lack of statistical power to detect individual genes differences, pathway analysis suggested the involvement of innate immune response with higher CMV viral loads, and of anti-inflammatory markers in infected children that did not develop LTI. Finally, the T cell exhaustion observed in infected neonates, in particular with higher viral load, did not correlate with LTI, therefore other mechanisms are likely to be involved in the long-term immune dysfunction. Despite these data demonstrate limitation in determining prognostic markers for LTI by means of transcriptome analysis, this exploratory study represents a first step in unraveling the pathogenesis of cCMV, and the aforementioned pathways certainly merit further evaluation.

Every patient and every disease is different. Each patient therefore requires a personalized treatment approach. For technical reasons, a personalized approach is feasible for treatment strategies such as surgery, but not for drug-based therapy or drug development. The development of individual mechanistic models of the disease process in every patient offers the possibility of attaining truly personalized drug-based therapy and prevention. The concept of virtual clinical trials and the integrated use of in silico, in vitro, and in vivo models in preclinical development could lead to significant gains in efficiency and order of magnitude increases in the cost effectiveness of drug development and approval. We have developed mechanistic computational models of large-scale cellular signal transduction networks for prediction of drug effects and functional responses, based on patient-specific multi-level omics profiles. However, a major barrier to the use of such models in a clinical and developmental context is the reliability of predictions. Here we detail how the approach of using “models of models” has the potential to impact cancer treatment and drug development. We describe the iterative refinement process that leverages the flexibility of experimental systems to generate highly dimensional data, which can be used to train and validate computational model parameters and improve model predictions. In this way, highly optimized computational models with robust predictive capacity can be generated. Such models open up a number of opportunities for cancer drug treatment and development, from enhancing the design of experimental studies, reducing costs, and improving animal welfare, to increasing the translational value of results generated.

A central challenge in pharmaceutical research is to investigate genetic variation in response to drugs. The Collaborative Cross (CC) mouse reference population is a promising model for pharmacogenomic studies because of its large amount of genetic variation, genetic reproducibility, and dense recombination sites. While the CC lines are phenotypically diverse, their genetic diversity in drug disposition processes, such as detoxification reactions, is still largely uncharacterized. Here we systematically measured RNA-sequencing expression profiles from livers of 29 CC lines under baseline conditions. We then leveraged a reference collection of metabolic biotransformation pathways to map potential relations between drugs and their underlying expression quantitative trait loci (eQTLs). By applying this approach on proximal eQTLs, including eQTLs acting on the overall expression of genes and on the expression of particular transcript isoforms, we were able to construct the organization of hepatic eQTL-drug connectivity across the CC population. The analysis revealed a substantial impact of genetic variation acting on drug biotransformation, allowed mapping of potential joint genetic effects in the context of individual drugs, and demonstrated crosstalk between drug metabolism and lipid metabolism. Our findings provide a resource for investigating drug disposition in the CC strains, and offer a new paradigm for integrating biotransformation reactions to corresponding variations in DNA sequences.

Since the introduction of next-generation sequencing, several techniques have been developed to selectively enrich and sequence specific parts of the genome at high coverage. These techniques include enzymatic methods employing molecular inversion probes, PCR based approaches, hybrid capture, and in-solution capture. In-solution capture employs RNA probes transcribed from a pool of DNA template oligos designed to match regions of interest to specifically bind and enrich genomic DNA fragments. This method is highly efficient, especially if genomic target regions are large in size or quantity. Diverse in-solution capture kits are available, but are costly when large sample numbers need to be analyzed. Here we present a cost-effective strategy for the design of custom DNA libraries, their transcription into RNA libraries, and application for in-solution capture. We show the efficacy by comparing the method to a commercial kit and further demonstrate that emulsion PCR can be used for bias free amplification and virtual immortalization of DNA template libraries.

Despite a growing body of knowledge on the mechanisms underlying the onset and progression of cancer, treatment success rates in oncology are at best modest. Current approaches use statistical methods that fail to embrace the inherent and expansive complexity of the tumor/patient/drug interaction. Computational modeling, in particular mechanistic modeling, has the power to resolve this complexity. Using fundamental knowledge on the interactions occurring between the components of a complex biological system, large-scale in silico models with predictive capabilities can be generated. Here, we describe how mechanistic virtual patient models, based on systematic molecular characterization of patients and their diseases, have the potential to shift the theranostic paradigm for oncology, both in the fields of personalized medicine and targeted drug development. In particular, we highlight the mechanistic modeling platform ModCell™ for individualized prediction of patient responses to treatment, emphasizing modeling techniques and avenues of application.

BackgroundLarge-scale genomic analyses of patient cohorts have revealed extensive heterogeneity between individual tumors, contributing to treatment failure and drug resistance. In malignant melanoma, heterogeneity is thought to arise as a consequence of the differentiation of melanoma-initiating cells that are defined by cell-surface markers like CD271 or CD133.ResultsHere we confirmed that the nerve growth factor receptor (CD271) is a crucial determinant of tumorigenicity, stem-like properties, heterogeneity and plasticity in melanoma cells. Stable shRNA mediated knock-down of CD271 in patient-derived melanoma cells abrogated their tumor-initiating and colony-forming capacity. A genome-wide expression profiling and gene-set enrichment analysis revealed novel connections of CD271 with melanoma-associated genes like CD133 and points to a neural crest stem cell (NCSC) signature lost upon CD271 knock-down. In a meta-analysis we have determined a shared set of 271 differentially regulated genes, linking CD271 to SOX10, a marker that specifies the neural crest. To dissect the connection of CD271 and CD133 we have analyzed 10 patient-derived melanoma-cell strains for cell-surface expression of both markers compared to established cell lines MeWo and A375. We found CD271+ cells in the majority of cell strains analyzed as well as in a set of 16 different patient-derived melanoma metastases. Strikingly, only 2/12 cell strains harbored a CD133+ sub-set that in addition comprised a fraction of cells of a CD271+/CD133+ phenotype. Those cells were found in the label-retaining fraction and in vitro deduced from CD271+ but not CD271 knock-down cells.ConclusionsOur present study provides a deeper insight into the regulation of melanoma cell properties and points CD271 out as a regulator of several melanoma-associated genes. Further, our data strongly suggest that CD271 is a crucial determinant of stem-like properties of melanoma cells like colony-formation and tumorigenicity.

BACKGROUND:Non-alcoholic fatty liver disease (NAFLD) has a broad spectrum of disease states ranging from mild steatosis characterized by an abnormal retention of lipids within liver cells to steatohepatitis (NASH) showing fat accumulation, inflammation, ballooning and degradation of hepatocytes, and fibrosis. Ultimately, steatohepatitis can result in liver cirrhosis and hepatocellular carcinoma. METHODOLOGY AND RESULTS:In this study we have analyzed three different mouse strains, A/J, C57BL/6J, and PWD/PhJ, that show different degrees of steatohepatitis when administered a 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) containing diet. RNA-Seq gene expression analysis, protein analysis and metabolic profiling were applied to identify differentially expressed genes/proteins and perturbed metabolite levels of mouse liver samples upon DDC-treatment. Pathway analysis revealed alteration of arachidonic acid (AA) and S-adenosylmethionine (SAMe) metabolism upon other pathways. To understand metabolic changes of arachidonic acid metabolism in the light of disease expression profiles a kinetic model of this pathway was developed and optimized according to metabolite levels. Subsequently, the model was used to study in silico effects of potential drug targets for steatohepatitis. CONCLUSIONS:We identified AA/eicosanoid metabolism as highly perturbed in DDC-induced mice using a combination of an experimental and in silico approach. Our analysis of the AA/eicosanoid metabolic pathway suggests that 5-hydroxyeicosatetraenoic acid (5-HETE), 15-hydroxyeicosatetraenoic acid (15-HETE) and prostaglandin D2 (PGD2) are perturbed in DDC mice. We further demonstrate that a dynamic model can be used for qualitative prediction of metabolic changes based on transcriptomics data in a disease-related context. Furthermore, SAMe metabolism was identified as being perturbed due to DDC treatment. Several genes as well as some metabolites of this module show differences between A/J and C57BL/6J on the one hand and PWD/PhJ on the other.

Hybridization-based target enrichment protocols require relatively large starting amounts of genomic DNA, which is not always available. Here, we tested three approaches to pre-capture library preparation starting from 10 ng of genomic DNA: (i and ii) whole-genome amplification of DNA samples with REPLI-g (Qiagen) and GenomePlex (Sigma) kits followed by standard library preparation, and (iii) library construction with a low input oriented ThruPLEX kit (Rubicon Genomics). Exome capture with Agilent SureSelectXT2 Human AllExon v4+UTRs capture probes, and HiSeq2000 sequencing were performed for test libraries along with the control library prepared from 1 µg of starting DNA. Tested protocols were characterized in terms of mapping efficiency, enrichment ratio, coverage of the target region, and reliability of SNP genotyping. REPLI-g- and ThruPLEX-FD-based protocols seem to be adequate solutions for exome sequencing of low input samples.

Overexpression of ERG transcription factor due to genomic ERG-rearrangements defines a separate molecular subtype of prostate tumors. One of the consequences of ERG accumulation is modulation of the cell's gene expression profile. Tudor domain-containing protein 1 gene (TDRD1) was reported to be differentially expressed between TMPRSS2:ERG-negative and TMPRSS2:ERG-positive prostate cancer. The aim of our study was to provide a mechanistic explanation for the transcriptional activation of TDRD1 in ERG rearrangement-positive prostate tumors.Gene expression measurements by real-time quantitative PCR revealed a remarkable co-expression of TDRD1 and ERG (r(2) = 0.77) but not ETV1 (r(2)

Aberrant activation of Hedgehog (HH) signaling has been identified as a key etiologic factor in many human malignancies. Signal strength, target gene specificity, and oncogenic activity of HH signaling depend profoundly on interactions with other pathways, such as epidermal growth factor receptor-mediated signaling, which has been shown to cooperate with HH/GLI in basal cell carcinoma and pancreatic cancer. Our experimental data demonstrated that the Daoy human medulloblastoma cell line possesses a fully inducible endogenous HH pathway. Treatment of Daoy cells with Sonic HH or Smoothened agonist induced expression of GLI1 protein and simultaneously prevented the processing of GLI3 to its repressor form. To study interactions between HH- and EGF-induced signaling in greater detail, time-resolved measurements were carried out and analyzed at the transcriptomic and proteomic levels. The Daoy cells responded to the HH/EGF co-treatment by downregulating GLI1, PTCH, and HHIP at the transcript level; this was also observed when Amphiregulin (AREG) was used instead of EGF. We identified a novel crosstalk mechanism whereby EGFR signaling silences proteins acting as negative regulators of HH signaling, as AKT- and ERK-signaling independent process. EGFR/HH signaling maintained high GLI1 protein levels which contrasted the GLI1 downregulation on the transcript level. Conversely, a high-level synergism was also observed, due to a strong and significant upregulation of numerous canonical EGF-targets with putative tumor-promoting properties such as MMP7, VEGFA, and IL-8. In conclusion, synergistic effects between EGFR and HH signaling can selectively induce a switch from a canonical HH/GLI profile to a modulated specific target gene profile. This suggests that there are more wide-spread, yet context-dependent interactions, between HH/GLI and growth factor receptor signaling in human malignancies.

Aberrant CpG methylation is a universal epigenetic trait of cancer cell genomes. However, human cancer samples or cell lines preclude the investigation of epigenetic changes occurring early during tumour development. Here, we have used MeDIP-seq to analyse the DNA methylome of APC(Min) adenoma as a model for intestinal cancer initiation, and we present a list of more than 13,000 recurring differentially methylated regions (DMRs) characterizing intestinal adenoma of the mouse. We show that Polycomb Repressive Complex (PRC) targets are strongly enriched among hypermethylated DMRs, and several PRC2 components and DNA methyltransferases were up-regulated in adenoma. We further demonstrate by bisulfite pyrosequencing of purified cell populations that the DMR signature arises de novo in adenoma cells rather than by expansion of a pre-existing pattern in intestinal stem cells or undifferentiated crypt cells. We found that epigenetic silencing of tumour suppressors, which occurs frequently in colon cancer, was rare in adenoma. Quite strikingly, we identified a core set of DMRs, which is conserved between mouse adenoma and human colon cancer, thus possibly revealing a global panel of epigenetically modified genes for intestinal tumours. Our data allow a distinction between early conserved epigenetic alterations occurring in intestinal adenoma and late stochastic events promoting colon cancer progression, and may facilitate the selection of more specific clinical epigenetic biomarkers.

MiRNAs are discussed as diagnostic and therapeutic molecules. However, effective miRNA drug treatments with miRNAs are, so far, hampered by the complexity of the miRNA networks. To identify potential miRNA drugs in colorectal cancer, we profiled miRNA and mRNA expression in matching normal, tumor and metastasis tissues of eight patients by Illumina sequencing. We validated six miRNAs in a large tissue screen containing 16 additional tumor entities and identified miRNA-1, miRNA-129, miRNA-497 and miRNA-215 as constantly de-regulated within the majority of cancers. Of these, we investigated miRNA-1 as representative in a systems-biology simulation of cellular cancer models implemented in PyBioS and assessed the effects of depletion as well as overexpression in terms of miRNA-1 as a potential treatment option. In this system, miRNA-1 treatment reverted the disease phenotype with different effectiveness among the patients. Scoring the gene expression changes obtained through mRNA-Seq from the same patients we show that the combination of deep sequencing and systems biological modeling can help to identify patient-specific responses to miRNA treatments. We present this data as guideline for future pre-clinical assessments of new and personalized therapeutic options.

More than 800 published genetic association studies have implicated dozens of potential risk loci in Parkinson's disease (PD). To facilitate the interpretation of these findings, we have created a dedicated online resource, PDGene, that comprehensively collects and meta-analyzes all published studies in the field. A systematic literature screen of -27,000 articles yielded 828 eligible articles from which relevant data were extracted. In addition, individual-level data from three publicly available genome-wide association studies (GWAS) were obtained and subjected to genotype imputation and analysis. Overall, we performed meta-analyses on more than seven million polymorphisms originating either from GWAS datasets and/or from smaller scale PD association studies. Meta-analyses on 147 SNPs were supplemented by unpublished GWAS data from up to 16,452 PD cases and 48,810 controls. Eleven loci showed genome-wide significant (P < 5 × 10(-8)) association with disease risk: BST1, CCDC62/HIP1R, DGKQ/GAK, GBA, LRRK2, MAPT, MCCC1/LAMP3, PARK16, SNCA, STK39, and SYT11/RAB25. In addition, we identified novel evidence for genome-wide significant association with a polymorphism in ITGA8 (rs7077361, OR 0.88, P = 1.3 × 10(-8)). All meta-analysis results are freely available on a dedicated online database (www.pdgene.org), which is cross-linked with a customized track on the UCSC Genome Browser. Our study provides an exhaustive and up-to-date summary of the status of PD genetics research that can be readily scaled to include the results of future large-scale genetics projects, including next-generation sequencing studies.

Alternative splicing is a fundamental posttranscriptional mechanism for controlling gene expression, and splicing defects have been linked to various human disorders. The splicing factor FOX-2 is part of a main protein interaction hub in a network related to human inherited ataxias, however, its impact remains to be elucidated. Here, we focused on the reported interaction between FOX-2 and ataxin-1, the disease-causing protein in spinocerebellar ataxia type 1. In this line, we further evaluated this interaction by yeast-2-hybrid analyses and co-immunoprecipitation experiments in mammalian cells. Interestingly, we discovered that FOX-2 localization and splicing activity is affected in the presence of nuclear ataxin-1 inclusions. Moreover, we observed that FOX-2 directly interacts with ataxin-2, a protein modulating spinocerebellar ataxia type 1 pathogenesis. Finally, we provide evidence that splicing of pre-mRNA of ataxin-2 depends on FOX-2 activity, since reduction of FOX-2 levels led to increased skipping of exon 18 in ataxin-2 transcripts. Most striking, we observed that ataxin-1 overexpression has an effect on this splicing event as well. Thus, our results demonstrate that FOX-2 is involved in splicing of ataxin-2 transcripts and that this splicing event is altered by overexpression of ataxin-1.

Paralogs for several proteins implicated in neurodegenerative disorders have been identified and explored to further facilitate the identification of molecular mechanisms contributing to disease pathogenesis. For the disease-causing protein in spinocerebellar ataxia type 2, ataxin-2, a paralog of unknown function, termed ataxin-2-like, has been described. We discovered that ataxin-2-like associates with known interaction partners of ataxin-2, the RNA helicase DDX6 and the poly(A)-binding protein, and with ataxin-2 itself. Furthermore, we found that ataxin-2-like is a component of stress granules. Interestingly, sole ataxin-2-like overexpression led to the induction of stress granules, while a reduction of stress granules was detected in case of a low ataxin-2-like level. Finally, we observed that overexpression of ataxin-2-like as well as its reduction has an impact on the presence of microscopically visible processing bodies. Thus, our results imply a functional overlap between ataxin-2-like and ataxin-2, and further indicate a role for ataxin-2-like in the regulation of stress granules and processing bodies.

The immune system protects us from foreign substances or pathogens by generating specific antibodies. The variety of immunoglobulin (Ig) paratopes for antigen recognition is a result of the V(D)J rearrangement mechanism, while a fast and efficient immune response is mediated by specific immunoglobulin isotypes obtained through class switch recombination (CSR). To get a better understanding on how antibody-based immune protection works and how it changes with age, the interdependency between these two parameters need to be addressed. Here, we have performed an in depth analysis of antibody repertoires of 14 healthy donors representing different gender and age groups. For this task, we developed a unique pyrosequencing approach, which is able to monitor the expression levels of all immunoglobulin V(D)J recombinations of all isotypes including subtypes in an unbiased and quantitative manner. Our results show that donors have individual immunoglobulin repertoires and cannot be clustered according to V(D)J recombination patterns, neither by age nor gender. However, after incorporating isotype-specific analysis and considering CSR information into hierarchical clustering the situation changes. For the first time the donors cluster according to age and separate into young adults and elderly donors (>50). As a direct consequence, this clustering defines the onset of immune senescence at the age of fifty and beyond. The observed age-dependent reduction of CSR ability proposes a feasible explanation why reduced efficacy of vaccination is seen in the elderly and implies that novel vaccine strategies for the elderly should include the "Golden Agers".

Saccharomyces cerevisiae strain W303 is a widely used model organism. However, little is known about its genetic origins, as it was created in the 1970s from crossing yeast strains of uncertain genealogy. To obtain insights into its ancestry and physiology, we sequenced the genome of its variant W303-K6001, a yeast model of ageing research. The combination of two next-generation sequencing (NGS) technologies (Illumina and Roche/454 sequencing) yielded an 11.8 Mb genome assembly at an N50 contig length of 262 kb. Although sequencing was substantially more precise and sensitive than whole-genome tiling arrays, both NGS platforms produced a number of false positives. At a 378× average coverage, only 74 per cent of called differences to the S288c reference genome were confirmed by both techniques. The consensus W303-K6001 genome differs in 8133 positions from S288c, predicting altered amino acid sequence in 799 proteins, including factors of ageing and stress resistance. The W303-K6001 (85.4%) genome is virtually identical (less than equal to 0.5 variations per kb) to S288c, and thus originates in the same ancestor. Non-S288c regions distribute unequally over the genome, with chromosome XVI the most (99.6%) and chromosome XI the least (54.5%) S288c-like. Several of these clusters are shared with Σ1278B, another widely used S288c-related model, indicating that these strains share a second ancestor. Thus, the W303-K6001 genome pictures details of complex genetic relationships between the model strains that date back to the early days of experimental yeast genetics. Moreover, this study underlines the necessity of combining multiple NGS and genome-assembling techniques for achieving accurate variant calling in genomic studies.

MicroRNAs have gained significant interest due to their widespread occurrence and diverse functions as regulatory molecules, which are essential for cell division, growth, development and apoptosis in eukaryotes. The epidermal growth factor receptor (EGFR) signaling pathway is one of the best investigated cellular signaling pathways regulating important cellular processes and its deregulation is associated with severe diseases, such as cancer. In this study, we introduce a systems biological model of the EGFR signaling pathway integrating validated miRNA-target information according to diverse studies, in order to demonstrate essential roles of miRNA within this pathway. The model consists of 1241 reactions and contains 241 miRNAs. We analyze the impact of 100 specific miRNA inhibitors (anit-miRNAs) on this pathway and propose that the embedded miRNA-network can help to identify new drug targets of the EGFR signaling pathway and thereby support the development of new therapeutic strategies against cancer.

Transcription factors are proteins that regulate gene expression by binding to cis-regulatory sequences such as promoters and enhancers. In embryonic stem (ES) cells, binding of the transcription factors OCT4, SOX2 and NANOG is essential to maintain the capacity of the cells to differentiate into any cell type of the developing embryo. It is known that transcription factors interact to regulate gene expression. In this study we show that combinatorial binding is strongly associated with co-localization of the transcriptional co-activator Mediator, H3K27ac and increased expression of nearby genes in embryonic stem cells. We observe that the same loci bound by Oct4, Nanog and Sox2 in ES cells frequently drive expression in early embryonic development. Comparison of mouse and human ES cells shows that less than 5% of individual binding events for OCT4, SOX2 and NANOG are shared between species. In contrast, about 15% of combinatorial binding events and even between 53% and 63% of combinatorial binding events at enhancers active in early development are conserved. Our analysis suggests that the combination of OCT4, SOX2 and NANOG binding is critical for transcription in ES cells and likely plays an important role for embryogenesis by binding at conserved early developmental enhancers. Our data suggests that the fast evolutionary rewiring of regulatory networks mainly affects individual binding events, whereas "gene regulatory hotspots" which are bound by multiple factors and active in multiple tissues throughout early development are under stronger evolutionary constraints.

Ascertaining when and where genes are expressed is of crucial importance to understanding or predicting the physiological role of genes and proteins and how they interact to form the complex networks that underlie organ development and function. It is, therefore, crucial to determine on a genome-wide level, the spatio-temporal gene expression profiles at cellular resolution. This information is provided by colorimetric RNA in situ hybridization that can elucidate expression of genes in their native context and does so at cellular resolution. We generated what is to our knowledge the first genome-wide transcriptome atlas by RNA in situ hybridization of an entire mammalian organism, the developing mouse at embryonic day 14.5. This digital transcriptome atlas, the Eurexpress atlas (http://www.eurexpress.org), consists of a searchable database of annotated images that can be interactively viewed. We generated anatomy-based expression profiles for over 18,000 coding genes and over 400 microRNAs. We identified 1,002 tissue-specific genes that are a source of novel tissue-specific markers for 37 different anatomical structures. The quality and the resolution of the data revealed novel molecular domains for several developing structures, such as the telencephalon, a novel organization for the hypothalamus, and insight on the Wnt network involved in renal epithelial differentiation during kidney development. The digital transcriptome atlas is a powerful resource to determine co-expression of genes, to identify cell populations and lineages, and to identify functional associations between genes relevant to development and disease.

BackgroundSELEX is an iterative process in which highly diverse synthetic nucleic acid libraries are selected over many rounds to finally identify aptamers with desired properties. However, little is understood as how binders are enriched during the selection course. Next-generation sequencing offers the opportunity to open the black box and observe a large part of the population dynamics during the selection process.MethodologyWe have performed a semi-automated SELEX procedure on the model target streptavidin starting with a synthetic DNA oligonucleotide library and compared results obtained by the conventional analysis via cloning and Sanger sequencing with next-generation sequencing. In order to follow the population dynamics during the selection, pools from all selection rounds were barcoded and sequenced in parallel.ConclusionsHigh affinity aptamers can be readily identified simply by copy number enrichment in the first selection rounds. Based on our results, we suggest a new selection scheme that avoids a high number of iterative selection rounds while reducing time, PCR bias, and artifacts.

Somatic cells reprogrammed into induced pluripotent stem cells (iPSCs) acquire features of human embryonic stem cells (hESCs) and thus represent a promising source for cellular therapy of debilitating diseases, such as age-related disorders. However, reprogrammed cell lines have been found to harbor various genomic alterations. In addition, we recently discovered that the mitochondrial DNA of human fibroblasts also undergoes random mutational events upon reprogramming. Aged somatic cells might possess high susceptibility to nuclear and mitochondrial genome instability. Hence, concerns over the oncogenic potential of reprogrammed cells due to the lack of genomic integrity may hinder the applicability of iPSC-based therapies for age-associated conditions. Here, we investigated whether aged reprogrammed cells harboring chromosomal abnormalities show resistance to apoptotic cell death or mitochondrial-associated oxidative stress, both hallmarks of cancer transformation. Four iPSC lines were generated from dermal fibroblasts derived from an 84-year-old woman, representing the oldest human donor so far reprogrammed to pluripotency. Despite the presence of karyotype aberrations, all aged-iPSCs were able to differentiate into neurons, re-establish telomerase activity, and reconfigure mitochondrial ultra-structure and functionality to a hESC-like state. Importantly, aged-iPSCs exhibited high sensitivity to drug-induced apoptosis and low levels of oxidative stress and DNA damage, in a similar fashion as iPSCs derived from young donors and hESCs. Thus, the occurrence of chromosomal abnormalities within aged reprogrammed cells might not be sufficient to over-ride the cellular surveillance machinery and induce malignant transformation through the alteration of mitochondrial-associated cell death. Taken together, we unveiled that cellular reprogramming is capable of reversing aging-related features in somatic cells from a very old subject, despite the presence of genomic alterations. Nevertheless, we believe it will be essential to develop reprogramming protocols capable of safeguarding the integrity of the genome of aged somatic cells, before employing iPSC-based therapy for age-associated disorders.

It is essential to understand the network of transcription factors controlling self-renewal of human embryonic stem cells (ESCs) and human embryonal carcinoma cells (ECs) if we are to exploit these cells in regenerative medicine regimes. Correlating gene expression levels after RNAi-based ablation of OCT4 function with its downstream targets enables a better prediction of motif-specific driven expression modules pertinent for self-renewal and differentiation of embryonic stem cells and induced pluripotent stem cells.We initially identified putative direct downstream targets of OCT4 by employing CHIP-on-chip analysis. A comparison of three peak analysis programs revealed a refined list of OCT4 targets in the human EC cell line NCCIT, this list was then compared to previously published OCT4 CHIP-on-chip datasets derived from both ES and EC cells. We have verified an enriched POU-motif, discovered by a de novo approach, thus enabling us to define six distinct modules of OCT4 binding and regulation of its target genes.A selection of these targets has been validated, like NANOG, which harbours the evolutionarily conserved OCT4-SOX2 binding motif within its proximal promoter. Other validated targets, which do not harbour the classical HMG motif are USP44 and GADD45G, a key regulator of the cell cycle. Over-expression of GADD45G in NCCIT cells resulted in an enrichment and up-regulation of genes associated with the cell cycle (CDKN1B, CDKN1C, CDK6 and MAPK4) and developmental processes (BMP4, HAND1, EOMES, ID2, GATA4, GATA5, ISL1 and MSX1). A comparison of positively regulated OCT4 targets common to EC and ES cells identified genes such as NANOG, PHC1, USP44, SOX2, PHF17 and OCT4, thus further confirming their universal role in maintaining self-renewal in both cell types. Finally we have created a user-friendly database (http://biit.cs.ut.ee/escd/), integrating all OCT4 and stem cell related datasets in both human and mouse ES and EC cells.In the current era of systems biology driven research, we envisage that our integrated embryonic stem cell database will prove beneficial to the booming field of ES, iPS and cancer research.

BACKGROUND: Colorectal cancer (CRC) is with approximately 1 million cases the third most common cancer worldwide. Extensive research is ongoing to decipher the underlying genetic patterns with the hope to improve early cancer diagnosis and treatment. In this direction, the recent progress in next generation sequencing technologies has revolutionized the field of cancer genomics. However, one caveat of these studies remains the large amount of genetic variations identified and their interpretation. METHODOLOGY/PRINCIPAL FINDINGS: Here we present the first work on whole exome NGS of primary colon cancers. We performed 454 whole exome pyrosequencing of tumor as well as adjacent not affected normal colonic tissue from microsatellite stable (MSS) and microsatellite instable (MSI) colon cancer patients and identified more than 50,000 small nucleotide variations for each tissue. According to predictions based on MSS and MSI pathomechanisms we identified eight times more somatic non-synonymous variations in MSI cancers than in MSS and we were able to reproduce the result in four additional CRCs. Our bioinformatics filtering approach narrowed down the rate of most significant mutations to 359 for MSI and 45 for MSS CRCs with predicted altered protein functions. In both CRCs, MSI and MSS, we found somatic mutations in the intracellular kinase domain of bone morphogenetic protein receptor 1A, BMPR1A, a gene where so far germline mutations are associated with juvenile polyposis syndrome, and show that the mutations functionally impair the protein function. CONCLUSIONS/SIGNIFICANCE: We conclude that with deep sequencing of tumor exomes one may be able to predict the microsatellite status of CRC and in addition identify potentially clinically relevant mutations.

Human amniotic fluid cells (AFCs) are routinely obtained for prenatal diagnostics procedures. Recently, it has been illustrated that these cells may also serve as a valuable model system to study developmental processes and for application in regenerative therapies. Cellular reprogramming is a means of assigning greater value to primary AFCs by inducing self-renewal and pluripotency and, thus, bypassing senescence. Here, we report the generation and characterization of human amniotic fluid-derived induced pluripotent stem cells (AFiPSCs) and demonstrate their ability to differentiate into the trophoblast lineage after stimulation with BMP2/BMP4. We further carried out comparative transcriptome analyses of primary human AFCs, AFiPSCs, fibroblast-derived iPSCs (FiPSCs) and embryonic stem cells (ESCs). This revealed that the expression of key senescence-associated genes are down-regulated upon the induction of pluripotency in primary AFCs (AFiPSCs). By defining distinct and overlapping gene expression patterns and deriving the LARGE (Lost, Acquired and Retained Gene Expression) Principle of Cellular Reprogramming, we could further highlight that AFiPSCs, FiPSCs and ESCs share a core self-renewal gene regulatory network driven by OCT4, SOX2 and NANOG. Nevertheless, these cell types are marked by distinct gene expression signatures. For example, expression of the transcription factors, SIX6, EGR2, PKNOX2, HOXD4, HOXD10, DLX5 and RAXL1, known to regulate developmental processes, are retained in AFiPSCs and FiPSCs. Surprisingly, expression of the self-renewal-associated gene PRDM14 or the developmental processes-regulating genes WNT3A and GSC are restricted to ESCs. Implications of this, with respect to the stability of the undifferentiated state and long-term differentiation potential of iPSCs, warrant further studies.

BACKGROUND: Cancer re-sequencing programs rely on DNA isolated from fresh snap frozen tissues, the preparation of which is combined with additional preservation efforts. Tissue samples at pathology departments are routinely stored as formalin-fixed and paraffin-embedded (FFPE) samples and their use would open up access to a variety of clinical trials. However, FFPE preparation is incompatible with many down-stream molecular biology techniques such as PCR based amplification methods and gene expression studies. METHODOLOGY/PRINCIPAL FINDINGS: Here we investigated the sample quality requirements of FFPE tissues for massively parallel short-read sequencing approaches. We evaluated key variables of pre-fixation, fixation related and post-fixation processes that occur in routine medical service (e.g. degree of autolysis, duration of fixation and of storage). We also investigated the influence of tissue storage time on sequencing quality by using material that was up to 18 years old. Finally, we analyzed normal and tumor breast tissues using the Sequencing by Synthesis technique (Illumina Genome Analyzer, Solexa) to simultaneously localize genome-wide copy number alterations and to detect genomic variations such as substitutions and point-deletions and/or insertions in FFPE tissue samples. CONCLUSIONS/SIGNIFICANCE: The application of second generation sequencing techniques on small amounts of FFPE material opens up the possibility to analyze tissue samples which have been collected during routine clinical work as well as in the context of clinical trials. This is in particular important since FFPE samples are amply available from surgical tumor resections and histopathological diagnosis, and comprise tissue from precursor lesions, primary tumors, lymphogenic and/or hematogenic metastases. Large-scale studies using this tissue material will result in a better prediction of the prognosis of cancer patients and the early identification of patients which will respond to therapy.

Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is a key metabolic regulator implicated in a variety of cellular processes. It functions as a glycolytic enzyme, a protein kinase, and a metabolic switch under oxidative stress. Its enzymatic inactivation causes a major shift in the primary carbohydrate flux. Furthermore, the protein is implicated in regulating transcription, ER-to-Golgi transport, and apoptosis. We found that Saccharomyces cerevisiae cells null for all GAPDH paralogues (Tdh1, Tdh2, and Tdh3) survived the counter-selection of a GAPDH-encoding plasmid when the NAD(+) metabolizing deacetylase Sir2 was overexpressed. This phenotype required a fully functional copy of SIR2 and resulted from hyper-recombination between S. cerevisiae plasmids. In the wild-type background, GAPDH overexpression increased the plasmid recombination rate in a growth-condition dependent manner. We conclude that GAPDH influences yeast episome stability via Sir2 and propose a model for the interplay of Sir2, GAPDH, and the glycolytic flux.

Triosephosphate isomerase (TPI) deficiency is an autosomal recessive disorder caused by various mutations in the gene encoding the key glycolytic enzyme TPI. A drastic decrease in TPI activity and an increased level of its substrate, dihydroxyacetone phosphate, have been measured in unpurified cell extracts of affected individuals. These observations allowed concluding that the different mutations in the TPI alleles result in catalytically inactive enzymes. However, despite a high occurrence of TPI null alleles within several human populations, the frequency of this disorder is exceptionally rare. In order to address this apparent discrepancy, we generated a yeast model allowing us to perform comparative in vivo analyses of the enzymatic and functional properties of the different enzyme variants. We discovered that the majority of these variants exhibit no reduced catalytic activity per se. Instead, we observed, the dimerization behavior of TPI is influenced by the particular mutations investigated, and by the use of a potential alternative translation initiation site in the TPI gene. Additionally, we demonstrated that the overexpression of the most frequent TPI variant, Glu104Asp, which displays altered dimerization features, results in diminished endogenous TPI levels in mammalian cells. Thus, our results reveal that enzyme deregulation attributable to aberrant dimerization of TPI, rather than direct catalytic inactivation of the enzyme, underlies the pathogenesis of TPI deficiency. Finally, we discovered that yeast cells expressing a TPI variant exhibiting reduced catalytic activity are more resistant against oxidative stress caused by the thiol-oxidizing reagent diamide. This observed advantage might serve to explain the high allelic frequency of TPI null alleles detected among human populations.

BACKGROUND: The differential pathophysiologic mechanisms that trigger and maintain the two forms of inflammatory bowel disease (IBD), Crohn disease (CD), and ulcerative colitis (UC) are only partially understood. cDNA microarrays can be used to decipher gene regulation events at a genome-wide level and to identify novel unknown genes that might be involved in perpetuating inflammatory disease progression. METHODS AND FINDINGS: High-density cDNA microarrays representing 33,792 UniGene clusters were prepared. Biopsies were taken from the sigmoid colon of normal controls (n = 11), CD patients (n = 10) and UC patients (n = 10). 33P-radiolabeled cDNA from purified poly(A)+ RNA extracted from biopsies (unpooled) was hybridized to the arrays. We identified 500 and 272 transcripts differentially regulated in CD and UC, respectively. Interesting hits were independently verified by real-time PCR in a second sample of 100 individuals, and immunohistochemistry was used for exemplary localization. The main findings point to novel molecules important in abnormal immune regulation and the highly disturbed cell biology of colonic epithelial cells in IBD pathogenesis, e.g., CYLD (cylindromatosis, turban tumor syndrome) and CDH11 (cadherin 11, type 2). By the nature of the array setup, many of the genes identified were to our knowledge previously uncharacterized, and prediction of the putative function of a subsection of these genes indicate that some could be involved in early events in disease pathophysiology. CONCLUSION: A comprehensive set of candidate genes not previously associated with IBD was revealed, which underlines the polygenic and complex nature of the disease. It points out substantial differences in pathophysiology between CD and UC. The multiple unknown genes identified may stimulate new research in the fields of barrier mechanisms and cell signalling in the context of IBD, and ultimately new therapeutic approaches.