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As several countries gradually release social distancing measures, rapid detection of new localized COVID-19 hotspots and subsequent intervention will be key to avoiding large-scale resurgence of transmission. We introduce ASMODEE (automatic selection of models and outlier detection for epidemics), a new tool for detecting sudden changes in COVID-19 incidence. Our approach relies on automatically selecting the best (fitting or predicting) model from a range of user-defined time series models, excluding the most recent data points, to characterize the main trend in an incidence. We then derive prediction intervals and classify data points outside this interval as outliers, which provides an objective criterion for identifying departures from previous trends. We also provide a method for selecting the optimal breakpoints, used to define how many recent data points are to be excluded from the trend fitting procedure. The analysis of simulated COVID-19 outbreaks suggests ASMODEE compares favourably with a state-of-art outbreak-detection algorithm while being simpler and more flexible. As such, our method could be of wider use for infectious disease surveillance. We illustrate ASMODEE using publicly available data of National Health Service (NHS) Pathways reporting potential COVID-19 cases in England at a fine spatial scale, showing that the method would have enabled the early detection of the flare-ups in Leicester and Blackburn with Darwen, two to three weeks before their respective lockdown. ASMODEE is implemented in the free R package trendbreaker . This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK’.

Human cell line models have been widely used for testing of novel anticancer compounds and for predicting clinical response to monotherapies and combinatorial therapies. For many years, standard monolayer culture conditions were used as gold standard, only surpassed by in vivo testing of mouse models. Recently, the incorporation of three-dimensional culture has been shown to further improve predictive compound testing. In view of the renewed interest in anti-RAS cancer therapy, we provide a protocol for establishing colorectal cancer organoids which are characterized by a high prevalence of KRAS mutations.

SUMMARYRecent data suggests that colon tumors contain a subpopulation of therapy resistant quiescent cancer stem cells (qCSCs) that are the source of relapse following treatment. Here, using colon cancer patient-derived organoids (PDOs) and xenograft (PDX) models, we identify a rare population of long-term label-retaining (PKH26Positive) qCSCs that can re-enter the cell cycle to generate new tumors. RNA-sequencing analyses demonstrated that these cells are enriched for stem cell associated gene sets such as Wnt and hedgehog signaling, epithelial-to-mesenchymal transition (EMT), embryonic development, tissue development and p53 pathway but have downregulated expression of genes associated with cell cycle, transcription, biosynthesis and metabolism. Furthermore, qCSCs are enriched for p53 interacting negative regulators of cell cycle, includingAKAP12, CD82, CDKN1A, FHL2, GPX3, KIAA0247, LCN2, TFF2, UNC5BandZMAT3, that we show are indicators of poor prognosis and may be targeted for qCSC abolition. Interestingly, CD82, KIAA0247 and UNC5B proteins localize to the cell surface and may therefore be potential markers for the prospective isolation of qCSCs. These data support the temporal inhibition of p53 signaling for the elimination of qCSCs and prevention of relapse in colorectal cancer.

SUMMARYRecent data support a hierarchical model of colon cancer driven by a population of cancer stem cells (CSCs). Greater understanding of the mechanisms that regulate CSCs may therefore lead to more effective treatments. Serial limiting dilution xenotransplantation assays of colon cancer patient-derived tumors demonstrated ALDHPositivecells to be enriched for tumorigenic self-renewing CSCs. In order to identify CSC modulators, we performed RNA-sequencing analysis of ALDHPositiveCSCs from a panel of colon cancer patient-derived organoids (PDOs) and xenografts (PDXs). These studies demonstrated CSCs to be enriched for embryonic and neural development gene sets. Functional analyses of genes differentially expressed in both ALDHPositivePDO and PDX CSCs demonstrated the neural crest stem cell (NCSC) regulator and wound response geneEGR2to be required for CSC tumorigenicity and to control expression of homeobox superfamily embryonic master transcriptional regulatorHOXgenes and the embryonic and neural stem cell regulatorSOX2. In addition, we identifyEGR2,HOXA2,HOXA4,HOXA5,HOXA7,HOXB2,HOXB3and the tumor suppressorATOH1as new prognostic biomarkers in colorectal cancer.

Human cell line models have been widely used for testing of novel anticancer compounds and for predicting clinical response to monotherapies and combinatorial therapies. For many years, standard monolayer culture conditions were used as gold standard, only surpassed by in vivo testing of mouse models. Recently, the incorporation of three-dimensional culture has been shown to further improve predictive compound testing. In view of the renewed interest in anti-RAS cancer therapy, we provide a protocol for establishing colorectal cancer organoids which are characterized by a high prevalence of KRAS mutations.

Summary Recent data suggest that therapy-resistant quiescent cancer stem cells (qCSCs) are the source of relapse in colon cancer. Here, using colon cancer patient-derived organoids and xenografts, we identify rare long-term label-retaining qCSCs that can re-enter the cell cycle to generate new tumors. RNA sequencing analyses demonstrated that these cells display the molecular hallmarks of quiescent tissue stem cells, including expression of p53 signaling genes, and are enriched for transcripts common to damage-induced quiescent revival stem cells of the regenerating intestine. In addition, we identify negative regulators of cell cycle, downstream of p53, that we show are indicators of poor prognosis and may be targeted for qCSC abolition in both p53 wild-type and mutant tumors. These data support the temporal inhibition of downstream targets of p53 signaling, in combination with standard-of-care treatments, for the elimination of qCSCs and prevention of relapse in colon cancer., Graphical Abstract, Highlights • Colon tumors contain therapy-resistant quiescent cancer stem cells (qCSCs) • qCSC gene expression mirrors that of quiescent stem cells of the regenerating gut • qCSCs are enriched for p53 signaling genes • qCSC elimination may be achieved by inhibiting downstream targets of p53 signaling, Cancer stem cells ; Quiescence; Organoids; Colon cancer; p53 signaling; Transcriptomics

Recent evidence demonstrates that colon cancer stem cells (CSCs) can generate neurons that synapse with tumor innervating fibers required for tumorigenesis and disease progression. Greater understanding of the mechanisms that regulate CSC driven tumor neurogenesis may therefore lead to more effective treatments. RNA-sequencing analyses of ALDH

As of December 31, 2019, initial reports circulated internationally of an unusual cluster of pneumonia of unknown cause in China. By the end of January 2020, the virus affected Germany with the first case confirmed on January 27, 2020. Intensive contact tracing and infection control measures contained the first two clusters in the country. However, the dynamic of the first wave gained momentum as of March, and by mid-June 2020 over 190,000 laboratory-confirmed cases had been reported to the Robert Koch Institute. This article examines these cases as part of a retrospective descriptive analysis focused on disease severity. Most cases (80%) were mild and two thirds of the cases were younger than 60 years (median age: 50 years). Severe cases were primarily reported among men aged 60 or over who had at least one risk factor (particularly cardiovascular disease, diabetes, neurological disorders and/or lung diseases). Cases between the ages of 40 and 59 years had the longest interval between symptom onset and hospitalisation (median: six days) and - if admitted to an intensive care unit (ICU) - also the longest ICU stay (median: eleven days). This analysis provides valuable information about disease severity of COVID-19 and particularly affected groups.

As several countries gradually release social distancing measures, rapid detection of new localised COVID-19 hotspots and subsequent intervention will be key to avoiding large-scale resurgence of transmission. We introduce ASMODEE (Automatic Selection of Models and Outlier Detection for Epidemics), a new tool for detecting sudden changes in COVID-19 incidence. Our approach relies on automatically selecting the best (fitting or predicting) model from a range of user-defined time series models, excluding the most recent data points, to characterise the main trend in an incidence. We then derive prediction intervals and classify data points outside this interval as outliers, which provides an objective criterion for identifying departures from previous trends. We also provide a method for selecting the optimal breakpoints, used to define how many recent data points are to be excluded from the trend fitting procedure. The analysis of simulated COVID-19 outbreaks suggest ASMODEE compares favourably with a state-of-art outbreak-detection algorithm while being simpler and more flexible. We illustrate our method using publicly available data of NHS Pathways reporting potential COVID-19 cases in England at a fine spatial scale, for which we provide a template automated analysis pipeline. ASMODEE is implemented in the free R package trendbreaker.

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

Organoid cultures derived from colorectal cancer (CRC) samples are increasingly used as preclinical models for studying tumor biology and the effects of targeted therapies under conditions capturing in vitro the genetic make-up of heterogeneous and even individual neoplasms. While 3D cultures are initiated from surgical specimens comprising multiple cell populations, the impact of tumor heterogeneity on drug effects in organoid cultures has not been addressed systematically. Here we have used a cohort of well-characterized CRC organoids to study the influence of tumor heterogeneity on the activity of the KRAS/MAPK-signaling pathway and the consequences of treatment by inhibitors targeting EGFR and downstream effectors. MAPK signaling, analyzed by targeted proteomics, shows unexpected heterogeneity irrespective of RAS mutations and is associated with variable responses to EGFR inhibition. In addition, we obtained evidence for intratumoral heterogeneity in drug response among parallel "sibling" 3D cultures established from a single KRAS-mutant CRC. Our results imply that separate testing of drug effects in multiple subpopulations may help to elucidate molecular correlates of tumor heterogeneity and to improve therapy response prediction in patients.

The application of patient-derived three-dimensional culture systems as disease-specific drug sensitivity models has enormous potential to connect compound screening and clinical trials. However, the implementation of complex cell-based assay systems in drug discovery requires reliable and robust screening platforms. Here we describe the establishment of an automated platform in 384-well format for three-dimensional organoid cultures derived from colon cancer patients. Single cells were embedded in an extracellular matrix by an automated workflow and subsequently self-organized into organoid structures within 4 days of culture before being exposed to compound treatment. We performed validation of assay robustness and reproducibility via plate uniformity and replicate-experiment studies. After assay optimization, the patient-derived organoid platform passed all relevant validation criteria. In addition, we introduced a streamlined plate uniformity study to evaluate patient-derived colon cancer samples from different donors. Our results demonstrate the feasibility of using patient-derived tumor samples for high-throughput assays and their integration as disease-specific models in drug discovery.

One use of infectious disease surveillance systems is the statistical aberration detection performed on time series of counts resulting from the aggregation of individual case reports. However, inherent reporting delays in such surveillance systems make the considered time series incomplete, which can be an impediment to the timely detection and thus to the containment of emerging outbreaks. In this work, we synthesize the outbreak detection algorithms of Noufaily et al. (2013) and Manitz and Hohle (2013) while additionally addressing right truncation caused by reporting delays. We do so by considering the resulting time series as an incomplete two-way contingency table which we model using negative binomial regression. Our approach is defined in a Bayesian setting allowing a direct inclusion of all sources of uncertainty in the derivation of whether an observed case count is to be considered an aberration. The proposed algorithm is evaluated both on simulated data and on the time series of Salmonella Newport cases in Germany in 2011. Altogether, our method aims at allowing timely aberration detection in the presence of reporting delays and hence underlines the need for statistical modeling to address complications of reporting systems. An implementation of the proposed method is made available in the R package surveillance as the function "bodaDelay".

Time needed to report surveillance data within the public health service delays public health actions. The amendment to the infection protection act (IfSG) from 29 March 2013 requires local and state public health agencies to report surveillance data within one working day instead of one week. We analysed factors associated with reporting time and evaluated the IfSG amendment. Local reporting time is the time between date of notification and date of export to the state public health agency and state reporting time is time between date of arrival at the state public health agency and the date of export. We selected cases reported between 28 March 2012 and 28 March 2014. We calculated the median local and state reporting time, stratified by potentially influential factors, computed a negative binominal regression model and assessed quality and workload parameters. Before the IfSG amendment the median local reporting time was 4 days and 1 day afterwards. The state reporting time was 0 days before and after. Influential factors are the individual local public health agency, the notified disease, the notification software and the day of the week. Data quality and workload parameters did not change. The IfSG amendment has decreased local reporting time, no relevant loss of data quality or identifiable workload-increase could be detected. State reporting time is negligible. We recommend efforts to harmonise practices of local public health agencies including the exclusive use of software with fully compatible interfaces.

Genetic heterogeneity between and within tumours is a major factor determining cancer progression and therapy response. Here we examined DNA sequence and DNA copy-number heterogeneity in colorectal cancer (CRC) by targeted high-depth sequencing of 100 most frequently altered genes. In 97 samples, with primary tumours and matched metastases from 27 patients, we observe inter-tumour concordance for coding mutations; in contrast, gene copy numbers are highly discordant between primary tumours and metastases as validated by fluorescent in situ hybridization. To further investigate intra-tumour heterogeneity, we dissected a single tumour into 68 spatially defined samples and sequenced them separately. We identify evenly distributed coding mutations in APC and TP53 in all tumour areas, yet highly variable gene copy numbers in numerous genes. 3D morpho-molecular reconstruction reveals two clusters with divergent copy number aberrations along the proximal–distal axis indicating that DNA copy number variations are a major source of tumour heterogeneity in CRC., The contribution of intra-tumour heterogeneity is increasingly associated with resistance to therapy. Here, the authors use genomic analyses to study heterogeneity in colorectal cancer and perform in-depth reconstruction of heterogeneity in one sample.

Electronic Supplementary Material 3 for Garske et al, 2016, Heterogeneities in the Case Fatality Ratio in the West African Ebola Outbreak 2013 - 2016, Phil. Trans. R. Soc. B. doi: 10.1098/rstb.2016.0308.

For decades of molecular cancer research, immortal cancer cell lines have served as an easily accessible source for basic cancer biology research and preclinical testing of anticancer drugs. However, numerous studies have suggested that these cell lines poorly recapitulate the diversity, heterogeneity, and resulting drug resistance or relapse in patients. The derivation and (short-term) culture of primary cells from solid tumors have thus gained significant importance in personalized cancer therapy. This chapter focuses on our current understanding and the pros and cons of different preclinical and prospective clinical models of three-dimensional primary tumor cultures. We will discuss cell culture approaches, such as biomimetic scaffolds and growth factor supplemented, chemically defined media for various forms of solid tumors. Complex culture models of primary tumor cells could finally provide a key missing link between compound screening and clinical trials and ultimately will help redefining therapeutic intervention with high translational relevance at the level of the individual patient.

Colorectal carcinoma represents a heterogeneous entity, with only a fraction of the tumours responding to available therapies, requiring a better molecular understanding of the disease in precision oncology. To address this challenge, the OncoTrack consortium recruited 106 CRC patients (stages I–IV) and developed a pre-clinical platform generating a compendium of drug sensitivity data totalling >4,000 assays testing 16 clinical drugs on patient-derived in vivo and in vitro models. This large biobank of 106 tumours, 35 organoids and 59 xenografts, with extensive omics data comparing donor tumours and derived models provides a resource for advancing our understanding of CRC. Models recapitulate many of the genetic and transcriptomic features of the donors, but defined less complex molecular sub-groups because of the loss of human stroma. Linking molecular profiles with drug sensitivity patterns identifies novel biomarkers, including a signature outperforming RAS/RAF mutations in predicting sensitivity to the EGFR inhibitor cetuximab., 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.

Mutations in the transforming growth factor-β (TGF-β) pathway occur frequently in colorectal cancers (CRC). TGF-β is integral for key cellular processes, including proliferation, migration, differentiation and apoptosis. TGF-β/SMAD4 controls the activation of the pathway. A previously described R361H mutation in SMAD4 has been correlated with decreased overall survival and is suspected to modulate chemoresistance. The aim of the present study is to generate CRISPR-engineered SMAD4R361H CRC organoids and to utilize them as in vitro and in vivo models to investigate the effect of SMAD4R361H mutation on drug response. We have established independent organoid (PDO) and matching patient-derived xenograft (PDX) models from 5 different regions of a chemo-naïve CRC. By targeted amplicon sequencing using a cancer hot spot gene panel, we identified the SMAD4R361H mutation in two of the 5 subpopulations, whereas three of the PDOs were SMAD4wt. Semi-automated compound screening revealed a strong resistance phenotype to afatinib, sapitinib and gefitinib as compared to the wild-type models in vitro. Similar drug response was observed in in vivo testing. To investigate the mechanism of drug resistance, we have engineered isogenic organoids (SMAD4R361H/CRISPR) from SMAD4wt organoids using CRISPR-Cas9 genome-editing. In brief, SMAD4wt organoids were transfected with an all-in-one spCas9-sgRNA-vector and a ssODN as repair template bearing the R361H point mutation. To increase homologous-directed repair, we co-transfected the organoids with a plasmid vector containing i53-bpA, an inhibitor of 53BP1. Single clones were then isolated and genotyped by locus specific PCR to confirm the particular R361H point mutation. We were able to achieve up to 50 % knock-in efficiency in these organoids. Utilizing CRISPR-Cas9, engineered SMAD4R361H/CRISPR organoids were established. These PDOs were subjected with both, native SMAD4wt and SMAD4R361H PDOs, to an in vitro drug screening, allowing for a direct comparison of their drug sensitivity. Based on these results, confirmatory in vivo experiments were designed to investigate how SMAD4 may be involved in modulating resistance in CRC organoids. These models have a prominent role in discovering the connection between genotype and phenotype in complex PDO and PDX models. While this approach is not limited to studying the role of the R361H mutation, it has a broad range of applications in understanding cancer biology, intra-tumor heterogeneity, drug response and may eventually lead to new clinical insights, including design of new therapeutic strategies. Citation Format: Ulrike Pfohl, Alessandra Silvestri, Dirk Schumacher, Karsten Boehnke, Johannes Haybaeck, Sanam Bashir, Ralf Kühn, Marlen Keil, Reinhold Schäfer, Wolfgang Walther, Christian Regenbrecht. Modulating chemoresistance: Uncovering the role of mutant SMAD4R361H in colorectal cancer using PDO and PDX models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4525.

Background The ongoing West African Ebola epidemic began in December 2013 in Guinea, probably from a single zoonotic introduction. As a result of ineffective initial control efforts, an Ebola outbreak of unprecedented scale emerged. As of 4 May 2015, it had resulted in more than 19,000 probable and confirmed Ebola cases, mainly in Guinea (3,529), Liberia (5,343), and Sierra Leone (10,746). Here, we present analyses of data collected during the outbreak identifying drivers of transmission and highlighting areas where control could be improved. Methods and Findings Over 19,000 confirmed and probable Ebola cases were reported in West Africa by 4 May 2015. Individuals with confirmed or probable Ebola (“cases”) were asked if they had exposure to other potential Ebola cases (“potential source contacts”) in a funeral or non-funeral context prior to becoming ill. We performed retrospective analyses of a case line-list, collated from national databases of case investigation forms that have been reported to WHO. These analyses were initially performed to assist WHO’s response during the epidemic, and have been updated for publication. We analysed data from 3,529 cases in Guinea, 5,343 in Liberia, and 10,746 in Sierra Leone; exposures were reported by 33% of cases. The proportion of cases reporting a funeral exposure decreased over time. We found a positive correlation (r = 0.35, p < 0.001) between this proportion in a given district for a given month and the within-district transmission intensity, quantified by the estimated reproduction number (R). We also found a negative correlation (r = −0.37, p < 0.001) between R and the district proportion of hospitalised cases admitted within ≤4 days of symptom onset. These two proportions were not correlated, suggesting that reduced funeral attendance and faster hospitalisation independently influenced local transmission intensity. We were able to identify 14% of potential source contacts as cases in the case line-list. Linking cases to the contacts who potentially infected them provided information on the transmission network. This revealed a high degree of heterogeneity in inferred transmissions, with only 20% of cases accounting for at least 73% of new infections, a phenomenon often called super-spreading. Multivariable regression models allowed us to identify predictors of being named as a potential source contact. These were similar for funeral and non-funeral contacts: severe symptoms, death, non-hospitalisation, older age, and travelling prior to symptom onset. Non-funeral exposures were strongly peaked around the death of the contact. There was evidence that hospitalisation reduced but did not eliminate onward exposures. We found that Ebola treatment units were better than other health care facilities at preventing exposure from hospitalised and deceased individuals. The principal limitation of our analysis is limited data quality, with cases not being entered into the database, cases not reporting exposures, or data being entered incorrectly (especially dates, and possible misclassifications). Conclusions Achieving elimination of Ebola is challenging, partly because of super-spreading. Safe funeral practices and fast hospitalisation contributed to the containment of this Ebola epidemic. Continued real-time data capture, reporting, and analysis are vital to track transmission patterns, inform resource deployment, and thus hasten and maintain elimination of the virus from the human population., In this retrospective observational study, Christophe Fraser and colleagues analyze the exposure patterns associated with Ebola transmission during the 2013-2016 epidemic in West Africa., Author Summary Why Was This Study Done? Knowing how and from whom individuals acquire infection can help inform the response to limit the impact of an epidemic; this study presents updated versions of analyses initially performed to assist the international response during the 2013–2016 Ebola epidemic in West Africa. Over 19,000 individuals with confirmed or probable Ebola (“cases”) were reported in West Africa by 4 May 2015. Cases were asked whether they had exposure to potential Ebola cases (“potential source contacts”) in a funeral or non-funeral context prior to becoming ill. What Did the Researchers Do and Find? We analysed data from 3,529 cases in Guinea, 5,343 in Liberia, and 10,746 in Sierra Leone; exposures were reported by 33% of cases. Non-funeral exposures were strongly peaked around the time of death of the contact. There was evidence of super-spreading, with only 20% of cases accounting for at least 73% of new infections. What Do These Findings Mean? Safe funeral practices and fast hospitalisation contributed to the containment of this Ebola epidemic. The data are highly detailed despite the challenging circumstances in the three countries; however, the analyses were limited by data quality, mostly missing data and incorrect entries. In light of viral persistence in reservoirs, it is vital to maintain active surveillance and analysis of Ebola outbreaks to avoid and contain future outbreaks.

Between December 2013 and April 2016, the largest epidemic of Ebola virus disease (EVD) to date generated more than 28,000 cases and more than 11,000 deaths in the large, mobile populations of Guinea, Liberia, and Sierra Leone. Tracking the rapid rise and slower decline of the West African epidemic has reinforced some common understandings about the epidemiology and control of EVD but has also generated new insights. Despite having more information about the geographic distribution of the disease, the risk of human infection from animals and from survivors of EVD remains unpredictable over a wide area of equatorial Africa. Until human exposure to infection can be anticipated or avoided, future outbreaks will have to be managed with the classic approach to EVD control — extensive surveillance, rapid detection and diagnosis, comprehensive tracing of contacts, prompt patient isolation, supportive clinical care, rigorous efforts to prevent and control infection, safe and dignified burial, and engagement of the community. Empirical and modeling studies conducted during the West African epidemic have shown that large epidemics of EVD are preventable — a rapid response can interrupt transmission and restrict the size of outbreaks, even in densely populated cities. The critical question now is how to ensure that populations and their health services are ready for the next outbreak, wherever it may occur. Health security across Africa and beyond depends on committing resources to both strengthen national health systems and sustain investment in the next generation of vaccines, drugs, and diagnostics.

Ebola virus has caused substantial illness in West Africa in the past year. In this report, the burden of illness in children is described.

Despite efforts to control the outbreak of Ebola virus disease in West Africa, substantial transmission continues. As we reach the 1-year anniversary of the first known case from this outbreak, the WHO team updates the progress in controlling the epidemic.

The trialkylgallanes GaR"(3) [R' = Me, iPr (2a and 2b)] react with the ferrio-silanols Cp(OC)(2)Fe-Si(R)(R')OH [R = R' = Me, iPr, Ph (1a-c), R = Me, R' = Ph (1d)] by alkane elimination to yield the iron-substituted siloxy-gallanes [Cp(OC)(2)Fe-Si-(R)(R')OGaR"(2)](2) (3a-e). According to molecular mass determination in benzene (3a, 3b, 3d), X-ray analyses (3a, 3d) and NMR spectroscopy (3e), the novel hetero-siloxanes exist as dimers both in solution and in the solid state. The bonding situation and geometry of the ferrio-heterosiloxane [Cp(OC)(2)Fe-SiH2OGaH2](2) has been analyzed by density functional calculation. (C) Wiley-VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2003.

Reaction of the metalates Na[Fe(CO) 2 C 5 R 5 ] [R=H ( 1a ); Me ( 1b )] and Li[M(CO) 2 (PMe 3 )Cp] [M=Mo ( 1c ); W ( 1d )] with the chlorosiloxanes Cl 3 SiOSiCl 3 ( 2a ) and Cl 3 SiOSiCl 2 OSiCl 3 ( 2b ) leads to the metallo-siloxanes L n MSiCl 2 OSiCl 3 [L n M=Cp(OC) 2 Fe ( 3a ), Cp(OC) 2 (Me 3 P)Mo ( 4a ), Cp(OC) 2 (Me 3 P)W ( 4b )] and C 5 R 5 (OC) 2 FeSiCl 2 OSiCl 2 OSiCl 3 [(R=H ( 3b ), Me ( 3c )], respectively. Cp(OC) 2 FeSiCl 2 OSiCl 2 OSiCl 3 ( 3b ) has been converted to the bis-metalated polychlorinated siloxane Cp(OC) 2 FeSiCl 2 OSiCl 2 OSiCl 2 Fe(CO) 2 Cp ( 8 ) by reaction with a second equivalent of Na[Fe(CO) 2 Cp] ( 1a ). The structure of Cp(OC) 2 FeSiCl 2 OSiCl 3 ( 3a ) was obtained by X-ray diffraction.

The auxiliary-induced diastereoselectivities of [4+2] cycloaddition and the ene reaction of singlet oxygen and PTAD through a variety of auxiliaries is studied. The different trends in the diastereoselectivities that are observed for the diverse auxiliaries, which include 2,2-dimethyloxazolidines, a menthol derivative, several related cyclohexanes, and the Oppolzer sultam, are compared and backed by mechanistic interpretations. From this overview of two reaction modes for two electrophiles and four different types of auxiliaries, the advantages of the individual auxiliaries become evident and comprehensible. (© Wiley-VCH Verlag GmbH, 69451 Weinheim, Germany, 2002)

The synthesis of P-chiral secondary phosphines, characterized by phosphorus and side chain chirality, has been realized via insertion of various organic multiple bond systems into the PH-bond of the primary phosphine complexes {C 5 R 5 (OC) 2 Fe[P(R′)H 2 ]}BF 4 (R=H, Me; R′=alkyl, aryl). In the case of acetylenedicarboxylic acid dimethylester a double hydrophosphination is observed, leading diastereospecifically to the dinuclear complexes {C 5 R 5 (OC) 2 Fe{P(H)(R′)[C(H)(CO 2 Me)]}} 2 (BF 4 ) 2 (R=H, Me; R′= t -Bu, 2-py), bearing four stereogenic centers. The use of p -benzoquinone gives access to secondary 2,5-bis(hydroxy)aryl phosphine ligands, suitable for further derivatizations. α-Hydroxyalkyl phosphine iron complexes can be obtained by hydrophosphination of aldehydes and ketones. Transformation into highly functionalized tertiary phosphine complexes is performed by a further hydrophosphination step using the alkenes H 2 CCHX (X=CN, 2-py), diazoacetic ethylester, p -benzoquinone or ethylisocyanate, respectively, in special cases formation of functionalized azaphospholane ligands is observed. Release of the phosphines from the metal is achieved by photoinduced ligand exchange. In addition, primary phosphine iron complexes {C 5 H 5 (diphos)Fe[P(R)H 2 ]}BF 4 (diphos=DIOP, CHIRAPHOS) bearing chiral bis(phosphine) ligands have been used to provide the stereocontrol of the hydrophosphination process.

The Et3N-assisted condensation of the ferriomethyl-silanol Cp(OC)2Fe−CH2−SiMe2OH (1) with 1 equiv of Cp2MCl2 (M = Ti (2a), Zr (2b)) leads to the formation of the iron fragment substituted heterosiloxanes Cp(OC)2Fe−CH2−SiMe2O−M(Cl)Cp2 (M = Ti (3a), Zr (3b)). The bis(siloxy) zirconium complex [Cp(OC)2Fe−CH2−SiMe2O]2−ZrCp2 (4) is obtained by further condensation of the M−Cl functionality of 3b with 1. The new compounds have been identified spectroscopically, and in addition, 3b and 4 have been structurally characterized by single-crystal X-ray diffraction methods.

The novel bis(ferrio)silanols [Cp(OC)2Fe]2Si(X)OH [X = H (2), OH (4), Cl (7)] are obtained via hydrolysis of [Cp(OC)2Fe]2Si(H)Cl (1) or via oxygenation of the bis(ferrio)hydridosilanes [Cp(OC)2Fe]2Si(H)X [X = Cl (1), H (6)] with dimethyldioxirane. Subsequent condensation reactions with chlorodimethylsilane yield the bis(ferrio)siloxanes [Cp(OC)2Fe]2Si(X)(OSiMe2H) [X = H (12), OSiMe2H (13), OH (15)]. In an analogous manner the hetero-bismetalated silanol [Cp(OC)2Fe][Cp(OC)2(Me3P)W]Si(Me)OH (11) and the disiloxane [Cp(OC)2Fe][Cp(OC)2(Me3P)W]Si(Me)(OSiMe2H) (14) have been prepared. The influence of the transition metal substituents on the chemical and spectroscopic properties of these compounds has been investigated. The X-ray structure analyses of the bis(ferrio)silanol [Cp(OC)2Fe]2Si(H)OH and the bis(ferrio)dimethoxysilane [Cp(OC)2Fe]2Si(OCH3)2 (5)generated via methanolysis of [Cp(OC)2Fe]2SiCl2 (3)are presented.

One use of infectious disease surveillance systems is the statistical aberration detection performed on time series of counts resulting from the aggregation of individual case reports. However, inherent reporting delays in such surveillance systems make the considered time series incomplete, which can be an impediment to the timely detection and thus to the containment of emerging outbreaks. In this work, we synthesize the outbreak detection algorithms of Noufaily et al. (2013) and Manitz and Höhle (2013) while additionally addressing right truncation caused by reporting delays. We do so by considering the resulting time series as an incomplete two-way contingency table which we model using negative binomial regression. Our approach is defined in a Bayesian setting allowing a direct inclusion of all sources of uncertainty in the derivation of whether an observed case count is to be considered an aberration. The proposed algorithm is evaluated both on simulated data and on the time series of Salmonella Newport cases in Germany in 2011. Altogether, our method aims at allowing timely aberration detection in the presence of reporting delays and hence underlines the need for statistical modeling to address complications of reporting systems. An implementation of the proposed method is made available in the R package surveillance as the function "bodaDelay".

The use of next generation sequencing has expanded our view on whole mammalian methylome patterns. In particular, it provides a genome-wide insight of local DNA methylation diversity at single nucleotide level and enables the examination of single chromosome sequence sections at a sufficient statistical power. We describe a bisulfite-based sequence profiling pipeline, Bi-PROF, which is based on the 454 GS-FLX Titanium technology that allows to obtain up to one million sequence stretches at single base pair resolution without laborious subcloning. To illustrate the performance of the experimental workflow connected to a bioinformatics program pipeline (BiQ Analyzer HT) we present a test analysis set of 68 different epigenetic marker regions (amplicons) in five individual patient-derived xenograft tissue samples of colorectal cancer and one healthy colon epithelium sample as a control. After the 454 GS-FLX Titanium run, sequence read processing and sample decoding, the obtained alignments are quality controlled and statistically evaluated. Comprehensive methylation pattern interpretation (profiling) assessed by analyzing 10 (2)-10 (4) sequence reads per amplicon allows an unprecedented deep view on pattern formation and methylation marker heterogeneity in tissues concerned by complex diseases like cancer.

Analysis of the signaling response of colon cancer cells to systematic perturbations reveals an EGF receptor-mediated cross-talk between the MAPK and AKT pathways. Accordingly, the predicted combinatorial treatment is shown to inhibit tumor growth in vivo., A modular response analysis model trained on perturbation data in a panel of colon cancer cells revealed a negative feedback from MAPK signaling to the EGF receptor, which leads to AKT cross-activation after MEK inhibition. The model predicted that successful inhibition of growth-factor signaling in colon cancer requires combined inhibition of MEK and EGF receptor to prevent AKT activation and tumor cell survival, which was confirmed by growth assays. A xenograft tumor model of KRAS-mutant colon cancer showed that EGFR receptor inhibition alone has no effect, but in combination with a MEK inhibitor successfully reduces tumor growth., The epidermal growth factor receptor (EGFR) signaling network is activated in most solid tumors, and small-molecule drugs targeting this network are increasingly available. However, often only specific combinations of inhibitors are effective. Therefore, the prediction of potent combinatorial treatments is a major challenge in targeted cancer therapy. In this study, we demonstrate how a model-based evaluation of signaling data can assist in finding the most suitable treatment combination. We generated a perturbation data set by monitoring the response of RAS/PI3K signaling to combined stimulations and inhibitions in a panel of colorectal cancer cell lines, which we analyzed using mathematical models. We detected that a negative feedback involving EGFR mediates strong cross talk from ERK to AKT. Consequently, when inhibiting MAPK, AKT activity is increased in an EGFR-dependent manner. Using the model, we predict that in contrast to single inhibition, combined inactivation of MEK and EGFR could inactivate both endpoints of RAS, ERK and AKT. We further could demonstrate that this combination blocked cell growth in BRAF- as well as KRAS-mutated tumor cells, which we confirmed using a xenograft model.

During recent years, circumstantial evidence has suggested that tumor development and cancer heterogeneity are triggered by so-called cancer stem cells (CSCs). These cells comprise a distinct, yet rare population found in both hematological and solid tumors. CSCs initiate tumor formation when ectopically transplanted into immune-deficient mice and share properties of tissue stem cells and partially reprogrammed induced pluripotent stem cells (iPSCs). CSCs are capable of self-renewal and differentiation into every cell type of the primary tumor they reside in. CSCs are responsible for tumor recurrence given that they often develop resistance mechanisms against chemotherapeutic drugs, e.g., an increased expression of ABC transporters or increased DNA-repair activity. Understanding the mechanisms that maintain CSCs in their niche and the development of strategies for specific targeting are essential to improve cancer therapy.

Die Unternehmensgruppe Nassauische Heimstatte/ Wohnstadt erbringt seit knapp 90 Jahren umfassende Leistungen in den Bereichen Wohnen, Bauen und Entwickeln. Durch ihre Tatigkeit und ihr Selbstverstandnis tragt sie in sozialer, okologischer und okonomischer Hinsicht zur nachhaltigen Entwicklung des Landes Hessen und der hessischen Kommunen bei.

Precision medicine approaches seeking to predict individual susceptibility to single or combinatorial drugs for advanced and/or metastasized solid cancers heavily depend on biological model systems that maintain key morphological, phenotypic and genomic features of the original tumor. Here, we present a case study of a female patient with metastasized colorectal cancer. Using tissue from five distinct areas of the primary tumor and its metastasis of the synchronously removed primary tumor and liver metastasis, we generated cell cultures. To address cell morphology and phenotypic features we performed immunohistochemistry (IHC) and immunofluorescence imaging showing that these cell cultures express colon-specific marker proteins/combinations CDX2 and CK20+/CK7-. Ultra-deep panel sequencing of original tumor tissue samples revealed damaging mutations in KRAS (G12D), PIK3CA (H1047R) and TP53 (C242F). Two cell cultures showed an additional SNP in the tumor suppressor SMAD4 (R361H), which was not detected in the original tissue, thus hinting at the existence of a small sub-population of cancer cells with a divergent mutation pattern. In parallel we established patient-derived xenografts (PDX) models from each region and investigated the response to targeted therapeutics, aiming at key molecules of the MAPK, PI3K/AKT and mTOR pathways in these genetically heterogeneous populations. drug response in single and mixed cell populations to address differential growth characteristics and response to mono- and combinatorial drug treatment. To distinguish the cells-of-origin and to calculate distributions/contribution of each population to the in vivo tumor growth in this model, sub-populations were color-coded using lentiviral constructs, expressing either a green or red tag. FACS analyses after treatment were performed and ratios of SMAD4mut(green) vs. SMAD4wt(red) were determined for each PDX tumor. These analyses, together with confirmatory IHC staining for the respective tag, showed significant effects on both tumor growth and population distributions in a treatment-dependent manner, advocating for systematic evaluation of combinatorial treatment in patients. Citation Format: Dirk Schumacher, Karsten Boehnke, Marlen Keil, Alessandra Silvestri, Maxine Silvestrov, Jens Hoffman, Iduna Fichtner, Reinhold Schaefer, Christian RA Regenbrecht. Reconstructing intratumor heterogeneity: lessons from therapeutic intervention in patient-specific models. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2412.

Recent data support a hierarchical model of colon cancer in which tumor growth is driven by a subpopulation of cancer stem cells (CSCs) that may also be the source of relapse following treatment. Elucidation of the cellular heterogeneity within a tumor would therefore facilitate better characterization of patient subtypes and lead to more personalized and effective treatments. Here, as part of the OncoTrack* consortium, we report the use of Matrigel-based 3D in vitro models of patient-derived colon cancer for the characterization of molecular pathways important in the regulation of CSC self-renewal and survival. Cellular subpopulations were isolated from patient-derived 3D-culture models based on expression of the CSC marker aldehyde dehydrogenase (ALDH) and then functionally tested for tumor initiation and self-renewal capacity by limiting dilution serial xenotransplantation. These studies demonstrate CSCs to be ALDH+. ALDH+ and ALDH- cells from 3D-culture and xenograft models were then subjected to RNA sequencing for whole transcriptome analysis. These analyses demonstrated ALDH+ CSCs cells to be enriched for stem cell associated genes (ALDH1A1, LGR5, BMI1, CD44, CD166), developmental processes (embryonic, tissue development, EMT) and signaling pathways (Wnt signaling). In particular, the Hedgehog signaling pathway was found to be enriched in both 3D in vitro and xenograft models. The role of Hedgehog signaling in colon cancer remains controversial. It has been reported as a negative regulator of Wnt signaling and to be inactive in colon cancer cells lines. Here, using small molecule inhibitors and lentivirus mediated gene knockdown, we report on the role of Hedgehog signaling in the regulation of colon CSC self-renewal and identify non-canonical Hedgehog signaling as a positive regulator of Wnt signaling. *The research leading to these results has received funding from the European Union's Seventh Framework Program (FP7/2007-2013) for the Innovative Medicine Initiative under grant agreement n°115234. Citation Format: Joseph L. Regan, Stephanie Staudte, Dirk Schumacher, Ulrich Keilholz, Johannes Haybaeck, Hans Lehrach, Marie-Laure Yaspo, David Henderson, Andreas Steffen, Joern Toedling, Ralf Lesche, Reinhold Schaefer, Christian R. Regenbrecht, Dominik Mumberg, Martin Lange. The role of Hedgehog signaling in the regulation of human colon cancer stem cells. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1714.