The integrin αvβ6 drives pancreatic cancer through diverse mechanisms and represents an effective target for therapy

Pancreatic ductal adenocarcinoma (PDAC) has a five‐year survival rate of <4% and desperately needs novel effective therapeutics. Integrin αvβ6 has been linked with poor prognosis in cancer but its potential as a target in PDAC remains unclear. We report that transcriptional expression analysis revealed high levels of β6 mRNA correlated strongly with significantly poorer survival (n=491 cases, p= 3.17x10‐8). In two separate cohorts we showed that over 80% of PDAC expressed αvβ6 protein and that paired metastases retained αvβ6 expression. In vitro, integrin αvβ6 promoted PDAC cell growth, survival, migration and invasion. Treatment of both αvβ6‐positive human PDAC xenografts and transgenic mice bearing αvβ6‐positive PDAC with the αvβ6 blocking antibody 264RAD, combined with gemcitabine, significantly reduced tumour growth (p<0.0001) and increased survival (Log‐rank test, p<0.05). Antibody therapy was associated with suppression of both tumour cell activity (suppression of pErk growth signals, increased apoptosis seen as activated Caspase 3) and suppression of the pro‐tumourigenic microenvironment (suppression of TGFβ signalling, fewer αSMA‐positive myofibroblasts, decreased blood vessel density). These data show that αvβ6 promotes PDAC growth through both tumour cell and tumour microenvironment mechanisms and represents a valuable target for PDAC therapy

Nothing lasts forever: Dominant species decline under rapid environmental change in global grasslands

Dominance often indicates one or a few species being best suited for resource capture and retention in a given environment. Press perturbations that change availability of limiting resources can restructure competitive hierarchies, allowing new species to capture or retain resources and leaving once dominant species fated to decline. However, dominant species may maintain high abundances even when their new environments no longer favour them due to stochastic processes associated with their high abundance, impeding deterministic processes that would otherwise diminish them. Here, we quantify the persistence of dominance by tracking the rate of decline in dominant species at 90 globally distributed grassland sites under experimentally elevated soil nutrient supply and reduced vertebrate consumer pressure. We found that chronic experimental nutrient addition and vertebrate exclusion caused certain subsets of species to lose dominance more quickly than in control plots. In control plots, perennial species and species with high initial cover maintained dominance for longer than annual species and those with low initial cover respectively. In fertilized plots, species with high initial cover maintained dominance at similar rates to control plots, while those with lower initial cover lost dominance even faster than similar species in controls. High initial cover increased the estimated time to dominance loss more strongly in plots with vertebrate exclosures than in controls. Vertebrate exclosures caused a slight decrease in the persistence of dominance for perennials, while fertilization brought perennials' rate of dominance loss in line with those of annuals. Annual species lost dominance at similar rates regardless of treatments. Synthesis. Collectively, these results point to a strong role of a species' historical abundance in maintaining dominance following environmental perturbations. Because dominant species play an outsized role in driving ecosystem processes, their ability to remain dominant—regardless of environmental conditions—is critical to anticipating expected rates of change in the structure and function of grasslands. Species that maintain dominance while no longer competitively favoured following press perturbations due to their historical abundances may result in community compositions that do not maximize resource capture, a key process of system responses to global change.Fil: Wilfahrt, Peter A.. University of Minnesota; Estados UnidosFil: Seabloom, Eric. University of Minnesota; Estados UnidosFil: Bakker, Jonathan. University of Washington; Estados UnidosFil: Biederman, Lori. Iowa State University; Estados UnidosFil: Bugalho, Miguel N.. Universidade Nova de Lisboa; PortugalFil: Cadotte, Marc W.. University of Toronto–Scarborough; Estados UnidosFil: Caldeira, Maria C.. Universidade Nova de Lisboa; PortugalFil: Catford, Jane A.. University of Melbourne; AustraliaFil: Chen, Qingqing. Peking University; China. German Centre for Integrative Biodiversity Research; AlemaniaFil: Donohue, Ian. Trinity College Dublin; IrlandaFil: Ebeling, Anne. University of Jena; AlemaniaFil: Eisenhauer, Nico. German Centre for Integrative Biodiversity Research; Alemania. Leipzig University; AlemaniaFil: Haider, Sylvia. Martin Luther University Halle-Wittenberg; Alemania. Leuphana University of Lüneburg; AlemaniaFil: Heckman, Robert W.. University of Texas; Estados Unidos. United States Forest Service; Estados UnidosFil: Jentsch, Anke. University of Bayreuth; AlemaniaFil: Koerner, Sally E.. University of North Carolina Greensboro; Estados UnidosFil: Komatsu, Kimberly J.. University of North Carolina Greensboro; Estados UnidosFil: Laungani, Ramesh. Poly Prep Country Day School; Estados UnidosFil: MacDougall, Andrew. University of Guelph; CanadáFil: Smith, Nicholas G.. Texas Tech University; Estados UnidosFil: Stevens, Carly J.. Lancaster University; Reino UnidoFil: Sullivan, Lauren L.. Michigan State University; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Tedder, Michelle. University of KwaZulu-Natal; SudáfricaFil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia de Santa Cruz. Universidad Tecnológica Nacional. Facultad Regional Santa Cruz. Centro de Investigaciones y Transferencia de Santa Cruz. Universidad Nacional de la Patagonia Austral. Centro de Investigaciones y Transferencia de Santa Cruz; ArgentinaFil: Tognetti, Pedro Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Veen, Ciska. Netherlands Institute of Ecology; Países BajosFil: Wheeler, George. University of Nebraska-Lincoln; Estados UnidosFil: Young, Alyssa L.. University of North Carolina Greensboro; Estados UnidosFil: Young, Hillary. University of California; Estados UnidosFil: Borer, Elizabeth. University of Minnesota; Estados Unido

Identifying molecular features that distinguish fluvastatin-sensitive breast tumor cells

Statins, routinely used to treat hypercholesterolemia, selectively induce apoptosis in some tumor cells by inhibiting the mevalonate pathway. Recent clinical studies suggest that a subset of breast tumors is particularly susceptible to lipophilic statins, such as fluvastatin. To quickly advance statins as effective anticancer agents for breast cancer treatment, it is critical to identify the molecular features defining this sensitive subset. We have therefore characterized fluvastatin sensitivity by MTT assay in a panel of 19 breast cell lines that reflect the molecular diversity of breast cancer, and have evaluated the association of sensitivity with several clinicopathological and molecular features. A wide range of fluvastatin sensitivity was observed across breast tumor cell lines, with fluvastatin triggering cell death in a subset of sensitive cell lines. Fluvastatin sensitivity was associated with an estrogen receptor alpha (ERa)-negative, basal-like tumor subtype, features that can be scored with routine and/or strong preclinical diagnostics. To ascertain additional candidate sensitivity-associated molecular features, we mined publicly available gene expression datasets, identifying genes encoding regulators of mevalonate production, nonsterol lipid homeostasis, and global cellular metabolism, including the oncogene MYC. Further exploration of this data allowed us to generate a 10-gene mRNA abundance signature predictive of fluvastatin sensitivity, which showed preliminary validation in an independent set of breast tumor cell lines. Here, we have therefore identified several candidate predictors of sensitivity to fluvastatin treatment in breast cancer, which warrant further preclinical and clinical evaluation.Fil: Goard, Carolyn A.. University Health Network. Princess Margaret Cancer Centre. Ontario Cancer Institute and Campbell Family Institute for Breast Cancer Research; Canadá. University Of Toronto; CanadáFil: Chan Seng Yue, Michelle . University Health Network. Princess Margaret Cancer Centre. Ontario Cancer Institute and Campbell Family Institute for Breast Cancer Research; Canadá. Ontario Institute of Cancer Research. Informatics and Biocomputing Platform; CanadáFil: Mullen, Peter J.. University Health Network. Princess Margaret Cancer Centre. Ontario Cancer Institute and Campbell Family Institute for Breast Cancer Research; CanadáFil: Quiroga, Ariel Dario. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires; Argentina. University of Alberta; CanadáFil: Wasylishen, Amanda R.. University Health Network. Princess Margaret Cancer Centre. Ontario Cancer Institute and Campbell Family Institute for Breast Cancer Research; Canadá. University Of Toronto; CanadáFil: Clendening, James W.. University Health Network. Princess Margaret Cancer Centre. Ontario Cancer Institute and Campbell Family Institute for Breast Cancer Research; Canadá. University Of Toronto; CanadáFil: Sendorek, Dorota H. S.. Ontario Institute of Cancer Research. Informatics and Biocomputing Platform; CanadáFil: Haider, Syed. Ontario Institute of Cancer Research. Informatics and Biocomputing Platform; CanadáFil: Lehner, Richard. University of Alberta; CanadáFil: Boutros, Paul C.. University Of Toronto; Canadá. Ontario Institute of Cancer Research. Informatics and Biocomputing Platform; CanadáFil: Penn, Linda Z.. University Health Network. Princess Margaret Cancer Centre. Ontario Cancer Institute and Campbell Family Institute for Breast Cancer Research; Canadá. University Of Toronto; Canad

Quantitative Proteomics Identify Novel miR-155 Target Proteins

Background: MicroRNAs are 22 nucleotides long non-coding RNAs and exert their function either by transcriptional or translational inhibition. Although many microRNA profiles in different tissues and disease states have already been discovered, only little is known about their target proteins. The microRNA miR-155 is deregulated in many diseases, including cancer, where it might function as an oncoMir. Methodology/Principal Findings: We employed a proteomics technique called ‘‘stable isotope labelling by amino acids in cell culture’ ’ (SILAC) allowing relative quantification to reliably identify target proteins of miR-155. Using SILAC, we identified 46 putative miR-155 target proteins, some of which were previously reported. With luciferase reporter assays, CKAP5 was confirmed as a new target of miR-155. Functional annotation of miR-155 target proteins pointed to a role in cell cycle regulation. Conclusions/Significance: To the best of our knowledge we have investigated for the first time miR-155 target proteins in the HEK293T cell line in large scale. In addition, by comparing our results to previously identified miR-155 target proteins i

Think globally, measure locally: The MIREN standardized protocol for monitoring plant species distributions along elevation gradients

Climate change and other global change drivers threaten plant diversity in mountains worldwide. A widely documented response to such environmental modifications is for plant species to change their elevational ranges. Range shifts are often idiosyncratic and difficult to generalize, partly due to variation in sampling methods. There is thus a need for a standardized monitoring strategy that can be applied across mountain regions to assess distribution changes and community turnover of native and non-native plant species over space and time. Here, we present a conceptually intuitive and standardized protocol developed by the Mountain Invasion Research Network (MIREN) to systematically quantify global patterns of native and non-native species distributions along elevation gradients and shifts arising from interactive effects of climate change and human disturbance. Usually repeated every five years, surveys consist of 20 sample sites located at equal elevation increments along three replicate roads per sampling region. At each site, three plots extend from the side of a mountain road into surrounding natural vegetation. The protocol has been successfully used in 18 regions worldwide from 2007 to present. Analyses of one point in time already generated some salient results, and revealed region-specific elevational patterns of native plant species richness, but a globally consistent elevational decline in non-native species richness. Non-native plants were also more abundant directly adjacent to road edges, suggesting that disturbed roadsides serve as a vector for invasions into mountains. From the upcoming analyses of time series, even more exciting results can be expected, especially about range shifts. Implementing the protocol in more mountain regions globally would help to generate a more complete picture of how global change alters species distributions. This would inform conservation policy in mountain ecosystems, where some conservation policies remain poorly implemented

Orally Active Multi-Functional Antioxidants Are Neuroprotective in a Rat Model of Light-Induced Retinal Damage

Progression of age-related macular degeneration has been linked to iron dysregulation and oxidative stress that induce apoptosis of neural retinal cells. Since both antioxidants and chelating agents have been reported to reduce the progression of retinal lesions associated with AMD in experimental animals, the present study evaluates the ability of multi-functional antioxidants containing functional groups that can independently chelate redox metals and quench free radicals to protect the retina against light-induced retinal degeneration, a rat model of dry atrophic AMD.Proof of concept studies were conducted to evaluate the ability of 4-(5-hydroxypyrimidin-2-yl)-N,N-dimethyl-3,5-dioxopiperazine-1-sulfonamide (compound 4) and 4-(5-hydroxy-4,6-dimethoxypyrimidin-2-yl)-N,N-dimethyl-3,5-dioxopiperazine-1-sulfonamide (compound 8) to reduce retinal damage in 2-week dark adapted Wistar rats exposed to 1000 lx of light for 3 hours. Assessment of the oxidative stress markers 4- hydroxynonenal and nitrotyrosine modified proteins and Thioredoxin by ELISA and Western blots indicated that these compounds reduced the oxidative insult caused by light exposure. The beneficial antioxidant effects of these compounds in providing significant functional and structural protection were confirmed by electroretinography and quantitative histology of the retina.The present study suggests that multi-functional compounds may be effective candidates for preventive therapy of AMD

A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns.

In cancer, the primary tumour's organ of origin and histopathology are the strongest determinants of its clinical behaviour, but in 3% of cases a patient presents with a metastatic tumour and no obvious primary. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we train a deep learning classifier to predict cancer type based on patterns of somatic passenger mutations detected in whole genome sequencing (WGS) of 2606 tumours representing 24 common cancer types produced by the PCAWG Consortium. Our classifier achieves an accuracy of 91% on held-out tumor samples and 88% and 83% respectively on independent primary and metastatic samples, roughly double the accuracy of trained pathologists when presented with a metastatic tumour without knowledge of the primary. Surprisingly, adding information on driver mutations reduced accuracy. Our results have clinical applicability, underscore how patterns of somatic passenger mutations encode the state of the cell of origin, and can inform future strategies to detect the source of circulating tumour DNA

Non-random patterns in viral diversity

It is currently unclear whether changes in viral communities will ever be predictable. Here we investigate whether viral communities in wildlife are inherently structured (inferring predictability) by looking at whether communities are assembled through deterministic (often predictable) or stochastic (not predictable) processes. We sample macaque faeces across nine sites in Bangladesh and use consensus PCR and sequencing to discover 184 viruses from 14 viral families. We then use network modelling and statistical null-hypothesis testing to show the presence of non-random deterministic patterns at different scales, between sites and within individuals. We show that the effects of determinism are not absolute however, as stochastic patterns are also observed. In showing that determinism is an important process in viral community assembly we conclude that it should be possible to forecast changes to some portion of a viral community, however there will always be some portion for which prediction will be unlikely

Functional annotation of the 2q35 breast cancer risk locus implicates a structural variant in influencing activity of a long-range enhancer element

A combination of genetic and functional approaches has identified three independent breast cancer risk loci at 2q35. A recent fine-scale mapping analysis to refine these associations resulted in 1 (signal 1), 5 (signal 2), and 42 (signal 3) credible causal variants at these loci. We used publicly available in silico DNase I and ChIP-seq data with in vitro reporter gene and CRISPR assays to annotate signals 2 and 3. We identified putative regulatory elements that enhanced cell-type-specific transcription from the IGFBP5 promoter at both signals (30-to 40-fold increased expression by the putative regulatory element at signal 2, 2- to 3-fold by the putative regulatory element at signal 3). We further identified one of the five credible causal variants at signal 2, a 1.4 kb deletion (esv3594306), as the likely causal variant; the deletion allele of this variant was associated with an average additional increase in IGFBP5 expression of 1.3-fold (MCF-7) and 2.2-fold (T-47D). We propose a model in which the deletion allele of esv3594306 juxtaposes two transcription factor binding regions (annotated by estrogen receptor alpha ChIP-seq peaks) to generate a single extended regulatory element. This regulatory element increases cell-type-specific expression of the tumor suppressor gene IGFBP5 and, thereby, reduces risk of estrogen receptor-positive breast cancer (odds ratio = 0.77, 95% CI 0.74-0.81, p = 3.1 x 10(-31)).Peer reviewe