Membrane connectivity estimated by digital image analysis of HER2 immunohistochemistry is concordant with visual scoring and fluorescence in situ hybridization results: algorithm evaluation on breast cancer tissue microarrays

<p>Abstract</p> <p>Introduction</p> <p>The human epidermal growth factor receptor 2 (HER2) is an established biomarker for management of patients with breast cancer. While conventional testing of HER2 protein expression is based on semi-quantitative visual scoring of the immunohistochemistry (IHC) result, efforts to reduce inter-observer variation and to produce continuous estimates of the IHC data are potentiated by digital image analysis technologies.</p> <p>Methods</p> <p>HER2 IHC was performed on the tissue microarrays (TMAs) of 195 patients with an early ductal carcinoma of the breast. Digital images of the IHC slides were obtained by Aperio ScanScope GL Slide Scanner. Membrane connectivity algorithm (HER2-CONNECT™, Visiopharm) was used for digital image analysis (DA). A pathologist evaluated the images on the screen twice (visual evaluations: VE1 and VE2). HER2 fluorescence <it>in situ </it>hybridization (FISH) was performed on the corresponding sections of the TMAs. The agreement between the IHC HER2 scores, obtained by VE1, VE2, and DA was tested for individual TMA spots and patient's maximum TMA spot values (VE1max, VE2max, DAmax). The latter were compared with the FISH data. Correlation of the continuous variable of the membrane connectivity estimate with the FISH data was tested.</p> <p>Results</p> <p>The pathologist intra-observer agreement (VE1 and VE2) on HER2 IHC score was almost perfect: kappa 0.91 (by spot) and 0.88 (by patient). The agreement between visual evaluation and digital image analysis was almost perfect at the spot level (kappa 0.86 and 0.87, with VE1 and VE2 respectively) and at the patient level (kappa 0.80 and 0.86, with VE1max and VE2max, respectively). The DA was more accurate than VE in detection of FISH-positive patients by recruiting 3 or 2 additional FISH-positive patients to the IHC score 2+ category from the IHC 0/1+ category by VE1max or VE2max, respectively. The DA continuous variable of the membrane connectivity correlated with the FISH data (HER2 and CEP17 copy numbers, and HER2/CEP17 ratio).</p> <p>Conclusion</p> <p>HER2 IHC digital image analysis based on membrane connectivity estimate was in almost perfect agreement with the visual evaluation of the pathologist and more accurate in detection of HER2 FISH-positive patients. Most immediate benefit of integrating the DA algorithm into the routine pathology HER2 testing may be obtained by alerting/reassuring pathologists of potentially misinterpreted IHC 0/1+ versus 2+ cases.</p

Frontiers and Opportunities in Bioenergy Crop Microbiome Research Networks

Researchers from across the four United States Department of Energy Bioenergy Research Centers (BRCs) engaged in a microbiome workshop that focused on identifying challenges and collaboration opportunities to better understand bioenergy-relevant plant–microbe interactions. The virtual workshop included hands-on educational sessions and a keynote address on current best practices in microbiome science and community microbiome standards, as well as breakout sessions aimed at identifying microbiome-related data and measurements that should be prioritized, opportunities for and barriers to integrating plant metabolites to microbiome research, and strategies for more effectively integrating microbiome data and processes into existing models. Based on participant discussion, key findings of the workshop were the need to prioritize scaling data sharing across BRCs and the broader research community and securing collaborative infrastructure in the areas of microbiome-ecosystem modeling and molecular plant–microbe interactions. This workshop review highlights additional main findings from this event, to encourage cross-site and more holistic metaanalyses while promoting wide scientific community engagement across plant microbiome sciences

Impacts of altered precipitation regimes on soil communities and biogeochemistry in arid and semi-arid ecosystems

Altered precipitation patterns resulting from climate change will have particularly significant consequences in water-limited ecosystems, such as arid to semi-arid ecosystems, where discontinuous inputs of water control biological processes. Given that these ecosystems cover more than a third of Earth's terrestrial surface, it is important to understand how they respond to such alterations. Altered water availability may impact both aboveground and belowground communities and the interactions between these, with potential impacts on ecosystem functioning; however, most studies to date have focused exclusively on vegetation responses to altered precipitation regimes. To synthesize our understanding of potential climate change impacts on dryland ecosystems, we present here a review of current literature that reports the effects of precipitation events and altered precipitation regimes on belowground biota and biogeochemical cycling. Increased precipitation generally increases microbial biomass and fungal:bacterial ratio. Few studies report responses to reduced precipitation but the effects likely counter those of increased precipitation. Altered precipitation regimes have also been found to alter microbial community composition but broader generalizations are difficult to make. Changes in event size and frequency influences invertebrate activity and density with cascading impacts on the soil food web, which will likely impact carbon and nutrient pools. The long-term implications for biogeochemical cycling are inconclusive but several studies suggest that increased aridity may cause decoupling of carbon and nutrient cycling. We propose a new conceptual framework that incorporates hierarchical biotic responses to individual precipitation events more explicitly, including moderation of microbial activity and biomass by invertebrate grazing, and use this framework to make some predictions on impacts of altered precipitation regimes in terms of event size and frequency as well as mean annual precipitation. While our understanding of dryland ecosystems is improving, there is still a great need for longer term in situ manipulations of precipitation regime to test our model

Relative Abundance of and Composition within Fungal Orders Differ between Cheatgrass (Bromus tectorum) and Sagebrush (Artemisia tridentata)-Associated Soils

Nonnative Bromus tectorum (cheatgrass) is decimating sagebrush steppe, one of the largest ecosystems in the Western United States, and is causing regional-scale shifts in the predominant plant-fungal interactions. Sagebrush, a native perennial, hosts arbuscular mycorrhizal fungi (AMF), whereas cheatgrass, a winter annual, is a relatively poor host of AMF. This shift is likely intertwined with decreased carbon (C)-sequestration in cheatgrass-invaded soils and alterations in overall soil fungal community composition and structure, but the latter remain unresolved. We examined soil fungal communities using high throughput amplicon sequencing (ribosomal large subunit gene) in the 0-4 cm and 4-8 cm depth intervals of six cores from cheatgrass- and six cores from sagebrush-dominated soils. Sagebrush core surfaces (0-4 cm) contained higher nitrogen and total C than cheatgrass core surfaces; these differences mirrored the presence of glomalin related soil proteins (GRSP), which has been associated with AMF activity and increased C-sequestration. Fungal richness was not significantly affected by vegetation type, depth or an interaction of the two factors. However, the relative abundance of seven taxonomic orders was significantly affected by vegetation type or the interaction between vegetation type and depth. Teloschistales, Spizellomycetales, Pezizales and Cantharellales were more abundant in sagebrush libraries and contain mycorrhizal, lichenized and basal lineages of fungi. Only two orders (Coniochaetales and Sordariales), which contain numerous economically important pathogens and opportunistic saprotrophs, were more abundant in cheatgrass libraries. Pleosporales, Agaricales, Helotiales and Hypocreales were most abundant across all libraries, but the number of genera detected within these orders was as much as 29 times lower in cheatgrass relative to sagebrush libraries. These compositional differences between fungal communities associated with cheatgrass- and sagebrush-dominated soils warrant future research to examine soil fungal community composition across more sites and time points as well as in association with native grass species that also occupy cheatgrass-invaded ecosystems