| 1. |
- Classen, Aimee T., et al.
(författare)
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Direct and indirect effects of climate change on soil microbial and soil microbial-plant interactions : What lies ahead?
- 2015
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Ingår i: Ecosphere. - 2150-8925 .- 2150-8925. ; 6:8
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Tidskriftsartikel (refereegranskat)abstract
- Global change is altering species distributions and thus interactions among organisms. Organisms live in concert with thousands of other species, some beneficial, some pathogenic, some which have little to no effect in complex communities. Since natural communities are composed of organisms with very different life history traits and dispersal ability it is unlikely they will all respond to climatic change in a similar way. Disjuncts in plant-pollinator and plant-herbivore interactions under global change have been relatively well described, but plant-soil microorganism and soil microbe-microbe relationships have received less attention. Since soil microorganisms regulate nutrient transformations, provide plants with nutrients, allow co-existence among neighbors, and control plant populations, changes in soil microorganism-plant interactions could have significant ramifications for plant community composition and ecosystem function. In this paper we explore how climatic change affects soil microbes and soil microbe-plant interactions directly and indirectly, discuss what we see as emerging and exciting questions and areas for future research, and discuss what ramifications changes in these interactions may have on the composition and function of ecosystems.
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| 2. |
- Dolled-Filhart, Marisa, et al.
(författare)
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Classification of breast cancer using genetic algorithms and tissue microarrays
- 2006
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Ingår i: Clinical Cancer Research. - 1078-0432. ; 12:21, s. 6459-6468
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: A multitude of breast cancer mRNA profiling studies has stratified breast cancer and defined gene sets that correlate with outcome. However, the number of genes used to predict patient outcome or define tumor subtypes by RNA expression studies is variable, nonoverlapping, and generally requires specialized technologies that are beyond those used in the routine pathology laboratory. It would be ideal if the familiarity and streamlined nature of immunohistochemistry could be combined with the rigorously quantitative and highly specific properties of nucleic acid-based analysis to predict patient outcome. EXPERIMENTAL DESIGN: We have used AQUA-based objective quantitative analysis of tissue microarrays toward the goal of discovery of a minimal number of markers with maximal prognostic or predictive value that can be applied to the conventional formalin-fixed, paraffin-embedded tissue section. RESULTS: The minimal discovered multiplexed set of tissue biomarkers was GATA3, NAT1, and estrogen receptor. Genetic algorithms were then applied after division of our cohort into a training set of 223 breast cancer patients to discover a prospectively applicable solution that can define a subset of patients with 5-year survival of 96%. This algorithm was then validated on an internal validation set (n=223, 5-year survival=95.8%) and further validated on an independent cohort from Sweden, which showed 5-year survival of 92.7% (n=149). CONCLUSIONS: With further validation, this test has both the familiarity and specificity for widespread use in management of breast cancer. More generally, this work illustrates the potential for multiplexed biomarker discovery on the tissue microarray platform.
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| 3. |
- Giltnane, Jennifer M., et al.
(författare)
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Quantitative measurement of epidermal growth factor receptor is a negative predictive factor for tamoxifen response in hormone receptor - Positive premenopausal breast cancer
- 2007
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Ingår i: Journal of Clinical Oncology. - 1527-7755. ; 25:21, s. 3007-3014
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Tidskriftsartikel (refereegranskat)abstract
- Purpose Although there is evidence for interaction between epidermal growth factor receptor ( EGFR) and estrogen receptor ( ER), it is still not clear how this affects response to endocrine therapies like tamoxifen. Here we assess the relationship between EGFR expression and tamoxifen response, with a new quantitative technology. Patients and Methods A tissue microarray was constructed from breast cancer from a cohort of 564 patients enrolled in a randomized clinical trial for adjuvant tamoxifen treatment in early breast cancer, with a median follow-up of 14 years. EGFR expression was measured using automated quantitative analysis, a fluorescence-based method for quantitative analysis of in situ protein expression. Results In ER-positive patients, tamoxifen-treated patients with low EGFR expression ( n = 113) showed a significant effect by 2 years of adjuvant tamoxifen ( P = .01), in contrast to no treatment effect in the EGFR-high group ( n = 73, P = .69). The untreated group showed 49% v 57% 10-year recurrence-free survival for EGFR low versus high ( P = .466) in the corresponding group of ER-positive patients. A significant beneficial effect of tamoxifen treatment was seen in the EGFR-low group ( hazard ratio [ HR] = 0.43 ( 95% CI, 0.22 to 0.84; P = .013) in contrast to no effect in the EGFR-high group ( HR = 1.14; 95% CI, 0.59 to 2.22; P = .7) by using a Cox model. Conclusion This study provides clinical evidence that confirms the basic work that has shown high EGFR can indicate resistance to tamoxifen. It suggests that careful measurement of EGFR protein expression might define a subset of low-stage patients that could benefit from an alternative therapy.
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