| 1. |
- Bennett, Deborah, et al.
(author)
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Project TENDR : Targeting Environmental Neuro-Developmental Risks. The TENDR Consensus Statement
- 2016
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In: Journal of Environmental Health Perspectives. - : National Institute of Environmental Health Science. - 0091-6765 .- 1552-9924. ; 124:7, s. A118-A122
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Journal article (peer-reviewed)abstract
- Children in America today are at an unacceptably high risk of developing neurodevelopmental disorders that affect the brain and nervous system including autism, attention deficit hyperactivity disorder, intellectual disabilities, and other learning and behavioral disabilities. These are complex disorders with multiple causes-genetic, social, and environmental. The contribution of toxic chemicals to these disorders can be prevented. Approach: Leading scientific and medical experts, along with children's health advocates, came together in 2015 under the auspices of Project TENDR: Targeting Environmental Neuro-Developmental Risks to issue a call to action to reduce widespread exposures to chemicals that interfere with fetal and children's brain development. Based on the available scientific evidence, the TENDR authors have identified prime examples of toxic chemicals and pollutants that increase children's risks for neurodevelopmental disorders. These include chemicals that are used extensively in consumer products and that have become widespread in the environment. Some are chemicals to which children and pregnant women are regularly exposed, and they are detected in the bodies of virtually all Americans in national surveys conducted by the U.S. Centers for Disease Control and Prevention. The vast majority of chemicals in industrial and consumer products undergo almost no testing for developmental neurotoxicity or other health effects. Conclusion: Based on these findings, we assert that the current system in the United States for evaluating scientific evidence and making health-based decisions about environmental chemicals is fundamentally broken. To help reduce the unacceptably high prevalence of neurodevelopmental disorders in our children, we must eliminate or significantly reduce exposures to chemicals that contribute to these conditions. We must adopt a new framework for assessing chemicals that have the potential to disrupt brain development and prevent the use of those that may pose a risk. This consensus statement lays the foundation for developing recommendations to monitor, assess, and reduce exposures to neurotoxic chemicals. These measures are urgently needed if we are to protect healthy brain development so that current and future generations can reach their fullest potential.
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| 4. |
- Mucci, Lorelei A., et al.
(author)
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Nine-gene molecular signature is not associated with prostate cancer death in a watchful waiting cohort
- 2008
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In: Cancer Epidemiology, Biomarkers and Prevention. - Baltimore : Waverly Press. - 1055-9965 .- 1538-7755. ; 17:1, s. 249-251
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Journal article (peer-reviewed)abstract
- Tumor molecular markers hold promise to distinguish potentially lethal from indolent prostate cancer and to guide treatment choices. A previous study identified a nine-gene molecular signature in tumors associated with prostate-specific antigen relapse after prostatectomy. We examined this molecular model in relation to prostate cancer death among 172 men with initially localized disease. We quantified protein expression of the nine genes in tumors to classify progression risk. Accounting for clinical prognostic factors, the nine-gene model did not provide discrimination to predict lethal and indolent prostate cancer.
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| 5. |
- Mucci, Lorelei A., et al.
(author)
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Testing a multigene signature of prostate cancer death in the Swedish Watchful Waiting Cohort
- 2008
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In: Cancer Epidemiology, Biomarkers and Prevention. - Philadelphia : American Association for Cancer Research. - 1055-9965 .- 1538-7755. ; 17:7, s. 1682-1688
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Journal article (peer-reviewed)abstract
- Although prostate cancer is a leading cause of cancer death, most men die with and not from their disease, underscoring the urgency to distinguish potentially lethal from indolent prostate cancer. We tested the prognostic value of a previously identified multigene signature of prostate cancer progression to predict cancer-specific death. The Örebro Watchful Waiting Cohort included 172 men with localized prostate cancer of whom 40 died of prostate cancer. We quantified protein expression of the markers in tumor tissue by immunohistochemistry and stratified the cohort by quintiles according to risk classification. We accounted for clinical variables (age, Gleason, nuclear grade, and tumor volume) using Cox regression and calculated receiver operator curves to compare discriminatory ability. The hazard ratio of prostate cancer death increased with increasing risk classification by the multigene model, with a 16-fold greater risk comparing highest-risk versus lowest-risk strata, and predicted outcome independent of clinical factors (P = 0.002). The best discrimination came from combining information from the multigene markers and clinical data, which perfectly classified the lowest-risk stratum where no one developed lethal disease; using the two lowest-risk groups as reference, the hazard ratio (95% confidence interval) was 11.3 (4.0-32.8) for the highest-risk group and difference in mortality at 15 years was 60% (50-70%). The combined model provided greater discriminatory ability (area under the curve = 0.78) than the clinical model alone (area under the curve = 0.71; P = 0.04). Molecular tumor markers can add to clinical variables to help distinguish lethal and indolent prostate cancer and hold promise to guide treatment decisions.
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| 6. |
- Orlando, Ludovic, et al.
(author)
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Recalibrating Equus evolution using the genome sequence of an early Middle Pleistocene horse
- 2013
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 499:7456, s. 74-
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Journal article (peer-reviewed)abstract
- The rich fossil record of equids has made them a model for evolutionary processes(1). Here we present a 1.12-times coverage draft genome from a horse bone recovered from permafrost dated to approximately 560-780 thousand years before present (kyr BP)(2,3). Our data represent the oldest full genome sequence determined so far by almost an order of magnitude. For comparison, we sequenced the genome of a Late Pleistocene horse (43 kyr BP), and modern genomes of five domestic horse breeds (Equus ferus caballus), a Przewalski's horse (E. f. prze-walskii) and a donkey (E. asinus). Our analyses suggest that the Equus lineage giving rise to all contemporary horses, zebras and donkeys originated 4.0-4.5 million years before present (Myr BP), twice the conventionally accepted time to the most recent common ancestor of the genus Equus(4,5). We also find that horse population size fluctuated multiple times over the past 2 Myr, particularly during periods of severe climatic changes. We estimate that the Przewalski's and domestic horse populations diverged 38-72 kyr BP, and find no evidence of recent admixture between the domestic horse breeds and the Przewalski's horse investigated. This supports the contention that Przewalski's horses represent the last surviving wild horse population(6). We find similar levels of genetic variation among Przewalski's and domestic populations, indicating that the former are genetically viable and worthy of conservation efforts. We also find evidence for continuous selection on the immune system and olfaction throughout horse evolution. Finally, we identify 29 genomic regions among horse breeds that deviate from neutrality and show low levels of genetic variation compared to the Przewalski's horse. Such regions could correspond to loci selected early during domestication.
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| 7. |
- Raykova, Doroteya, 1986-, et al.
(author)
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A method for Boolean analysis of protein interactions at a molecular level
- 2022
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In: Nature Communications. - : Springer Nature. - 2041-1723. ; 13:1
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Journal article (peer-reviewed)abstract
- Determination of interactions between native proteins in cells is important for understanding function. Here the authors report MolBoolean as a method to detect interactions between endogenous proteins in subcellular compartments, using antibody-DNA conjugates for identification and signal amplification. Determining the levels of protein-protein interactions is essential for the analysis of signaling within the cell, characterization of mutation effects, protein function and activation in health and disease, among others. Herein, we describe MolBoolean - a method to detect interactions between endogenous proteins in various subcellular compartments, utilizing antibody-DNA conjugates for identification and signal amplification. In contrast to proximity ligation assays, MolBoolean simultaneously indicates the relative abundances of protein A and B not interacting with each other, as well as the pool of A and B proteins that are proximal enough to be considered an AB complex. MolBoolean is applicable both in fixed cells and tissue sections. The specific and quantifiable data that the method generates provide opportunities for both diagnostic use and medical research.
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| 8. |
- Rubin, Mark A., et al.
(author)
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Decreased alpha-methylacyl CoA racemase expression in localized prostate cancer is associated with an increased rate of biochemical recurrence and cancer-specific death
- 2005
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In: Cancer Epidemiology, Biomarkers and Prevention. - 1055-9965 .- 1538-7755. ; 18, s. 162A-162A
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Journal article (peer-reviewed)abstract
- alpha-Methylacyl CoA racemase (AMACR) is overexpressed in prostate cancer relative to benign prostatic tissue. AMACR expression is highest in localized prostate cancer and decreases in metastatic prostate cancer. Herein, we explored the use of AMACR as a biomarker for aggressive prostate cancer. AMACR protein expression was determined by immunohistochemistry using an image analysis system on two localized prostate cancer cohorts consisting of 204 men treated by radical prostatectomy and 188 men followed expectantly. The end points for the cohorts were time to prostate-specific antigen (PSA) failure (i.e., elevation > 0.2 ng/mL) and time to prostate cancer death in the watchful waiting cohort. Using a regression tree method, optimal AMACR protein expression cutpoints were determined to best differentiate prostate cancer outcome in each of the cohorts separately. Cox proportional hazard models were then employed to examine the effect of the AMACR cutpoint on prostate cancer outcome, and adjusted for clinical variables. Lower AMACR tissue expression was associated with worse prostate cancer outcome, independent of clinical variables (hazard ratio, 3.7 for PSA failure; P = 0.018; hazard ratio, 4.1 for prostate cancer death, P = 0.0006). Among those with both low AMACR expression and high Gleason score, the risk of prostate cancer death was 18-fold higher (P = 0.006). The AMACR cutpoint developed using prostate cancer-specific death as the end point predicted PSA failures independent of Gleason score, PSA, and margin status. This is the first study to show that AMACR expression is significantly associated with prostate cancer progression and suggests that not all surrogate end points may be optimal to define biomarkers of aggressive prostate cancer.
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| 10. |
- Sboner, Andrea, et al.
(author)
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Molecular sampling of prostate cancer: a dilemma for predicting disease progression
- 2010
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In: BMC Medical Genomics. - London, United Kingdom : BioMed Central. - 1755-8794. ; 3:8
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Journal article (peer-reviewed)abstract
- Background: Current prostate cancer prognostic models are based on pre-treatment prostate specific antigen (PSA) levels, biopsy Gleason score, and clinical staging but in practice are inadequate to accurately predict disease progression. Hence, we sought to develop a molecular panel for prostate cancer progression by reasoning that molecular profiles might further improve current clinical models. Methods: We analyzed a Swedish Watchful Waiting cohort with up to 30 years of clinical follow up using a novel method for gene expression profiling. This cDNA-mediated annealing, selection, ligation, and extension (DASL) method enabled the use of formalin-fixed paraffin-embedded transurethral resection of prostate (TURP) samples taken at the time of the initial diagnosis. We determined the expression profiles of 6100 genes for 281 men divided in two extreme groups: men who died of prostate cancer and men who survived more than 10 years without metastases (lethals and indolents, respectively). Several statistical and machine learning models using clinical and molecular features were evaluated for their ability to distinguish lethal from indolent cases. Results: Surprisingly, none of the predictive models using molecular profiles significantly improved over models using clinical variables only. Additional computational analysis confirmed that molecular heterogeneity within both the lethal and indolent classes is widespread in prostate cancer as compared to other types of tumors. Conclusions: The determination of the molecularly dominant tumor nodule may be limited by sampling at time of initial diagnosis, may not be present at time of initial diagnosis, or may occur as the disease progresses making the development of molecular biomarkers for prostate cancer progression challenging.
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