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- Campbell, PJ, et al.
(author)
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Pan-cancer analysis of whole genomes
- 2020
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In: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 578:7793, s. 82-
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Journal article (peer-reviewed)abstract
- Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1–3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10–18.
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- Wang, HD, et al.
(author)
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Global, regional, national, and selected subnational levels of stillbirths, neonatal, infant, and under-5 mortality, 1980-2015: a systematic analysis for the Global Burden of Disease Study 2015
- 2016
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In: Lancet (London, England). - : Elsevier. - 1474-547X .- 0140-6736. ; 388:10053, s. 1725-1774
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- Chen, W, et al.
(author)
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Temperature and pressure dependences of the Mn2+ and donor-acceptor emissions in ZnS : Mn2+ nanoparticles
- 2002
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In: Applied Physics Reviews. - : AIP Publishing. - 1931-9401. ; 92:4, s. 1950-1955
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Journal article (peer-reviewed)abstract
- Temperature and pressure dependent measurements have been performed on 3.5 nm ZnS:Mn2+ nanoparticles. As temperature increases, the donor-acceptor (DA) emission of ZnS:Mn2+ nanoparticles at 440 nm shifts to longer wavelengths while the Mn2+ emission (T-4(1)-(6)A(1)) shifts to shorter wavelengths. Both the DA and Mn2+ emission intensities decrease with temperature with the intensity decrease of the DA emission being much more pronounced. The intensity decreases are fit well with the theory of thermal quenching. As pressure increases, the Mn2+ emission shifts to longer wavelengths while the DA emission wavelength remains almost constant. The pressure coefficient of the DA emission in ZnS:Mn2+ nanoparticles is approximately -3.2 meV/GPa, which is significantly smaller than that measured for bulk materials. The relatively weak pressure dependence of the DA emission is attributed to the increase of the binding energies and the localization of the defect wave functions in nanoparticles. The pressure coefficient of Mn2+ emission in ZnS:Mn2+ nanoparticles is roughly -34.3 meV/GPa, consistent with crystal field theory. The results indicate that the energy transfer from the ZnS host to Mn2+ ions is mainly from the recombination of carriers localized at Mn2+ ions. (C) 2002 American Institute of Physics.
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- Kang, JS, et al.
(author)
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Risk prediction for malignant intraductal papillary mucinous neoplasm of the pancreas: logistic regression versus machine learning
- 2020
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In: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 10:1, s. 20140-
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Journal article (peer-reviewed)abstract
- Most models for predicting malignant pancreatic intraductal papillary mucinous neoplasms were developed based on logistic regression (LR) analysis. Our study aimed to develop risk prediction models using machine learning (ML) and LR techniques and compare their performances. This was a multinational, multi-institutional, retrospective study. Clinical variables including age, sex, main duct diameter, cyst size, mural nodule, and tumour location were factors considered for model development (MD). After the division into a MD set and a test set (2:1), the best ML and LR models were developed by training with the MD set using a tenfold cross validation. The test area under the receiver operating curves (AUCs) of the two models were calculated using an independent test set. A total of 3,708 patients were included. The stacked ensemble algorithm in the ML model and variable combinations containing all variables in the LR model were the most chosen during 200 repetitions. After 200 repetitions, the mean AUCs of the ML and LR models were comparable (0.725 vs. 0.725). The performances of the ML and LR models were comparable. The LR model was more practical than ML counterpart, because of its convenience in clinical use and simple interpretability.
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- Lu, HX, et al.
(author)
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Combinatorial protein therapy of angiogenic and arteriogenic factors remarkably improves collaterogenesis and cardiac function in pigs
- 2007
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In: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424. ; 104:29, s. 12140-12145
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Journal article (peer-reviewed)abstract
- Establishment of functional and stable collaterals in the ischemic myocardium is crucial to restoring cardiac function after myocardial infarction. Here, we show that only dual delivery of a combination of angiogenic and arteriogenic factors to the ischemic myocardium could significantly reestablish stable collateral networks and improve myocardial perfusion and function. A combination of FGF-2 with PDGF-BB, two factors primarily targeting endothelial cells and vascular smooth muscle cells, remarkably promotes myocardial collateral growth and stabilizes the newly formed collateral networks, which significantly restore myocardial perfusion and function. Using various members of the PDGF family together with FGF-2 in an angiogenesis assay, we demonstrate that PDGFR-α is mainly involved in angiogenic synergism, whereas PDGFR-β mediates vessel stability signals. Our findings provide conceptual guidelines for the clinical development of proangiogenic/arteriogenic factors for the treatment of ischemic heart disease.
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- Ruilope, LM, et al.
(author)
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Design and Baseline Characteristics of the Finerenone in Reducing Cardiovascular Mortality and Morbidity in Diabetic Kidney Disease Trial
- 2019
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In: American journal of nephrology. - : S. Karger AG. - 1421-9670 .- 0250-8095. ; 50:5, s. 345-356
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Journal article (peer-reviewed)abstract
- <b><i>Background:</i></b> Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. <b><i>Patients and</i></b> <b><i>Methods:</i></b> The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate ≥25 mL/min/1.73 m<sup>2</sup> and albuminuria (urinary albumin-to-creatinine ratio ≥30 to ≤5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level α = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. <b><i>Conclusions:</i></b> FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049.
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- Zhang, D, et al.
(author)
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Spatial epigenome-transcriptome co-profiling of mammalian tissues
- 2023
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In: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 615616:79547955, s. 113-122
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Journal article (peer-reviewed)abstract
- Emerging spatial technologies, including spatial transcriptomics and spatial epigenomics, are becoming powerful tools for profiling of cellular states in the tissue context1–5. However, current methods capture only one layer of omics information at a time, precluding the possibility of examining the mechanistic relationship across the central dogma of molecular biology. Here, we present two technologies for spatially resolved, genome-wide, joint profiling of the epigenome and transcriptome by cosequencing chromatin accessibility and gene expression, or histone modifications (H3K27me3, H3K27ac or H3K4me3) and gene expression on the same tissue section at near-single-cell resolution. These were applied to embryonic and juvenile mouse brain, as well as adult human brain, to map how epigenetic mechanisms control transcriptional phenotype and cell dynamics in tissue. Although highly concordant tissue features were identified by either spatial epigenome or spatial transcriptome we also observed distinct patterns, suggesting their differential roles in defining cell states. Linking epigenome to transcriptome pixel by pixel allows the uncovering of new insights in spatial epigenetic priming, differentiation and gene regulation within the tissue architecture. These technologies are of great interest in life science and biomedical research.
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