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- Campbell, PJ, et al.
(författare)
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Pan-cancer analysis of whole genomes
- 2020
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 578:7793, s. 82-
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Tidskriftsartikel (refereegranskat)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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| 4. |
- Munn-Chernoff, M. A., et al.
(författare)
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Shared genetic risk between eating disorder- and substance-use-related phenotypes: Evidence from genome-wide association studies
- 2021
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Ingår i: Addiction Biology. - : Wiley. - 1355-6215 .- 1369-1600. ; 26:1
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Tidskriftsartikel (refereegranskat)abstract
- Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [r(g)], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from similar to 2400 to similar to 537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (r(g) = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (r(g) = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (r(g) = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (r(gs) = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors.
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| 7. |
- Niessen, Peter, et al.
(författare)
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Recent results from the amanda experiment
- 2003
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Ingår i: Proceedings of 38th Rencontres de Moriond on Electroweak Interactions and Unified Theories 15-22 Mar 2003. Les Arcs, France.
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Konferensbidrag (refereegranskat)abstract
- AMANDA (Antarctic Muon And Neutrino Detector Array) is a neutrino telescope built under the southern polar icecap and its scope is to explore the possibility to detect high energy cosmic neutrinos. This should generate insight into the powerful celestial objects where acceleration mechanisms can bring up to 10 20 eV. We describe the achievements and results from the AMANDA-B10 prototype and the preliminary results from the current AMANDA-II detector which show dramatic increase in sensitivity.
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| 10. |
- Leymarie, N., et al.
(författare)
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Interlaboratory Study on Differential Analysis of Protein Glycosylation by Mass Spectrometry: The ABRF Glycoprotein Research Multi-Institutional Study 2012
- 2013
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Ingår i: Molecular & Cellular Proteomics. - 1535-9476. ; 12:10, s. 2935-2951
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Tidskriftsartikel (refereegranskat)abstract
- One of the principal goals of glycoprotein research is to correlate glycan structure and function. Such correlation is necessary in order for one to understand the mechanisms whereby glycoprotein structure elaborates the functions of myriad proteins. The accurate comparison of glycoforms and quantification of glycosites are essential steps in this direction. Mass spectrometry has emerged as a powerful analytical technique in the field of glycoprotein characterization. Its sensitivity, high dynamic range, and mass accuracy provide both quantitative and sequence/structural information. As part of the 2012 ABRF Glycoprotein Research Group study, we explored the use of mass spectrometry and ancillary methodologies to characterize the glycoforms of two sources of human prostate specific antigen (PSA). PSA is used as a tumor marker for prostate cancer, with increasing blood levels used to distinguish between normal and cancer states. The glycans on PSA are believed to be biantennary N-linked, and it has been observed that prostate cancer tissues and cell lines contain more antennae than their benign counterparts. Thus, the ability to quantify differences in glycosylation associated with cancer has the potential to positively impact the use of PSA as a biomarker. We studied standard peptide-based proteomics/glycomics methodologies, including LC-MS/MS for peptide/glycopeptide sequencing and label-free approaches for differential quantification. We performed an interlaboratory study to determine the ability of different laboratories to correctly characterize the differences between glycoforms from two different sources using mass spectrometry methods. We used clustering analysis and ancillary statistical data treatment on the data sets submitted by participating laboratories to obtain a consensus of the glycoforms and abundances. The results demonstrate the relative strengths and weaknesses of top-down glycoproteomics, bottom-up glycoproteomics, and glycomics methods. T6G 2G2, Canada. [Cipollo, John F.; An, Yanming] US FDA, Ctr Biol Evaluat & Res, Bethesda, MD 20993 USA. [Desaire, Heather; Go, Eden P.] Univ Kansas, Lawrence, KS 66045 USA. [Goldman, Radoslav; Pompach, Petr; Sanda, Miloslav] Georgetown Univ, Dept Oncol, Washington, DC [Halim, Adnan; Larson, Goran; Nilsson, Jonas] Univ Gothenburg, Sahlgrenska Acad, Dept Clin Chem & [Hensbergen, Paul J.; Wuhrer, Manfred] Leiden Univ, Med Ctr, Biomol Mass Spectrometry Unit, NL- [Jabs, Wolfgang; Marx, Kristina; Resemann, Anja; Schweiger-Hufnagel, Ulrike; Suckau, Detlev] Bruker [Ly, Mellisa; Staples, Gregory O.] Agilent Technol, Agilent Labs, Santa Clara, CA 95051 USA. [Mechref, Yehia; Song, Ehwang] Texas Tech Univ, Dept Chem & Biochem, Lubbock, TX 79409 USA. [Nyalwidhe, Julius O.; Watson, Megan] Eastern Virginia Med Sch, Leroy T Canoles Jr Canc Res Ctr, Dept [Packer, Nicolle H.; Thaysen-Andersen, Morten] Macquarie Univ, Dept Chem & Biomol Sci, Biomol [Sihlbom, Carina] Gothenburg Univ, Prote Core Facil, Gothenburg, Sweden. [Tang, Haixu] Indiana Univ, Sch Informat, Bloomington, IN 47405 USA. [Valmuv, Leena] Finnish Red Cross Blood Serv, Helsinki 00310, Finland. [Wada, Yoshinao] Osaka Med Ctr Maternal & Child Hlth, Res Inst, Izumi Ku, Osaka 5941101, Japan.
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