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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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- Reynolds, SJ, et al.
(författare)
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Interlaboratory evaluation of endotoxin analyses in agricultural dusts - comparison of LAL assay and mass spectrometry
- 2005
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Ingår i: Journal of Environmental Monitoring. - : Royal Society of Chemistry (RSC). - 1464-0325 .- 1464-0333. ; 7:12, s. 1371-1377
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Tidskriftsartikel (refereegranskat)abstract
- Endotoxin exposure is associated with wheeze and asthma morbidity, while early life exposure may reduce risk of allergy and asthma. Unfortunately, it is difficult to compare endotoxin results from different laboratories and environments. We undertook this study to determine if lipopolysaccharide ( LPS) extraction efficiency could account for differences among laboratories. We generated and collected aerosols from chicken and swine barns, and corn processing. We randomly allocated side-by-side filter samples to five laboratories for Limulus assay of endotoxin. Lyophilized aliquots of filter extracts were analyzed for 3-hydroxy fatty acids ( 3-OHFAs) as a marker of LPS using gas chromatography-mass spectrometry. There were significant differences in endotoxin assay and GC-MS ( LPS) results between laboratories for all dust types ( p < 0.01). Patterns of differences between labs varied by dust type. Relationships between assay and GC/MS results also depended on dust type. The percentages of individual 3-OHFA chain lengths varied across labs ( p < 0.0001) suggesting that each lab recovered a different fraction of the LPS available. The presence of large amounts of particle associated LPS and absence of a freezing thawing cycle were associated with lower correlations between LPS and bioactivity, consistent with an absence of Limulus response to cell-bound endotoxin. These data suggest that extraction methods affect endotoxin measurements. The LAL methods may be most suitable when comparing exposures within similar environments; GC-MS offers additional information helpful in optimizing sample treatment and extraction. GC-MS may be of use when comparing across heterogeneous environments and should be considered for inclusion in future studies of human health outcomes.
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