| 1. |
- Campbell, PJ, et al.
(författare)
-
Pan-cancer analysis of whole genomes
- 2020
-
Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 578:7793, s. 82-
-
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.
|
|
| 2. |
|
|
| 3. |
|
|
| 4. |
|
|
| 5. |
|
|
| 6. |
|
|
| 7. |
|
|
| 8. |
- Hughes, T, et al.
(författare)
-
Analysis of autosomal genes reveals gene-sex interactions and higher total genetic risk in men with systemic lupus erythematosus
- 2012
-
Ingår i: Annals of the rheumatic diseases. - : BMJ. - 1468-2060 .- 0003-4967. ; 71:5, s. 694-699
-
Tidskriftsartikel (refereegranskat)abstract
- Systemic lupus erythematosus (SLE) is a sexually dimorphic autoimmune disease which is more common in women, but affected men often experience a more severe disease. The genetic basis of sexual dimorphism in SLE is not clearly defined. A study was undertaken to examine sex-specific genetic effects among SLE susceptibility loci.MethodsA total of 18 autosomal genetic susceptibility loci for SLE were genotyped in a large set of patients with SLE and controls of European descent, consisting of 5932 female and 1495 male samples. Sex-specific genetic association analyses were performed. The sex–gene interaction was further validated using parametric and non-parametric methods. Aggregate differences in sex-specific genetic risk were examined by calculating a cumulative genetic risk score for SLE in each individual and comparing the average genetic risk between male and female patients.ResultsA significantly higher cumulative genetic risk for SLE was observed in men than in women. (P=4.52x10-8) A significant sex–gene interaction was seen primarily in the human leucocyte antigen (HLA) region but also in IRF5, whereby men with SLE possess a significantly higher frequency of risk alleles than women. The genetic effect observed in KIAA1542 is specific to women with SLE and does not seem to have a role in men.ConclusionsThe data indicate that men require a higher cumulative genetic load than women to develop SLE. These observations suggest that sex bias in autoimmunity could be influenced by autosomal genetic susceptibility loci.
|
|
| 9. |
|
|
| 10. |
|
|
