41 research outputs found
The evolutionary history of 2,658 cancers
Cancer develops through a process of somatic evolution1,2. Sequencing data from a single biopsy represent a snapshot of this process that can reveal the timing of specific genomic aberrations and the changing influence of mutational processes3. Here, by whole-genome sequencing analysis of 2,658 cancers as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA)4, we reconstruct the life history and evolution of mutational processes and driver mutation sequences of 38 types of cancer. Early oncogenesis is characterized by mutations in a constrained set of driver genes, and specific copy number gains, such as trisomy 7 in glioblastoma and isochromosome 17q in medulloblastoma. The mutational spectrum changes significantly throughout tumour evolution in 40% of samples. A nearly fourfold diversification of driver genes and increased genomic instability are features of later stages. Copy number alterations often occur in mitotic crises, and lead to simultaneous gains of chromosomal segments. Timing analyses suggest that driver mutations often precede diagnosis by many years, if not decades. Together, these results determine the evolutionary trajectories of cancer, and highlight opportunities for early cancer detection
Characterizing genetic intra-tumor heterogeneity across 2,658 human cancer genomes.
Intra-tumor heterogeneity (ITH) is a mechanism of therapeutic resistance and therefore an important clinical challenge. However, the extent, origin, and drivers of ITH across cancer types are poorly understood. To address this, we extensively characterize ITH across whole-genome sequences of 2,658 cancer samples spanning 38 cancer types. Nearly all informative samples (95.1%) contain evidence of distinct subclonal expansions with frequent branching relationships between subclones. We observe positive selection of subclonal driver mutations across most cancer types and identify cancer type-specific subclonal patterns of driver gene mutations, fusions, structural variants, and copy number alterations as well as dynamic changes in mutational processes between subclonal expansions. Our results underline the importance of ITH and its drivers in tumor evolution and provide a pan-cancer resource of comprehensively annotated subclonal events from whole-genome sequencing data
In vivo NMR as a tool for probing molecular structure and dynamics in intact Chlamydomonas reinhardtii cells
Solid state NMR/Biophysical Organic Chemistr
A Broad Line-width, Compact, Millimeter-bright Molecular Emission Line Source near the Galactic Center
A compact source, G0.02467-0.0727, was detected in Atacama Large Millimeter/submillimeter Array 3 mm observations in continuum and very broad line emission. The continuum emission has a spectral index α ≈ 3.3, suggesting that the emission is from dust. The line emission is detected in several transitions of CS, SO, and SO2 and exhibits a line width FWHM ≈ 160 km s−1. The line profile appears Gaussian. The emission is weakly spatially resolved, coming from an area on the sky ≲1″ in diameter (≲104 au at the distance of the Galactic center, GC). The centroid velocity is v LSR ≈ 40-50 km s−1, which is consistent with a location in the GC. With multiple SO lines detected, and assuming local thermodynamic equilibrium (LTE) conditions, the gas temperature is T LTE = 13 K, which is colder than seen in typical GC clouds, though we cannot rule out low-density, subthermally excited, warmer gas. Despite the high velocity dispersion, no emission is observed from SiO, suggesting that there are no strong (≳10 km s−1) shocks in the molecular gas. There are no detections at other wavelengths, including X-ray, infrared, and radio. We consider several explanations for the millimeter ultra-broad-line object (MUBLO), including protostellar outflow, explosive outflow, a collapsing cloud, an evolved star, a stellar merger, a high-velocity compact cloud, an intermediate-mass black hole, and a background galaxy. Most of these conceptual models are either inconsistent with the data or do not fully explain them. The MUBLO is, at present, an observationally unique object
Pan-cancer analysis of whole genomes
Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). 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 promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe
Mining the human phenome using allelic scores that index biological intermediates
J. Kaprio ja M-L. Lokki työryhmien jäseniä.It is common practice in genome-wide association studies (GWAS) to focus on the relationship between disease risk and genetic variants one marker at a time. When relevant genes are identified it is often possible to implicate biological intermediates and pathways likely to be involved in disease aetiology. However, single genetic variants typically explain small amounts of disease risk. Our idea is to construct allelic scores that explain greater proportions of the variance in biological intermediates, and subsequently use these scores to data mine GWAS. To investigate the approach's properties, we indexed three biological intermediates where the results of large GWAS meta-analyses were available: body mass index, C-reactive protein and low density lipoprotein levels. We generated allelic scores in the Avon Longitudinal Study of Parents and Children, and in publicly available data from the first Wellcome Trust Case Control Consortium. We compared the explanatory ability of allelic scores in terms of their capacity to proxy for the intermediate of interest, and the extent to which they associated with disease. We found that allelic scores derived from known variants and allelic scores derived from hundreds of thousands of genetic markers explained significant portions of the variance in biological intermediates of interest, and many of these scores showed expected correlations with disease. Genome-wide allelic scores however tended to lack specificity suggesting that they should be used with caution and perhaps only to proxy biological intermediates for which there are no known individual variants. Power calculations confirm the feasibility of extending our strategy to the analysis of tens of thousands of molecular phenotypes in large genome-wide meta-analyses. We conclude that our method represents a simple way in which potentially tens of thousands of molecular phenotypes could be screened for causal relationships with disease without having to expensively measure these variables in individual disease collections.Peer reviewe
Recommended from our members
Near-infrared variability study of the central 2.3 arcmin × 2.3 arcmin of the Galactic Centre - I. Catalogue of variable sources
We used 4-yr baseline Hubble Space Telescope/Wide Field Camera 3 IR observations of the Galactic Centre in the F153M band (1.53 μm) to identify variable stars in the central ~2.3 arcmin × 2.3 arcmin field.We classified 3845 long-term (periods from months to years) and 76 short-term (periods of a few days or less) variables among a total sample of 33 070 stars. For 36 of the latter ones, we also derived their periods (< 3 d). Our catalogue not only confirms bright long period variables and massive eclipsing binaries identified in previous works but also contains many newly recognized dim variable stars. For example, we found δ Scuti and RR Lyrae stars towards the Galactic Centre for the first time, as well as one BL Her star (period < 1.3 d). We cross-correlated our catalogue with previous spectroscopic studies and found that 319 variables have well-defined stellar types, such as Wolf-Rayet, OB main sequence, supergiants and asymptotic giant branch stars. We used colours and magnitudes to infer the probable variable types for those stars without accurately measured periods or spectroscopic information. We conclude that the majority of unclassified variables could potentially be eclipsing/ellipsoidal binaries and Type II Cepheids. Our source catalogue will be valuable for future studies aimed at constraining the distance, star formation history and massive binary fraction of the Milky Way nuclear star cluster
Recommended from our members
Near-infrared variability study of the central 2.3 × 2.3 arcmin2 of the Galactic Centre - II. Identification of RR Lyrae stars in the Milky Way nuclear star cluster
Because of strong and spatially highly variable interstellar extinction and extreme source crowding, the faint (K ≥ 15) stellar population in the Milky Way's nuclear star cluster is still poorly studied. RR Lyrae stars provide us with a tool to estimate the mass of the oldest, relative dim stellar population. Recently, we analysed HST/WFC3/IR observations of the central 2.3 × 2.3 arcmin2 of the Milky Way and found 21 variable stars with periods between 0.2 and 1 d. Here, we present a further comprehensive analysis of these stars. The period- luminosity relationship of RR Lyrae is used to derive their extinctions and distances. Using multiple approaches, we classify our sample as 4 RRc stars, 4 RRab stars, 3 RRab candidates and 10 binaries. Especially, the four RRab stars show sawtooth light curves and fall exactly on to the Oosterhoff I division in the Bailey diagram. Compared to the RRab stars reported by Minniti et al., our new RRab stars have higher extinction (AK > 1.8) and should be closer to the Galactic Centre. The extinction and distance of one RRab stars match those for the Milky Way's nuclear star cluster given in previous works. We perform simulations and find that after correcting for incompleteness, there could be not more than 40 RRab stars within the Milky Way's nuclear star cluster and in our field of view. Through comparing with the known globular clusters of the Milky Way, we estimate that if there exists an old, metal-poor (-1.5 < [Fe/H] < -1) stellar population in the Milky Way nuclear star cluster on a scale of 5 × 5 pc, then it contributes at most 4.7 × 105 M⊙, i.e. ~18 per cent of the stellar mass
Recommended from our members
Near-infrared variability study of the central 2.3 × 2.3 arcmin2 of the Galactic Centre - II. Identification of RR Lyrae stars in the Milky Way nuclear star cluster
Because of strong and spatially highly variable interstellar extinction and extreme source crowding, the faint (K ≥ 15) stellar population in the Milky Way's nuclear star cluster is still poorly studied. RR Lyrae stars provide us with a tool to estimate the mass of the oldest, relative dim stellar population. Recently, we analysed HST/WFC3/IR observations of the central 2.3 × 2.3 arcmin2 of the Milky Way and found 21 variable stars with periods between 0.2 and 1 d. Here, we present a further comprehensive analysis of these stars. The period- luminosity relationship of RR Lyrae is used to derive their extinctions and distances. Using multiple approaches, we classify our sample as 4 RRc stars, 4 RRab stars, 3 RRab candidates and 10 binaries. Especially, the four RRab stars show sawtooth light curves and fall exactly on to the Oosterhoff I division in the Bailey diagram. Compared to the RRab stars reported by Minniti et al., our new RRab stars have higher extinction (AK > 1.8) and should be closer to the Galactic Centre. The extinction and distance of one RRab stars match those for the Milky Way's nuclear star cluster given in previous works. We perform simulations and find that after correcting for incompleteness, there could be not more than 40 RRab stars within the Milky Way's nuclear star cluster and in our field of view. Through comparing with the known globular clusters of the Milky Way, we estimate that if there exists an old, metal-poor (-1.5 < [Fe/H] < -1) stellar population in the Milky Way nuclear star cluster on a scale of 5 × 5 pc, then it contributes at most 4.7 × 105 M⊙, i.e. ~18 per cent of the stellar mass