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Gains and losses of DNA are prevalent in cancer and emerge as a consequence of inter-related processes of replication stress, mitotic errors, spindle multipolarity and breakage–fusion–bridge cycles, among others, which may lead to chromosomal instability and aneuploidy 1 , 2 . These copy number alterations contribute to cancer initiation, progression and therapeutic resistance 3 – 5 . Here we present a conceptual framework to examine the patterns of copy number alterations in human cancer that is widely applicable to diverse data types, including whole-genome sequencing, whole-exome sequencing, reduced representation bisulfite sequencing, single-cell DNA sequencing and SNP6 microarray data. Deploying this framework to 9,873 cancers representing 33 human cancer types from The Cancer Genome Atlas 6 revealed a set of 21 copy number signatures that explain the copy number patterns of 97% of samples. Seventeen copy number signatures were attributed to biological phenomena of whole-genome doubling, aneuploidy, loss of heterozygosity, homologous recombination deficiency, chromothripsis and haploidization. The aetiologies of four copy number signatures remain unexplained. Some cancer types harbour amplicon signatures associated with extrachromosomal DNA, disease-specific survival and proto-oncogene gains such as MDM2 . In contrast to base-scale mutational signatures, no copy number signature was associated with many known exogenous cancer risk factors. Our results synthesize the global landscape of copy number alterations in human cancer by revealing a diversity of mutational processes that give rise to these alterations. A new framework enables a pan-cancer reference set of copy number signatures derived from allele-specific profiles from different experimental assays.

Background High tumor mutational burden (TMB) is an emerging biomarker of sensitivity to immune checkpoint inhibitors and has been shown to be more significantly associated with response to PD-1 and PD-L1 blockade immunotherapy than PD-1 or PD-L1 expression, as measured by immunohistochemistry (IHC). The distribution of TMB and the subset of patients with high TMB has not been well characterized in the majority of cancer types. Methods In this study, we compare TMB measured by a targeted comprehensive genomic profiling (CGP) assay to TMB measured by exome sequencing and simulate the expected variance in TMB when sequencing less than the whole exome. We then describe the distribution of TMB across a diverse cohort of 100,000 cancer cases and test for association between somatic alterations and TMB in over 100 tumor types. Results We demonstrate that measurements of TMB from comprehensive genomic profiling are strongly reflective of measurements from whole exome sequencing and model that below 0.5 Mb the variance in measurement increases significantly. We find that a subset of patients exhibits high TMB across almost all types of cancer, including many rare tumor types, and characterize the relationship between high TMB and microsatellite instability status. We find that TMB increases significantly with age, showing a 2.4-fold difference between age 10 and age 90 years. Finally, we investigate the molecular basis of TMB and identify genes and mutations associated with TMB level. We identify a cluster of somatic mutations in the promoter of the gene PMS2 , which occur in 10% of skin cancers and are highly associated with increased TMB. Conclusions These results show that a CGP assay targeting ~1.1 Mb of coding genome can accurately assess TMB compared with sequencing the whole exome. Using this method, we find that many disease types have a substantial portion of patients with high TMB who might benefit from immunotherapy. Finally, we identify novel, recurrent promoter mutations in PMS2 , which may be another example of regulatory mutations contributing to tumorigenesis.

Individuals with Li-Fraumeni syndrome have a high lifetime risk of developing cancer. We assessed the feasibility and potential clinical effect of a comprehensive surveillance protocol in asymptomatic TP53 mutation carriers in families with this syndrome. We implemented a clinical surveillance protocol, using frequent biochemical and imaging studies, for asymptomatic TP53 mutation carriers on Jan 1, 2004, and did a prospective observational study of members of eight families with Li-Fraumeni syndrome who either chose to undergo surveillance or chose not to undergo surveillance. The primary outcome measure was detection of new cancers. The secondary outcome measure was overall survival. As of Nov 1, 2010, 33 TP53 mutation carriers were identified, 18 of whom underwent surveillance. The surveillance protocol detected ten asymptomatic tumours in seven patients, including small, high-grade tumours and low-grade or premalignant tumours. All seven mutation carriers were alive after a median follow-up of 24 months (IQR 22–65 months). 12 high-grade, high-stage tumours developed in 10 individuals in the non-surveillance group, two of whom (20%) were alive at the end of follow-up (p=0·0417 for comparison with survival in the surveillance group). 3-year overall survival was 100% in the surveillance group and 21% (95% CI 4–48%) in the non-surveillance group (p=0·0155). Our findings show the feasibility of a clinical surveillance protocol for the detection of asymptomatic neoplasms in individuals with germline TP53 mutations. This strategy offers a management option for affected individuals, and its benefits lend support to the use of early genetic testing of at-risk individuals and families. Canadian Cancer Society Research Institute, Canadian Institutes of Health Research, SickKids Foundation, and Soccer for Hope.

Germline pathogenic TP53 variants predispose individuals to a high lifetime risk of developing multiple cancers and are the hallmark feature of Li-Fraumeni syndrome (LFS). Our group has previously shown that LFS patients harbor shorter plasma cell-free DNA fragmentation; independent of cancer status. To understand the functional underpinning of cfDNA fragmentation in LFS, we conducted a fragmentomic analysis of 199 cfDNA samples from 82 TP53 mutation carriers and 30 healthy TP53 -wildtype controls. We find that LFS individuals exhibit an increased prevalence of A/T nucleotides at fragment ends, dysregulated nucleosome positioning at p53 binding sites, and loci-specific changes in chromatin accessibility at development-associated transcription factor binding sites and at cancer-associated open chromatin regions. Machine learning classification resulted in robust differentiation between TP53 mutant versus wildtype cfDNA samples (AUC-ROC = 0.710–1.000) and intra-patient longitudinal analysis of ctDNA fragmentation signal enabled early cancer detection. These results suggest that cfDNA fragmentation may be a useful diagnostic tool in LFS patients and provides an important baseline for cancer early detection. Here, Wong et al investigate the cell-free DNA landscape of individuals with Li-Fraumeni syndrome (LFS), a cancer predisposition, and find altered composition compared to non-LFS individuals which can be used to detect and track cancer development.

Background Simple translocations and complex rearrangements are formed through illegitimate ligations of double-strand breaks of fusion partners and lead to generation of oncogenic fusion genes that affect cellular function. The contact first hypothesis states that fusion partners tend to colocalize prior to fusion in normal cells. Here we test this hypothesis at the single-cell level and explore the underlying mechanism. Results By analyzing published single-cell diploid Hi-C datasets, we find partner genes fused in leukemia exhibit smaller spatial distances than those fused in solid tumor and control gene pairs. Intriguingly, multiple partners tend to colocalize with KMT2A in the same cell. 3D genome architecture has little association with lineage decision of KMT2A fusion types in leukemia. Besides simple translocations, complex rearrangement-related KMT2A fusion genes (CRGs) also show closer proximity and belong to a genome-wide mutual proximity network. We find CRGs are co-expressed, co-localized, and enriched in the targets of the transcriptional factor RUNX1, suggesting they may be involved in RUNX1-mediated transcription factories. Knockdown of RUNX1 leads to significantly fewer contacts among CRGs. We also find CRGs are enriched in active transcriptional regions and loop anchors, and exhibit high levels of TOP2-mediated DNA breakages. Inhibition of transcription leads to reduced DNA breakages of CRGs. Conclusions Our results demonstrate KMT2A partners and CRGs may form dynamic and multipartite spatial clusters in individual cells that may be involved in RUNX1-mediated transcription factories, wherein massive DNA damages and illegitimate ligations of genes may occur, leading to complex rearrangements and KMT2A fusions in leukemia.

Non-homologous chromosomal contacts (NHCCs) between different chromosomes participate considerably in gene and genome regulation. Due to analytical challenges, NHCCs are currently considered as singular, stochastic events, and their extent and fundamental principles across cell types remain controversial. We develop a supervised and unsupervised learning algorithm, termed Signature , to call NHCCs in Hi-C datasets to advance our understanding of genome topology. Signature reveals 40,282 NHCCs and their properties across 62 Hi-C datasets of 53 diploid human cell types. Genomic regions of NHCCs are gene-dense, highly expressed, and harbor genes for cell-specific and sex-specific functions. Extensive inter- telomeric and inter- centromeric clustering occurs across cell types [Rabl’s configuration] and 61 NHCCs are consistently found at the nuclear speckles. These constitutive ‘anchor loci’ facilitate an axis of genome activity whilst cell-type-specific NHCCs act in discrete hubs. Our results suggest that non-random chromosome positioning is supported by constitutive NHCCs that shape genome topology along an off-centered spatial gradient of genome activity. The authors develop a supervised and unsupervised learning algorithm Signature. Machine learning and network model analysis of Hi-C datasets across 62 2n genomes suggest that inter-chromosomal contacts demarcate genome topology along a spatial gradient of genome activity.

Haplotypes are often critical for the interpretation of genetic laboratory observations into medically actionable findings. Current massively parallel DNA sequencing technologies produce short sequence reads that are often unable to resolve haplotype information. Phasing short read data typically requires supplemental statistical phasing based on known haplotype structure in the population or parental genotypic data. Here we demonstrate that the MinION nanopore sequencer is capable of producing very long reads to resolve both variants and haplotypes of HLA-A , HLA-B and CYP2D6 genes important in determining patient drug response in sample NA12878 of CEPH/UTAH pedigree 1463, without the need for statistical phasing. Long read data from a single 24-hour nanopore sequencing run was used to reconstruct haplotypes, which were confirmed by HapMap data and statistically phased Complete Genomics and Sequenom genotypes. Our results demonstrate that nanopore sequencing is an emerging standalone technology with potential utility in a clinical environment to aid in medical decision-making.

Technological advances have enabled the analysis of cellular protein and RNA levels with unprecedented depth and sensitivity, allowing for an unbiased re-evaluation of gene regulation during fundamental biological processes. Here, we have chronicled the dynamics of protein and mRNA expression levels across a minimally perturbed cell cycle in human myeloid leukemia cells using centrifugal elutriation combined with mass spectrometry-based proteomics and RNA-Seq, avoiding artificial synchronization procedures. We identify myeloid-specific gene expression and variations in protein abundance, isoform expression and phosphorylation at different cell cycle stages. We dissect the relationship between protein and mRNA levels for both bulk gene expression and for over ∼6000 genes individually across the cell cycle, revealing complex, gene-specific patterns. This data set, one of the deepest surveys to date of gene expression in human cells, is presented in an online, searchable database, the Encyclopedia of Proteome Dynamics (http://www.peptracker.com/epd/). Cells are complex environments: at any one time, thousands of different genes act as molecular templates to produce messenger RNA (mRNA) molecules, which themselves are templates used to produce proteins. However, not all genes are active at all times inside all cells: as cells grow and divide as part of the cell division cycle, genes are switched on and off on a regular basis. Similarly, the patterns of mRNA and protein production are different in, say, immune and skin cells. In recent years, the tools available for detecting mRNA molecules and proteins have become more powerful, allowing researchers to move beyond just measuring the total amounts of mRNA and protein in the cell to now measuring individual amounts of specific mRNA and protein molecules encoded by specific genes. However, it has been a challenge to make these measurements at different stages of the cell cycle. Most of the methods used to do this have involved artificially ‘arresting’ the cell cycle, which can lead to side effects that are difficult to account for. Ly et al. have now overcome these problems using a combination of three methods to measure the levels of mRNA and protein molecules associated with over 6000 genes in human cancer cells derived from myeloid leukemia. Exploiting the fact that cells change size during the cell cycle, Ly et al. used a centrifugation technique to separate cells based on their size and, therefore, the stage of the cell cycle they were at, thus avoiding the need to arrest the cell cycle. An approach called RNA-Seq was then employed to measure the levels of the different mRNA molecules in the cells, and a device called a mass spectrometer was used to identify and measure the levels of many different proteins. In addition to being able to follow the level of mRNA and protein production for a large number of genes throughout the cell division cycle, while also obtaining detailed information about how many of the proteins are modified, Ly et al. discovered that—contrary to expectations—low numbers of mRNA molecules were sometimes associated with high numbers of the corresponding protein, and vice versa. This work provides a better understanding of the complex relationship between the levels of an mRNA and its corresponding protein product, and also demonstrates how it may be possible to detect subtle but important differences between cell types and disease states, including different types of cancer.

DNA copy number variations (CNVs) are a significant and ubiquitous source of inherited human genetic variation. However, the importance of CNVs to cancer susceptibility and tumor progression has not yet been explored. Li-Fraumeni syndrome (LFS) is an autosomal dominantly inherited disorder characterized by a strikingly increased risk of early-onset breast cancer, sarcomas, brain tumors and other neoplasms in individuals harboring germline TP53 mutations. Known genetic determinants of LFS do not fully explain the variable clinical phenotype in affected family members. As part of a wider study of CNVs and cancer, we conducted a genome-wide profile of germline CNVs in LFS families. Here, by examining DNA from a large healthy population and an LFS cohort using high-density oligonucleotide arrays, we show that the number of CNVs per genome is well conserved in the healthy population, but strikingly enriched in these cancer-prone individuals. We found a highly significant increase in CNVs among carriers of germline TP53 mutations with a familial cancer history. Furthermore, we identified a remarkable number of genomic regions in which known cancer-related genes coincide with CNVs, in both LFS families and healthy individuals. Germline CNVs may provide a foundation that enables the more dramatic chromosomal changes characteristic of TP53-related tumors to be established. Our results suggest that screening families predisposed to cancer for CNVs may identify individuals with an abnormally high number of these events.

Determination of recombination rates across the human genome has been constrained by the limited resolution and accuracy of existing genetic maps and the draft genome sequence. We have genotyped 5,136 microsatellite markers for 146 families, with a total of 1,257 meiotic events, to build a high-resolution genetic map meant to: (i) improve the genetic order of polymorphic markers; (ii) improve the precision of estimates of genetic distances; (iii) correct portions of the sequence assembly and SNP map of the human genome; and (iv) build a map of recombination rates. Recombination rates are significantly correlated with both cytogenetic structures (staining intensity of G bands) and sequence (GC content, CpG motifs and poly(A)/poly(T) stretches). Maternal and paternal chromosomes show many differences in locations of recombination maxima. We detected systematic differences in recombination rates between mothers and between gametes from the same mother, suggesting that there is some underlying component determined by both genetic and environmental factors that affects maternal recombination rates.