Kerstin Haase

Mutational signatures associated with tobacco smoking in human cancer

Assessing smoke damage in cancer genomes We have known for over 60 years that smoking tobacco is one of the most avoidable risk factors for cancer. Yet the detailed mechanisms by which tobacco smoke damages the genome and creates the mutations that ultimately cause cancer are still not fully understood. Alexandrov et al. examined mutational signatures and DNA methylation changes in over 5000 genome sequences from 17 different cancer types linked to smoking (see the Perspective by Pfeifer). They found a complex pattern of mutational signatures. Only cancers originating in tissues directly exposed to smoke showed a signature characteristic of the known tobacco carcinogen benzo[a]pyrene. One mysterious signature was shared by all smoking-associated cancers but is of unknown origin. Smoking had only a modest effect on DNA methylation. Science, this issue p. 618; see also p. 549 Tobacco smoke causes cancer through mutational processes that are more complex than previously thought. Tobacco smoking increases the risk of at least 17 classes of human cancer. We analyzed somatic mutations and DNA methylation in 5243 cancers of types for which tobacco smoking confers an elevated risk. Smoking is associated with increased mutation burdens of multiple distinct mutational signatures, which contribute to different extents in different cancers. One of these signatures, mainly found in cancers derived from tissues directly exposed to tobacco smoke, is attributable to misreplication of DNA damage caused by tobacco carcinogens. Others likely reflect indirect activation of DNA editing by APOBEC cytidine deaminases and of an endogenous clocklike mutational process. Smoking is associated with limited differences in methylation. The results are consistent with the proposition that smoking increases cancer risk by increasing the somatic mutation load, although direct evidence for this mechanism is lacking in some smoking-related cancer types.

Universal Patterns of Selection in Cancer and Somatic Tissues

Summary Cancer develops as a result of somatic mutation and clonal selection, but quantitative measures of selection in cancer evolution are lacking. We adapted methods from molecular evolution and applied them to 7,664 tumors across 29 cancer types. Unlike species evolution, positive selection outweighs negative selection during cancer development. On average, <1 coding base substitution/tumor is lost through negative selection, with purifying selection almost absent outside homozygous loss of essential genes. This allows exome-wide enumeration of all driver coding mutations, including outside known cancer genes. On average, tumors carry ∼4 coding substitutions under positive selection, ranging from <1/tumor in thyroid and testicular cancers to >10/tumor in endometrial and colorectal cancers. Half of driver substitutions occur in yet-to-be-discovered cancer genes. With increasing mutation burden, numbers of driver mutations increase, but not linearly. We systematically catalog cancer genes and show that genes vary extensively in what proportion of mutations are drivers versus passengers.

Recurrent mutation of IGF signalling genes and distinct patterns of genomic rearrangement in osteosarcoma

Osteosarcoma is a primary malignancy of bone that affects children and adults. Here, we present the largest sequencing study of osteosarcoma to date, comprising 112 childhood and adult tumours encompassing all major histological subtypes. A key finding of our study is the identification of mutations in insulin-like growth factor (IGF) signalling genes in 8/112 (7%) of cases. We validate this observation using fluorescence in situ hybridization (FISH) in an additional 87 osteosarcomas, with IGF1 receptor (IGF1R) amplification observed in 14% of tumours. These findings may inform patient selection in future trials of IGF1R inhibitors in osteosarcoma. Analysing patterns of mutation, we identify distinct rearrangement profiles including a process characterized by chromothripsis and amplification. This process operates recurrently at discrete genomic regions and generates driver mutations. It may represent an age-independent mutational mechanism that contributes to the development of osteosarcoma in children and adults alike.

The evolutionary history of 2,658 cancers

Cancer develops through a process of somatic evolution. Here, we use whole-genome sequencing of 2,778 tumour samples from 2,658 donors to reconstruct the life history, evolution of mutational processes, and driver mutation sequences of 39 cancer types. The early phases of oncogenesis are driven by point mutations in a small set of driver genes, often including biallelic inactivation of tumour suppressors. Early oncogenesis is also characterised by specific copy number gains, such as trisomy 7 in glioblastoma or isochromosome 17q in medulloblastoma. By contrast, increased genomic instability, a nearly four-fold diversification of driver genes, and an acceleration of point mutation processes are features of later stages. Copy-number alterations often occur in mitotic crises leading to simultaneous gains of multiple chromosomal segments. Timing analysis suggests that driver mutations often precede diagnosis by many years, and in some cases decades, providing a window of opportunity for early cancer detection.

Appraising the relevance of DNA copy number loss and gain in prostate cancer using whole genome DNA sequence data.

A variety of models have been proposed to explain regions of recurrent somatic copy number alteration (SCNA) in human cancer. Our study employs Whole Genome DNA Sequence (WGS) data from tumor samples (n = 103) to comprehensively assess the role of the Knudson two hit genetic model in SCNA generation in prostate cancer. 64 recurrent regions of loss and gain were detected, of which 28 were novel, including regions of loss with more than 15% frequency at Chr4p15.2-p15.1 (15.53%), Chr6q27 (16.50%) and Chr18q12.3 (17.48%). Comprehensive mutation screens of genes, lincRNA encoding sequences, control regions and conserved domains within SCNAs demonstrated that a two-hit genetic model was supported in only a minor proportion of recurrent SCNA losses examined (15/40). We found that recurrent breakpoints and regions of inversion often occur within Knudson model SCNAs, leading to the identification of ZNF292 as a target gene for the deletion at 6q14.3-q15 and NKX3.1 as a two-hit target at 8p21.3-p21.2. The importance of alterations of lincRNA sequences was illustrated by the identification of a novel mutational hotspot at the KCCAT42, FENDRR, CAT1886 and STCAT2 loci at the 16q23.1-q24.3 loss. Our data confirm that the burden of SCNAs is predictive of biochemical recurrence, define nine individual regions that are associated with relapse, and highlight the possible importance of ion channel and G-protein coupled-receptor (GPCR) pathways in cancer development. We concluded that a two-hit genetic model accounts for about one third of SCNA indicating that mechanisms, such haploinsufficiency and epigenetic inactivation, account for the remaining SCNA losses.

Portraits of genetic intra-tumour heterogeneity and subclonal selection across cancer types

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 question, 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 an unprecedented pan-cancer resource of comprehensively annotated subclonal events from whole-genome sequencing data.Continued evolution in cancers gives rise to intra-tumour heterogeneity (ITH), which is a major mechanism of therapeutic resistance and therefore an important clinical challenge. However, the extent, origin and drivers of ITH across cancer types are poorly understood. Here, we extensively characterise ITH across 2,778 cancer whole genome sequences from 36 cancer types. We demonstrate that nearly all tumours (95.1%) with sufficient sequencing depth contain evidence of recent subclonal expansions and most cancer types show clear signs of positive selection in both clonal and subclonal protein coding variants. We find distinctive subclonal patterns of driver gene mutations, fusions, structural variation and copy-number alterations across cancer types. Dynamic, tumour-type specific changes of mutational processes between subclonal expansions shape differences between clonal and subclonal events. Our results underline the importance of ITH and its drivers in tumour evolution and provide an unprecedented pan-cancer resource of extensively annotated subclonal events, laying a foundation for future cancer genomic studies.

33 PAN-cancer whole genome sequencing reveals patterns of subclonal mutations, signature changes and selection

Introduction During their development, tumour cells accumulate somatic mutations, structural variants and copy number alterations (CNAs). Driver events facilitate clonal expansions and lead to intra-tumour heterogeneity (ITH). While ITH is an important therapeutic challenge, its degree among different cancer types is largely unknown. Material and methods The pan-cancer analysis of whole genomes (PCAWG) enabled us to characterise ITH in an unprecedented set of 2778 tumour samples representing 36 histologically distinct cancer types. We applied six CNA callers and eleven subclonal reconstruction algorithms to integrate their solutions into robust consensus copy number profiles and subclonal reconstructions. Results and discussions Our analysis revealed pervasive ITH in all examined cancer types. We found at least one subclone in 96.7% of the 1801 samples for which we had statistical power to detect subclones. In addition, we find that the average proportions of subclonal point mutations, indels, SVs and CNAs are highly variable across cancer types. These observations suggest distinct evolutionary narratives of each histological cancer type. Analysis of dN/dS ratios shows clear signs of positive selection within both clonal and subclonal mutations. We also identified subclonal mutations in driver genes that are recurrently hit and we found a significant enrichment of subclonal mutations in genes responsible for chromatin regulation. More than 5% of tumours contain driver mutations in genes for which specific treatment is available only in subclones, indicating the importance of assessing the clonality of targeted mutations for clinical decisions. Mutational signatures in the analysed samples show changes in activity over the course of tumour development. Characteristic carcinogen signatures, e.g. UV light exposure in melanomas, make less contributions to subclonal than clonal mutations, while APOBEC-induced mutagenesis has increased activity during the subclonal phase. Conclusion The absence of a detectable driver mutation in a majority of subclones suggests that late tumour development is frequently driven by CNAs or genomic rearrangements, or that a significant number of late drivers have yet to be identified. We found that selection is widespread and likely the rule rather than the exception and we identified differential activity of mutational signatures, reflecting successive waves of subclonal expansion.

Characterization of Nigerian breast cancer reveals prevalent homologous recombination deficiency and aggressive molecular features

Racial/ethnic disparities in breast cancer mortality continue to widen but genomic studies rarely interrogate breast cancer in diverse populations. Through genome, exome, and RNA sequencing, we examined the molecular features of breast cancers using 194 patients from Nigeria and 1037 patients from The Cancer Genome Atlas (TCGA). Relative to Black and White cohorts in TCGA, Nigerian HR + /HER2 − tumors are characterized by increased homologous recombination deficiency signature, pervasive TP53 mutations, and greater structural variation—indicating aggressive biology. GATA3 mutations are also more frequent in Nigerians regardless of subtype. Higher proportions of APOBEC-mediated substitutions strongly associate with PIK3CA and CDH1 mutations, which are underrepresented in Nigerians and Blacks. PLK2, KDM6A, and B2M are also identified as previously unreported significantly mutated genes in breast cancer. This dataset provides novel insights into potential molecular mechanisms underlying outcome disparities and lay a foundation for deployment of precision therapeutics in underserved populations.Research on racial and ethnic influence on breast cancer mortality is stymied by a lack of genomic studies in diverse populations. Here, the authors genomically interrogate 194 Nigerian breast cancers, unveiling molecular features that could explain the high mortality rate from breast cancer in an indigenous African population.

Abstract 218: The evolutionary history of 2,658 cancers

Cancer develops through a continuous process of somatic evolution. Whole genome sequencing provides a snapshot of the tumor genome at the point of sampling, however, the data can contain information that permits the reconstruction of a tumor9s evolutionary past. Here, we apply such life history analyses on an unprecedented scale, to a set of 2,658 tumors spanning 39 cancer types. We estimated the timing of large chromosomal gains during tumor evolution, by comparing the rates of doubled to non-doubled point mutations within gained regions. Although we find that such events typically occur in the second half of clonal evolution, we also observe distinctive and early chromosomal gains in some cancer types, such as gains of chromosomes 7, 19 and 20 in glioblastoma, and isochromosome 17q in medulloblastoma. By integrating these results with the qualitative timing of individual driver mutations, we obtained an overall ranking, from early to late, of frequent somatic events per cancer type, which both identified novel patterns of tumor evolution, and incorporated additional detail into known models, such as the progression of APC-KRAS-TP53 in colorectal cancer proposed by Vogelstein and Fearon. To estimate how mutational processes acting on the tumor genome change over time, we classified mutations in each sample according to three broad time periods (early clonal, late clonal, and subclonal), and quantified the activity of mutational signatures in each period. Most mutational processes appear to remain remarkably constant, however, certain signatures show clear and consistent changes during clonal evolution. Particularly, mutational signatures associated with exposure to carcinogens, such as smoking and UV light, tend to decrease over time. In contrast, signatures associated with defective endogenous processes, such as APOBEC mutagenesis and defective double strand break repair, show an increase between early and late phases of tumor evolution. Making use of clock-like mutational signatures, we converted mutational time estimates for large events, such as whole genome duplication (WGD), and the emergence of the most recent common ancestor (MRCA), into real time estimates, which allowed us to combine our analyses into overall timelines of cancer evolution, per tumor type. For example, the typical timeline of ovarian adenocarcinoma development shows that early tumor evolution is characterized by mutations in TP53, and widespread genome instability, with WGD events taking place on average 8 years prior to diagnosis. In later stages of evolution, signatures of defective repair processes increase, and the MRCA emerges on average 1 year before diagnosis. Taken together, these data reveal the common and divergent evolutionary trajectories available to a cancer, which might be crucial in understanding specific tumor biology, and in providing new opportunities for early detection and cancer prevention. Citation Format: Clemency Jolly, Moritz Gerstung, Ignaty Leshchiner, Stefan C. Dentro, Santiago Gonzalez, Thomas J. Mitchell, Yulia Rubanova, Pavana Anur, Daniel Rosebrock, Kaixian Yu, Maxime Tarabichi, Amit Deshwar, Jeff Wintersinger, Kortine Kleinheinz, Ignacio Vasquez-Garcia, Kerstin Haase, Subhajit Sengupta, Geoff Macintyre, Salem Malikic, Nilgun Donmez, Dimitri G. Livitz, Mark Cmero, Jonas Demeulemeester, Steve Schumacher, Yu Fan, Xiaotong Yao, Juhee Lee, Matthias Schlesner, Paul C. Boutros, David D. Bowtell, Hongtu Zhu, Gad Getz, Marcin Imielinski, Rameen Beroukhim, S Cenk Sahinalp, Yuan Ji, Martin Peifer, Florian Markowetz, Ville Mustonen, Ke Juan, Wenyi Wang, Quaid D. Morris, Paul T. Spellman, David C. Wedge, Peter Van Loo, PCAWG Evolution and Heterogeneity Working Group. The evolutionary history of 2,658 cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 218.

Allele-specific multi-sample copy number segmentation

Motivation Allele-specific copy number alterations are commonly used to trace the evolution of tumours. A key step of the analysis is to segment genomic data into regions of constant copy number. For precise phylogenetic inference, breakpoints shared between samples need to be aligned to each other. Results Here we present asmultipcf, an algorithm for allele-specific segmentation of multiple samples that infers private and shared segment boundaries of phylogenetically related samples. The output of this algorithm can directly be used for allele-specific copy number calling using ASCAT. Availability asmultipcf is available as part of the ASCAT R package (version 2.5) from github.com/Crick-CancerGenomics/ascat