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.

Characterizing Mutational Signatures in Human Cancer Cell Lines Reveals Episodic APOBEC Mutagenesis.

Multiple signatures of somatic mutations have been identified in cancer genomes. Exome sequences of 1,001 human cancer cell lines and 577 xenografts revealed most common mutational signatures, indicating past activity of the underlying processes, usually in appropriate cancer types. To investigate ongoing patterns of mutational-signature generation, cell lines were cultured for extended periods and subsequently DNA sequenced. Signatures of discontinued exposures, including tobacco smoke and ultraviolet light, were not generated in vitro. Signatures of normal and defective DNA repair and replication continued to be generated at roughly stable mutation rates. Signatures of APOBEC cytidine deaminase DNA-editing exhibited substantial fluctuations in mutation rate over time with episodic bursts of mutations. The initiating factors for the bursts are unclear, although retrotransposon mobilization may contribute. The examined cell lines constitute a resource of live experimental models of mutational processes, which potentially retain patterns of activity and regulation operative in primary human cancers.

Timing the Landmark Events in the Evolution of Clear Cell Renal Cell Cancer: TRACERx Renal.

Clear cell renal cell carcinoma (ccRCC) is characterized by near-universal loss of the short arm of chromosome 3, deleting several tumor suppressor genes. We analyzed whole genomes from 95 biopsies across 33 patients with clear cell renal cell carcinoma. We find hotspots of point mutations in the 5' UTR of TERT, targeting a MYC-MAX-MAD1 repressor associated with telomere lengthening. The most common structural abnormality generates simultaneous 3p loss and 5q gain (36% patients), typically through chromothripsis. This event occurs in childhood or adolescence, generally as the initiating event that precedes emergence of the tumor's most recent common ancestor by years to decades. Similar genomic changes drive inherited ccRCC. Modeling differences in age incidence between inherited and sporadic cancers suggests that the number of cells with 3p loss capable of initiating sporadic tumors is no more than a few hundred. Early development of ccRCC follows well-defined evolutionary trajectories, offering opportunity for early intervention.

African-specific molecular taxonomy of prostate cancer.

Prostate cancer is characterized by considerable geo-ethnic disparity. African ancestry is a significant risk factor, with mortality rates across sub-Saharan Africa of 2.7-fold higher than global averages1. The contributing genetic and non-genetic factors, and associated mutational processes, are unknown2,3. Here, through whole-genome sequencing of treatment-naive prostate cancer samples from 183 ancestrally (African versus European) and globally distinct patients, we generate a large cancer genomics resource for sub-Saharan Africa, identifying around 2 million somatic variants. Significant African-ancestry-specific findings include an elevated tumour mutational burden, increased percentage of genome alteration, a greater number of predicted damaging mutations and a higher total of mutational signatures, and the driver genes NCOA2, STK19, DDX11L1, PCAT1 and SETBP1. Examining all somatic mutational types, we describe a molecular taxonomy for prostate cancer differentiated by ancestry and defined as global mutational subtypes (GMS). By further including Chinese Asian data, we confirm that GMS-B (copy-number gain) and GMS-D (mutationally noisy) are specific to African populations, GMS-A (mutationally quiet) is universal (all ethnicities) and the African-European-restricted subtype GMS-C (copy-number losses) predicts poor clinical outcomes. In addition to the clinical benefit of including individuals of African ancestry, our GMS subtypes reveal different evolutionary trajectories and mutational processes suggesting that both common genetic and environmental factors contribute to the disparity between ethnicities. Analogous to gene-environment interaction-defined here as a different effect of an environmental surrounding in people with different ancestries or vice versa-we anticipate that GMS subtypes act as a proxy for intrinsic and extrinsic mutational processes in cancers, promoting global inclusion in landmark studies.

Genome sequencing and analysis of the Tasmanian devil and its transmissible cancer.

The Tasmanian devil (Sarcophilus harrisii), the largest marsupial carnivore, is endangered due to a transmissible facial cancer spread by direct transfer of living cancer cells through biting. Here we describe the sequencing, assembly, and annotation of the Tasmanian devil genome and whole-genome sequences for two geographically distant subclones of the cancer. Genomic analysis suggests that the cancer first arose from a female Tasmanian devil and that the clone has subsequently genetically diverged during its spread across Tasmania. The devil cancer genome contains more than 17,000 somatic base substitution mutations and bears the imprint of a distinct mutational process. Genotyping of somatic mutations in 104 geographically and temporally distributed Tasmanian devil tumors reveals the pattern of evolution and spread of this parasitic clonal lineage, with evidence of a selective sweep in one geographical area and persistence of parallel lineages in other populations.

The life history of 21 breast cancers.

Cancer evolves dynamically as clonal expansions supersede one another driven by shifting selective pressures, mutational processes, and disrupted cancer genes. These processes mark the genome, such that a cancer's life history is encrypted in the somatic mutations present. We developed algorithms to decipher this narrative and applied them to 21 breast cancers. Mutational processes evolve across a cancer's lifespan, with many emerging late but contributing extensive genetic variation. Subclonal diversification is prominent, and most mutations are found in just a fraction of tumor cells. Every tumor has a dominant subclonal lineage, representing more than 50% of tumor cells. Minimal expansion of these subclones occurs until many hundreds to thousands of mutations have accumulated, implying the existence of long-lived, quiescent cell lineages capable of substantial proliferation upon acquisition of enabling genomic changes. Expansion of the dominant subclone to an appreciable mass may therefore represent the final rate-limiting step in a breast cancer's development, triggering diagnosis.

Mutational processes molding the genomes of 21 breast cancers.

All cancers carry somatic mutations. The patterns of mutation in cancer genomes reflect the DNA damage and repair processes to which cancer cells and their precursors have been exposed. To explore these mechanisms further, we generated catalogs of somatic mutation from 21 breast cancers and applied mathematical methods to extract mutational signatures of the underlying processes. Multiple distinct single- and double-nucleotide substitution signatures were discernible. Cancers with BRCA1 or BRCA2 mutations exhibited a characteristic combination of substitution mutation signatures and a distinctive profile of deletions. Complex relationships between somatic mutation prevalence and transcription were detected. A remarkable phenomenon of localized hypermutation, termed "kataegis," was observed. Regions of kataegis differed between cancers but usually colocalized with somatic rearrangements. Base substitutions in these regions were almost exclusively of cytosine at TpC dinucleotides. The mechanisms underlying most of these mutational signatures are unknown. However, a role for the APOBEC family of cytidine deaminases is proposed.

Author Correction: The evolutionary history of lethal metastatic prostate cancer.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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.

Benchmarking small-variant genotyping in polyploids.

Genotyping from sequencing is the basis of emerging strategies in the molecular breeding of polyploid plants. However, compared with the situation for diploids, in which genotyping accuracies are confidently determined with comprehensive benchmarks, polyploids have been neglected; there are no benchmarks measuring genotyping error rates for small variants using real sequencing reads. We previously introduced a variant calling method, Octopus, that accurately calls germline variants in diploids and somatic mutations in tumors. Here, we evaluate Octopus and other popular tools on whole-genome tetraploid and hexaploid data sets created using in silico mixtures of diploid Genome in a Bottle (GIAB) samples. We find that genotyping errors are abundant for typical sequencing depths but that Octopus makes 25% fewer errors than other methods on average. We supplement our benchmarks with concordance analysis in real autotriploid banana data sets.

AmplificationTimeR: an R package for timing sequential amplification events.

MOTIVATION: Few methods exist for timing individual amplification events in regions of focal amplification. Current methods are also limited in the copy number states that they are able to time. Here we introduce AmplificationTimeR, a method for timing higher level copy number gains and inferring the most parsimonious order of events for regions that have undergone both single gains and whole genome duplication. Our method is an extension of established approaches for timing genomic gains. RESULTS: We can time more copy number states, and in states covered by other methods our results are comparable to previously published methods. AVAILABILITY AND IMPLEMENTATION: AmplificationTimer is freely available as an R package hosted at https://github.com/Wedge-lab/AmplificationTimeR.

Author Correction: Landscape of somatic mutations in 560 breast cancer whole-genome sequences.

In the Methods section of this Article, 'greater than' should have been 'less than' in the sentence 'Putative regions of clustered rearrangements were identified as having an average inter-rearrangement distance that was at least 10 times greater than the whole-genome average for the individual sample. '. The Article has not been corrected.

A practical guide to cancer subclonal reconstruction from DNA sequencing.

Subclonal reconstruction from bulk tumor DNA sequencing has become a pillar of cancer evolution studies, providing insight into the clonality and relative ordering of mutations and mutational processes. We provide an outline of the complex computational approaches used for subclonal reconstruction from single and multiple tumor samples. We identify the underlying assumptions and uncertainties in each step and suggest best practices for analysis and quality assessment. This guide provides a pragmatic resource for the growing user community of subclonal reconstruction methods.

Evolution and lineage dynamics of a transmissible cancer in Tasmanian devils.

Devil facial tumour 1 (DFT1) is a transmissible cancer clone endangering the Tasmanian devil. The expansion of DFT1 across Tasmania has been documented, but little is known of its evolutionary history. We analysed genomes of 648 DFT1 tumours collected throughout the disease range between 2003 and 2018. DFT1 diverged early into five clades, three spreading widely and two failing to persist. One clade has replaced others at several sites, and rates of DFT1 coinfection are high. DFT1 gradually accumulates copy number variants (CNVs), and its telomere lengths are short but constant. Recurrent CNVs reveal genes under positive selection, sites of genome instability, and repeated loss of a small derived chromosome. Cultured DFT1 cell lines have increased CNV frequency and undergo highly reproducible convergent evolution. Overall, DFT1 is a remarkably stable lineage whose genome illustrates how cancer cells adapt to diverse environments and persist in a parasitic niche.

Somatic mutations reveal asymmetric cellular dynamics in the early human embryo.

Somatic cells acquire mutations throughout the course of an individual's life. Mutations occurring early in embryogenesis are often present in a substantial proportion of, but not all, cells in postnatal humans and thus have particular characteristics and effects. Depending on their location in the genome and the proportion of cells they are present in, these mosaic mutations can cause a wide range of genetic disease syndromes and predispose carriers to cancer. They have a high chance of being transmitted to offspring as de novo germline mutations and, in principle, can provide insights into early human embryonic cell lineages and their contributions to adult tissues. Although it is known that gross chromosomal abnormalities are remarkably common in early human embryos, our understanding of early embryonic somatic mutations is very limited. Here we use whole-genome sequences of normal blood from 241 adults to identify 163 early embryonic mutations. We estimate that approximately three base substitution mutations occur per cell per cell-doubling event in early human embryogenesis and these are mainly attributable to two known mutational signatures. We used the mutations to reconstruct developmental lineages of adult cells and demonstrate that the two daughter cells of many early embryonic cell-doubling events contribute asymmetrically to adult blood at an approximately 2:1 ratio. This study therefore provides insights into the mutation rates, mutational processes and developmental outcomes of cell dynamics that operate during early human embryogenesis.

APOBEC3 mutational signatures are associated with extensive and diverse genomic instability across multiple tumour types.

BACKGROUND: The APOBEC3 (apolipoprotein B mRNA editing enzyme catalytic polypeptide 3) family of cytidine deaminases is responsible for two mutational signatures (SBS2 and SBS13) found in cancer genomes. APOBEC3 enzymes are activated in response to viral infection, and have been associated with increased mutation burden and TP53 mutation. In addition to this, it has been suggested that APOBEC3 activity may be responsible for mutations that do not fall into the classical APOBEC3 signatures (SBS2 and SBS13), through generation of double strand breaks.Previous work has mainly focused on the effects of APOBEC3 within individual tumour types using exome sequencing data. Here, we use whole genome sequencing data from 2451 primary tumours from 39 different tumour types in the Pan-Cancer Analysis of Whole Genomes (PCAWG) data set to investigate the relationship between APOBEC3 and genomic instability (GI). RESULTS AND CONCLUSIONS: We found that the number of classical APOBEC3 signature mutations correlates with increased mutation burden across different tumour types. In addition, the number of APOBEC3 mutations is a significant predictor for six different measures of GI. Two GI measures (INDELs attributed to INDEL signatures ID6 and ID8) strongly suggest the occurrence and error prone repair of double strand breaks, and the relationship between APOBEC3 mutations and GI remains when SNVs attributed to kataegis are excluded.We provide evidence that supports a model of cancer genome evolution in which APOBEC3 acts as a causative factor in the development of diverse and widespread genomic instability through the generation of double strand breaks. This has important implications for treatment approaches for cancers that carry APOBEC3 mutations, and challenges the view that APOBECs only act opportunistically at sites of single stranded DNA.

The architecture of clonal expansions in morphologically normal tissue from cancerous and non-cancerous prostates.

BACKGROUND: Up to 80% of cases of prostate cancer present with multifocal independent tumour lesions leading to the concept of a field effect present in the normal prostate predisposing to cancer development. In the present study we applied Whole Genome DNA Sequencing (WGS) to a group of morphologically normal tissue (n = 51), including benign prostatic hyperplasia (BPH) and non-BPH samples, from men with and men without prostate cancer. We assess whether the observed genetic changes in morphologically normal tissue are linked to the development of cancer in the prostate. RESULTS: Single nucleotide variants (P = 7.0 × 10-03, Wilcoxon rank sum test) and small insertions and deletions (indels, P = 8.7 × 10-06) were significantly higher in morphologically normal samples, including BPH, from men with prostate cancer compared to those without. The presence of subclonal expansions under selective pressure, supported by a high level of mutations, were significantly associated with samples from men with prostate cancer (P = 0.035, Fisher exact test). The clonal cell fraction of normal clones was always higher than the proportion of the prostate estimated as epithelial (P = 5.94 × 10-05, paired Wilcoxon signed rank test) which, along with analysis of primary fibroblasts prepared from BPH specimens, suggests a stromal origin. Constructed phylogenies revealed lineages associated with benign tissue that were completely distinct from adjacent tumour clones, but a common lineage between BPH and non-BPH morphologically normal tissues was often observed. Compared to tumours, normal samples have significantly less single nucleotide variants (P = 3.72 × 10-09, paired Wilcoxon signed rank test), have very few rearrangements and a complete lack of copy number alterations. CONCLUSIONS: Cells within regions of morphologically normal tissue (both BPH and non-BPH) can expand under selective pressure by mechanisms that are distinct from those occurring in adjacent cancer, but that are allied to the presence of cancer. Expansions, which are probably stromal in origin, are characterised by lack of recurrent driver mutations, by almost complete absence of structural variants/copy number alterations, and mutational processes similar to malignant tissue. Our findings have implications for treatment (focal therapy) and early detection approaches.

Landscape of somatic mutations in 560 breast cancer whole-genome sequences.

We analysed whole-genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. We found that 93 protein-coding cancer genes carried probable driver mutations. Some non-coding regions exhibited high mutation frequencies, but most have distinctive structural features probably causing elevated mutation rates and do not contain driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed twelve base substitution and six rearrangement signatures. Three rearrangement signatures, characterized by tandem duplications or deletions, appear associated with defective homologous-recombination-based DNA repair: one with deficient BRCA1 function, another with deficient BRCA1 or BRCA2 function, the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operating, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.

Tracing Lung Cancer Risk Factors Through Mutational Signatures in Never-Smokers.

Epidemiologic studies often rely on questionnaire data, exposure measurement tools, and/or biomarkers to identify risk factors and the underlying carcinogenic processes. An emerging and promising complementary approach to investigate cancer etiology is the study of somatic "mutational signatures" that endogenous and exogenous processes imprint on the cellular genome. These signatures can be identified from a complex web of somatic mutations thanks to advances in DNA sequencing technology and analytical algorithms. This approach is at the core of the Sherlock-Lung study (2018-ongoing), a retrospective case-only study of over 2,000 lung cancers in never-smokers (LCINS), using different patterns of mutations observed within LCINS tumors to trace back possible exposures or endogenous processes. Whole genome and transcriptome sequencing, genome-wide methylation, microbiome, and other analyses are integrated with data from histological and radiological imaging, lifestyle, demographic characteristics, environmental and occupational exposures, and medical records to classify LCINS into subtypes that could reveal distinct risk factors. To date, we have received samples and data from 1,370 LCINS cases from 17 study sites worldwide and whole-genome sequencing has been completed on 1,257 samples. Here, we present the Sherlock-Lung study design and analytical strategy, also illustrating some empirical challenges and the potential for this approach in future epidemiologic studies.