Lawrence Bower

A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing

As whole-genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Here using tumour-normal sample pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, we conduct a benchmarking exercise within the context of the International Cancer Genome Consortium. We compare sequencing methods, analysis pipelines and validation methods. We show that using PCR-free methods and increasing sequencing depth to ∼100 × shows benefits, as long as the tumour:control coverage ratio remains balanced. We observe widely varying mutation call rates and low concordance among analysis pipelines, reflecting the artefact-prone nature of the raw data and lack of standards for dealing with the artefacts. However, we show that, using the benchmark mutation set we have created, many issues are in fact easy to remedy and have an immediate positive impact on mutation detection accuracy.

Mutational signatures in esophageal adenocarcinoma define etiologically distinct subgroups with therapeutic relevance

Esophageal adenocarcinoma (EAC) has a poor outcome, and targeted therapy trials have thus far been disappointing owing to a lack of robust stratification methods. Whole-genome sequencing (WGS) analysis of 129 cases demonstrated that this is a heterogeneous cancer dominated by copy number alterations with frequent large-scale rearrangements. Co-amplification of receptor tyrosine kinases (RTKs) and/or downstream mitogenic activation is almost ubiquitous; thus tailored combination RTK inhibitor (RTKi) therapy might be required, as we demonstrate in vitro. However, mutational signatures showed three distinct molecular subtypes with potential therapeutic relevance, which we verified in an independent cohort (n = 87): (i) enrichment for BRCA signature with prevalent defects in the homologous recombination pathway; (ii) dominant T>G mutational pattern associated with a high mutational load and neoantigen burden; and (iii) C>A/T mutational pattern with evidence of an aging imprint. These subtypes could be ascertained using a clinically applicable sequencing strategy (low coverage) as a basis for therapy selection.

A comparative analysis of whole genome sequencing of esophageal adenocarcinoma pre- and post-chemotherapy

The scientific community has avoided using tissue samples from patients that have been exposed to systemic chemotherapy to infer the genomic landscape of a given cancer. Esophageal adenocarcinoma is a heterogeneous, chemoresistant tumor for which the availability and size of pretreatment endoscopic samples are limiting. This study compares whole-genome sequencing data obtained from chemo-naive and chemo-treated samples. The quality of whole-genomic sequencing data is comparable across all samples regardless of chemotherapy status. Inclusion of samples collected post-chemotherapy increased the proportion of late-stage tumors. When comparing matched pre- and post-chemotherapy samples from 10 cases, the mutational signatures, copy number, and SNV mutational profiles reflect the expected heterogeneity in this disease. Analysis of SNVs in relation to allele-specific copy-number changes pinpoints the common ancestor to a point prior to chemotherapy. For cases in which pre- and post-chemotherapy samples do show substantial differences, the timing of the divergence is near-synchronous with endoreduplication. Comparison across a large prospective cohort (62 treatment-naive, 58 chemotherapy-treated samples) reveals no significant differences in the overall mutation rate, mutation signatures, specific recurrent point mutations, or copy-number events in respect to chemotherapy status. In conclusion, whole-genome sequencing of samples obtained following neoadjuvant chemotherapy is representative of the genomic landscape of esophageal adenocarcinoma. Excluding these samples reduces the material available for cataloging and introduces a bias toward the earlier stages of cancer.

A Comprehensive Assessment of Somatic Mutation Calling in Cancer Genomes

The emergence of next generation DNA sequencing technology is enabling high-resolution cancer genome analysis. Large-scale projects like the International Cancer Genome Consortium (ICGC) are systematically scanning cancer genomes to identify recurrent somatic mutations. Second generation DNA sequencing, however, is still an evolving technology and procedures, both experimental and analytical, are constantly changing. Thus the research community is still defining a set of best practices for cancer genome data analysis, with no single protocol emerging to fulfil this role. Here we describe an extensive benchmark exercise to identify and resolve issues of somatic mutation calling. Whole genome sequence datasets comprising tumor-normal pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, were shared within the ICGC and submissions of somatic mutation calls were compared to verified mutations and to each other. Varying strategies to call mutations, incomplete awareness of sources of artefacts, and even lack of agreement on what constitutes an artefact or real mutation manifested in widely varying mutation call rates and somewhat low concordance among submissions. We conclude that somatic mutation calling remains an unsolved problem. However, we have identified many issues that are easy to remedy that are presented here. Our study highlights critical issues that need to be addressed before this valuable technology can be routinely used to inform clinical decision-making. Abbreviations and Definitions SSM Somatic Single-base Mutations or Simple Somatic Mutations, refers to a somatic single base change SIM Somatic Insertion/deletion Mutation CNV Copy Number Variant SV Structural Variant SNP Single Nucleotide Polymorphisms, refers to a single base variable position in the germline with a frequency of > 1% in the general population CLL Chronic Lymphocytic Leukaemia MB Medulloblastoma ICGC International Cancer Genome Consortium BM Benchmark aligner = mapper, these terms are used interchangeably

Whole-genome sequencing of nine esophageal adenocarcinoma cell lines.

Esophageal adenocarcinoma (EAC) is highly mutated and molecularly heterogeneous. The number of cell lines available for study is limited and their genome has been only partially characterized. The availability of an accurate annotation of their mutational landscape is crucial for accurate experimental design and correct interpretation of genotype-phenotype findings. We performed high coverage, paired end whole genome sequencing on eight EAC cell lines—ESO26, ESO51, FLO-1, JH-EsoAd1, OACM5.1 C, OACP4 C, OE33, SK-GT-4—all verified against original patient material, and one esophageal high grade dysplasia cell line, CP-D. We have made available the aligned sequence data and report single nucleotide variants (SNVs), small insertions and deletions (indels), and copy number alterations, identified by comparison with the human reference genome and known single nucleotide polymorphisms (SNPs). We compare these putative mutations to mutations found in primary tissue EAC samples, to inform the use of these cell lines as a model of EAC.

Low-cost and clinically applicable copy number profiling using repeat DNA

Large-scale cancer genome studies suggest that tumors are driven by somatic copy number alterations (SCNAs) or single-nucleotide variants (SNVs). Due to the low-cost, the clinical use of genomics assays is biased towards targeted gene panels, which identify SNVs. There is a need for a comparably low-cost and simple assay for high-resolution SCNA profiling. Here we present our method, conliga, which infers SCNA profiles from a low-cost and simple assay.

The landscape of selection in 551 Esophageal Adenocarcinomas defines genomic biomarkers for the clinic

Esophageal Adenocarcinoma (EAC) is a poor prognosis cancer type with rapidly rising incidence. Our understanding of genetic events which drive EAC development is limited and there are few molecular biomarkers for prognostication or therapeutics. We have accumulated a cohort of 551 genomically characterised EACs (73% WGS and 27% WES) with clinical annotation and matched RNA-seq. Using a variety of driver gene detection methods we discover 65 EAC drivers (66% novel) and describe mutation and CNV types with specific functional impact. We identify a mean of 3.7 driver events per case derived almost equally from copy number events and mutations. We compare driver mutation rates to the exome-wide mutational excess calculated using Non-synonymous vs Synonymous mutation rates (dNdS). We see mutual exclusivity or co-occurrence of events within and between a number of EAC pathways (GATA factors, Core Cell cycle genes, TP53 regulators and the SWI/SNF complex) suggestive of important functional relationships. These driver variants correlate with tumour differentiation, sex and prognosis. Poor prognostic indicators (SMAD4, GATA4) are verified in independent cohorts with significant predictive value. Over 50% of EACs contain sensitising events for CDK4/6 inhibitors which are highly correlated with clinically relevant sensitivity in a panel EAC cell lines.

Organoid cultures recapitulate esophageal adenocarcinoma heterogeneity providing a model for clonality studies and precision therapeutics.

Esophageal adenocarcinoma (EAC) incidence is increasing while 5-year survival rates remain less than 15%. A lack of experimental models has hampered progress. We have generated clinically annotated EAC organoid cultures that recapitulate the morphology, genomic, and transcriptomic landscape of the primary tumor including point mutations, copy number alterations, and mutational signatures. Karyotyping of organoid cultures has confirmed polyclonality reflecting the clonal architecture of the primary tumor. Furthermore, subclones underwent clonal selection associated with driver gene status. Medium throughput drug sensitivity testing demonstrates the potential of targeting receptor tyrosine kinases and downstream mediators. EAC organoid cultures provide a pre-clinical tool for studies of clonal evolution and precision therapeutics.Esophageal adenocarcinoma (EAC) has a poor 5-year survival rate and lacks robust preclinical models for use in research. Here, the authors show that newly derived organoids recapitulate the transcriptomic, genetic, and morphological landscape of the primary EAC tumors and provide a platform to test drug sensitivity and study tumor clonality.

Impact of mutations in Toll-like receptor pathway genes on esophageal carcinogenesis

Esophageal adenocarcinoma (EAC) develops in an inflammatory microenvironment with reduced microbial diversity, but mechanisms for these influences remain poorly characterized. We hypothesized that mutations targeting the Toll-like receptor (TLR) pathway could disrupt innate immune signaling and promote a microenvironment that favors tumorigenesis. Through interrogating whole genome sequencing data from 171 EAC patients, we showed that non-synonymous mutations collectively affect the TLR pathway in 25/171 (14.6%, PathScan p = 8.7x10-5) tumors. TLR mutant cases were associated with more proximal tumors and metastatic disease, indicating possible clinical significance of these mutations. Only rare mutations were identified in adjacent Barrett’s esophagus samples. We validated our findings in an external EAC dataset with non-synonymous TLR pathway mutations in 33/149 (22.1%, PathScan p = 0.05) tumors, and in other solid tumor types exposed to microbiomes in the COSMIC database (10,318 samples), including uterine endometrioid carcinoma (188/320, 58.8%), cutaneous melanoma (377/988, 38.2%), colorectal adenocarcinoma (402/1519, 26.5%), and stomach adenocarcinoma (151/579, 26.1%). TLR4 was the most frequently mutated gene with eleven mutations in 10/171 (5.8%) of EAC tumors. The TLR4 mutants E439G, S570I, F703C and R787H were confirmed to have impaired reactivity to bacterial lipopolysaccharide with marked reductions in signaling by luciferase reporter assays. Overall, our findings show that TLR pathway genes are recurrently mutated in EAC, and TLR4 mutations have decreased responsiveness to bacterial lipopolysaccharide and may play a role in disease pathogenesis in a subset of patients.

Erratum: Corrigendum: Mutational signatures in esophageal adenocarcinoma define etiologically distinct subgroups with therapeutic relevance

Nat. Genet.; 10.1038/ng.3659; corrected online 19 September 2016 In the version of this article initially published online, the mutation signature illustrations for S1 and S2 in Figure 3a were switched. Additionally, in the Online Methods, the text originally stated that structural variants were called using BWA-MEM, when it should have stated that these were called using BWA.