OpEx - a validated, automated pipeline optimised for clinical exome sequence analysis

Challenges targeting cancer neoantigens in 2021: a systematic literature review

Introduction: Cancer neoantigens represent important targets of cancer immunotherapy. The goal of cancer neoantigen vaccines is to induce neoantigen-specific immune responses and antitumor immunity while minimizing the potential for autoimmune toxicity. Advances in sequencing technologies, neoantigen prediction algorithms, and other technologies have dramatically improved the ability to identify and prioritize cancer neoantigens. Unfortunately, results from preclinical studies and early phase clinical trials highlight important challenges to the successful clinical translation of neoantigen cancer vaccines.Areas covered: In this review, we provide an overview of current strategies for the identification and prioritization of cancer neoantigens with a particular emphasis on the two most common strategies used for neoantigen identification: (1) direct identification of peptide ligands eluted from peptide-MHC complexes, and (2) next-generation sequencing combined with neoantigen prediction algorithms. We highlight the limitations of current neoantigen prediction pipelines, and discuss broader challenges associated with cancer neoantigen vaccines including tumor purity/heterogeneity and the immunosuppressive tumor microenvironment.Expert opinion: Despite current limitations, neoantigen prediction is likely to improve rapidly based on advances in sequencing, machine learning, and information sharing. The successful development of robust cancer neoantigen prediction strategies is likely to have a significant impact, with the potential to facilitate cancer neoantigen vaccine design.

Insights into BRCA Cancer Predisposition from Integrated Germline and Somatic Analyses in 7632 Cancers

BACKGROUND

It is often assumed any cancer in a germline BRCA1 or BRCA2 (collectively termed BRCA) mutation carrier was caused by that mutation. It is also often assumed the occurrence of breast or ovarian cancer in an individual with a variant of uncertain significance (VUS) suggests the VUS is pathogenic. These assumptions have profound management implications for cancer patients and healthy individuals.

METHODS

We compared the frequency of BRCA mutations, allele loss, and Signature 3 in 7632 individuals with 28 cancers and 1000 population controls. Because only increased frequency was the focus of the study, all statistical tests were one-sided.

RESULTS

Individuals with breast or ovarian cancer had increased germline BRCA pathogenic mutation frequencies compared to controls (P = 1.0x10-10 and P = 1.4x10-34, respectively). There was no increase in other cancer types. Wild-type allele loss and Signature 3 were statistically significantly higher in breast and ovarian cancers with BRCA mutations compared with other cancers with BRCA mutations (P = 5.1x10-10 and P = 3.7x10-9) and cancers without BRCA mutations (P = 2.8x10-53 and P = 1.0x10-134). There was no difference between non-breast and non-ovarian cancers with BRCA mutations and cancers without BRCA mutations. Allele loss and Signature 3 were statistically significantly higher in breast and ovarian cancers in individuals with BRCA pathogenic mutations compared to those with VUS (P = 3.8x10-17 and P = 1.6x10-8) or benign variants (P = 1.2x10-28 and P = 2.2x10-10). There was no difference between individuals with BRCA VUS and those with benign variants.

CONCLUSIONS

These data show that non-breast and non-ovarian cancers in individuals with germline BRCA pathogenic mutations are often not causally related to the mutation and that BRCA VUS are highly unlikely to be pathogenic. These results should reduce inappropriate management of germline BRCA information.

Identification of new Wilms tumour predisposition genes: an exome sequencing study

BACKGROUND

Wilms tumour is the most common childhood renal cancer and is genetically heterogeneous. While several Wilms tumour predisposition genes have been identified, there is strong evidence that further predisposition genes are likely to exist. Our study aim was to identify new predisposition genes for Wilms tumour.

METHODS

In this exome sequencing study, we analysed lymphocyte DNA from 890 individuals with Wilms tumour, including 91 affected individuals from 49 familial Wilms tumour pedigrees. We used the protein-truncating variant prioritisation method to prioritise potential disease-associated genes for further assessment. We evaluated new predisposition genes in exome sequencing data that we generated in 334 individuals with 27 other childhood cancers and in exome data from The Cancer Genome Atlas obtained from 7632 individuals with 28 adult cancers.

FINDINGS

We identified constitutional cancer-predisposing mutations in 33 individuals with childhood cancer. The three identified genes with the strongest signal in the protein-truncating variant prioritisation analyses were TRIM28, FBXW7, and NYNRIN. 21 of 33 individuals had a mutation in TRIM28; there was a strong parent-of-origin effect, with all ten inherited mutations being maternally transmitted (p=0·00098). We also found a strong association with the rare epithelial subtype of Wilms tumour, with 14 of 16 tumours being epithelial or epithelial predominant. There were no TRIM28 mutations in individuals with other childhood or adult cancers. We identified truncating FBXW7 mutations in four individuals with Wilms tumour and a de-novo non-synonymous FBXW7 mutation in a child with a rhabdoid tumour. Biallelic truncating mutations in NYNRIN were identified in three individuals with Wilms tumour, which is highly unlikely to have occurred by chance (p<0·0001). Finally, we identified two de-novo KDM3B mutations, supporting the role of KDM3B as a childhood cancer predisposition gene.

INTERPRETATION

The four new Wilms tumour predisposition genes identified-TRIM28, FBXW7, NYNRIN, and KDM3B-are involved in diverse biological processes and, together with the other 17 known Wilms tumour predisposition genes, account for about 10% of Wilms tumour cases. The overlap between these 21 constitutionally mutated predisposition genes and 20 genes somatically mutated in Wilms tumour is limited, consisting of only four genes. We recommend that all individuals with Wilms tumour should be offered genetic testing and particularly, those with epithelial Wilms tumour should be offered TRIM28 genetic testing. Only a third of the familial Wilms tumour clusters we analysed were attributable to known genes, indicating that further Wilms tumour predisposition factors await discovery.

FUNDING

Wellcome Trust.

ICR142 Benchmarker: evaluating, optimising and benchmarking variant calling performance using the ICR142 NGS validation series

Evaluating, optimising and benchmarking of next generation sequencing (NGS) variant calling performance are essential requirements for clinical, commercial and academic NGS pipelines. Such assessments should be performed in a consistent, transparent and reproducible fashion, using independently, orthogonally generated data. Here we present ICR142 Benchmarker, a tool to generate outputs for assessing germline base substitution and indel calling performance using the ICR142 NGS validation series, a dataset of Illumina platform-based exome sequence data from 142 samples together with Sanger sequence data at 704 sites. ICR142 Benchmarker provides summary and detailed information on the sensitivity, specificity and false detection rates of variant callers. ICR142 Benchmarker also automatically generates a single page report highlighting key performance metrics and how performance compares to widely-used open-source tools. We used ICR142 Benchmarker with VCF files outputted by GATK, OpEx and DeepVariant to create a benchmark for variant calling performance. This evaluation revealed pipeline-specific differences and shared challenges in variant calling, for example in detecting indels in short repeating sequence motifs. We next used ICR142 Benchmarker to perform regression testing with DeepVariant versions 0.5.2 and 0.6.1. This showed that v0.6.1 improves variant calling performance, but there was evidence of minor changes in indel calling behaviour that may benefit from attention. The data also allowed us to evaluate filters to optimise DeepVariant calling, and we recommend using 30 as the QUAL threshold for base substitution calls when using DeepVariant v0.6.1. Finally, we used ICR142 Benchmarker with VCF files from two commercial variant calling providers to facilitate optimisation of their in-house pipelines and to provide transparent benchmarking of their performance. ICR142 Benchmarker consistently and transparently analyses variant calling performance based on the ICR142 NGS validation series, using the standard VCF input and outputting informative metrics to enable user understanding of pipeline performance. ICR142 Benchmarker is freely available at https://github.com/RahmanTeamDevelopment/ICR142_Benchmarker/releases.

ICR142 Benchmarker: evaluating, optimising and benchmarking variant calling using the ICR142 NGS validation series

Evaluating, optimising and benchmarking of next generation sequencing (NGS) variant calling performance are essential requirements for clinical, commercial and academic NGS pipelines. Such assessments should be performed in a consistent, transparent and reproducible fashion, using independently, orthogonally generated data. Here we present ICR142 Benchmarker, a tool to generate outputs for assessing variant calling performance using the ICR142 NGS validation series, a dataset of exome sequence data from 142 samples together with Sanger sequence data at 704 sites. ICR142 Benchmarker provides summary and detailed information on the sensitivity, specificity and false detection rates of variant callers. ICR142 Benchmarker also automatically generates a single page report highlighting key performance metrics and how performance compares to widely-used open-source tools. We used ICR142 Benchmarker with VCF files outputted by GATK, OpEx and DeepVariant to create a benchmark for variant calling performance. This evaluation revealed pipeline-specific differences and shared challenges in variant calling, for example in detecting indels in short repeating sequence motifs. We next used ICR142 Benchmarker to perform regression testing with versions 0.5.2 and 0.6.1 of DeepVariant. This showed that v0.6.1 improves variant calling performance, but there was evidence of some minor changes in indel calling behaviour that may benefit from attention in future updates. The data also allowed us to evaluate filters to optimise DeepVariant calling, and we recommend using 30 as the QUAL threshold for base substitution calls when using DeepVariant v0.6.1. Finally, we used ICR142 Benchmarker with VCF files from two commercial variant calling providers to facilitate optimisation of their in-house pipelines and to provide transparent benchmarking of their performance. ICR142 Benchmarker consistently and transparently analyses variant calling performance based on the ICR142 NGS validation series, using the standard VCF input and outputting informative metrics to enable user understanding of pipeline performance. ICR142 Benchmarker is freely available at https://github.com/RahmanTeamDevelopment/ICR142_Benchmarker/releases.

CoverView: a sequence quality evaluation tool for next generation sequencing data

Quality assurance and quality control are essential for robust next generation sequencing (NGS). Here we present CoverView, a fast, flexible, user-friendly quality evaluation tool for NGS data. CoverView processes mapped sequencing reads and user-specified regions to report depth of coverage, base and mapping quality metrics with increasing levels of detail from a chromosome-level summary to per-base profiles. CoverView can flag regions that do not fulfil user-specified quality requirements, allowing suboptimal data to be systematically and automatically presented for review. It also provides an interactive graphical user interface (GUI) that can be opened in a web browser and allows intuitive exploration of results.

We have integrated CoverView into our accredited clinical cancer predisposition gene testing laboratory that uses the TruSight Cancer Panel (TSCP). CoverView has been invaluable for optimisation and quality control of our testing pipeline, providing transparent, consistent quality metric information and automatic flagging of regions that fall below quality thresholds. We demonstrate this utility with TSCP data from the Genome in a Bottle reference sample, which CoverView analysed in 13 seconds.

CoverView uses data routinely generated by NGS pipelines, reads standard input formats, and rapidly creates easy-to-parse output text (.txt) files that are customised by a simple configuration file. CoverView can therefore be easily integrated into any NGS pipeline. CoverView and detailed documentation for its use are freely available at github.com/RahmanTeamDevelopment/CoverView/releases and www.icr.ac.uk/CoverView

Insertion-and-deletion-derived tumour-specific neoantigens and the immunogenic phenotype: a pan-cancer analysis

BACKGROUND

The focus of tumour-specific antigen analyses has been on single nucleotide variants (SNVs), with the contribution of small insertions and deletions (indels) less well characterised. We investigated whether the frameshift nature of indel mutations, which create novel open reading frames and a large quantity of mutagenic peptides highly distinct from self, might contribute to the immunogenic phenotype.

METHODS

We analysed whole-exome sequencing data from 5777 solid tumours, spanning 19 cancer types from The Cancer Genome Atlas. We compared the proportion and number of indels across the cohort, with a subset of results replicated in two independent datasets. We assessed in-silico tumour-specific neoantigen predictions by mutation type with pan-cancer analysis, together with RNAseq profiling in renal clear cell carcinoma cases (n=392), to compare immune gene expression across patient subgroups. Associations between indel burden and treatment response were assessed across four checkpoint inhibitor datasets.

FINDINGS

We observed renal cell carcinomas to have the highest proportion (0·12) and number of indel mutations across the pan-cancer cohort (p<2·2 × 10-16), more than double the median proportion of indel mutations in all other cancer types examined. Analysis of tumour-specific neoantigens showed that enrichment of indel mutations for high-affinity binders was three times that of non-synonymous SNV mutations. Furthermore, neoantigens derived from indel mutations were nine times enriched for mutant specific binding, as compared with non-synonymous SNV derived neoantigens. Immune gene expression analysis in the renal clear cell carcinoma cohort showed that the presence of mutant-specific neoantigens was associated with upregulation of antigen presentation genes, which correlated (r=0·78) with T-cell activation as measured by CD8-positive expression. Finally, analysis of checkpoint inhibitor response data revealed frameshift indel count to be significantly associated with checkpoint inhibitor response across three separate melanoma cohorts (p=4·7 × 10-4).

INTERPRETATION

Renal cell carcinomas have the highest pan-cancer proportion and number of indel mutations. Evidence suggests indels are a highly immunogenic mutational class, which can trigger an increased abundance of neoantigens and greater mutant-binding specificity.

FUNDING

Cancer Research UK, UK National Institute for Health Research (NIHR) at the Royal Marsden Hospital National Health Service Foundation Trust, Institute of Cancer Research and University College London Hospitals Biomedical Research Centres, the UK Medical Research Council, the Rosetrees Trust, Novo Nordisk Foundation, the Prostate Cancer Foundation, the Breast Cancer Research Foundation, the European Research Council.

Biallelic TRIP13 mutations predispose to Wilms tumor and chromosome missegregation

Through exome sequencing, we identified six individuals with biallelic loss-of-function mutations in TRIP13. All six developed Wilms tumor. Constitutional mosaic aneuploidies, microcephaly, developmental delay and seizures, which are features of mosaic variegated aneuploidy (MVA) syndrome, were more variably present. Through functional studies, we show that TRIP13-mutant patient cells have no detectable TRIP13 and have substantial impairment of the spindle assembly checkpoint (SAC), leading to a high rate of chromosome missegregation. Accurate segregation, as well as SAC proficiency, is rescued by restoring TRIP13 function. Individuals with biallelic TRIP13 or BUB1B mutations have a high risk of embryonal tumors, and here we show that their cells display severe SAC impairment. MVA due to biallelic CEP57 mutations, or of unknown cause, is not associated with embryonal tumors and cells from these individuals show minimal SAC deficiency. These data provide insights into the complex relationships between aneuploidy and carcinogenesis.

Mutations in Epigenetic Regulation Genes Are a Major Cause of Overgrowth with Intellectual Disability

To explore the genetic architecture of human overgrowth syndromes and human growth control, we performed experimental and bioinformatic analyses of 710 individuals with overgrowth (height and/or head circumference ≥+2 SD) and intellectual disability (OGID). We identified a causal mutation in 1 of 14 genes in 50% (353/710). This includes HIST1H1E, encoding histone H1.4, which has not been associated with a developmental disorder previously. The pathogenic HIST1H1E mutations are predicted to result in a product that is less effective in neutralizing negatively charged linker DNA because it has a reduced net charge, and in DNA binding and protein-protein interactions because key residues are truncated. Functional network analyses demonstrated that epigenetic regulation is a prominent biological process dysregulated in individuals with OGID. Mutations in six epigenetic regulation genes—NSD1, EZH2, DNMT3A, CHD8, HIST1H1E, and EED—accounted for 44% of individuals (311/710). There was significant overlap between the 14 genes involved in OGID and 611 genes in regions identified in GWASs to be associated with height (p = 6.84 × 10⁻⁸), suggesting that a common variation impacting function of genes involved in OGID influences height at a population level. Increased cellular growth is a hallmark of cancer and there was striking overlap between the genes involved in OGID and 260 somatically mutated cancer driver genes (p = 1.75 × 10⁻¹⁴). However, the mutation spectra of genes involved in OGID and cancer differ, suggesting complex genotype-phenotype relationships. These data reveal insights into the genetic control of human growth and demonstrate that exome sequencing in OGID has a high diagnostic yield.

Accurate clinical detection of exon copy number variants in a targeted NGS panel using DECoN

Background: Targeted next generation sequencing (NGS) panels are increasingly being used in clinical genomics to increase capacity, throughput and affordability of gene testing. Identifying whole exon deletions or duplications (termed exon copy number variants, ‘exon CNVs’) in exon-targeted NGS panels has proved challenging, particularly for single exon CNVs. 

Methods: We developed a tool for the Detection of Exon Copy Number variants (DECoN), which is optimised for analysis of exon-targeted NGS panels in the clinical setting. We evaluated DECoN performance using 96 samples with independently validated exon CNV data. We performed simulations to evaluate DECoN detection performance of single exon CNVs and to evaluate performance using different coverage levels and sample numbers. Finally, we implemented DECoN in a clinical laboratory that tests BRCA1 and BRCA2 with the TruSight Cancer Panel (TSCP). We used DECoN to analyse 1,919 samples, validating exon CNV detections by multiplex ligation-dependent probe amplification (MLPA). 

Results: In the evaluation set, DECoN achieved 100% sensitivity and 99% specificity for BRCA exon CNVs, including identification of 8 single exon CNVs. DECoN also identified 14/15 exon CNVs in 8 other genes. Simulations of all possible BRCA single exon CNVs gave a mean sensitivity of 98% for deletions and 95% for duplications. DECoN performance remained excellent with different levels of coverage and sample numbers; sensitivity and specificity was >98% with the typical NGS run parameters. In the clinical pipeline, DECoN automatically analyses pools of 48 samples at a time, taking 24 minutes per pool, on average. DECoN detected 24 BRCA exon CNVs, of which 23 were confirmed by MLPA, giving a false discovery rate of 4%. Specificity was 99.7%. 

Conclusions: DECoN is a fast, accurate, exon CNV detection tool readily implementable in research and clinical NGS pipelines. It has high sensitivity and specificity and acceptable false discovery rate. DECoN is freely available at www.icr.ac.uk/decon.