Clinical application of tumour-in-normal contamination assessment from whole genome sequencing.

The unexpected contamination of normal samples with tumour cells reduces variant detection sensitivity, compromising downstream analyses in canonical tumour-normal analyses. Leveraging whole-genome sequencing data available at Genomics England, we develop a tool for normal sample contamination assessment, which we validate in silico and against minimal residual disease testing. From a systematic review of [Formula: see text] patients with haematological malignancies and sarcomas, we find contamination across a range of cancer clinical indications and DNA sources, with highest prevalence in saliva samples from acute myeloid leukaemia patients, and sorted CD3+ T-cells from myeloproliferative neoplasms. Further exploration reveals 108 hotspot mutations in genes associated with haematological cancers at risk of being subtracted by standard variant calling pipelines. Our work highlights the importance of contamination assessment for accurate somatic variants detection in research and clinical settings, especially with large-scale sequencing projects being utilised to deliver accurate data from which to make clinical decisions for patient care.

Computational validation of clonal and subclonal copy number alterations from bulk tumor sequencing using CNAqc.

Copy number alterations (CNAs) are among the most important genetic events in cancer, but their detection from sequencing data is challenging because of unknown sample purity, tumor ploidy, and general intra-tumor heterogeneity. Here, we present CNAqc, an evolution-inspired method to perform the computational validation of clonal and subclonal CNAs detected from bulk DNA sequencing. CNAqc is validated using single-cell data and simulations, is applied to over 4000 TCGA and PCAWG samples, and is incorporated into the validation process for the clinically accredited bioinformatics pipeline at Genomics England. CNAqc is designed to support automated quality control procedures for tumor somatic data validation.

Insights for precision oncology from the integration of genomic and clinical data of 13,880 tumors from the 100,000 Genomes Cancer Programme.

The Cancer Programme of the 100,000 Genomes Project was an initiative to provide whole-genome sequencing (WGS) for patients with cancer, evaluating opportunities for precision cancer care within the UK National Healthcare System (NHS). Genomics England, alongside NHS England, analyzed WGS data from 13,880 solid tumors spanning 33 cancer types, integrating genomic data with real-world treatment and outcome data, within a secure Research Environment. Incidence of somatic mutations in genes recommended for standard-of-care testing varied across cancer types. For instance, in glioblastoma multiforme, small variants were present in 94% of cases and copy number aberrations in at least one gene in 58% of cases, while sarcoma demonstrated the highest occurrence of actionable structural variants (13%). Homologous recombination deficiency was identified in 40% of high-grade serous ovarian cancer cases with 30% linked to pathogenic germline variants, highlighting the value of combined somatic and germline analysis. The linkage of WGS and longitudinal life course clinical data allowed the assessment of treatment outcomes for patients stratified according to pangenomic markers. Our findings demonstrate the utility of linking genomic and real-world clinical data to enable survival analysis to identify cancer genes that affect prognosis and advance our understanding of how cancer genomics impacts patient outcomes.

Sarcoma and the 100,000 Genomes Project: our experience and changes to practice.

The largest whole genome sequencing (WGS) endeavour involving cancer and rare diseases was initiated in the UK in 2015 and ran for 5 years. Despite its rarity, sarcoma ranked third overall among the number of patients' samples sent for sequencing. Herein, we recount the lessons learned by a specialist sarcoma centre that recruited close to 1000 patients to the project, so that we and others may learn from our experience. WGS data was generated from 597 patients, but samples from the remaining approximately 400 patients were not sequenced. This was largely accounted for by unsuitability due to extensive necrosis, secondary to neoadjuvant radiotherapy or chemotherapy, or being placed in formalin. The number of informative genomes produced was reduced further by a PCR amplification step. We showed that this loss of genomic data could be mitigated by sequencing whole genomes from needle core biopsies. Storage of resection specimens at 4 °C for up to 96 h overcame the challenge of freezing tissue out of hours including weekends. Removing access to formalin increased compliance to these storage arrangements. With over 70 different sarcoma subtypes described, WGS was a useful tool for refining diagnoses and identifying novel alterations. Genomes from 350 of the cohort of 597 patients were analysed in this study. Overall, diagnoses were modified for 3% of patients following review of the WGS findings. Continued refinement of the variant-calling bioinformatic pipelines is required as not all alterations were identified when validated against histology and standard of care diagnostic tests. Further research is necessary to evaluate the impact of germline mutations in patients with sarcoma, and sarcomas with evidence of hypermutation. Despite 50% of the WGS exhibiting domain 1 alterations, the number of patients with sarcoma who were eligible for clinical trials remains small, highlighting the need to revaluate clinical trial design.

Clinical-grade validation of whole genome sequencing reveals robust detection of low-frequency variants and copy number alterations in CLL.

The 100 000 Genome Project aims to develop a diagnostics platform by introducing whole genome sequencing (WGS) into clinical practice. Samples from patients with chronic lymphocytic leukaemia were subjected to WGS. WGS detection of single nucleotide variants and insertion/deletions were validated by targeted next generation sequencing showing high concordance (96·3%), also for detection of sub-clonal variants and low-frequency TP53 variants. Copy number alteration detection was verified by fluorescent in situ hybridisation and genome-wide single nucleotide polymorphism array (concordances of 86·7% and 92·9%, respectively), confirming adequate sensitivity by WGS. Our results confirm that WGS can provide comprehensive genomic characterisation for clinical trials, drug discovery and, ultimately, precision medicine.

Next-Generation Sequencing-Assisted DNA-Based Digital PCR for a Personalized Approach to the Detection and Quantification of Residual Disease in Chronic Myeloid Leukemia Patients.

Recent studies indicate that 40% of chronic myeloid leukemia patients who achieve sustained undetectable BCR-ABL1 transcripts on tyrosine kinase inhibitor therapy remain disease-free after drug discontinuation. In contrast, 60% experience return of detectable disease and have to restart treatment, thus highlighting the need for an improved method of identifying patients with the lowest likelihood of relapse. Here we describe the validation of a personalized DNA-based digital PCR (dPCR) approach for quantifying very low levels of residual disease, which involves the rapid identification of t(9;22) fusion junctions using targeted next-generation sequencing coupled with the use of a dPCR platform. t(9;22) genomic breakpoints were successfully mapped in samples from 32 of 32 patients with early stage disease. Disease quantification by DNA-based dPCR was performed using the Fluidigm BioMark platform on 46 follow-up samples from 6 of the 32 patients, including 36 samples that were in deep molecular remission. dPCR detected persistent disease in 81% of molecular-remission samples, outperforming both RT-dPCR (25%) and DNA-based quantitative PCR (19%). We conclude that dPCR for BCR-ABL1 DNA is the most sensitive available method of residual-disease detection in chronic myeloid leukemia and may prove useful in the management of tyrosine kinase inhibitor withdrawal.

Truncating Homozygous Mutation of Carboxypeptidase E (CPE) in a Morbidly Obese Female with Type 2 Diabetes Mellitus, Intellectual Disability and Hypogonadotrophic Hypogonadism.

Carboxypeptidase E is a peptide processing enzyme, involved in cleaving numerous peptide precursors, including neuropeptides and hormones involved in appetite control and glucose metabolism. Exome sequencing of a morbidly obese female from a consanguineous family revealed homozygosity for a truncating mutation of the CPE gene (c.76_98del; p.E26RfsX68). Analysis detected no CPE expression in whole blood-derived RNA from the proband, consistent with nonsense-mediated decay. The morbid obesity, intellectual disability, abnormal glucose homeostasis and hypogonadotrophic hypogonadism seen in this individual recapitulates phenotypes in the previously described fat/fat and Cpe knockout mouse models, evidencing the importance of this peptide/hormone-processing enzyme in regulating body weight, metabolism, and brain and reproductive function in humans.

The transcription factor Pitx2 positions the embryonic axis and regulates twinning.

Embryonic polarity of invertebrates, amphibians and fish is specified largely by maternal determinants, which fixes cell fates early in development. In contrast, amniote embryos remain plastic and can form multiple individuals until gastrulation. How is their polarity determined? In the chick embryo, the earliest known factor is cVg1 (homologous to mammalian growth differentiation factor 1, GDF1), a transforming growth factor beta (TGFß) signal expressed posteriorly before gastrulation. A molecular screen to find upstream regulators of cVg1 in normal embryos and in embryos manipulated to form twins now uncovers the transcription factor Pitx2 as a candidate. We show that Pitx2 is essential for axis formation, and that it acts as a direct regulator of cVg1 expression by binding to enhancers within neighbouring genes. Pitx2, Vg1/GDF1 and Nodal are also key actors in left-right asymmetry, suggesting that the same ancient polarity determination mechanism has been co-opted to different functions during evolution.

Computational tools and resources for prediction and analysis of gene regulatory regions in the chick genome.

The discovery of cis-regulatory elements is a challenging problem in bioinformatics, owing to distal locations and context-specific roles of these elements in controlling gene regulation. Here we review the current bioinformatics methodologies and resources available for systematic discovery of cis-acting regulatory elements and conserved transcription factor binding sites in the chick genome. In addition, we propose and make available, a novel workflow using computational tools that integrate CTCF analysis to predict putative insulator elements, enhancer prediction, and TFBS analysis. To demonstrate the usefulness of this computational workflow, we then use it to analyze the locus of the gene Sox2 whose developmental expression is known to be controlled by a complex array of cis-acting regulatory elements. The workflow accurately predicts most of the experimentally verified elements along with some that have not yet been discovered. A web version of the CTCF tool, together with instructions for using the workflow can be accessed from http://toolshed.g2.bx.psu.edu/view/mkhan1980/ctcf_analysis. For local installation of the tool, relevant Perl scripts and instructions are provided in the directory named "code" in the supplementary materials.

Experimental approaches for gene regulatory network construction: the chick as a model system.

Setting up the body plan during embryonic development requires the coordinated action of many signals and transcriptional regulators in a precise temporal sequence and spatial pattern. The last decades have seen an explosion of information describing the molecular control of many developmental processes. The next challenge is to integrate this information into logic "wiring diagrams" that visualize gene actions and outputs, have predictive power and point to key control nodes. Here, we provide an experimental workflow on how to construct gene regulatory networks using the chick as model system.

The role of DNA shape in protein-DNA recognition.

The recognition of specific DNA sequences by proteins is thought to depend on two types of mechanism: one that involves the formation of hydrogen bonds with specific bases, primarily in the major groove, and one involving sequence-dependent deformations of the DNA helix. By comprehensively analysing the three-dimensional structures of protein-DNA complexes, here we show that the binding of arginine residues to narrow minor grooves is a widely used mode for protein-DNA recognition. This readout mechanism exploits the phenomenon that narrow minor grooves strongly enhance the negative electrostatic potential of the DNA. The nucleosome core particle offers a prominent example of this effect. Minor-groove narrowing is often associated with the presence of A-tracts, AT-rich sequences that exclude the flexible TpA step. These findings indicate that the ability to detect local variations in DNA shape and electrostatic potential is a general mechanism that enables proteins to use information in the minor groove, which otherwise offers few opportunities for the formation of base-specific hydrogen bonds, to achieve DNA-binding specificity.

Functional specificity of a Hox protein mediated by the recognition of minor groove structure.

The recognition of specific DNA-binding sites by transcription factors is a critical yet poorly understood step in the control of gene expression. Members of the Hox family of transcription factors bind DNA by making nearly identical major groove contacts via the recognition helices of their homeodomains. In vivo specificity, however, often depends on extended and unstructured regions that link Hox homeodomains to a DNA-bound cofactor, Extradenticle (Exd). Using a combination of structure determination, computational analysis, and in vitro and in vivo assays, we show that Hox proteins recognize specific Hox-Exd binding sites via residues located in these extended regions that insert into the minor groove but only when presented with the correct DNA sequence. Our results suggest that these residues, which are conserved in a paralog-specific manner, confer specificity by recognizing a sequence-dependent DNA structure instead of directly reading a specific DNA sequence.

Discovering transcriptional regulatory regions in Drosophila by a nonalignment method for phylogenetic footprinting.

The functional annotation of the nonprotein-coding DNA of eukaryotic genomes is a problem of central importance. Phylogenetic footprinting methods, which attempt to identify functional regulatory regions by comparing orthologous genomic sequences of evolutionarily related species, have shown promising results. The main advantage of this class of approaches is that they do not require any knowledge of the regulating transcription factors. Here we describe a method called Enhancer Detection using only Genomic Information (EDGI), which integrates a traditional motif-discovery algorithm with a local permutation-clustering algorithm. Together, they can identify large regulatory elements (e.g., enhancers) as evolutionarily conserved order-independent clusters of short conserved motifs. We show that EDGI can distinguish between established sets of known enhancers and nonenhancers with 88% accuracy, rivaling predictions by methods that rely on the knowledge of the regulating transcription factors and their DNA-binding specificities. We tested EDGI's performance on a set of Drosophila genomes. Our results demonstrate that comparative genomic analysis of multiple closely related species has substantial power to identify key functional elements without additional biological knowledge.

Lozenge directly activates argos and klumpfuss to regulate programmed cell death.

We show that reducing the activity of the Drosophila Runx protein Lozenge (Lz) during pupal development causes a decrease in cell death in the eye. We identified Lz-binding sites in introns of argos (aos) and klumpfuss (klu) and demonstrate that these genes are directly activated targets of Lz. Loss of either aos or klu reduces cell death, suggesting that Lz promotes apoptosis at least in part by regulating aos and klu. These results provide novel insights into the control of programmed cell death (PCD) by Lz during Drosophila eye development.

Target Explorer: An automated tool for the identification of new target genes for a specified set of transcription factors.

With the increasing number of eukaryotic genomes available, high-throughput automated tools for identification of regulatory DNA sequences are becoming increasingly feasible. Several computational approaches for the prediction of regulatory elements were recently developed. Here we combine the prediction of clusters of binding sites for transcription factors with context information taken from genome annotations. Target Explorer automates the entire process from the creation of a customized library of binding sites for known transcription factors through the prediction and annotation of putative target genes that are potentially regulated by these factors. It was specifically designed for the well-annotated Drosophila melanogaster genome, but most options can be used for sequences from other genomes as well. Target Explorer is available at http://trantor.bioc.columbia.edu/Target_Explorer/