Whole-slide laser microdissection for tumour enrichment.

The practical application of genome-scale technologies to precision oncology research requires flexible tissue processing strategies that can be used to differentially select both tumour and normal cell populations from formalin-fixed, paraffin-embedded tissues. As tumour sequencing scales towards clinical implementation, practical difficulties in scheduling and obtaining fresh tissue biopsies at scale, including blood samples as surrogates for matched 'normal' DNA, have focused attention on the use of formalin-preserved clinical samples collected routinely for diagnostic purposes. In practice, such samples often contain both tumour and normal cells which, if correctly partitioned, could be used to profile both tumour and normal genomes, thus identifying somatic alterations. Here we report a semi-automated method for laser microdissecting entire slide-mounted tissue sections to enrich for cells of interest with sufficient yield for whole genome and transcriptome sequencing. Using this method, we demonstrated enrichment of tumour material from mixed tumour-normal samples by up to 67%. Leveraging new methods that allow for the extraction of high-quality nucleic acids from small amounts of formalin-fixed tissues, we further showed that the method was successful in yielding sequence data of sufficient quality for use in BC Cancer's Personalized OncoGenomics (POG) program. © 2020 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Divergent clonal selection dominates medulloblastoma at recurrence.

The development of targeted anti-cancer therapies through the study of cancer genomes is intended to increase survival rates and decrease treatment-related toxicity. We treated a transposon-driven, functional genomic mouse model of medulloblastoma with 'humanized' in vivo therapy (microneurosurgical tumour resection followed by multi-fractionated, image-guided radiotherapy). Genetic events in recurrent murine medulloblastoma exhibit a very poor overlap with those in matched murine diagnostic samples (<5%). Whole-genome sequencing of 33 pairs of human diagnostic and post-therapy medulloblastomas demonstrated substantial genetic divergence of the dominant clone after therapy (<12% diagnostic events were retained at recurrence). In both mice and humans, the dominant clone at recurrence arose through clonal selection of a pre-existing minor clone present at diagnosis. Targeted therapy is unlikely to be effective in the absence of the target, therefore our results offer a simple, proximal, and remediable explanation for the failure of prior clinical trials of targeted therapy.

Sources of erroneous sequences and artifact chimeric reads in next generation sequencing of genomic DNA from formalin-fixed paraffin-embedded samples.

Tissues used in pathology laboratories are typically stored in the form of formalin-fixed, paraffin-embedded (FFPE) samples. One important consideration in repurposing FFPE material for next generation sequencing (NGS) analysis is the sequencing artifacts that can arise from the significant damage to nucleic acids due to treatment with formalin, storage at room temperature and extraction. One such class of artifacts consists of chimeric reads that appear to be derived from non-contiguous portions of the genome. Here, we show that a major proportion of such chimeric reads align to both the 'Watson' and 'Crick' strands of the reference genome. We refer to these as strand-split artifact reads (SSARs). This study provides a conceptual framework for the mechanistic basis of the genesis of SSARs and other chimeric artifacts along with supporting experimental evidence, which have led to approaches to reduce the levels of such artifacts. We demonstrate that one of these approaches, involving S1 nuclease-mediated removal of single-stranded fragments and overhangs, also reduces sequence bias, base error rates, and false positive detection of copy number and single nucleotide variants. Finally, we describe an analytical approach for quantifying SSARs from NGS data.

Subgroup-specific structural variation across 1,000 medulloblastoma genomes.

Medulloblastoma, the most common malignant paediatric brain tumour, is currently treated with nonspecific cytotoxic therapies including surgery, whole-brain radiation, and aggressive chemotherapy. As medulloblastoma exhibits marked intertumoural heterogeneity, with at least four distinct molecular variants, previous attempts to identify targets for therapy have been underpowered because of small samples sizes. Here we report somatic copy number aberrations (SCNAs) in 1,087 unique medulloblastomas. SCNAs are common in medulloblastoma, and are predominantly subgroup-enriched. The most common region of focal copy number gain is a tandem duplication of SNCAIP, a gene associated with Parkinson's disease, which is exquisitely restricted to Group 4α. Recurrent translocations of PVT1, including PVT1-MYC and PVT1-NDRG1, that arise through chromothripsis are restricted to Group 3. Numerous targetable SCNAs, including recurrent events targeting TGF-ß signalling in Group 3, and NF-κB signalling in Group 4, suggest future avenues for rational, targeted therapy.

Increasing quality, throughput and speed of sample preparation for strand-specific messenger RNA sequencing.

BACKGROUND: RNA-Sequencing (RNA-seq) is now commonly used to reveal quantitative spatiotemporal snapshots of the transcriptome, the structures of transcripts (splice variants and fusions) and landscapes of expressed mutations. However, standard approaches for library construction typically require relatively high amounts of input RNA, are labor intensive, and are time consuming. METHODS: Here, we report the outcome of a systematic effort to optimize and streamline steps in strand-specific RNA-seq library construction. RESULTS: This work has resulted in the identification of an optimized messenger RNA isolation protocol, a potent reverse transcriptase for cDNA synthesis, and an efficient chemistry and a simplified formulation of library construction reagents. We also present an optimization of bead-based purification and size selection designed to maximize the recovery of cDNA fragments. CONCLUSIONS: These developments have allowed us to assemble a rapid high throughput pipeline that produces high quality data from amounts of total RNA as low as 25 ng. While the focus of this study is on RNA-seq sample preparation, some of these developments are also relevant to other next-generation sequencing library types.

Frequent mutation of histone-modifying genes in non-Hodgkin lymphoma.

Follicular lymphoma (FL) and diffuse large B-cell lymphoma (DLBCL) are the two most common non-Hodgkin lymphomas (NHLs). Here we sequenced tumour and matched normal DNA from 13 DLBCL cases and one FL case to identify genes with mutations in B-cell NHL. We analysed RNA-seq data from these and another 113 NHLs to identify genes with candidate mutations, and then re-sequenced tumour and matched normal DNA from these cases to confirm 109 genes with multiple somatic mutations. Genes with roles in histone modification were frequent targets of somatic mutation. For example, 32% of DLBCL and 89% of FL cases had somatic mutations in MLL2, which encodes a histone methyltransferase, and 11.4% and 13.4% of DLBCL and FL cases, respectively, had mutations in MEF2B, a calcium-regulated gene that cooperates with CREBBP and EP300 in acetylating histones. Our analysis suggests a previously unappreciated disruption of chromatin biology in lymphomagenesis.

Mutational and structural analysis of diffuse large B-cell lymphoma using whole-genome sequencing.

Diffuse large B-cell lymphoma (DLBCL) is a genetically heterogeneous cancer composed of at least 2 molecular subtypes that differ in gene expression and distribution of mutations. Recently, application of genome/exome sequencing and RNA-seq to DLBCL has revealed numerous genes that are recurrent targets of somatic point mutation in this disease. Here we provide a whole-genome-sequencing-based perspective of DLBCL mutational complexity by characterizing 40 de novo DLBCL cases and 13 DLBCL cell lines and combining these data with DNA copy number analysis and RNA-seq from an extended cohort of 96 cases. Our analysis identified widespread genomic rearrangements including evidence for chromothripsis as well as the presence of known and novel fusion transcripts. We uncovered new gene targets of recurrent somatic point mutations and genes that are targeted by focal somatic deletions in this disease. We highlight the recurrence of germinal center B-cell-restricted mutations affecting genes that encode the S1P receptor and 2 small GTPases (GNA13 and GNAI2) that together converge on regulation of B-cell homing. We further analyzed our data to approximate the relative temporal order in which some recurrent mutations were acquired and demonstrate that ongoing acquisition of mutations and intratumoral clonal heterogeneity are common features of DLBCL. This study further improves our understanding of the processes and pathways involved in lymphomagenesis, and some of the pathways mutated here may indicate new avenues for therapeutic intervention.

Complete genomic landscape of a recurring sporadic parathyroid carcinoma.

Parathyroid carcinoma is a rare endocrine malignancy with an estimated incidence of less than 1 per million population. Excessive secretion of parathyroid hormone, extremely high serum calcium level, and the deleterious effects of hypercalcaemia are the clinical manifestations of the disease. Up to 60% of patients develop multiple disease recurrences and although long-term survival is possible with palliative surgery, permanent remission is rarely achieved. Molecular drivers of sporadic parathyroid carcinoma have remained largely unknown. Previous studies, mostly based on familial cases of the disease, suggested potential roles for the tumour suppressor MEN1 and proto-oncogene RET in benign parathyroid tumourigenesis, while the tumour suppressor HRPT2 and proto-oncogene CCND1 may also act as drivers in parathyroid cancer. Here, we report the complete genomic analysis of a sporadic and recurring parathyroid carcinoma. Mutational landscapes of the primary and recurrent tumour specimens were analysed using high-throughput sequencing technologies. Such molecular profiling allowed for identification of somatic mutations never previously identified in this malignancy. These included single nucleotide point mutations in well-characterized cancer genes such as mTOR, MLL2, CDKN2C, and PIK3CA. Comparison of acquired mutations in patient-matched primary and recurrent tumours revealed loss of PIK3CA activating mutation during the evolution of the tumour from the primary to the recurrence. Structural variations leading to gene fusions and regions of copy loss and gain were identified at a single-base resolution. Loss of the short arm of chromosome 1, along with somatic missense and truncating mutations in CDKN2C and THRAP3, respectively, provides new evidence for the potential role of these genes as tumour suppressors in parathyroid cancer. The key somatic mutations identified in this study can serve as novel diagnostic markers as well as therapeutic targets.

Rapid microdissection of tissue sections via laser ablation.

We demonstrate a method for tissue microdissection using scanning laser ablation that is approximately two orders of magnitude faster than conventional laser capture microdissection. Our novel approach uses scanning laser optics and a slide coating under the tissue that can be excited by the laser to selectively eject regions of tissue for further processing. Tissue was dissected at 0.117 s/mm2 without reduction in yield, sequencing insert size or base quality compared with undissected tissue. From eight cases, 58-416 mm2 of tissue was obtained from one to four slides in 7-48 seconds total dissection time per case. These samples underwent exome sequencing and we found the variant allelic fraction increased in regions enriched for tumour as expected. This suggests that our ablation technique may be useful as a tool in both clinical and research labs.

Barnacle: detecting and characterizing tandem duplications and fusions in transcriptome assemblies.

BACKGROUND: Chimeric transcripts, including partial and internal tandem duplications (PTDs, ITDs) and gene fusions, are important in the detection, prognosis, and treatment of human cancers. RESULTS: We describe Barnacle, a production-grade analysis tool that detects such chimeras in de novo assemblies of RNA-seq data, and supports prioritizing them for review and validation by reporting the relative coverage of co-occurring chimeric and wild-type transcripts. We demonstrate applications in large-scale disease studies, by identifying PTDs in MLL, ITDs in FLT3, and reciprocal fusions between PML and RARA, in two deeply sequenced acute myeloid leukemia (AML) RNA-seq datasets. CONCLUSIONS: Our analyses of real and simulated data sets show that, with appropriate filter settings, Barnacle makes highly specific predictions for three types of chimeric transcripts that are important in a range of cancers: PTDs, ITDs, and fusions. High specificity makes manual review and validation efficient, which is necessary in large-scale disease studies. Characterizing an extended range of chimera types will help generate insights into progression, treatment, and outcomes for complex diseases.

A high-throughput pipeline for DNA/RNA/small RNA purification from tissue samples for sequencing.

High-throughput total nucleic acid (TNA) purification methods based on solid-phase reversible immobilization (SPRI) beads produce TNA suitable for both genomic and transcriptomic applications. Even so, small RNA species, including miRNA, bind weakly to SPRI beads under standard TNA purification conditions, necessitating a separate workflow using column-based methods that are difficult to automate. Here, an SPRI-based high-throughput TNA purification protocol that recovers DNA, RNA and small RNA, called GSC-modified RLT+ Aline bead-based protocol (GRAB-ALL), which incorporates modifications to enhance small RNA recovery is presented. GRAB-ALL was benchmarked against existing nucleic acid purification workflows and GRAB-ALL efficiently purifies TNA, including small RNA, for next-generation sequencing applications in a plate-based format suitable for automated high-throughput sample preparation.

Multi-Omic Analysis of CIC's Functional Networks Reveals Novel Interaction Partners and a Potential Role in Mitotic Fidelity.

CIC encodes a transcriptional repressor and MAPK signalling effector that is inactivated by loss-of-function mutations in several cancer types, consistent with a role as a tumour suppressor. Here, we used bioinformatic, genomic, and proteomic approaches to investigate CIC's interaction networks. We observed both previously identified and novel candidate interactions between CIC and SWI/SNF complex members, as well as novel interactions between CIC and cell cycle regulators and RNA processing factors. We found that CIC loss is associated with an increased frequency of mitotic defects in human cell lines and an in vivo mouse model and with dysregulated expression of mitotic regulators. We also observed aberrant splicing in CIC-deficient cell lines, predominantly at 3' and 5' untranslated regions of genes, including genes involved in MAPK signalling, DNA repair, and cell cycle regulation. Our study thus characterises the complexity of CIC's functional network and describes the effect of its loss on cell cycle regulation, mitotic integrity, and transcriptional splicing, thereby expanding our understanding of CIC's potential roles in cancer. In addition, our work exemplifies how multi-omic, network-based analyses can be used to uncover novel insights into the interconnected functions of pleiotropic genes/proteins across cellular contexts.

Genomic structures and regulation patterns at HPV integration sites in cervical cancer.

Human papillomavirus (HPV) integration has been implicated in transforming HPV infection into cancer, but its genomic consequences have been difficult to study using short-read technologies. To resolve the dysregulation associated with HPV integration, we performed long-read sequencing on 63 cervical cancer genomes. We identified six categories of integration events based on HPV-human genomic structures. Of all HPV integrants, defined as two HPV-human breakpoints bridged by an HPV sequence, 24% contained variable copies of HPV between the breakpoints, a phenomenon we termed heterologous integration. Analysis of DNA methylation within and in proximity to the HPV genome at individual integration events revealed relationships between methylation status of the integrant and its orientation and structure. Dysregulation of the human epigenome and neighboring gene expression in cis with the HPV-integrated allele was observed over megabase-ranges of the genome. By elucidating the structural, epigenetic, and allele-specific impacts of HPV integration, we provide insight into the role of integrated HPV in cervical cancer.

Combinatorial and Machine Learning Approaches for Improved Somatic Variant Calling From Formalin-Fixed Paraffin-Embedded Genome Sequence Data.

Formalin fixation of paraffin-embedded tissue samples is a well-established method for preserving tissue and is routinely used in clinical settings. Although formalin-fixed, paraffin-embedded (FFPE) tissues are deemed crucial for research and clinical applications, the fixation process results in molecular damage to nucleic acids, thus confounding their use in genome sequence analysis. Methods to improve genomic data quality from FFPE tissues have emerged, but there remains significant room for improvement. Here, we use whole-genome sequencing (WGS) data from matched Fresh Frozen (FF) and FFPE tissue samples to optimize a sensitive and precise FFPE single nucleotide variant (SNV) calling approach. We present methods to reduce the prevalence of false-positive SNVs by applying combinatorial techniques to five publicly available variant callers. We also introduce FFPolish, a novel variant classification method that efficiently classifies FFPE-specific false-positive variants. Our combinatorial and statistical techniques improve precision and F1 scores compared to the results of publicly available tools when tested individually.

TMBur: a distributable tumor mutation burden approach for whole genome sequencing.

BACKGROUND: Tumor mutation burden (TMB) is a key characteristic used in a tumor-type agnostic context to inform the use of immune checkpoint inhibitors (ICI). Accurate and consistent measurement of TMB is crucial as it can significantly impact patient selection for therapy and clinical trials, with a threshold of 10 mutations/Mb commonly used as an inclusion criterion. Studies have shown that the most significant contributor to variability in mutation counts in whole genome sequence (WGS) data is differences in analysis methods, even more than differences in extraction or library construction methods. Therefore, tools for improving consistency in whole genome TMB estimation are of clinical importance. METHODS: We developed a distributable TMB analysis suite, TMBur, to address the need for genomic TMB estimate consistency in projects that span jurisdictions. TMBur is implemented in Nextflow and performs all analysis steps to generate TMB estimates directly from fastq files, incorporating somatic variant calling with Manta, Strelka2, and Mutect2, and microsatellite instability profiling with MSISensor. These tools are provided in a Singularity container downloaded by the workflow at runtime, allowing the entire workflow to be run identically on most computing platforms. To test the reproducibility of TMBur TMB estimates, we performed replicate runs on WGS data derived from the COLO829 and COLO829BL cell lines at multiple research centres. The clinical value of derived TMB estimates was then evaluated using a cohort of 90 patients with advanced, metastatic cancer that received ICIs following WGS analysis. Patients were split into groups based on a threshold of 10/Mb, and time to progression from initiation of ICIs was examined using Kaplan-Meier and cox-proportional hazards analyses. RESULTS: TMBur produced identical TMB estimates across replicates and at multiple analysis centres. The clinical utility of TMBur-derived TMB estimates were validated, with a genomic TMB ≥ 10/Mb demonstrating improved time to progression, even after correcting for differences in tumor type (HR = 0.39, p = 0.012). CONCLUSIONS: TMBur, a shareable workflow, generates consistent whole genome derived TMB estimates predictive of response to ICIs across multiple analysis centres. Reproducible TMB estimates from this approach can improve collaboration and ensure equitable treatment and clinical trial access spanning jurisdictions.

Automated Library Construction and Analysis for High-Throughput Nanopore Sequencing of SARS-CoV-2.

BACKGROUND: To support the implementation of high-throughput pipelines suitable for SARS-CoV-2 sequencing and analysis in a clinical laboratory, we developed an automated sample preparation and analysis workflow. METHODS: We used the established ARTIC protocol with approximately 400 bp amplicons sequenced on Oxford Nanopore's MinION. Sequences were analyzed using Nextclade, assigning both a clade and quality score to each sample. RESULTS: A total of 2179 samples on twenty-five 96-well plates were sequenced. Plates of purified RNA were processed within 12 h, sequencing required up to 24 h, and analysis of each pooled plate required 1 h. The use of samples with known threshold cycle (Ct) values enabled normalization, acted as a quality control check, and revealed a strong correlation between sample Ct values and successful analysis, with 85% of samples with Ct < 30 achieving a "good" Nextclade score. Less abundant samples responded to enrichment with the fraction of Ct > 30 samples achieving a "good" classification rising by 60% after addition of a post-ARTIC PCR normalization. Serial dilutions of 3 variant of concern samples, diluted from approximately Ct = 16 to approximately Ct = 50, demonstrated successful sequencing to Ct = 37. The sample set contained a median of 24 mutations per sample and a total of 1281 unique mutations with reduced sequence read coverage noted in some regions of some samples. A total of 10 separate strains were observed in the sample set, including 3 variants of concern prevalent in British Columbia in the spring of 2021. CONCLUSIONS: We demonstrated a robust automated sequencing pipeline that takes advantage of input Ct values to improve reliability.

A Scalable Strand-Specific Protocol Enabling Full-Length Total RNA Sequencing From Single Cells.

RNA sequencing (RNAseq) has been widely used to generate bulk gene expression measurements collected from pools of cells. Only relatively recently have single-cell RNAseq (scRNAseq) methods provided opportunities for gene expression analyses at the single-cell level, allowing researchers to study heterogeneous mixtures of cells at unprecedented resolution. Tumors tend to be composed of heterogeneous cellular mixtures and are frequently the subjects of such analyses. Extensive method developments have led to several protocols for scRNAseq but, owing to the small amounts of RNA in single cells, technical constraints have required compromises. For example, the majority of scRNAseq methods are limited to sequencing only the 3' or 5' termini of transcripts. Other protocols that facilitate full-length transcript profiling tend to capture only polyadenylated mRNAs and are generally limited to processing only 96 cells at a time. Here, we address these limitations and present a novel protocol that allows for the high-throughput sequencing of full-length, total RNA at single-cell resolution. We demonstrate that our method produced strand-specific sequencing data for both polyadenylated and non-polyadenylated transcripts, enabled the profiling of transcript regions beyond only transcript termini, and yielded data rich enough to allow identification of cell types from heterogeneous biological samples.

A Distributed Whole Genome Sequencing Benchmark Study.

Population sequencing often requires collaboration across a distributed network of sequencing centers for the timely processing of thousands of samples. In such massive efforts, it is important that participating scientists can be confident that the accuracy of the sequence data produced is not affected by which center generates the data. A study was conducted across three established sequencing centers, located in Montreal, Toronto, and Vancouver, constituting Canada's Genomics Enterprise (www.cgen.ca). Whole genome sequencing was performed at each center, on three genomic DNA replicates from three well-characterized cell lines. Secondary analysis pipelines employed by each site were applied to sequence data from each of the sites, resulting in three datasets for each of four variables (cell line, replicate, sequencing center, and analysis pipeline), for a total of 81 datasets. These datasets were each assessed according to multiple quality metrics including concordance with benchmark variant truth sets to assess consistent quality across all three conditions for each variable. Three-way concordance analysis of variants across conditions for each variable was performed. Our results showed that the variant concordance between datasets differing only by sequencing center was similar to the concordance for datasets differing only by replicate, using the same analysis pipeline. We also showed that the statistically significant differences between datasets result from the analysis pipeline used, which can be unified and updated as new approaches become available. We conclude that genome sequencing projects can rely on the quality and reproducibility of aggregate data generated across a network of distributed sites.

Pan-cancer analysis of advanced patient tumors reveals interactions between therapy and genomic landscapes.

Advanced and metastatic tumors with complex treatment histories drive cancer mortality. Here we describe the POG570 cohort, a comprehensive whole-genome, transcriptome and clinical dataset, amenable for exploration of the impacts of therapies on genomic landscapes. Previous exposure to DNA-damaging chemotherapies and mutations affecting DNA repair genes, including POLQ and genes encoding Polζ, were associated with genome-wide, therapy-induced mutagenesis. Exposure to platinum therapies coincided with signatures SBS31 and DSB5 and, when combined with DNA synthesis inhibitors, signature SBS17b. Alterations in ESR1, EGFR, CTNNB1, FGFR1, VEGFA and DPYD were consistent with drug resistance and sensitivity. Recurrent noncoding events were found in regulatory region hotspots of genes including TERT, PLEKHS1, AP2A1 and ADGRG6. Mutation burden and immune signatures corresponded with overall survival and response to immunotherapy. Our data offer a rich resource for investigation of advanced cancers and interpretation of whole-genome and transcriptome sequencing in the context of a cancer clinic.

Evaluation of protocols for rRNA depletion-based RNA sequencing of nanogram inputs of mammalian total RNA.

Next generation RNA-sequencing (RNA-seq) is a flexible approach that can be applied to a range of applications including global quantification of transcript expression, the characterization of RNA structure such as splicing patterns and profiling of expressed mutations. Many RNA-seq protocols require up to microgram levels of total RNA input amounts to generate high quality data, and thus remain impractical for the limited starting material amounts typically obtained from rare cell populations, such as those from early developmental stages or from laser micro-dissected clinical samples. Here, we present an assessment of the contemporary ribosomal RNA depletion-based protocols, and identify those that are suitable for inputs as low as 1-10 ng of intact total RNA and 100-500 ng of partially degraded RNA from formalin-fixed paraffin-embedded tissues.