A Biobank of Breast Cancer Explants with Preserved Intra-tumor Heterogeneity to Screen Anticancer Compounds.

The inter- and intra-tumor heterogeneity of breast cancer needs to be adequately captured in pre-clinical models. We have created a large collection of breast cancer patient-derived tumor xenografts (PDTXs), in which the morphological and molecular characteristics of the originating tumor are preserved through passaging in the mouse. An integrated platform combining in vivo maintenance of these PDTXs along with short-term cultures of PDTX-derived tumor cells (PDTCs) was optimized. Remarkably, the intra-tumor genomic clonal architecture present in the originating breast cancers was mostly preserved upon serial passaging in xenografts and in short-term cultured PDTCs. We assessed drug responses in PDTCs on a high-throughput platform and validated several ex vivo responses in vivo. The biobank represents a powerful resource for pre-clinical breast cancer pharmacogenomic studies (http://caldaslab.cruk.cam.ac.uk/bcape), including identification of biomarkers of response or resistance.

RNA sequencing: the teenage years.

Over the past decade, RNA sequencing (RNA-seq) has become an indispensable tool for transcriptome-wide analysis of differential gene expression and differential splicing of mRNAs. However, as next-generation sequencing technologies have developed, so too has RNA-seq. Now, RNA-seq methods are available for studying many different aspects of RNA biology, including single-cell gene expression, translation (the translatome) and RNA structure (the structurome). Exciting new applications are being explored, such as spatial transcriptomics (spatialomics). Together with new long-read and direct RNA-seq technologies and better computational tools for data analysis, innovations in RNA-seq are contributing to a fuller understanding of RNA biology, from questions such as when and where transcription occurs to the folding and intermolecular interactions that govern RNA function.

Expression profiling of cerebrospinal fluid identifies dysregulated antiviral mechanisms in multiple sclerosis.

Despite the overwhelming evidence that multiple sclerosis is an autoimmune disease, relatively little is known about the precise nature of the immune dysregulation underlying the development of the disease. Reasoning that the CSF from patients might be enriched for cells relevant in pathogenesis, we have completed a high-resolution single-cell analysis of 96 732 CSF cells collected from 33 patients with multiple sclerosis (n = 48 675) and 48 patients with other neurological diseases (n = 48 057). Completing comprehensive cell type annotation, we identified a rare population of CD8+ T cells, characterized by the upregulation of inhibitory receptors, increased in patients with multiple sclerosis. Applying a Multi-Omics Factor Analysis to these single-cell data further revealed that activity in pathways responsible for controlling inflammatory and type 1 interferon responses are altered in multiple sclerosis in both T cells and myeloid cells. We also undertook a systematic search for expression quantitative trait loci in the CSF cells. Of particular interest were two expression quantitative trait loci in CD8+ T cells that were fine mapped to multiple sclerosis susceptibility variants in the viral control genes ZC3HAV1 (rs10271373) and IFITM2 (rs1059091). Further analysis suggests that these associations likely reflect genetic effects on RNA splicing and cell-type specific gene expression respectively. Collectively, our study suggests that alterations in viral control mechanisms might be important in the development of multiple sclerosis.

Ebola Virus Transmission Initiated by Relapse of Systemic Ebola Virus Disease.

During the 2018-2020 Ebola virus disease (EVD) outbreak in North Kivu province in the Democratic Republic of Congo, EVD was diagnosed in a patient who had received the recombinant vesicular stomatitis virus-based vaccine expressing a ZEBOV glycoprotein (rVSV-ZEBOV) (Merck). His treatment included an Ebola virus (EBOV)-specific monoclonal antibody (mAb114), and he recovered within 14 days. However, 6 months later, he presented again with severe EVD-like illness and EBOV viremia, and he died. We initiated epidemiologic and genomic investigations that showed that the patient had had a relapse of acute EVD that led to a transmission chain resulting in 91 cases across six health zones over 4 months. (Funded by the Bill and Melinda Gates Foundation and others.).

Development and validation of blood tumor mutational burden reference standards.

Tumor mutational burden (TMB), measured by exome or panel sequencing of tumor tissue or blood (bTMB), is a potential predictive biomarker for treatment benefit in patients with various cancer types receiving immunotherapy targeting checkpoint pathways. However, significant variability in TMB measurement has been observed. We developed contrived bTMB reference materials using DNA from tumor cell lines and donor-matched lymphoblastoid cell lines to support calibration and alignment across laboratories and platforms. Contrived bTMB reference materials were developed using genomic DNA from lung tumor cell lines blended into donor-matched lymphoblastoid cell lines at 0.5% and 2% tumor content, fragmented and size-selected to mirror the size profile of circulating cell-free tumor DNA with TMB scores of 7, 9, 20, and 26 mut/Mb. Variant allele frequency (VAF) and bTMB scores were assessed using PredicineATLAS and GuardantOMNI next-generation sequencing assays. DNA fragment sizes in the contrived reference samples were similar to those found within patient plasma-derived cell-free DNA, and mutational patterns aligned with those in the parental tumor lines. For the 7, 20, and 26 mut/Mb contrived reference samples with 2% tumor content, bTMB scores estimated using either assay aligned with expected scores from the parental tumor cell lines and showed good reproducibility. A bioinformatic filtration step was required to account for low-VAF artifact variants. We demonstrate the feasibility and challenges of producing and using bTMB reference standards across a range of bTMB levels, and how such standards could support the calibration and validation of bTMB platforms and help harmonization between panels and laboratories.

RCandy: an R package for visualizing homologous recombinations in bacterial genomes.

SUMMARY: Homologous recombination is an important evolutionary process in bacteria and other prokaryotes, which increases genomic sequence diversity and can facilitate adaptation. Several methods and tools have been developed to detect genomic regions recently affected by recombination. Exploration and visualization of such recombination events can reveal valuable biological insights, but it remains challenging. Here, we present RCandy, a platform-independent R package for rapid, simple and flexible visualization of recombination events in bacterial genomes. AVAILABILITY AND IMPLEMENTATION: RCandy is an R package freely available for use under the MIT license. It is platform-independent and has been tested on Windows, Linux and MacOSX. The source code comes together with a detailed vignette available on GitHub at https://github.com/ChrispinChaguza/RCandy. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A Phylodynamic Workflow to Rapidly Gain Insights into the Dispersal History and Dynamics of SARS-CoV-2 Lineages.

Since the start of the COVID-19 pandemic, an unprecedented number of genomic sequences of SARS-CoV-2 have been generated and shared with the scientific community. The unparalleled volume of available genetic data presents a unique opportunity to gain real-time insights into the virus transmission during the pandemic, but also a daunting computational hurdle if analyzed with gold-standard phylogeographic approaches. To tackle this practical limitation, we here describe and apply a rapid analytical pipeline to analyze the spatiotemporal dispersal history and dynamics of SARS-CoV-2 lineages. As a proof of concept, we focus on the Belgian epidemic, which has had one of the highest spatial densities of available SARS-CoV-2 genomes. Our pipeline has the potential to be quickly applied to other countries or regions, with key benefits in complementing epidemiological analyses in assessing the impact of intervention measures or their progressive easement.

Characterising the epidemic spread of influenza A/H3N2 within a city through phylogenetics.

Infecting large portions of the global population, seasonal influenza is a major burden on societies around the globe. While the global source sink dynamics of the different seasonal influenza viruses have been studied intensively, its local spread remains less clear. In order to improve our understanding of how influenza is transmitted on a city scale, we collected an extremely densely sampled set of influenza sequences alongside patient metadata. To do so, we sequenced influenza viruses isolated from patients of two different hospitals, as well as private practitioners in Basel, Switzerland during the 2016/2017 influenza season. The genetic sequences reveal that repeated introductions into the city drove the influenza season. We then reconstruct how the effective reproduction number changed over the course of the season. While we did not find that transmission dynamics in Basel correlate with humidity or school closures, we did find some evidence that it may positively correlated with temperature. Alongside the genetic sequence data that allows us to see how individual cases are connected, we gathered patient information, such as the age or household status. Zooming into the local transmission outbreaks suggests that the elderly were to a large extent infected within their own transmission network. In the remaining transmission network, our analyses suggest that school-aged children likely play a more central role than pre-school aged children. These patterns will be valuable to plan interventions combating the spread of respiratory diseases within cities given that similar patterns are observed for other influenza seasons and cities.

Real-Time Genomics for Tracking Severe Acute Respiratory Syndrome Coronavirus 2 Border Incursions after Virus Elimination, New Zealand.

Since severe acute respiratory syndrome coronavirus 2 was first eliminated in New Zealand in May 2020, a total of 13 known coronavirus disease (COVID-19) community outbreaks have occurred, 2 of which led health officials to issue stay-at-home orders. These outbreaks originated at the border via isolating returnees, airline workers, and cargo vessels. Because a public health system was informed by real-time viral genomic sequencing and complete genomes typically were available within 12 hours of community-based positive COVID-19 test results, every outbreak was well-contained. A total of 225 community cases resulted in 3 deaths. Real-time genomics were essential for establishing links between cases when epidemiologic data could not do so and for identifying when concurrent outbreaks had different origins.

Use of Genomics to Track Coronavirus Disease Outbreaks, New Zealand.

Real-time genomic sequencing has played a major role in tracking the global spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), contributing greatly to disease mitigation strategies. In August 2020, after having eliminated the virus, New Zealand experienced a second outbreak. During that outbreak, New Zealand used genomic sequencing in a primary role, leading to a second elimination of the virus. We generated genomes from 78% of the laboratory-confirmed samples of SARS-CoV-2 from the second outbreak and compared them with the available global genomic data. Genomic sequencing rapidly identified that virus causing the second outbreak in New Zealand belonged to a single cluster, thus resulting from a single introduction. However, successful identification of the origin of this outbreak was impeded by substantial biases and gaps in global sequencing data. Access to a broader and more heterogenous sample of global genomic data would strengthen efforts to locate the source of any new outbreaks.

Genomic Evidence of In-Flight Transmission of SARS-CoV-2 Despite Predeparture Testing.

Since the first wave of coronavirus disease in March 2020, citizens and permanent residents returning to New Zealand have been required to undergo managed isolation and quarantine (MIQ) for 14 days and mandatory testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As of October 20, 2020, of 62,698 arrivals, testing of persons in MIQ had identified 215 cases of SARS-CoV-2 infection. Among 86 passengers on a flight from Dubai, United Arab Emirates, that arrived in New Zealand on September 29, test results were positive for 7 persons in MIQ. These passengers originated from 5 different countries before a layover in Dubai; 5 had negative predeparture SARS-CoV-2 test results. To assess possible points of infection, we analyzed information about their journeys, disease progression, and virus genomic data. All 7 SARS-CoV-2 genomes were genetically identical, except for a single mutation in 1 sample. Despite predeparture testing, multiple instances of in-flight SARS-CoV-2 transmission are likely.

Twenty years of West Nile virus spread and evolution in the Americas visualized by Nextstrain.

It has been 20 years since West Nile virus first emerged in the Americas, and since then, little progress has been made to control outbreaks caused by this virus. After its first detection in New York in 1999, West Nile virus quickly spread across the continent, causing an epidemic of human disease and massive bird die-offs. Now the virus has become endemic to the United States, where an estimated 7 million human infections have occurred, making it the leading mosquito-borne virus infection and the most common cause of viral encephalitis in the country. To bring new attention to one of the most important mosquito-borne viruses in the Americas, we provide an interactive review using Nextstrain: a visualization tool for real-time tracking of pathogen evolution (nextstrain.org/WNV/NA). Nextstrain utilizes a growing database of more than 2,000 West Nile virus genomes and harnesses the power of phylogenetics for students, educators, public health workers, and researchers to visualize key aspects of virus spread and evolution. Using Nextstrain, we use virus genomics to investigate the emergence of West Nile virus in the U S, followed by its rapid spread, evolution in a new environment, establishment of endemic transmission, and subsequent international spread. For each figure, we include a link to Nextstrain to allow the readers to directly interact with and explore the underlying data in new ways. We also provide a brief online narrative that parallels this review to further explain the data and highlight key epidemiological and evolutionary features (nextstrain.org/narratives/twenty-years-of-WNV). Mirroring the dynamic nature of outbreaks, the Nextstrain links provided within this paper are constantly updated as new West Nile virus genomes are shared publicly, helping to stay current with the research. Overall, our review showcases how genomics can track West Nile virus spread and evolution, as well as potentially uncover novel targeted control measures to help alleviate its public health burden.

Progesterone receptor modulates ERα action in breast cancer.

Progesterone receptor (PR) expression is used as a biomarker of oestrogen receptor-α (ERα) function and breast cancer prognosis. Here we show that PR is not merely an ERα-induced gene target, but is also an ERα-associated protein that modulates its behaviour. In the presence of agonist ligands, PR associates with ERα to direct ERα chromatin binding events within breast cancer cells, resulting in a unique gene expression programme that is associated with good clinical outcome. Progesterone inhibited oestrogen-mediated growth of ERα(+) cell line xenografts and primary ERα(+) breast tumour explants, and had increased anti-proliferative effects when coupled with an ERα antagonist. Copy number loss of PGR, the gene coding for PR, is a common feature in ERα(+) breast cancers, explaining lower PR levels in a subset of cases. Our findings indicate that PR functions as a molecular rheostat to control ERα chromatin binding and transcriptional activity, which has important implications for prognosis and therapeutic interventions.

Comprehensive global genome dynamics of Chlamydia trachomatis show ancient diversification followed by contemporary mixing and recent lineage expansion.

Chlamydia trachomatis is the world's most prevalent bacterial sexually transmitted infection and leading infectious cause of blindness, yet it is one of the least understood human pathogens, in part due to the difficulties of in vitro culturing and the lack of available tools for genetic manipulation. Genome sequencing has reinvigorated this field, shedding light on the contemporary history of this pathogen. Here, we analyze 563 full genomes, 455 of which are novel, to show that the history of the species comprises two phases, and conclude that the currently circulating lineages are the result of evolution in different genomic ecotypes. Temporal analysis indicates these lineages have recently expanded in the space of thousands of years, rather than the millions of years as previously thought, a finding that dramatically changes our understanding of this pathogen's history. Finally, at a time when almost every pathogen is becoming increasingly resistant to antimicrobials, we show that there is no evidence of circulating genomic resistance in C. trachomatis.

Independence of HIF1a and androgen signaling pathways in prostate cancer.

BACKGROUND: Therapeutic targeting of the androgen signaling pathway is a mainstay treatment for prostate cancer. Although initially effective, resistance to androgen targeted therapies develops followed by disease progression to castrate-resistant prostate cancer (CRPC). Hypoxia and HIF1a have been implicated in the development of resistance to androgen targeted therapies and progression to CRCP. The interplay between the androgen and hypoxia/HIF1a signaling axes was investigated. METHODS: In vitro stable expression of HIF1a was established in the LNCaP cell line by physiological induction or retroviral transduction. Tumor xenografts with stable expression of HIF1a were established in castrated and non-castrated mouse models. Gene expression analysis identified transcriptional changes in response to androgen treatment, hypoxia and HIF1a. The binding sites of the AR and HIF transcription factors were identified using ChIP-seq. RESULTS: Androgen and HIF1a signaling promoted proliferation in vitro and enhanced tumor growth in vivo. The stable expression of HIF1a in vivo restored tumor growth in the absence of endogenous androgens. Hypoxia reduced AR binding sites whereas HIF binding sites were increased with androgen treatment under hypoxia. Gene expression analysis identified seven genes that were upregulated both by AR and HIF1a, of which six were prognostic. CONCLUSIONS: The oncogenic AR, hypoxia and HIF1a pathways support prostate cancer development through independent signaling pathways and transcriptomic profiles. AR and hypoxia/HIF1a signaling pathways independently promote prostate cancer progression and therapeutic targeting of both pathways simultaneously is warranted.

Phandango: an interactive viewer for bacterial population genomics.

SUMMARY: Fully exploiting the wealth of data in current bacterial population genomics datasets requires synthesizing and integrating different types of analysis across millions of base pairs in hundreds or thousands of isolates. Current approaches often use static representations of phylogenetic, epidemiological, statistical and evolutionary analysis results that are difficult to relate to one another. Phandango is an interactive application running in a web browser allowing fast exploration of large-scale population genomics datasets combining the output from multiple genomic analysis methods in an intuitive and interactive manner. AVAILABILITY AND IMPLEMENTATION: Phandango is a web application freely available for use at www.phandango.net and includes a diverse collection of datasets as examples. Source code together with a detailed wiki page is available on GitHub at https://github.com/jameshadfield/phandango.

Nextstrain: real-time tracking of pathogen evolution.

Summary: Understanding the spread and evolution of pathogens is important for effective public health measures and surveillance. Nextstrain consists of a database of viral genomes, a bioinformatics pipeline for phylodynamics analysis, and an interactive visualization platform. Together these present a real-time view into the evolution and spread of a range of viral pathogens of high public health importance. The visualization integrates sequence data with other data types such as geographic information, serology, or host species. Nextstrain compiles our current understanding into a single accessible location, open to health professionals, epidemiologists, virologists and the public alike. Availability and implementation: All code (predominantly JavaScript and Python) is freely available from github.com/nextstrain and the web-application is available at nextstrain.org.

The Hidden Genomics of Chlamydia trachomatis.

The application of whole-genome sequencing has moved us on from sequencing single genomes to defining unravelling population structures in different niches, and at the -species, -serotype or even -genus level, and in local, national and global settings. This has been instrumental in cataloguing and revealing a huge a range of diversity in this bacterium, when at first we thought there was little. Genomics has challenged assumptions, added insight, as well as confusion and glimpses of truths. What is clear is that at a time when we start to realise the extent and nature of the diversity contained within a genus or a species like this, the huge depth of knowledge communities have developed, through cell biology, as well as the new found molecular approaches will be more precious than ever to link genotype to phenotype. Here we detail the technological developments and insights we have seen during the relatively short time since we began to see the hidden genome of Chlamydia trachomatis.

Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA.

Cancers acquire resistance to systemic treatment as a result of clonal evolution and selection. Repeat biopsies to study genomic evolution as a result of therapy are difficult, invasive and may be confounded by intra-tumour heterogeneity. Recent studies have shown that genomic alterations in solid cancers can be characterized by massively parallel sequencing of circulating cell-free tumour DNA released from cancer cells into plasma, representing a non-invasive liquid biopsy. Here we report sequencing of cancer exomes in serial plasma samples to track genomic evolution of metastatic cancers in response to therapy. Six patients with advanced breast, ovarian and lung cancers were followed over 1-2 years. For each case, exome sequencing was performed on 2-5 plasma samples (19 in total) spanning multiple courses of treatment, at selected time points when the allele fraction of tumour mutations in plasma was high, allowing improved sensitivity. For two cases, synchronous biopsies were also analysed, confirming genome-wide representation of the tumour genome in plasma. Quantification of allele fractions in plasma identified increased representation of mutant alleles in association with emergence of therapy resistance. These included an activating mutation in PIK3CA (phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha) following treatment with paclitaxel; a truncating mutation in RB1 (retinoblastoma 1) following treatment with cisplatin; a truncating mutation in MED1 (mediator complex subunit 1) following treatment with tamoxifen and trastuzumab, and following subsequent treatment with lapatinib, a splicing mutation in GAS6 (growth arrest-specific 6) in the same patient; and a resistance-conferring mutation in EGFR (epidermal growth factor receptor; T790M) following treatment with gefitinib. These results establish proof of principle that exome-wide analysis of circulating tumour DNA could complement current invasive biopsy approaches to identify mutations associated with acquired drug resistance in advanced cancers. Serial analysis of cancer genomes in plasma constitutes a new paradigm for the study of clonal evolution in human cancers.