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A proof of principle study shows that by exome sequencing of cell-free circulating DNA from cancer patient plasma samples, the genomic evolution of metastatic cancers and the acquisition of resistance in response to therapy can be tracked over time. Plasma screening tracks tumour evolution This proof-of-principle study shows that by sequencing cancer exomes from patient plasma samples, it is possible to track genomic evolution of metastatic cancers and acquisition of resistance in response to therapy. In six patients with advanced breast, lung and ovarian cancers, sequences were derived from two to five plasma samples taken during multiple courses of treatment. Mutations associated with the emergence of resistance to drugs including cisplatin, tamoxifen and gefitinib were identified. Cancers acquire resistance to systemic treatment as a result of clonal evolution and selection 1 , 2 . Repeat biopsies to study genomic evolution as a result of therapy are difficult, invasive and may be confounded by intra-tumour heterogeneity 3 , 4 . 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 5 , 6 , 7 . 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 8 ; a truncating mutation in RB1 (retinoblastoma 1) following treatment with cisplatin 9 ; a truncating mutation in MED1 (mediator complex subunit 1) following treatment with tamoxifen and trastuzumab 10 , 11 , and following subsequent treatment with lapatinib 12 , 13 , 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 14 . 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.

Characterising the hierarchy of mammary epithelial cells (MECs) and how they are regulated during adult development is important for understanding how breast cancer arises. Here we report the use of single-cell RNA sequencing to determine the gene expression profile of MECs across four developmental stages; nulliparous, mid gestation, lactation and post involution. Our analysis of 23,184 cells identifies 15 clusters, few of which could be fully characterised by a single marker gene. We argue instead that the epithelial cells—especially in the luminal compartment—should rather be conceptualised as being part of a continuous spectrum of differentiation. Furthermore, our data support the existence of a common luminal progenitor cell giving rise to intermediate, restricted alveolar and hormone-sensing progenitors. This luminal progenitor compartment undergoes transcriptional changes in response to a full pregnancy, lactation and involution. In summary, our results provide a global, unbiased view of adult mammary gland development. There is a need to understand how mammary epithelial cells respond to changes at various developmental stages. Here, the authors use single-cell RNA sequencing of mammary epithelial cells at different adult developmental stages, identifying different cell types and charting their developmental trajectory.

Glioma‐derived cell‐free DNA (cfDNA) is challenging to detect using liquid biopsy because quantities in body fluids are low. We determined the glioma‐derived DNA fraction in cerebrospinal fluid (CSF), plasma, and urine samples from patients using sequencing of personalized capture panels guided by analysis of matched tumor biopsies. By sequencing cfDNA across thousands of mutations, identified individually in each patient’s tumor, we detected tumor‐derived DNA in the majority of CSF (7/8), plasma (10/12), and urine samples (10/16), with a median tumor fraction of 6.4 × 10 −3 , 3.1 × 10 −5 , and 4.7 × 10 −5 , respectively. We identified a shift in the size distribution of tumor‐derived cfDNA fragments in these body fluids. We further analyzed cfDNA fragment sizes using whole‐genome sequencing, in urine samples from 35 glioma patients, 27 individuals with non‐malignant brain disorders, and 26 healthy individuals. cfDNA in urine of glioma patients was significantly more fragmented compared to urine from patients with non‐malignant brain disorders ( P  = 1.7 × 10 −2 ) and healthy individuals ( P  = 5.2 × 10 −9 ). Machine learning models integrating fragment length could differentiate urine samples from glioma patients (AUC = 0.80–0.91) suggesting possibilities for truly non‐invasive cancer detection. SYNOPSIS Gliomas are challenging to detect using tumor derived cell‐free DNA (cfDNA) in body fluids. In this study, two novel analysis methods (tumor‐guided sequencing and sWGS) were developed to explore the potential of using plasma and urine cfDNA as a liquid biopsy for this malignancy. Multiple tumor regions were sequenced to recover a high number of mutations for designing tumor‐guided sequencing panels. Using tumor‐guided sequencing and the INVAR analysis approach, mutations were detected in 7/8 CSF, 10/12 plasma and 10/16 urine gliomas samples. Using low coverage whole genome sequencing, cfDNA fragmentation patterns were analysed in urine samples from 35 glioma patients, 27 individuals with non‐malignant brain disorders, and 26 healthy individuals. Fragment lengths differed significantly between these groups; Machine learning models (LR, SVM, RF, GLMEN) integrating fragment length could differentiate urine samples from glioma patients (AUC = 0.80–0.91). Graphical Abstract Gliomas are challenging to detect using tumor derived cell‐free DNA (cfDNA) in body fluids. In this study, two novel analysis methods (tumor‐guided sequencing and sWGS) were developed to explore the potential of using plasma and urine cfDNA as a liquid biopsy for this malignancy.

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.

New Zealand, a geographically remote Pacific island with easily sealable borders, implemented a nationwide ‘lockdown’ of all non-essential services to curb the spread of COVID-19. Here, we generate 649 SARS-CoV-2 genome sequences from infected patients in New Zealand with samples collected during the ‘first wave’, representing 56% of all confirmed cases in this time period. Despite its remoteness, the viruses imported into New Zealand represented nearly all of the genomic diversity sequenced from the global virus population. These data helped to quantify the effectiveness of public health interventions. For example, the effective reproductive number, R e of New Zealand’s largest cluster decreased from 7 to 0.2 within the first week of lockdown. Similarly, only 19% of virus introductions into New Zealand resulted in ongoing transmission of more than one additional case. Overall, these results demonstrate the utility of genomic pathogen surveillance to inform public health and disease mitigation. New Zealand implemented stringent COVID-19 control measures early after identification of its first case. Here, the authors perform whole genome sequencing of samples taken until 22 May 2020 and find high viral diversity indicative of multiple separate introductions and limited community transmission.

In the second quarter of 2022, there was a global surge of emergent SARS-CoV-2 lineages that had a distinct growth advantage over then-dominant Omicron BA.1 and BA.2 lineages. By generating 10,403 Omicron genomes, we show that Aotearoa New Zealand observed an influx of these immune-evasive variants (BA.2.12.1, BA.4, and BA.5) through the border. This is explained by the return to significant levels of international travel following the border’s reopening in March 2022. We estimate one Omicron transmission event from the border to the community for every ~5,000 passenger arrivals at the current levels of travel and restriction. Although most of these introductions did not instigate any detected onward transmission, a small minority triggered large outbreaks. Genomic surveillance at the border provides a lens on the rate at which new variants might gain a foothold and trigger new waves of infection. In March 2022, Aotearoa New Zealand re-opened its border allowing quarantine-free travel for many travellers. Here, the authors describe circulating Omicron sub-variants before and after the reopening of the border and show that the rate of viral introductions grew roughly linearly with the increase in daily international travel.

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.

New Zealand’s COVID-19 elimination strategy heavily relied on the use of genomics to inform contact tracing, linking cases to the border and to clusters during community outbreaks. In August 2021, New Zealand entered its second nationwide lockdown after the detection of a single community case with no immediately apparent epidemiological link to the border. This incursion resulted in the largest outbreak seen in New Zealand caused by the Delta Variant of Concern. Here we generated 3806 high quality SARS-CoV-2 genomes from cases reported in New Zealand between 17 August and 1 December 2021, representing 43% of reported cases. We detected wide geographical spread coupled with undetected community transmission, characterised by the apparent extinction and reappearance of genomically linked clusters. We also identified the emergence, and near replacement, of genomes possessing a 10-nucleotide frameshift deletion that caused the likely truncation of accessory protein ORF7a. By early October, New Zealand moved from an elimination strategy to a suppression strategy and the role of genomics changed markedly from being used to track and trace, towards population-level surveillance. Aotearoa New Zealand pursued a COVID-19 elimination strategy until October 2021 when it moved to a suppression strategy. In this genomic surveillance study, the authors describe spread of the virus during the transition between these strategies, with evidence of substantial undetected community transmission.

Morris Brown and colleagues identify somatic mutations in ATP1A1 and CACNA1D in aldosterone-producing adenomas with features resembling zonaglomerulosa cells. They further show that the ATP1A1 mutations cause inward leak currents under physiological conditions, whereas the CACNA1D mutations induce a shift of voltage-dependent gating to more negative potentials and suppress channel inactivation. At least 5% of individuals with hypertension have adrenal aldosterone-producing adenomas (APAs). Gain-of-function mutations in KCNJ5 and apparent loss-of-function mutations in ATP1A1 and ATP2A3 were reported to occur in APAs 1 , 2 . We find that KCNJ5 mutations are common in APAs resembling cortisol-secreting cells of the adrenal zona fasciculata but are absent in a subset of APAs resembling the aldosterone-secreting cells of the adrenal zona glomerulosa 3 . We performed exome sequencing of ten zona glomerulosa–like APAs and identified nine with somatic mutations in either ATP1A1 , encoding the Na + /K + ATPase α1 subunit, or CACNA1D , encoding Ca v 1.3. The ATP1A1 mutations all caused inward leak currents under physiological conditions, and the CACNA1D mutations induced a shift of voltage-dependent gating to more negative voltages, suppressed inactivation or increased currents. Many APAs with these mutations were <1 cm in diameter and had been overlooked on conventional adrenal imaging. Recognition of the distinct genotype and phenotype for this subset of APAs could facilitate diagnosis.

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.