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Oral squamous cell carcinoma (OSCC) in the young (50 years), without known carcinogenic risk factors, is on the rise globally. Whole genome duplication (WGD) has been shown to occur at higher rates in cancers without an identifiable carcinogenic agent. We aimed to evaluate the prevalence of WGD in a cohort of OSCC patients under the age of 50 years.Whole genome sequencing (WGS) was performed on 28 OSCC patients from the Sydney Head and Neck Cancer Institute (SHNCI) biobank. An additional nine cases were obtained from The Cancer Genome Atlas (TCGA).WGD was seen in 27 of 37 (73%) cases. Non-synonymous, somatic TP53 mutations occurred in 25 of 27 (93%) cases of WGD and were predicted to precede WGD in 21 (77%). WGD was significantly associated with larger tumor size (p = 0.01) and was frequent in patients with recurrences (87%, p = 0.36). Overall survival was significantly worse in those with WGD (p = 0.05).Our data, based on one of the largest WGS datasets of young patients with OSCC, demonstrates a high frequency of WGD and its association with adverse pathologic characteristics and clinical outcomes. TP53 mutations also preceded WGD, as has been described in other tumors without a clear mutagenic driver.

In January 2020, a novel betacoronavirus (family Coronaviridae), named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified as the etiological agent of a cluster of pneumonia cases occurring in Wuhan City, Hubei Province, China1,2. The disease arising from SARS-CoV-2 infection, coronavirus disease 2019 (COVID-19), subsequently spread rapidly causing a worldwide pandemic. Here we examine the added value of near real-time genome sequencing of SARS-CoV-2 in a subpopulation of infected patients during the first 10 weeks of COVID-19 containment in Australia and compare findings from genomic surveillance with predictions of a computational agent-based model (ABM). Using the Australian census data, the ABM generates over 24 million software agents representing the population of Australia, each with demographic attributes of an anonymous individual. It then simulates transmission of the disease over time, spreading from specific infection sources, using contact rates of individuals within different social contexts. We report that the prospective sequencing of SARS-CoV-2 clarified the probable source of infection in cases where epidemiological links could not be determined, significantly decreased the proportion of COVID-19 cases with contentious links, documented genomically similar cases associated with concurrent transmission in several institutions and identified previously unsuspected links. Only a quarter of sequenced cases appeared to be locally acquired and were concordant with predictions from the ABM. These high-resolution genomic data are crucial to track cases with locally acquired COVID-19 and for timely recognition of independent importations once border restrictions are lifted and trade and travel resume.

Candida glabrata can rapidly acquire mutations that result in drug resistance, especially to azoles and echinocandins. Identification of genetic mutations is essential, as resistance detected in vitro can often be correlated with clinical failure. We examined the feasibility of using whole genome sequencing (WGS) for genome-wide analysis of antifungal drug resistance in C. glabrata. The aim was torecognize enablers and barriers in the implementation WGS and measure its effectiveness. This paper outlines the key quality control checkpoints and essential components of WGS methodology to investigate genetic markers associated with reduced susceptibility to antifungal agents. It also estimates the accuracy of data analysis and turn-around-time of testing. Phenotypic susceptibility of 12 clinical, and one ATCC strain of C. glabrata was determined through antifungal susceptibility testing. These included three isolate pairs, from three patients, that developed rise in drug minimum inhibitory concentrations. In two pairs, the second isolate of each pair developed resistance to echinocandins. The second isolate of the third pair developed resistance to 5-flucytosine. The remaining comprised of susceptible and azole resistant isolates. Single nucleotide polymorphisms (SNPs) in genes linked to echinocandin, azole and 5-flucytosine resistance were confirmed in resistant isolates through WGS using the next generation sequencing. Non-synonymous SNPs in antifungal resistance genes such as FKS1, FKS2, CgPDR1, CgCDR1 and FCY2 were identified. Overall, an average of 98% of the WGS reads of C. glabrata isolates mapped to the reference genome with about 75-fold read depth coverage. The turnaround time and cost were comparable to Sanger sequencing. In conclusion, WGS of C. glabrata was feasible in revealing clinically significant gene mutations involved in resistance to different antifungal drug classes without the need for multiple PCR/DNA sequencing reactions. This represents a positive step towards establishing WGS capability in the clinical laboratory for simultaneous detection of antifungal resistance conferring substitutions.

Background Improved tuberculosis control and the need to contain the spread of drug-resistant strains provide a strong rationale for exploring tuberculosis transmission dynamics at the population level. Whole-genome sequencing provides optimal strain resolution, facilitating detailed mapping of potential transmission pathways. Methods We sequenced 22 isolates from a Mycobacterium tuberculosis cluster in New South Wales, Australia, identified during routine 24-locus mycobacterial interspersed repetitive unit typing. Following high-depth paired-end sequencing using the Illumina HiSeq 2000 platform, two independent pipelines were employed for analysis, both employing read mapping onto reference genomes as well as de novo assembly, to control biases in variant detection. In addition to single-nucleotide polymorphisms, the analyses also sought to identify insertions, deletions and structural variants. Results Isolates were highly similar, with a distance of 13 variants between the most distant members of the cluster. The most sensitive analysis classified the 22 isolates into 18 groups. Four of the isolates did not appear to share a recent common ancestor with the largest clade; another four isolates had an uncertain ancestral relationship with the largest clade. Conclusion Whole genome sequencing, with analysis of single-nucleotide polymorphisms, insertions, deletions, structural variants and subpopulations, enabled the highest possible level of discrimination between cluster members, clarifying likely transmission pathways and exposing the complexity of strain origin. The analysis provides a basis for targeted public health intervention and enhanced classification of future isolates linked to the cluster.