BackgroundMolecularly-guided trials (i.e. PMed) now seek to aid clinical decision-making by matching cancer targets with therapeutic options. Progress has been hampered by the lack of cancer models that account for individual-to-individual heterogeneity within and across cancer types. Naturally occurring cancers in pet animals are heterogeneous and thus provide an opportunity to answer questions about these PMed strategies and optimize translation to human patients. In order to realize this opportunity, it is now necessary to demonstrate the feasibility of conducting molecularly-guided analysis of tumors from dogs with naturally occurring cancer in a clinically relevant setting.MethodologyA proof-of-concept study was conducted by the Comparative Oncology Trials Consortium (COTC) to determine if tumor collection, prospective molecular profiling, and PMed report generation within 1 week was feasible in dogs. Thirty-one dogs with cancers of varying histologies were enrolled. Twenty-four of 31 samples (77%) successfully met all predefined QA/QC criteria and were analyzed via Affymetrix gene expression profiling. A subsequent bioinformatics workflow transformed genomic data into a personalized drug report. Average turnaround from biopsy to report generation was 116 hours (4.8 days). Unsupervised clustering of canine tumor expression data clustered by cancer type, but supervised clustering of tumors based on the personalized drug report clustered by drug class rather than cancer type.ConclusionsCollection and turnaround of high quality canine tumor samples, centralized pathology, analyte generation, array hybridization, and bioinformatic analyses matching gene expression to therapeutic options is achievable in a practical clinical window (<1 week). Clustering data show robust signatures by cancer type but also showed patient-to-patient heterogeneity in drug predictions. This lends further support to the inclusion of a heterogeneous population of dogs with cancer into the preclinical modeling of personalized medicine. Future comparative oncology studies optimizing the delivery of PMed strategies may aid cancer drug development.
SARS-CoV-2 infections can be symptomatic as well as asymptomatic. In this study, we analyzed 460,814 saliva samples collected from July 2020 to January 2021 for a SARS-CoV-2-specific gene target using the FDA EUA test, CRL Rapid ResponseTM, based on reverse transcription polymerase chain reaction (RT-PCR). We measured SARS-CoV-2 viral loads using cycle threshold (Ct) values. A total of 17,813 samples tested positive for COVID-19 using self-collected saliva samples. The Ct values ranged from 11 to 40, 91.3% distributed between 22 to 38 Ct. We then compared Ct values for symptomatic and asymptomatic cases for all positive saliva samples. A total of 8,706 cases were symptomatic with an average Ct value of 29.24, and 9,107 cases were asymptomatic with an average Ct value of 30.99. Hence, SARS-CoV-2 viral loads (Ct) in saliva samples for both symptomatic and asymptomatic cases are similar.
The most recent virus from the Coronaviridae family infecting humans, SARS-CoV-2, has resulted in a global pandemic. As part of the surveillance efforts, SARS-CoV-2 genomes are increasingly being made publicly available. Methods that include both short- and long-read sequencing have been used to elucidate SARS-CoV-2 genomes; however, many of these untargeted approaches may require deeper sequencing for greater genome coverage. For this reason, sequence capture or amplicon-based approaches for SARS-CoV-2 genome sequencing have been developed. The present study evaluated a modified sequence capture approach, namely, tailed amplicon sequencing, to determine SARS-CoV-2 near complete genome sequences from the saliva of infected individuals. Particularly, the suitability of saliva samples stored at room temperature using OMNIgene®·ORAL OME-505 was evaluated. The tailed amplicon sequencing approach poses the additional advantage of being a cost-effective method for library preparation. Different known SARS-CoV-2 variants were identified across the infected subjects, with an average of > 99.4% genome coverage. This methodology also enabled robust genomic surveillance using phylogenetic analyses. The present study supports the suitability of saliva stored at room temperature using collection devices for SARS-CoV-2 variant detection. Importantly, the present study supports the use of tailed amplicon sequencing approaches as an alternative, cost-effective method for SARS-CoV-2 detection in saliva for genomic surveillance.
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