Prospective Molecular Profiling of Canine Cancers Provides a Clinically Relevant Comparative Model for Evaluating Personalized Medicine (PMed) Trials.

Background Molecularly-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. Methodology A 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. Conclusions Collection 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 (\u3c1 \u3eweek). 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

Targeted bisulfite sequencing for biomarker discovery.

Cytosine methylation is one of the best studied epigenetic modifications. In mammals, DNA methylation patterns vary among cells and is mainly found in the CpG context. DNA methylation is involved in important processes during development and differentiation and its dysregulation can lead to or is associated with diseases, such as cancer, loss-of-imprinting syndromes and neurological disorders. It has been also shown that DNA methylation at the cellular, tissue and organism level varies with age. To overcome the costs of Whole-Genome Bisulfite Sequencing, the gold standard method to detect 5-methylcytosines at a single base resolution, DNA methylation arrays have been developed and extensively used. This method allows one to assess the status of a fraction of the CpG sites present in the genome of an organism. In order to combine the relatively low cost of Methylation Arrays and digital signals of bisulfite sequencing, we developed a Targeted Bisulfite Sequencing method that can be applied to biomarker discovery for virtually any phenotype. Here we describe a comprehensive step-by-step protocol to build a DNA methylation-based epigenetic clock

Rapid SARS-CoV-2 Virus Enrichment and RNA Extraction for Efficient Diagnostic Screening of Pooled Nasopharyngeal or Saliva Samples for Dilutions Up to 1:100

As COVID-19 transmission control measures are gradually being lifted, a sensitive and rapid diagnostic method for large-scale screening could prove essential for monitoring population infection rates. However, many rapid workflows for SARS-CoV-2 detection and diagnosis are not amenable to the analysis of large-volume samples. Previously, our group demonstrated a technique for SARS-CoV-2 nanoparticle-facilitated enrichment and enzymatic lysis from clinical samples in under 10 min. Here, this sample preparation strategy was applied to pooled samples originating from nasopharyngeal (NP) swabs eluted in viral transport medium (VTM) and saliva samples diluted up to 1:100. This preparation method was coupled with conventional RT-PCR on gold-standard instrumentation for proof-of-concept. Additionally, real-time PCR analysis was conducted using an in-house, ultra-rapid real-time microfluidic instrument paired with an experimentally optimized rapid protocol. Following pooling and extraction from clinical samples, average cycle threshold (CT) values from resultant eluates generally increased as the pooling dilution factor increased; further, results from a double-blind study demonstrated 100% concordance with clinical values. In addition, preliminary data obtained from amplification of eluates prepared by this technique and analyzed using our portable, ultra-rapid real-time microfluidic PCR amplification instrument showed progress toward a streamlined method for rapid SARS-CoV-2 analysis from pooled samples

Antigen receptor regulation of phosphoinositide-dependent kinase 1 pathways during thymocyte development

AbstractPhosphoinositide-dependent kinase 1 (PDK1) is essential for T cell development but little is know about the stimuli that regulate PDK1 signaling in vivo. The thymus contains a heterogeneous mixture of cells at different stages of development making it difficult to use biochemical techniques to examine the activity of PDK1 pathways as thymocytes develop in situ. Herein, we use a single cell assay to quantify activation of the PDK1 target kinase ribosomal S6 kinase 1 (S6K1) in different murine thymocyte subsets immediately ex vivo. This technique allows an assessment of S6K1 activation as thymocytes respond to developmental stimuli in vivo. These studies reveal that only a small percentage of thymocytes show evidence for activation of PDK1 mediated signaling in situ. The thymic subpopulations that contain active PDK1/S6K1 are those known to be responding to signaling by the pre T cell receptor and the mature alpha/beta T cell antigen receptor (TCR). Moreover, loss of antigen receptor signaling in T cell progenitors that cannot rearrange their TCR beta locus prevents in vivo activation of S6K1. The present data identifying antigen receptor signaling as a key activator of PDK1 mediated signaling afford a molecular explanation for the important role of this molecule in T cells

Reasons samples failed QA/QC.

<p>Reasons samples failed QA/QC.</p

Cancer type defines canine tumor gene expression signatures.

<p>Multidimensional scaling (MDS) coordinates were generated using individual tumor gene (mRNA) expression z-scores to define relationships within the dataset. Tumor gene expression clustered by tumor type. Additionally, histologic categories share genomic signatures, with carcinomas (bladder TCC, nasal carcinoma, hepatocellular carcinoma (HCC)), mesenchymal (soft tissue sarcomas, hemangiosarcoma, histiocytic sarcoma, melanoma), and round cell (lymphoma) tumors clustering together in subgroups.</p

Bioinformatic analysis defines the platform for PMed report generation.

<p>Gene expression data from each tumor was compared to a reference sample set (canine normal tissue compendium, GSE20113 from Gene Expression Omnibus) to obtain a relative gene expression profile. Each gene probeset was represented by a z-score depicting its expression in the tumor in terms of the number of standard-deviations from the mean expression in the reference set. In the iteration of the PMed tools used in this study, data were analyzed by six distinct predictive methodologies (Drug Target Expression, Drug Response Signatures, Drug Sensitivity Signatures, Network Target Activity, Biomarker-Based-Rules-Sensitive, Biomarker-Based-Rules-Insensitive) to identify (or exclude in the case of biomarker resistant rules) potential agents for consideration. All predictions were based on the conversion of canine genomic data into human homologs (for both patient tumor samples and the reference set of normal tissues) prior to the application of the specific algorithms that rely exclusively on human knowledge and/or empirical drug screens using human cell lines (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090028#s4" target="_blank">Methods</a>). While individual patient tumor PMed report generation and distribution was the final step in this process, this specific study did not have therapeutic intent and drug prescription was not performed.</p

Study Cohorts.

<p>Study Cohorts.</p