9 research outputs found

    Histopathology and RNA quality assurance and control measures were successful in procuring high quality canine tumor samples.

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    <p>Formalin-fixed, paraffin-embedded tumor biopsy samples were sectioned, paraffin embedded, and H&E stained for light microscopic evaluation. A single board-certified veterinary pathologist (EJE) assessed % tumor surface area, % tumor nuclei and % tumor necrosis to determine their quality prior to molecular profiling. Images of representative H&E images are shown: <b>A.</b> Sample 0209, a golden retriever with lymphoma, passed QA/QC. (Tumor 75–100%, necrosis <10%), while <b>B.</b> sample 0503, a beagle with lymphoma, failed QA/QC (Tumor 75–100%, necrosis >20%). Biopsies that failed to pass QA/QC in any category were excluded from subsequent analysis. Additionally RNA isolation was performed for all enrolled cases (n = 31) at a CLIA certified laboratory. RNA was extracted from Tumor A biopsy samples. Quality measures included quantity (total yield >20 ng) and integrity (A<sub>260</sub>/A<sub>280</sub>>1.8, RIN>8.0) measured by Nanodrop and Agilent Bioanalyzer. Electropherograms from cases <b>C.</b> 0210 and <b>D.</b> 0507 are depicted. Sample 0210, an oral melanoma, passed RNA QA/QC while sample 0507, a mast cell tumor, failed QA/QC (poor quality RNA due to a large connective tissue component).</p

    Cancer type defines canine tumor gene expression signatures.

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    <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

    Clinical turn around time.

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    <p>*Clinical turnaround time for case 0508 (TCC) was an outlier (completed in 212 business hours).</p><p>The expression data was generated in 91 business hours (3.79 days) but there was a delay in the PMed report being sent to investigators. Overall the turn around for sample analysis fits a clinical window and its inclusion in the analysis did not impact the study conclusions.</p

    Bioinformatic analysis defines the platform for PMed report generation.

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    <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
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