8 research outputs found

    Animal Models to Study the Mutational Landscape for Oral Cavity and Oropharyngeal Cancers

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    Objectives: Cancer is likely caused by alterations in gene structure or expression. Recently, next generation sequencing has documented mutations in 106 head and neck squamous cell cancer genomes, suggesting several new candidate genes. However, it remains difficult to determine which mutations directly contributed to cancer. Here, summarize the animal models which have already validated and may test cancer causing mutations identified by next generation sequencing approaches. Material and Methods: We reviewed the existing literature on genetically engineered mouse models and next generation sequencing (NGS), as it relates to animal models of squamous cell cancers of the head and neck (HNSCC) in PubMed. Results: NSG has identified an average of 19 to 130 distinct mutations per HNSCC specimen. While many mutations likely had biological significance, it remains unclear which mutations were essential to, or “drive,” carcinogenesis. In contrast, “passenger” mutations also exist that provide no selection advantage. The genes identified by NGS included p53, RAS, Human Papillomavirus oncogenes, as well as novel genes such as Notch1, Dicer and SYNE1,2. Animal models of HNSCC have already validated some of these common gene mutations identified by NGS. Conclusions: The advent of next generation sequencing will provide new leads to the genetic changes occurring in squamous cell cancers of the head and neck. Animal models will enable us to validate these new leads in order to better elucidate the biology of squamous cell cancers of the head and neck

    The microbiome of an outpatient rehabilitation clinic and predictors of contamination: A pilot study.

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    BackgroundUnderstanding sources of microbial contamination in outpatient rehabilitation (REHAB) clinics is important to patients and healthcare providers.PurposeThe purpose of this study was to characterize the microbiome of an outpatient REHAB clinic and examine relationships between clinic factors and contamination.MethodsForty commonly contacted surfaces in an outpatient REHAB clinic were observed for frequency of contact and swiped using environmental sample collection kits. Surfaces were categorized based on frequency of contact and cleaning and surface type. Total bacterial and fungal load was assessed using primer sets specific for the 16S rRNA and ITS genes, respectively. Bacterial samples were sequenced using the Illumina system and analyzed using Illumina-utils, Minimum Entropy Decomposition, QIIME2 (for alpha and beta diversity), LEfSe and ANCOM-BC for taxonomic differential abundance and ADONIS to test for differences in beta diversity (pResultsPorous surfaces had more bacterial DNA compared to non-porous surfaces (median non-porous = 0.0016ng/ÎĽL, 95%CI = 0.0077-0.00024ng/ÎĽL, N = 15; porous = 0.0084 ng/ÎĽL, 95%CI = 0.0046-0.019 ng/ÎĽL, N = 18. p = 0.0066,DNA. Samples clustered by type of surface with non-porous surfaces further differentiated by those contacted by hand versus foot. ADONIS two-way ANOVA showed that the interaction of porosity and contact frequency (but neither alone) had a significant effect on 16S communities (F = 1.7234, R2 = 0.0609, p = 0.032).DiscussionPorosity of surfaces and the way they are contacted may play an underestimated, but important role in microbial contamination. Additional research involving a broader range of clinics is required to confirm results. Results suggest that surface and contact-specific cleaning and hygiene measures may be needed for optimal sanitization in outpatient REHAB clinics
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