PilotNA
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB77810 | ENA |
REPOSITORIES: ENA
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Project description:Spontaneous canine head and neck squamous cell carcinoma (HNSCC) represents an excellent model of human HNSCC but is greatly understudied. To better understand and utilize this valuable resource, we performed a pilot study that represents its first genome-wide characterization by investigating 12 canine HNSCC cases, of which 9 are oral, via high density array comparative genomic hybridization and RNA-seq. The analyses reveal that these canine cancers recapitulate many molecular features of human HNSCC. These include analogous genomic copy number abnormality landscapes and sequence mutation patterns, recurrent alteration of known HNSCC genes and pathways (e.g., cell cycle, PI3K/AKT signaling), and comparably extensive heterogeneity. Amplification or overexpression of protein kinase genes, matrix metalloproteinase genes, and epithelial–mesenchymal transition genes TWIST1 and SNAI1 are also prominent in these canine tumors. This pilot study, along with a rapidly growing body of literature on canine cancer, reemphasizes the potential value of spontaneous canine cancers in HNSCC basic and translational research.
2015-06-02 | GSE61231 | GEO
Project description:Honey bees (Apis mellifera) are essential pollinators in agricultural systems, particularly in fruit-producing agroecosystems such as highbush blueberry and cranberry. However, their health is increasingly compromised by multiple interacting stressors, including pesticide exposure, pathogen infections, and changing nutritional landscapes. To test the hypothesis that distinct agricultural ecosystems, with different combinations of agrochemical exposure, pathogen loads, and floral resources, elicit ecosystem specific, tissue level molecular responses in honey bees, we conducted an integrated multiomics analysis.
We combined RNA sequencing, quantitative proteomics, and gut microbiome profiling across three key tissues: head, abdomen, and gut collected from bees in blueberry and cranberry agroecosystems over two field seasons. In parallel, we quantified pesticide residues and pathogen and parasite loads (e.g., Nosema spp., Varroa destructor, and several viruses). Notably, our weighted gene co-expression network analysis (WGCNA) revealed tissue specific coregulated protein modules with ecosystem associated patterns. Bees from blueberry agroecosystems exhibited elevated expression of modules in oxidative phosphorylation, and translation, while those from cranberry agroecosystems showed increased activity in immune pathways and endoplasmic reticulum associated protein processing, indicating potential as robust markers for ecosystem induced physiological adaptation. To further explore the molecular mechanisms underlying different ecosystems, we also conducted the integrative analysis of proteomics, transcriptomics and gut microbiome metagenomics. Gut microbiota composition also differed significantly, with key genera (e.g., Gilliamella, Snodgrassella, Bartonella) correlating with host metabolic and immune modules.
These findings underscore the complex, environment-dependent impacts of agroecosystem conditions on bee health. Our study provides a systems level understanding of how combined pesticide, pathogen, and parasitic stressors, mediated by diet and microbiome, shape molecular phenotypes in honey bees, informing strategies for pollinator protection in managed landscapes.
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