Project description:Several canine breeds, including boxers, Boston terriers, and French bulldogs, belong to the same phylogenetic clade and have a higher risk for high-grade oligodendroglioma (HGO) than the general canine population. Despite their shared increased risk for HGO, French bulldogs treated with immunotherapy have experienced worse survival outcomes compared to boxers and Boston terriers. Given the narrow genetic pools of purebred dogs, we hypothesized that the French bulldog HGO transcriptome differs from those of boxers and Boston terriers, which may account for the disparity in survival. We performed RNA sequencing on formalin-fixed, paraffin-embedded tissue from French bulldogs, boxers, and Boston terriers to determine differentially expressed genes (DEGs) between French bulldogs and the other evaluated breeds. We identified 31 DEGs in HGO samples from French bulldogs compared to boxers and Boston terriers. Gene set enrichment analysis revealed activated enrichment of 15 cell cycle progression, oncogene, and immune pathways, including E2F targets, mTOR signaling, IL2-STAT 5 signaling, and allograft rejection. These data confirm the presence of breed- specific canine HGO transcriptomes that can be used to advance our understanding of canine glioma, its translational capacity for human glioma, and precision-based therapies for individual canine patients.
Project description:Glioblastoma (GB) is the most aggressive form of glioma and is characterized by a poor prognosis and high recurrence, despite intensive clinical interventions. To retrieve the key factors underlying the high malignancy of GB, we performed differential expression analysis between low and high-grade gliomas by using RNA-seq.
Project description:Glioblastoma (GB) is the most aggressive form of glioma and is characterized by a poor prognosis and high recurrence, despite intensive clinical interventions. To retrieve the key factors underlying the high malignancy of GB, we performed differential methylation analysis between low and high-grade gliomas by using Infinium MethylationEPIC beadchips.
Project description:Targeted treatment of high-grade gliomas (HGGs) is challenging due to intra- and inter-tumoral heterogeneity. Prognosis of these tumors relies largely on the extent of resection. Fluorescence guided surgery using 5-ALA as adjunct has been on the rise in the recent years. However, 5-ALA has been ineffective in a small subset of population with similar histological phenotypes but varying metabolic/biochemical properties. Visualized fluorescence can sometimes be subjective and lead to variability in defining fluorescing regions with respect to their biological grade. Objective assessment of fluorescence is possible using spectroscopic techniques and with ex vivo PpIX assessment assays. The biometric study in our previous work revealed that even with objective assessment using PpIX assays, there exists a small subpopulation of tumor cells with similar histological phenotypes but discordant metabolic/biochemical properties w.r.t accumulation of PpIX. In the current study, we extended the investigation further and have carried out proteomic analysis of high-grade glioma tissue samples resected using 5-ALA fluorescence guided surgery to understand molecular differences leading to differential fluorescence in these complex and heterogenous tumors.
Project description:We performed genome-wide gene expression data of high-grade osteosarcoma samples. In order to detect osteosarcoma drivers, we integrated these data with copy number data. We performed two different methods - a non-paired and a paired integrative analysis. Genome-wide gene expression analysis was performed on 84 pre-treatment high-grade osteosarcoma diagnostic biopsies, of which 29 overlapped with the 32 samples used for copy number analysis. Two different sets of control samples were used for comparison: osteoblasts (n=3) and mesenchymal stem cells (n=12, GEO accession number GSE28974).
Project description:We performed copy number analysis of high-grade osteosarcoma samples. in order to detect osteosarcoma drivers, we integrated these data with genome-wide gene expression data. We performed two different methods - a non-paired and a paired integrative analysis. Copy number analysis was performed on 32 pre-treatment high-grade osteosarcoma diagnostic biopsies, of which 29 overlapped with the 84 samples used for gene expression analyses.
Project description:We performed genome-wide gene expression data of high-grade osteosarcoma samples. In order to detect osteosarcoma drivers, we integrated these data with copy number data. We performed two different methods - a non-paired and a paired integrative analysis.