Project description:Glioblastoma (GBM) is the most common and most aggressive primary brain tumor in adults. The existence of a small population of stem-like tumor cells that efficiently propagate tumors and resist cytotoxic therapy is one proposed mechanism leading to the resilient behavior of tumor cells and poor prognosis. In this study, we performed an in-depth analysis of the DNA methylation landscape in GBM-derived cancer stem cells (GSCs). Parallel comparisons of primary tumors and GSC lines derived from these tumors with normal controls (a neural stem cell (NSC) line and normal brain tissue) identified groups of hyper- and hypomethylated genes that display a trend of either increasing or decreasing methylation levels in the order of controls, primary GBMs, and their counterpart GSC lines, respectively. Interestingly, concurrent promoter hypermethylation and gene body hypomethylation were observed in a subset of genes including MGMT, AJAP1 and PTPRN2. These unique DNA methylation signatures were also found in primary GBM-derived xenograft tumors indicating that they are not tissue culture-related epigenetic changes. Integration of GSC-specific epigenetic signatures with gene expression analysis further identified candidate tumor suppressor genes that are frequently down regulated in GBMs such as SPINT2, NEFM and PENK. Forced re-expression of SPINT2 reduced glioma cell proliferative capacity, anchorage independent growth, cell motility, and tumor sphere formation in vitro. The results from this study demonstrate that GSCs possess unique epigenetic signatures that may play important roles in the pathogenesis of GBM. The reduced representation bisulfite sequencing (RRBS) approach (Meissner et al., 2008) was used to generate genome-wide single-base resolution CpG methylation profiles of three primary GBMs (1063T, 1133T, and 1142T) and three GSC lines (1063S, 1133S, 1142S) derived from these primary GBM tumors. The NSC line and the normal brain (NB) tissue sample were used as controls for comparison purposes. In addition, we analyzed three GBM xenograft tumor tissue samples (Mayo22, Mayo39, Mayo59) developed by Dr. Jann N. Sarkaria of Mayo Clinic.
Project description:For the current study we performed whole genome expression profiling on 69 unique patients with soft-tissue sarcoma who underwent curative-intent surgical resection to identify prognostic gene signatures. Specimens were obtained from the Mayo Clinic Florida STS Biobank and RNA was sequenced using the Tempus xT RNA-seq protocol. This protocol uses transcriptome-capture via more than 415,000 IDT xGen probes spanning greater than 19,000 genes, with at least 50 ng of extracted RNA required before proceeding to library preparation and a minimum depth of 30 million reads a on a NovaSeq 6000. RNA-seq data was analyzed using the MAP-RSeq pipeline developed by Mayo Clinic Bioinformatics Shared Resource.
