Transcriptome analysis from muscle biopsy tissues in late-onset myopathies identifies potential biomarkers correlating to muscle pathology.

The diagnosis of adult-onset genetic muscle diseases is challenging because of the diversity of clinical phenotypes, findings on muscle biopsy that may be nonspecific, and the large number of genetic causes. Even with thorough investigation, the diagnostic yield for genetic testing in these populations is very low, and the distinction from acquired conditions such as sporadic inclusion body myositis [sIBM] can also prove difficult. In this study, we analysed whole transcriptome data generated from RNA isolated from muscle biopsy tissues, from a cohort of 16 participants with sIBM and other histologic diagnoses. Our objective was to identify candidate RNA biomarkers that could be an adjunctive tool in differentiating these conditions. Principal component analysis was able to delineate the groups based on their histologic diagnoses. Gene ontology and pathway analyses demonstrated dysregulation of immune pathways in sIBM. In mitochondrial myopathy we observed upregulation of FGF21, GDF15, ASNS and TRIB3, which are known candidate biomarkers for mitochondrial myopathy. Novel findings included the identification of transcripts of unknown function that were dysregulated in myofibrillar myopathy [JPX], dystrophic changes [MEG3], and mitochondrial myopathy [GAS5]. We suggest future investigations with larger cohorts of participants to confirm the findings of this study, with further directed experiments to determine the role of novel transcripts in disease pathogenesis.

Comparative genomic and genetic analysis of glioblastoma-derived brain tumor-initiating cells and their parent tumors.

BACKGROUND: Glioblastoma (GBM) is a fatal cancer that has eluded major therapeutic advances. Failure to make progress may reflect the absence of a human GBM model that could be used to test compounds for anti-GBM activity. In this respect, the development of brain tumor-initiating cell (BTIC) cultures is a step forward because BTICs appear to capture the molecular diversity of GBM better than traditional glioma cell lines. Here, we perform a comparative genomic and genetic analysis of BTICs and their parent tumors as preliminary evaluation of the BTIC model. METHODS: We assessed single nucleotide polymorphisms (SNPs), genome-wide copy number variations (CNVs), gene expression patterns, and molecular subtypes of 11 established BTIC lines and matched parent tumors. RESULTS: Although CNV differences were noted, BTICs retained the major genomic alterations characteristic of GBM. SNP patterns were similar between BTICs and tumors. Importantly, recurring SNP or CNV alterations specific to BTICs were not seen. Comparative gene expression analysis and molecular subtyping revealed differences between BTICs and GBMs. These differences formed the basis of a 63-gene expression signature that distinguished cells from tumors; differentially expressed genes primarily involved metabolic processes. We also derived a set of 73 similarly expressed genes; these genes were not associated with specific biological functions. CONCLUSIONS: Although not identical, established BTIC lines preserve the core molecular alterations seen in their parent tumors, as well as the genomic hallmarks of GBM, without acquiring recurring BTIC-specific changes.