| Literature DB >> 24634586 |
Jasmina S Redzic1, Timothy H Ung2, Michael W Graner2.
Abstract
Glioblastoma multiforme (GBM) is the most frequent and most devastating of the primary central nervous system tumors, with few patients living beyond 2 years postdiagnosis. The damage caused by the disease and our treatments for the patients often leave them physically and cognitively debilitated. Generally, GBMs appear after very short clinical histories and are discovered by imaging (using magnetic resonance imaging [MRI]), and the diagnosis is validated by pathology, following surgical resection. The treatment response and diagnosis of tumor recurrence are also tracked by MRI, but there are numerous problems encountered with these monitoring modalities, such as ambiguous interpretation and forms of pseudoprogression. Diagnostic, prognostic, and predictive biomarkers would be an immense boon in following treatment schemes and in determining recurrence, which often requires an invasive intracranial biopsy to verify imaging data. Extracellular vesicles (EVs) are stable, membrane-enclosed, virus-sized particles released from either the cell surface or from endosomal pathways that lead to the systemic release of EVs into accessible biofluids, such as serum/plasma, urine, cerebrospinal fluid, and saliva. EVs carry a wide variety of proteins, nucleic acids, lipids, and other metabolites, with many common features but with enough individuality to be able to identify the cell of origin of the vesicles. These components, if properly interrogated, could allow for the identification of tumor-derived EVs in biofluids, indicating tumor progression, relapse, or treatment failure. That knowledge would allow clinicians to continue with treatment regimens that were actually effective or to change course if the therapies were failing. Here, we review the features of GBM EVs, in terms of EV content and activities that may lead to the use of EVs as serially accessible biomarkers for diagnosis and treatment response in neuro-oncology.Entities:
Keywords: brain tumors; exosomes; lipidomics; microvesicles; proteomics; ribonomics
Year: 2014 PMID: 24634586 PMCID: PMC3952682 DOI: 10.2147/PGPM.S39768
Source DB: PubMed Journal: Pharmgenomics Pers Med ISSN: 1178-7066
Figure 1Radiographic (MRI) images and histology of GBMs.
Notes: (A) shows an MRI of a GBM before (left) and after (right) surgery. Yellow circles show the area of tumor (left) and the resection cavity following surgery (right). (B) (low power, 100×) and (C) (high power, 600×) are hematoxylin/eosin stains of a section of a GBM used in histopathologic diagnosis. (B) shows the typical hypercellularity, cytological atypia, and prominent pseudopalisading necrosis of a GBM. (C) at higher power (same tumor, different section), better illustrates the cellular atypia and mitotic activity in the GBM.
Abbreviations: GBM, glioblastoma multiforme; MRI, magnetic resonance imaging.
Figure 2Two main modes of EV formation.
Notes: (A) shows the exosome pathway, whereby materials are taken from the cell surface into the endosomal system, with later invaginations forming MVB. If the MVB fuses with the plasma membrane, it releases the internal vesicles into the extracellular space as exosomes. (B) shows the formation of microvesicles as shed vesicles, budding directly off from the plasma membrane.
Abbreviations: EV, extracellular vesicle; MVB, multivesicular body.
Subclassifications of glioblastomas (based on TCGA)25
| Subclass | Chromosome alterations | Gene/protein expression changes | Drugs/targets | Relative survival |
|---|---|---|---|---|
| Classical | cs7 gain with cs10 loss; loss 9p21.3 | ↓ | TMZ | Poor |
| Mesenchymal | Loss 17q11.2 | ↑ | TMZ/XRT | Poor |
| Proneural | Amplification cs7; loss cs10; amplification 4q12, but low amplification of 7p11.2 | ↑ | Inhibitors of HIF | Better |
| Neural | cs7 gain | ↑ | Poor |
Abbreviations: ASCL1, achaete-scute complex homolog 1; CD44, cluster of differentiation 44; CDKN2A, cyclin-dependent kinase inhibitor 2A; CHI3L1, chitinase-3-like protein 1; cs, chromosome; DCX, doublecortin; DLL3, delta-like 3; EGFR, epidermal growth factor receptor; EGFRvIII, mutated EGFR variant III; GABRA1, gamma-aminobutyric acid (GABA) receptor alpha 1; GAS1, growth arrest-specific 1; GLI1, glioma-associated oncogene 1; HIF, hypoxia-inducible factor; IDH1, isocitrate dehydrogenase 1 (NADP+), soluble; JAG1, jagged 1; LFNG, lunatic fringe (O-fucosylpeptide 3-beta-N-acetylglucosaminlytransferase); MDM2, mouse double minute 2 homolog; MET, mesenchymal-epithelial transition factor; MERTK, MER proto-oncogene tyrosine kinase; NEFL, neurofilament, light polypeptide; NES, nestin; NF1, neurofibromatosis 1; NFKB, nuclear factor kappa-light-chain-enhancer of activated B cells; NKX2-2, NK2 homeobox 2; NOTCH3, 3rd human notch homolog; OLIG2, oligodendrocyte lineage transcription factor 2; PDGFRA, platelet-derived growth factor receptor alpha; PI3K, phosphoinositide-3-kinase; PIK3CA, phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha; PIK3R1, PI3K regulatory subunit 1; PTEN, phosphatase and tensin homolog; SLC12A5, solute carrier family 12 (potassium/chloride transporter), member 5; SMO, smoothened; gas1, growth arrest specific 1; SOX, Sry-related HMG box; SYT1, synaptotagmin 1; TCF3/4, transcription factor 3 or 4; TCGA, The Cancer Genome Atlas; TNF, tumor necrosis factor; TMZ, temozolomide; PI3KCA, phosphatidylinositol-4,5-bisphosphate 3 kinase, catalytic subunit alpha; XRT, external beam radiation therapy; YKL40, chitinase-3-like protein 1; VEGFR, vascular endothelial growth factor receptor.