Different mutants of Cowpea Mosaic Virus (CPMV) have been used as scaffolds to bind 2 and 5 nm gold nanoparticles through gold−sulfur bond formation at specific locations on the virus to produce patterns of specific interparticle distances. TEM images confirm that the bound gold particles produce patterns of gold nanoparticles that correlate well with models built from the known locations of the inserted cysteine groups on the capsid. These results demonstrate that it is possible to use CPMV mutants as nanoscale scaffolds to place gold nanoparticles at fixed interparticle distances.

Patients with ependymoma exhibit a wide range of clinical outcomes that is currently unexplained by clinical or histological factors. Little is known regarding molecular biomarkers that could predict clinical behavior. Since recent data suggests that these tumors display biological characteristics according to their location (cerebral vs. infratentorial vs. spinal cord), rather than explore a broad spectrum of ependymoma, we focused on molecular alterations in ependymomas arising in the infratentorial compartment. Unsupervised clustering of available gene expression microarray data revealed two major subgroups of infratentorial ependymoma. Group 1 tumors over expressed genes that were associated with mesenchyme, Group 2 tumors showed no distinct gene ontologies. To assess the prognostic significance of these gene expression subgroups, real-time reverse-transcriptase polymerase chain reaction assays were performed on genes defining the subgroups in a training set. This resulted in a 10-gene prognostic signature. Multivariate analysis showed that the 10-gene signature was an independent predictor of recurrence-free survival after adjusting for clinical factors. Evaluation of an external dataset describing subgroups of infratentorial ependymomas showed concordance of subgroup definition, including validation of the mesenchymal subclass. Importantly, the 10-gene signature was validated as a predictor of recurrence-free survival in this dataset. Taken together, the results indicate a link between clinical outcome and biologically-identified subsets of infratentorial ependymoma and offer the potential for prognostic testing to estimate clinical aggressiveness in these tumors.

Meningioma is the most common primary brain tumor and carries a substantial risk of local recurrence. Methylation profiles of meningioma and their clinical implications are not well understood. We hypothesized that aggressive meningiomas have unique DNA methylation patterns that could be used to better stratify patient management. Samples (n=140) were profiled using the Illumina HumanMethylation450 BeadChip. Unsupervised modeling on a training set (n=89) identified 2 molecular methylation subgroups of meningioma (MM) with significantly different recurrence free survival (RFS) times between the groups: a prognostically unfavorable subgroup (MM-UNFAV) and a prognostically favorable subgroup (MM-FAV). This finding was validated in the remaining 51 samples and led to a baseline meningioma methylation classifier (bMMC) defined by 283 CpG loci (283-bMMC). To further optimize a recurrence predictor, probes subsumed within the baseline classifier were subject to additional modeling using a similar training/validation approach, leading to a 64-CpG loci meningioma methylation predictor (64-MMP). After adjustment for relevant clinical variables [WHO grade, mitotic index, Simpson grade, sex, location, and copy number aberrations (CNA)] multivariable analyses for RFS showed that the baseline methylation classifier was not significant (p=0.0793). The methylation predictor however was significantly associated with tumor recurrence (p<0.0001). CNA were extracted from the 450k intensity profiles. Tumor samples in the MM-UNFAV subgroup showed an overall higher proportion of CNAs compared to the MM-FAV subgroup tumors and the CNAs were complex in nature. CNAs in the MM-UNFAV subgroup included recurrent losses of 1p, 6q, 14q and 18q, and gain of 1q, all of which were previously identified as indicators of poor outcome. In conclusion, our analyses demonstrate robust DNA methylation signatures in meningioma that correlate with CNAs and stratify patients by recurrence risk.

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