Noerholm et al. BMC Cancer 2012, 12:22 http://www.biomedcentral.com/1471-2407/12/22 We observed that, coinciding with the significantly increased amounts of microvesicle RNA in GBM patient serum compared to normal controls, the expression levels of all the genes we investigated by qRT-PCR were lower than in normal controls when normalized to total RNA amount (Figure 5). It is likely that this is a general trend across most mRNAs, and since all these genes are down-regulated other transcripts must be up-regulated to account for the overall increase in RNA amounts. The Bioanalyzer profiles of the different RNA serum samples suggest that this up-regulation of RNA in the GBM patients mainly falls in the range of < 300 nt. This could explain why the majority of the tumour exoRNA transcripts appeared down-regulated on the array. If the < 300 nt RNAs do not contain sequences belonging to the coding genes, they would not have been picked up by the microarray and the mRNA-fraction recognized by the capture probes would be relatively smaller since the same amount of input RNA was used for hybridiza- tion. There are many RNA species that are not covered by the microarray, including miRNA (mature and pre- cursors), repetitive elements and other non-coding RNAs, as well as single stranded DNA [28,34]. Balaj et al. [28] showed that human endogenous retro- viruses and other transposable elements, as well as sin- gle stranded DNA fragments are very abundant in microvesicles from cancer cells, as compared to normal fibroblasts, including Alu, LINE and HERV sequences and it is likely that these and other non-coding RNAs are contributing to the increased amounts of RNA we observe in GBM patient serum (single stranded DNA is also detected on the Bioanalyzer RNA chip). We tested a single transposable element Alu-Y by qRT-PCR and found it to be extremely abundant in the microvesicles, but did not observe any differential expression between the GBMs and normal controls. The human genome consists of about 40% retrotransposon sequences [35], and there is an increasing number of publications show- ing the dysregulation of transposable elements and other non-coding RNAs in cancer [36-38]. The very existence of the peak of < 500 nt RNAs in GBM serum exoRNA make it a fertile ground for bio- marker discovery, and it warrants further investigation to establish the exact nature and distribution of the nucleic acid species contained in this fraction. A num- ber of regulatory non-coding RNAs are transcribed off coding elements [39]. Collectively, down-regulation of specific RNAs and up-regulation of RNA levels in exo- somes/microvesicles from serum of GBM patients, as compared to controls provides promising biomarkers. In addition, in other studies, tumour mutant mRNAs [18] and elevated oncogene mRNA [28] have been detected in serum exosomes/microvesicles from human GBM patients and mice bearing medulloblastoma tumours, Page 9 of 11 respectively. Tumour mutant RNA from prostate cancer patients can also be found in urine exosomes/microvesi- cles [40]. More detailed analysis of exoRNA released by tumour cells into serum should be possible as isolation methods are developed with tumour specific surface markers for different types of cancer, e.g. with magnetic activated sorting [30] and microfluidic capture [41]. Conclusions Currently, there are no biomarkers for gliomas to distin- guish tumor recurrence from radiation necrosis or to monitor tumor response to therapy. Here we demon- strate that frozen, biobanked glioblastoma serum micro- vesicles contain RNA in amounts and qualities sufficient to perform qPCR and microarray analysis, and we show that glioma exoRNA profiles are unique compared to tumor free individuals. The most significant expression differences pertained to down-regulated genes in the GBM patient exoRNA, which we were able to validate by qRT-PCR. However, overall yields of exoRNA from GBM patient serum microvesicles was higher than yields from normal controls, but the additional RNA was pri- marily of size < 500 nt, evident by a peak of small RNAs on the bioanalyzer profiles. Gene ontology analysis of the down-regulated genes indicated these are primarily mRNAs coding for ribosomal proteins and other genes related to ribosome production. The observation may be explained by a reduced contribution of exoRNA from lymphocytes, which have previously been reported to have high expression levels of these transcripts. This theory was supported by the lymphocyte counts in the blood of the patients investigated in this study, which was substantially lower than the normal reference interval. Additional material Additional file 1: This file describes the R/BioConductor commands used to analyze the raw data deposited in GEO with accession# GSE24084. Additional file 2: Table S1: Top 200 most down-regulated genes with p < 0.05 in all three normalizations after correction for False Discovery Rate. Table S2: Top 200 most up-regulated genes with p < 0.05 in all three normalizations after correction for False Discovery Rate. Table S3: Sequences and ABI IDs of TaqMan qPCR assays. Abbreviations GBM: Glioblastoma multiforme; MGMT: Methyl guanidine methyl transferase; PBMC: Peripheral blood mononuclear cells; MiRNA: MicroRNA; r.t: Room temperature; VSN: Variance stabilized normalization; WBC: White blood cell; GEO: Gene expression omnibus; FDR: False discovery rate; qRT-PCR: Quantitative reverse transcriptase PCR. Acknowledgements We would like to thank Lori LoGuidice for kind assistance with RNA extractions and Suzanne McDavitt for review and formatting of the