Dataset Information

A small noncoding RNA signature found in exosomes of GBM patient serum as a diagnostic tool.

ABSTRACT:

Background

Glioblastoma multiforme (GBM) is the most frequent malignant brain tumor in adults, and its prognosis remains dismal despite intensive research and therapeutic advances. Diagnostic biomarkers would be clinically meaningful to allow for early detection of the tumor and for those cases in which surgery is contraindicated or biopsy results are inconclusive. Recent findings show that GBM cells release microvesicles that contain a select subset of cellular proteins and RNA. The aim of this hypothesis-generating study was to assess the diagnostic potential of miRNAs found in microvesicles isolated from the serum of GBM patients.

Methods

To control disease heterogeneity, we used patients with newly diagnosed GBM. In the discovery stage, PCR-based TaqMan Low Density Arrays followed by individual quantitative reverse transcriptase polymerase chain reaction were used to test the differences in the miRNA expression levels of serum microvesicles among 25 GBM patients and healthy controls paired by age and sex. The detected noncoding RNAs were then validated in another 50 GBM patients.

Results

We found that the expression levels of 1 small noncoding RNA (RNU6-1) and 2 microRNAs (miR-320 and miR-574-3p) were significantly associated with a GBM diagnosis. In addition, RNU6-1 was consistently an independent predictor of a GBM diagnosis.

Conclusions

Altogether our results uncovered a small noncoding RNA signature in microvesicles isolated from GBM patient serum that could be used as a fast and reliable differential diagnostic biomarker.

SUBMITTER: Manterola L

PROVIDER: S-EPMC3956347 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

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Publications

A small noncoding RNA signature found in exosomes of GBM patient serum as a diagnostic tool.

Manterola Lorea L Guruceaga Elizabeth E Gállego Pérez-Larraya Jaime J González-Huarriz Marisol M Jauregui Patricia P Tejada Sonia S Diez-Valle Ricardo R Segura Victor V Samprón Nicolás N Barrena Cristina C Ruiz Irune I Agirre Amaia A Ayuso Angel A Rodríguez Javier J González Alvaro A Xipell Enric E Matheu Ander A López de Munain Adolfo A Tuñón Teresa T Zazpe Idoya I García-Foncillas Jesús J Paris Sophie S Delattre Jean Yves JY Alonso Marta M MM

Neuro-oncology 20140116 4

<h4>Background</h4>Glioblastoma multiforme (GBM) is the most frequent malignant brain tumor in adults, and its prognosis remains dismal despite intensive research and therapeutic advances. Diagnostic biomarkers would be clinically meaningful to allow for early detection of the tumor and for those cases in which surgery is contraindicated or biopsy results are inconclusive. Recent findings show that GBM cells release microvesicles that contain a select subset of cellular proteins and RNA. The aim ...[more]

PMID: 24435880

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Project description:Patient-tailored therapy based on tumor drivers is promising for lung cancer treatment. For this, we combined in vitro tissue models with in silico analyses. Using individual cell lines with specific mutations, we demonstrate a generic and rapid stratification pipeline for targeted tumor therapy. We improve in vitro models of tissue conditions by a biological matrix-based three-dimensional (3D) tissue culture that allows in vitro drug testing: It correctly shows a strong drug response upon gefitinib (Gef) treatment in a cell line harboring an EGFR-activating mutation (HCC827), but no clear drug response upon treatment with the HSP90 inhibitor 17AAG in two cell lines with KRAS mutations (H441, A549). In contrast, 2D testing implies wrongly KRAS as a biomarker for HSP90 inhibitor treatment, although this fails in clinical studies. Signaling analysis by phospho-arrays showed similar effects of EGFR inhibition by Gef in HCC827 cells, under both 2D and 3D conditions. Western blot analysis confirmed that for 3D conditions, HSP90 inhibitor treatment implies different p53 regulation and decreased MET inhibition in HCC827 and H441 cells. Using in vitro data (western, phospho-kinase array, proliferation, and apoptosis), we generated cell line-specific in silico topologies and condition-specific (2D, 3D) simulations of signaling correctly mirroring in vitro treatment responses. Networks predict drug targets considering key interactions and individual cell line mutations using the Human Protein Reference Database and the COSMIC database. A signature of potential biomarkers and matching drugs improve stratification and treatment in KRAS-mutated tumors. In silico screening and dynamic simulation of drug actions resulted in individual therapeutic suggestions, that is, targeting HIF1A in H441 and LKB1 in A549 cells. In conclusion, our in vitro tumor tissue model combined with an in silico tool improves drug effect prediction and patient stratification. Our tool is used in our comprehensive cancer center and is made now publicly available for targeted therapy decisions.

Project description:Glioblastoma multiforme (GBM) is the most common and aggressive malignant adult primary brain tumor. Despite surgical resection followed by radiotherapy and chemotherapy, the median survival rate is approximately 14 months. Although experimental therapies are in clinical trials for GBM, there is an urgent need for a peripheral GBM biomarker for measuring treatment response. As we have previously demonstrated that the long noncoding RNA HOX Transcript Antisense Intergenic RNA, or HOTAIR, is dysregulated in GBM and required for GBM cell proliferation, we hypothesized that HOTAIR expression may be utilized as a peripheral biomarker for GBM. HOTAIR expression was measured in serum from 43 GBM and 40 controls using quantitative real-time PCR (qRT-PCR). The PCR products were subsequently subcloned into pCR™4-TOPO®TA vectors for DNA sequencing. A ROC curve was also generated to examine HOTAIR's prognostic value. The amount of HOTAIR in serum exosomes and exosome-depleted supernatant was calculated by qRT-PCR. The relative HOTAIR expression was also investigated in 15 pairs of GBM serum and tumors. We detected HOTAIR in serum from GBM patients. HOTAIR levels in serum samples from GBM patients was significantly higher than in the corresponding controls (P < 0.0001). The area under the ROC curve distinguishing GBM patients from controls was 0.913 (95% CI: 0.845-0.982, P < 0.0001), with 86.1% sensitivity and 87.5% specificity at the cut-off value of 10.8. HOTAIR expression was significantly correlated with high grade brain tumors. In addition, Pearson correlation analysis indicated a medium correlation of serum HOTAIR levels and the corresponding tumor HOTAIR levels (r = 0.734, P < 0.01). We confirmed via sequencing that the amplified HOTAIR from serum contained the HOTAIR sequence and maps to the known HOTAIR locus at 12q13. The serum-derived exosomes contain HOTAIR and the purified exosomes were validated by western blot and nanoparticle tracking analysis. Importantly, our results demonstrate that serum HOTAIR can be used as a novel prognostic and diagnostic biomarker for GBM.

Dataset Information

A small noncoding RNA signature found in exosomes of GBM patient serum as a diagnostic tool.

Background

Methods

Results

Conclusions

Publications

A small noncoding RNA signature found in exosomes of GBM patient serum as a diagnostic tool.

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