Protein typing of circulating microvesicles allows real-time monitoring of glioblastoma therapy

Journal name:
Nature Medicine
Volume:
18,
Pages:
1835–1840
Year published:
DOI:
doi:10.1038/nm.2994
Received
Accepted
Published online

Abstract

Glioblastomas shed large quantities of small, membrane-bound microvesicles into the circulation. Although these hold promise as potential biomarkers of therapeutic response, their identification and quantification remain challenging. Here, we describe a highly sensitive and rapid analytical technique for profiling circulating microvesicles directly from blood samples of patients with glioblastoma. Microvesicles, introduced onto a dedicated microfluidic chip, are labeled with target-specific magnetic nanoparticles and detected by a miniaturized nuclear magnetic resonance system. Compared with current methods, this integrated system has a much higher detection sensitivity and can differentiate glioblastoma multiforme (GBM) microvesicles from nontumor host cell–derived microvesicles. We also show that circulating GBM microvesicles can be used to analyze primary tumor mutations and as a predictive metric of treatment-induced changes. This platform could provide both an early indicator of drug efficacy and a potential molecular stratifier for human clinical trials.

At a glance

Figures

  1. Human glioblastoma cells produce abundant microvesicles, which can be analyzed by [mu]NMR.
    Figure 1: Human glioblastoma cells produce abundant microvesicles, which can be analyzed by μNMR.

    (a) Scanning electron microscopy image of a primary human glioblastoma cell (GBM20/3) grown in culture, releasing abundant microvesicles. (b) High-magnification image shows that many of the microvesicles on the cell surface assume the typical saucer-shaped characteristics of exosomes. (c) Transmission electron microscopy image of microvesicles (~80 nm) targeted with MNPs via a CD63-specific antibody. The MNPs appear as black dots (indicated by an arrow). (d) Two-step labeling procedure used to maximize MNP binding onto target proteins on microvesicles (not to scale). (e) The microfluidic system for on-chip detection of circulating microvesicles (MV) is designed to detect MNP-targeted microvesicles, concentrate MNP-tagged microvesicles (while removing unbound MNPs) and provide in-line μNMR detection.

  2. [mu]NMR assay for microvesicle detection.
    Figure 2: μNMR assay for microvesicle detection.

    (a) Correlation between μNMR measurements for CD63 and microvesicle number in a dilution series. Microvesicle numbers were estimated by NTA. The transverse relaxation (R2), as determined by μNMR, varied linearly with microvesicle number (R2 > 98%). (b) Using microvesicles from model cell lines, the expression levels of EGFR and EGFRvIII were measured by μNMR and ELISA. The microvesicle expression (ξ) of a target protein marker was obtained by normalizing the marker-associated R2 against R2CD63. (c) The detection threshold for microvesicles using the μNMR assay. For CD63-tagged microvesicles, the detection threshold was approximately ~104 microvesicles, as measured by the relative changes in the transverse relaxation time (T2 = 1 / R2) with respect to controls. (d) Comparison of microvesicle detection sensitivity. In a series of microvesicle dilution assays, μNMR was considerably more sensitive than western blotting (WB; Supplementary Fig. 4b), flow cytometry (FC), ELISA and NTA. All measurements in ac were performed in triplicate, and the data are mean ± s.e.m.

  3. Protein typing of GBM-derived microvesicles from cell lines and patient samples.
    Figure 3: Protein typing of GBM-derived microvesicles from cell lines and patient samples.

    (a) GBM markers (EGFR, EGFRvIII, PDGFR, PDPN, EphA2 and IDH1 R132H), a positive microvesicle control marker (HSP90), as well as host cell markers (CD41, MHCII) were profiled in both parental cells (left) and their corresponding microvesicles (right). Using a four-GBM marker combination (EGFR, EGFRvIII, PDPN and IDH1 R132H), GBM-derived microvesicles could be distinguished from host cell–derived microvesicles. HBMVEC, human brain microvascular endothelial cell; NHA, normal human astrocyte; buffy coat and plasma were isolated from whole blood donated by healthy volunteers. (b) Analysis of clinical patient samples. Waterfall plots show the expression levels of different biomarkers sorted from high (left) to low (right). In patient-derived samples, there was higher expression of EGFR and PDPN in addition to unique expression of EGFRvIII and IDH1 R132H. (c) ROC curves (left) were used to determine the detection sensitivity, specificity and accuracy of each marker. Although the overall accuracy for a single marker alone (right) was <76%, when all markers were combined (Quad) the detection accuracy was >90%. AUC, area under curve.

  4. Effects of geldanamycin treatment on T103 GBM model.
    Figure 4: Effects of geldanamycin treatment on T103 GBM model.

    (a) The expression levels of CD63, EGFR and EGFRvIII in geldanamycin-treated cells profiled by flow cytometry (top) and western blotting (bottom). (b) Microvesicles from geldanamycin-treated cells screened by μNMR for EGFR and EGFRvIII expression (ξ; normalized with respect to CD63 expression). (c) Total number of cells and microvesicles after drug treatment, normalized against untreated samples. (d) Total expression levels of CD63, EGFR and EGFRvIII measured by μNMR, normalized against untreated samples. (e,f) Plots of drug response index (RI) for T103 (e) and GLI36vIII (f) cell lines after treatment with TMZ or geldanamycin. Owing to geldanamycin's ability to reduce both microvesicle number as well as receptor expression, tits RI was higher for both T103 and GLI36vIII cell lines compared to TMZ. All changes with respect to untreated samples were statistically significant (P < 0.001). All analytical measurements were performed in triplicate, and the data are shown as mean ± s.e.m.

  5. Analysis of circulating microvesicles in GBM mice and human patients undergoing treatment.
    Figure 5: Analysis of circulating microvesicles in GBM mice and human patients undergoing treatment.

    (a,b) Microvesicles and tumor volume in untreated (a) and TMZ-treated (b) tumor-bearing mice. Each data point is the mean ± s.e.m of three mice. TPI is used to reflect changes in both microvesicle number and microvesicle molecular expression. (c) With TMZ treatment, the drug efficacy index (ηMV), defined as the temporal change in TPI−1, switched from negative (tumor progression/no treatment effect) to positive (treatment response). (d,e) Clinical trial results. Plots showing TPI values (d) and their corresponding ηMV values (e) from the same patients both before and after combined TMZ and radiation treatment. Dashed lines in e indicate the median values.

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Author information

  1. These authors contributed equally to this work.

    • Ralph Weissleder &
    • Hakho Lee

Affiliations

  1. Center for Systems Biology, Massachusetts General Hospital, Boston, Massachusetts, USA.

    • Huilin Shao,
    • Jaehoon Chung,
    • Ralph Weissleder &
    • Hakho Lee
  2. Harvard Biophysics Program, Harvard Medical School, Boston, Massachusetts, USA.

    • Huilin Shao
  3. Neuroscience Center, Department of Neurology, Massachusetts General Hospital, Charlestown Navy Yard, Boston, Massachusetts, USA.

    • Leonora Balaj &
    • Xandra O Breakefield
  4. Molecular Oncology Research Institute, Tufts University School of Medicine, Boston, Massachusetts, USA.

    • Alain Charest
  5. Brain Tumor Center, Department of Pathology, Duke University Medical Center, Durham, North Carolina, USA.

    • Darell D Bigner
  6. Division of Neurological Surgery, University of California–San Diego School of Medicine, San Diego, California, USA.

    • Bob S Carter
  7. Massachusetts General Hospital Cancer Center, Boston, Massachusetts, USA.

    • Fred H Hochberg &
    • Ralph Weissleder
  8. Program in Neuroscience, Harvard Medical School, Boston, Massachusetts, USA.

    • Xandra O Breakefield
  9. Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA.

    • Ralph Weissleder

Contributions

H.S., R.W. and H.L. designed the study. H.S., J.C., L.B. and H.L. performed the experiments. H.S., J.C., R.W. and H.L. analyzed the data and wrote the manuscript. A.C. generated the mouse T103 model. D.D.B. recommended GBM biomarkers and generated the EGFRvIII-specific antibody. B.S.C., F.H.H. and X.O.B. coordinated the clinical study and analyzed the results.

Competing financial interests

The authors declare no competing financial interests.

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    Supplementary Methods, Supplementary Figures 1–8 and Supplementary Tables 1–4

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