Evidence map›Paper›PMID 28365151›Full record

ArticleCell systems2017

A Cell-Surface Membrane Protein Signature for Glioblastoma.

Dhimankrishna Ghosh, Cory C Funk, Juan Caballero, Nameeta Shah, Katherine Rouleau, John C Earls, Liliana Soroceanu, Greg Foltz, Charles S Cobbs, Nathan D Price and 1 more

Abstract read
In one paragraph

Article in Cell systems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed.

  1. Article
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  4. Article
  5. Review
  6. Article
  7. Article
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  9. Article
  10. Review
  11. Review
  12. Nucleic acid drug vectors for diagnosis and treatment of brain diseases.Signal transduction and targeted therapy · 2023
    Review
  13. GeneratingFrontiers in oncology · 2023
    Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Membrane Bound Peroxiredoxin-1 Serves as a Biomarker forAntioxidants & redox signaling · 2022
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Dhimankrishna GhoshInstitute for Systems Biology, Seattle, WA 98109, USA.
Cory C FunkInstitute for Systems Biology, Seattle, WA 98109, USA.
Juan CaballeroInstitute for Systems Biology, Seattle, WA 98109, USA.
Nameeta ShahThe Ben and Catherine Ivy Center for Advanced Brain Tumor Treatment, Swedish Neuroscience Institute, Seattle, WA 98122, USA.
Katherine RouleauInstitute for Systems Biology, Seattle, WA 98109, USA.
John C EarlsInstitute for Systems Biology, Seattle, WA 98109, USA; Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195, USA.
Liliana SoroceanuCalifornia Pacific Medical Center Research Institute, San Francisco, CA 94107, USA.
Greg FoltzThe Ben and Catherine Ivy Center for Advanced Brain Tumor Treatment, Swedish Neuroscience Institute, Seattle, WA 98122, USA.
Charles S CobbsThe Ben and Catherine Ivy Center for Advanced Brain Tumor Treatment, Swedish Neuroscience Institute, Seattle, WA 98122, USA.
Nathan D PriceInstitute for Systems Biology, Seattle, WA 98109, USA; Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195, USA.
Leroy HoodInstitute for Systems Biology, Seattle, WA 98109, USA. Electronic address: lhood@systemsbiology.org.

Funding

Quantitative Systems BiologyP50GM076547 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI DUDLEY, AIMEE M · 2006 to 2016
$30.6M
UCLA Institute for Molecular Medicine (IMED) CoreU54CA151819 · NCI · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI HEATH, JAMES R. · 2010 to 2014
$12.1M
NCI NIH HHS U54 CA151819NIGMS NIH HHS P50 GM076547
6 · The paper itself

Abstract

We present a systems strategy that facilitated the development of a molecular signature for glioblastoma (GBM), composed of 33 cell-surface transmembrane proteins. This molecular signature, GBMSig, was developed through the integration of cell-surface proteomics and transcriptomics from patient tumors in the REMBRANDT (n = 228) and TCGA datasets (n = 547) and can separate GBM patients from control individuals with a Matthew's correlation coefficient value of 0.87 in a lock-down test. Functionally, 17/33 GBMSig proteins are associated with transforming growth factor β signaling pathways, including CD47, SLC16A1, HMOX1, and MRC2. Knockdown of these genes impaired GBM invasion, reflecting their role in disease-perturbed changes in GBM. ELISA assays for a subset of GBMSig (CD44, VCAM1, HMOX1, and BIGH3) on 84 plasma specimens from multiple clinical sites revealed a high degree of separation of GBM patients from healthy control individuals (area under the curve is 0.98 in receiver operating characteristic). In addition, a classifier based on these four proteins differentiated the blood of pre- and post-tumor resections, demonstrating potential clinical value as biomarkers.

Indexed as

Biomarkers, TumorBrain NeoplasmsCell DifferentiationCell Line, TumorCell MembraneCell ProliferationComputational BiologyGene Expression ProfilingGene Expression Regulation, NeoplasticGlioblastomaHumansMembrane ProteinsProteomicsSystems BiologyTranscriptomeTransforming Growth Factor betaBiomarkers, TumorMembrane ProteinsTransforming Growth Factor betacell-surface proteinsGBMGBMSiginvasion

Identifiers

PMID28365151
PMCPMC5512565

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.