Evidence map›Paper›PMID 23592955›Full record

ArticlePLoS computational biology2013

Computational biomarker pipeline from discovery to clinical implementation: plasma proteomic biomarkers for cardiac transplantation.

Gabriela V Cohen Freue, Anna Meredith, Derek Smith, Axel Bergman, Mayu Sasaki, Karen K Y Lam, Zsuzsanna Hollander, Nina Opushneva, Mandeep Takhar, David Lin and 8 more

Registry-linked trialAbstract read
In one paragraph

Article in PLoS computational biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03575910 (HEARTBiT), which is not on this map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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.

NCT03575910 completednot on this mapstarted 2018, after this paper: background citation

HEARTBiT: A Novel Multi-Marker Blood Test for Management of Acute Cardiac Allograft Rejection

TypeobservationalSponsorUniversity of British ColumbiaRan2018 to 2026Enrolled196ConditionsHeart Transplant Failure and Rejection, Heart Failure, Heart Diseases, Heart Failure,Congestive
3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. A Roadmap towards Precision Periodontics.Medicina (Kaunas, Lithuania) · 2021
    Review
  5. Article
  6. The acute respiratory distress syndrome biomarker pipeline: crippling gaps between discovery and clinical utility.Translational research : the journal of laboratory and clinical medicine · 2020
    Review
  7. Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. Identification of altered protein abundances in cholesteatoma matrix via mass spectrometry-based proteomic analysis.Journal of otolaryngology - head & neck surgery = Le Journal d'oto-rhino-laryngologie et de chirurgie cervico-faciale · 2015
    Article
  16. Review
  17. Article
  18. Heparan sulfate differences in rheumatoid arthritis versus healthy sera.Matrix biology : journal of the International Society for Matrix Biology · 2014
    Article
  19. Review
  20. Review
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

18 authors.

Gabriela V Cohen FreueNCE CECR Prevention of Organ Failure (PROOF) Centre of Excellence, Vancouver, British Columbia, Canada.
Anna Meredith
Derek Smith
Axel Bergman
Mayu Sasaki
Karen K Y Lam
Zsuzsanna Hollander
Nina Opushneva
Mandeep Takhar
David Lin
Janet Wilson-McManus
Robert Balshaw
Paul A Keown
Christoph H Borchers
Bruce McManus
Raymond T Ng
W Robert McMaster
Biomarkers in Transplantation and the NCE CECR Prevention of Organ Failure Centre of Excellence Teams

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent technical advances in the field of quantitative proteomics have stimulated a large number of biomarker discovery studies of various diseases, providing avenues for new treatments and diagnostics. However, inherent challenges have limited the successful translation of candidate biomarkers into clinical use, thus highlighting the need for a robust analytical methodology to transition from biomarker discovery to clinical implementation. We have developed an end-to-end computational proteomic pipeline for biomarkers studies. At the discovery stage, the pipeline emphasizes different aspects of experimental design, appropriate statistical methodologies, and quality assessment of results. At the validation stage, the pipeline focuses on the migration of the results to a platform appropriate for external validation, and the development of a classifier score based on corroborated protein biomarkers. At the last stage towards clinical implementation, the main aims are to develop and validate an assay suitable for clinical deployment, and to calibrate the biomarker classifier using the developed assay. The proposed pipeline was applied to a biomarker study in cardiac transplantation aimed at developing a minimally invasive clinical test to monitor acute rejection. Starting with an untargeted screening of the human plasma proteome, five candidate biomarker proteins were identified. Rejection-regulated proteins reflect cellular and humoral immune responses, acute phase inflammatory pathways, and lipid metabolism biological processes. A multiplex multiple reaction monitoring mass-spectrometry (MRM-MS) assay was developed for the five candidate biomarkers and validated by enzyme-linked immune-sorbent (ELISA) and immunonephelometric assays (INA). A classifier score based on corroborated proteins demonstrated that the developed MRM-MS assay provides an appropriate methodology for an external validation, which is still in progress. Plasma proteomic biomarkers of acute cardiac rejection may offer a relevant post-transplant monitoring tool to effectively guide clinical care. The proposed computational pipeline is highly applicable to a wide range of biomarker proteomic studies.

Indexed as

Heart TransplantationBiomarkersBlood ProteinsCalibrationCohort StudiesComputational BiologyEnzyme-Linked Immunosorbent AssayGraft RejectionHeart FailureHumansInflammationMass SpectrometryProteomeProteomicsBiomarkersBlood ProteinsProteome

Identifiers

PMID23592955
PMCPMC3617196

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Registered trials

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.