Evidence map›Paper›PMID 31695805›Full record

ReviewTheranostics2019

Quantitative Proteomics and Metabolomics Reveal Biomarkers of Disease as Potential Immunotherapy Targets and Indicators of Therapeutic Efficacy.

Melanie A MacMullan, Zachary S Dunn, Nicolas Graham, Lili Yang, Pin Wang

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Theranostics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.9field-weighted citation impact, top 14% of its field
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

18 citing papers in PubMed, 67 citations in OpenAlex.

  1. Article
  2. Review
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  6. Article
  7. Article
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  11. Review
  12. Review
  13. Modeling the Th17 and Tregs Paradigm: Implications for Cancer Immunotherapy.Frontiers in cell and developmental biology · 2021
    Review
  14. Article
  15. Article
  16. Systems Biology Approaches for Therapeutics Development Against COVID-19.Frontiers in cellular and infection microbiology · 2020
    Review
  17. Review
  18. 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

5 authors at 2 institutions in 1 country.

Melanie A MacMullanMork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, California.
Zachary S DunnMork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, California.
Nicolas GrahamMork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, California.
Lili YangDepartment of Microbiology, Immunology & Molecular Genetics, University of California, Los Angeles, California.
Pin WangMork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, California.
University of Southern California · USUniversity of California, Los Angeles · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative mass spectrometry (MS) continues to deepen our understanding of the immune system, quickly becoming the gold standard for obtaining high-throughput, quantitative data on biomolecules. The development of targeted and multiplexed assays for biomarker quantification makes MS an attractive tool both for diagnosing diseases and for quantifying the effects of immunotherapeutics. Because of its accuracy, the use of MS for identifying biomarkers of disease reduces the potential for misdiagnosis and overtreatment. Advances in workflows for sample processing have drastically reduced processing time and complexities due to sample preparation, making MS a more accessible technology. In this review, we present how recent developments in proteomics and metabolomics make MS an essential component of enhancing and monitoring the efficacy of immunotherapeutic treatments.

Indexed as

AnimalsBiomarkersHumansImmunologic FactorsImmunotherapyMetabolomicsProteomicsTandem Mass SpectrometryTherapeutic UsesBiomarkersImmunologic FactorsTherapeutic Usesimmunotherapy targetsmetabolomicsproteomicsQuantitative mass spectrometry

Identifiers

PMID31695805
PMCPMC6831481
OpenAlexW2982396153

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.