Evidence map›Paper›PMID 34439085›Full record

ReviewCancers2021

Hitting the Bull's-Eye: Mesothelin's Role as a Biomarker and Therapeutic Target for Malignant Pleural Mesothelioma.

Dannel Yeo, Laura Castelletti, Nico van Zandwijk, John E J Rasko

Abstract readReview
In one paragraph

Review in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

  1. Review
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  15. Review
  16. Article
  17. Target Therapy in Malignant Pleural Mesothelioma: Hope or Mirage?International journal of molecular sciences · 2023
    Review
  18. Review
  19. Article
  20. 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

4 authors.

Dannel YeoLi Ka Shing Cell & Gene Therapy Program, The University of Sydney, Camperdown, NSW 2050, Australia.ORCID 0000-0002-6546-1209
Laura CastellettiLi Ka Shing Cell & Gene Therapy Program, The University of Sydney, Camperdown, NSW 2050, Australia.ORCID 0000-0001-5037-8595
Nico van ZandwijkFaculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2050, Australia.ORCID 0000-0002-8405-9688
John E J RaskoLi Ka Shing Cell & Gene Therapy Program, The University of Sydney, Camperdown, NSW 2050, Australia.ORCID 0000-0003-2975-807X

Funding

Cancer Council NSW PW18-03Cancer Council NSW RG20-07CSR Australia Project FundLi Ka Shing Cell & Gene Therapy InitiativeNational Health and Medical Research Council 1177305
6 · The paper itself

Abstract

Malignant pleural mesothelioma (MPM) is an aggressive cancer with limited treatment options and poor prognosis. MPM originates from the mesothelial lining of the pleura. Mesothelin (MSLN) is a glycoprotein expressed at low levels in normal tissues and at high levels in MPM. Many other solid cancers overexpress MSLN, and this is associated with worse survival rates. However, this association has not been found in MPM, and the exact biological role of MSLN in MPM requires further exploration. Here, we discuss the current research on the diagnostic and prognostic value of MSLN in MPM patients. Furthermore, MSLN has become an attractive immunotherapy target in MPM, where better treatment strategies are urgently needed. Several MSLN-targeted monoclonal antibodies, antibody-drug conjugates, immunotoxins, cancer vaccines, and cellular therapies have been tested in the clinical setting. The biological rationale underpinning MSLN-targeted immunotherapies and their potential to improve MPM patient outcomes are reviewed.

Indexed as

biomarkercancerCAR T cellsimmunotherapymalignant mesotheliomamalignant pleural mesotheliomamesothelintherapeutic target

Identifiers

PMID34439085
PMCPMC8391149

What OpenQuestion holds

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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.