Evidence map›Paper›PMID 33251010›Full record

ReviewClinical & translational immunology2020

The evolving landscape of predictive biomarkers in immuno-oncology with a focus on spatial technologies.

Habib Sadeghi Rad, Sajad Razavi Bazaz, James Monkman, Majid Ebrahimi Warkiani, Nima Rezaei, Ken O'Byrne, Arutha Kulasinghe

Open access · goldAbstract readReview
In one paragraph

Review in Clinical & translational immunology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
1.8field-weighted citation impact, top 12% 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

19 citing papers in PubMed, 43 citations in OpenAlex.

  1. Article
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  3. Review
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  5. Review
  6. Article
  7. Review
  8. Article
  9. Immune Checkpoint Inhibitors in Cancer Therapy.Current oncology (Toronto, Ont.) · 2022
    Review
  10. Review
  11. Review
  12. Article
  13. Review
  14. Article
  15. Review
  16. Review
  17. Spatial Profiles of Intratumoral PD-1Frontiers in immunology · 2021
    Article
  18. Article
  19. 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

7 authors at 4 institutions in 3 countries.

Habib Sadeghi RadSchool of Medicine Tehran University of Medical Sciences Tehran Iran.
Sajad Razavi BazazSchool of Biomedical Engineering University of Technology Sydney Sydney NSW Australia.ORCID https://orcid.org/0000-0002-6419-3361
James MonkmanThe School of Biomedical Science, Institute of Health and Biomedical Innovation Queensland University of Technology Brisbane QLD Australia.ORCID https://orcid.org/0000-0002-7219-8402
Majid Ebrahimi WarkianiSchool of Biomedical Engineering University of Technology Sydney Sydney NSW Australia.ORCID https://orcid.org/0000-0002-4184-1944
Nima RezaeiSchool of Medicine Tehran University of Medical Sciences Tehran Iran.ORCID https://orcid.org/0000-0002-3836-1827
Ken O'ByrneThe School of Biomedical Science, Institute of Health and Biomedical Innovation Queensland University of Technology Brisbane QLD Australia.ORCID https://orcid.org/0000-0002-6754-5633
Arutha KulasingheThe School of Biomedical Science, Institute of Health and Biomedical Innovation Queensland University of Technology Brisbane QLD Australia.ORCID https://orcid.org/0000-0003-3224-7350
Translational Research Institute · AUUniversity of Technology Sydney · AUTehran University of Medical Sciences · IRUniversal Scientific Education and Research Network · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immunotherapies have shown long-lasting and unparalleled responses for cancer patients compared to conventional therapy. However, they seem to only be effective in a subset of patients. Therefore, it has become evident that a greater understanding of the tumor microenvironment (TME) is required to understand the nuances which may be at play for a favorable outcome to therapy. The immune contexture of the TME is an important factor in dictating how well a tumor may respond to immune checkpoint inhibitors. While traditional immunohistochemistry techniques allow for the profiling of cells in the tumor, this is often lost when tumors are analysed using bulk tissue genomic approaches. Moreover, the actual cellular proportions, cellular heterogeneity and deeper spatial distribution are lacking in characterisation. Advances in tissue interrogation technologies have given rise to spatially resolved characterisation of the TME. This review aims to provide an overview of the current methodologies that are used to profile the TME, which may provide insights into the immunopathology associated with a favorable outcome to immunotherapy.

Indexed as

digital spatial profilingimmunotherapyspatial profilingtumor microenvironment

Identifiers

PMID33251010
PMCPMC7680923
OpenAlexW3107455121

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.