Evidence map›Paper›PMID 25505970›Full record

ReviewClinical & translational immunology2014

Improved mouse models to assess tumour immunity and irAEs after combination cancer immunotherapies.

Jing Liu, Stephen J Blake, Mark J Smyth, Michele Wl Teng

Abstract readReview
In one paragraph

Review in Clinical & translational immunology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing 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

43 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Review
  6. Article
  7. Review
  8. Review
  9. Review
  10. Novel Mouse Models for Cancer Immunology.Annual review of cancer biology · 2022
    Article
  11. Review
  12. Review
  13. Non-invasive Detection of Immunotherapy-Induced Adverse Events.Clinical cancer research : an official journal of the American Association for Cancer Research · 2021
    Article
  14. Deletion ofInternational journal of molecular sciences · 2021
    Article
  15. Article
  16. Review
  17. Article
  18. Article
  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.

Jing LiuCancer Immunoregulation and Immunotherapy Laboratory, QIMR Berghofer Medical Research Institute , Herston, Queensland, Australia ; Immunology in Cancer and Infection Laboratory, QIMR Berghofer Medical Research Institute , Herston, Queensland, Australia ; School of Medicine, University of Queensland , Herston, Queensland, Australia.
Stephen J BlakeCancer Immunoregulation and Immunotherapy Laboratory, QIMR Berghofer Medical Research Institute , Herston, Queensland, Australia.
Mark J SmythImmunology in Cancer and Infection Laboratory, QIMR Berghofer Medical Research Institute , Herston, Queensland, Australia ; School of Medicine, University of Queensland , Herston, Queensland, Australia.
Michele Wl TengCancer Immunoregulation and Immunotherapy Laboratory, QIMR Berghofer Medical Research Institute , Herston, Queensland, Australia ; School of Medicine, University of Queensland , Herston, Queensland, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current excitement surrounding cancer immunotherapy stems particularly from clinical data involving agents mediating immune checkpoint receptor blockade, which have induced unprecedented efficacy against a range of tumours compared with previous immunotherapeutic approaches. However, an important consideration in targeting checkpoint receptors has been the emergence of associated toxicities termed immune-related adverse events (irAEs). In light of the clinical benefits observed after co-blockade of checkpoint receptors and data from preclinical mouse models, there is now a strong rationale to combine different checkpoint receptors together, with other immunotherapies or more conventional therapies to assess if clinical benefits to cancer patients can be further improved. However, one may predict the frequency and severity of irAEs will increase with combinations, which may result in premature therapy cessation, thus limiting the realization of such an approach. In addition, there is a limit to how many different combination therapies that can be tested in a timely manner given the legal, regulatory and budgetary issues associated with conducting clinical trials. Thus, there is a need to develop preclinical mouse models that more accurately inform us as to which immunotherapies might combine best to provide the optimal therapeutic index (maximal anti-tumour efficacy and low level irAEs) in different cancer settings. In this review we will discuss the irAEs observed in patients after checkpoint blockade and discuss which mouse models of cancer can be appropriate to assess the development of tumour immunity and irAEs following combination cancer immunotherapies.

Identifiers

PMID25505970
PMCPMC4232074

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.