Evidence map›Paper›PMID 30309862›Full record

ReviewCancer discovery2018

Mouse Models for Cancer Immunotherapy Research.

Brian Olson, Yadi Li, Yu Lin, Edison T Liu, Akash Patnaik

Open access · greenAbstract readReview
In one paragraph

Review in Cancer discovery, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 262 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
262citing papers in PubMed, 3 pooled it
12.7field-weighted citation impact, top 1% 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

262 citing papers in PubMed, 3 syntheses or guidelines pooled it, 419 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Review
  19. Review
  20. Review

202 more citing papers are in PubMed but not listed here.

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.

Brian OlsonSection of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, Illinois.
Yadi LiSection of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, Illinois.
Yu LinSection of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, Illinois.
Edison T LiuThe Jackson Laboratory Cancer Center, Bar Harbor, Maine.
Akash PatnaikSection of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, Illinois. apatnaik@medicine.bsd.uchicago.edu.
University of Chicago · USJackson Laboratory · US

Funding

Targeting FOXA1-downstream pathways: a novel therapeutic strategy for castration-resistant prostate cancerP50CA180995 · NCI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI ABDULKADIR, SARKI A., HUSSAIN, MAHA H · 2015 to 2025
$19.9M
NCI NIH HHS P50 CA180995
6 · The paper itself

Abstract

Immunotherapy has revolutionized cancer therapy, largely attributed to the success of immune-checkpoint blockade. However, there are subsets of patients across multiple cancers who have not shown robust responses to these agents. A major impediment to progress in the field is the availability of faithful mouse models that recapitulate the complexity of human malignancy and immune contexture within the tumor microenvironment. These models are urgently needed across all malignancies to interrogate and predict antitumor immune responses and therapeutic efficacy in clinical trials. Herein, we seek to review pros and cons of different cancer mouse models, and how they can be used as platforms to predict efficacy and resistance to cancer immunotherapies.

Indexed as

Biomedical ResearchDisease Models, AnimalImmunotherapyAnimalsHumansMiceNeoplasms

Identifiers

PMID30309862
PMCPMC8725605
OpenAlexW2897100571

What OpenQuestion holds

Textmetadata
LicenceTDM
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.