↓ Skip to main content

Mechanisms of Resistance to Immune Checkpoint Blockade

Overview of attention for article published in American Journal of Clinical Dermatology, September 2018
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

news
1 news outlet
twitter
6 X users
facebook
1 Facebook page
googleplus
1 Google+ user

Citations

dimensions_citation
89 Dimensions

Readers on

mendeley
139 Mendeley
Title
Mechanisms of Resistance to Immune Checkpoint Blockade
Published in
American Journal of Clinical Dermatology, September 2018
DOI 10.1007/s40257-018-0389-y
Pubmed ID
Authors

David Liu, Russell W. Jenkins, Ryan J. Sullivan

Abstract

The recent development of effective immune checkpoint inhibition (ICI), first demonstrated in melanoma, has revolutionized cancer treatment. Monoclonal antibodies blocking the immune checkpoints cytotoxic T lymphocyte-associated antigen 4 (CTLA-4) and programmed death 1 receptor (PD-1) have shown substantial clinical benefit in a subset of patients across tumor types and in both the metastatic and adjuvant settings. In this article, we review the interaction between the immune system and solid tumors, and describe modes of immune response failure and the physiologic role of immune checkpoints. We also review the known mechanisms of immune checkpoint inhibitors, focusing on US FDA-approved agents targeting CTLA-4 and PD-1. Within this framework, we classify hypothesized tumor intrinsic and extrinsic predictive markers for response and resistance to ICI, and map them to their putative underlying biological mechanism. Finally, we outline future directions in ICI, including the development of new therapeutic targets, rational combination therapies, integrated predictive models for individual patients to optimize therapy, and expansion into different disease types.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 139 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 139 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 17%
Student > Bachelor 20 14%
Student > Ph. D. Student 16 12%
Student > Master 14 10%
Student > Doctoral Student 7 5%
Other 15 11%
Unknown 43 31%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 35 25%
Medicine and Dentistry 21 15%
Immunology and Microbiology 14 10%
Pharmacology, Toxicology and Pharmaceutical Science 9 6%
Neuroscience 3 2%
Other 8 6%
Unknown 49 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 June 2021.
All research outputs
#2,249,831
of 23,105,443 outputs
Outputs from American Journal of Clinical Dermatology
#154
of 988 outputs
Outputs of similar age
#49,539
of 341,556 outputs
Outputs of similar age from American Journal of Clinical Dermatology
#4
of 23 outputs
Altmetric has tracked 23,105,443 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 988 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one has done well, scoring higher than 84% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 341,556 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.