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Distinct predictive biomarker candidates for response to anti-CTLA-4 and anti-PD-1 immunotherapy in melanoma patients

Overview of attention for article published in Journal for Immunotherapy of Cancer, March 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

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34 X users
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6 patents
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1 Google+ user

Citations

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150 Dimensions

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200 Mendeley
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Title
Distinct predictive biomarker candidates for response to anti-CTLA-4 and anti-PD-1 immunotherapy in melanoma patients
Published in
Journal for Immunotherapy of Cancer, March 2018
DOI 10.1186/s40425-018-0328-8
Pubmed ID
Authors

Priyanka B. Subrahmanyam, Zhiwan Dong, Daniel Gusenleitner, Anita Giobbie-Hurder, Mariano Severgnini, Jun Zhou, Michael Manos, Lauren M. Eastman, Holden T. Maecker, F. Stephen Hodi

Abstract

While immune checkpoint blockade has greatly improved clinical outcomes in diseases such as melanoma, there remains a need for predictive biomarkers to determine who will likely benefit most from which therapy. To date, most biomarkers of response have been identified in the tumors themselves. Biomarkers that could be assessed from peripheral blood would be even more desirable, because of ease of access and reproducibility of sampling. We used mass cytometry (CyTOF) to comprehensively profile peripheral blood of melanoma patients, in order to find predictive biomarkers of response to anti-CTLA-4 or anti-PD-1 therapy. Using a panel of ~ 40 surface and intracellular markers, we performed in-depth phenotypic and functional immune profiling to identify potential predictive biomarker candidates. Immune profiling of baseline peripheral blood samples using CyTOF revealed that anti-CTLA-4 and anti-PD-1 therapies have distinct sets of candidate biomarkers. The distribution of CD4+and CD8+memory/non-memory cells and other memory subsets was different between responders and non-responders to anti-CTLA-4 therapy. In anti-PD-1 (but not anti-CTLA-4) treated patients, we discovered differences in CD69 and MIP-1β expressing NK cells between responders and non-responders. Finally, multivariate analysis was used to develop a model for the prediction of response. Our results indicate that anti-CTLA-4 and anti-PD-1 have distinct predictive biomarker candidates. CD4+and CD8+memory T cell subsets play an important role in response to anti-CTLA-4, and are potential biomarker candidates. For anti-PD-1 therapy, NK cell subsets (but not memory T cell subsets) correlated with clinical response to therapy. These functionally active NK cell subsets likely play a critical role in the anti-tumor response triggered by anti-PD-1.

X Demographics

X Demographics

The data shown below were collected from the profiles of 34 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 200 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 200 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 44 22%
Student > Ph. D. Student 26 13%
Student > Master 22 11%
Other 15 8%
Student > Bachelor 15 8%
Other 25 13%
Unknown 53 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 35 18%
Immunology and Microbiology 34 17%
Medicine and Dentistry 34 17%
Agricultural and Biological Sciences 24 12%
Pharmacology, Toxicology and Pharmaceutical Science 3 2%
Other 13 7%
Unknown 57 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 32. 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 13 February 2024.
All research outputs
#1,229,179
of 25,394,764 outputs
Outputs from Journal for Immunotherapy of Cancer
#289
of 3,428 outputs
Outputs of similar age
#27,294
of 347,447 outputs
Outputs of similar age from Journal for Immunotherapy of Cancer
#3
of 25 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,428 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.4. This one has done particularly well, scoring higher than 91% 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 347,447 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.