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Drug response to PD-1/PD-L1 blockade: based on biomarkers

Overview of attention for article published in OncoTargets and therapy, August 2018
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Title
Drug response to PD-1/PD-L1 blockade: based on biomarkers
Published in
OncoTargets and therapy, August 2018
DOI 10.2147/ott.s168313
Pubmed ID
Authors

Qi Chen, Tianhe Li, Wentao Yue

Abstract

In recent years, immunotherapies targeting programmed death-1 (PD-1)/programmed death ligand 1 (PD-L1) have provided great hopes for patients with cancer. A successful anti-PD-1/PD-L1 therapy includes not only the elimination of immunosuppressive tumor cells but also the rejuvenation of exhausted T cells. Nevertheless, the efficacy of therapy is still low, so that biomarker-driven therapy has attracted more and more attention to identify patients who are likely to benefit from therapy and to reduce unnecessary disease progression. While many studies have focused on characteristics of tumor biopsies, biomarkers linked to T cell exhaustion and rejuvenation have just become new hot spots in drug response studies. However, no biomarker is perfect in drug response prediction currently, so there is an urgent need for other biomarkers to compensate for the deficiency. In this review, we summarize some approved and candidate biomarkers predictive of drug response before and during PD-1/PD-L1 blockade, including those characterizing responsive or suppressive tumor cells and those evaluating the T cell rejuvenation. Overall, we set up a comprehensive network of biomarkers of tumor characteristics and T cell rejuvenation, predicting drug response before and during anti-PD-1/PD-L1 therapies.

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The data shown below were collected from the profile of 1 X user 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 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 63 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 16%
Student > Ph. D. Student 9 14%
Student > Bachelor 7 11%
Researcher 7 11%
Student > Doctoral Student 5 8%
Other 8 13%
Unknown 17 27%
Readers by discipline Count As %
Medicine and Dentistry 14 22%
Biochemistry, Genetics and Molecular Biology 13 21%
Agricultural and Biological Sciences 4 6%
Pharmacology, Toxicology and Pharmaceutical Science 4 6%
Immunology and Microbiology 3 5%
Other 7 11%
Unknown 18 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 21 August 2018.
All research outputs
#22,767,715
of 25,385,509 outputs
Outputs from OncoTargets and therapy
#2,080
of 3,016 outputs
Outputs of similar age
#299,007
of 341,886 outputs
Outputs of similar age from OncoTargets and therapy
#75
of 114 outputs
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So far Altmetric has tracked 3,016 research outputs from this source. They receive a mean Attention Score of 2.9. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 114 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.