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Optimizing Breast Cancer Management

Overview of attention for book
Attention for Chapter 10: Immune Checkpoint Blockade for Breast Cancer
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Chapter title
Immune Checkpoint Blockade for Breast Cancer
Chapter number 10
Book title
Optimizing Breast Cancer Management
Published in
Cancer treatment and research, January 2018
DOI 10.1007/978-3-319-70197-4_10
Pubmed ID
Book ISBNs
978-3-31-970195-0, 978-3-31-970197-4
Authors

April Swoboda, Rita Nanda

Abstract

An effective antitumor immune response requires interaction between cells of the adaptive and innate immune system. Three key elements are required: generation of activated tumor-directed T cells, infiltration of activated T cells into the tumor microenvironment, and killing of tumor cells by activated T cells. Tumor immune evasion can occur as a result of the disruption of each of these three key T cell activities, resulting in three distinct cancer-immune phenotypes. The immune inflamed phenotype, characterized by the presence of a robust tumor immune infiltrate, suggests impaired activated T cell killing of tumor cells related to the presence of inhibitory factors. Programmed death receptor-1 (PD-1) is an inhibitory transmembrane protein expressed on T cells, B cells, and NK cells. The interaction between PD-1 and its ligands (PD-L1/L2) functions as an immune checkpoint against unrestrained cytotoxic T effector cell activity-it promotes peripheral T effector cell exhaustion and conversion of T effector cells to immunosuppressive T regulatory (Treg) cells. Immune checkpoint inhibitors, which block the PD-1/PD-L1 axis and reactivate cytotoxic T effector cell function, are actively being investigated for the treatment of breast cancer.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 107 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 107 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 18%
Student > Bachelor 17 16%
Student > Master 13 12%
Researcher 9 8%
Student > Doctoral Student 6 6%
Other 11 10%
Unknown 32 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 24 22%
Medicine and Dentistry 18 17%
Immunology and Microbiology 6 6%
Agricultural and Biological Sciences 4 4%
Engineering 3 3%
Other 12 11%
Unknown 40 37%
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 20 January 2018.
All research outputs
#20,459,801
of 23,016,919 outputs
Outputs from Cancer treatment and research
#146
of 167 outputs
Outputs of similar age
#378,196
of 442,354 outputs
Outputs of similar age from Cancer treatment and research
#5
of 7 outputs
Altmetric has tracked 23,016,919 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 167 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 442,354 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.