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Prediction of treatment responses to neoadjuvant chemotherapy in triple-negative breast cancer by analysis of immune checkpoint protein expression

Overview of attention for article published in Journal of Translational Medicine, April 2018
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Title
Prediction of treatment responses to neoadjuvant chemotherapy in triple-negative breast cancer by analysis of immune checkpoint protein expression
Published in
Journal of Translational Medicine, April 2018
DOI 10.1186/s12967-018-1458-y
Pubmed ID
Authors

Yuka Asano, Shinichiro Kashiwagi, Wataru Goto, Koji Takada, Katsuyuki Takahashi, Tamami Morisaki, Hisakazu Fujita, Tsutomu Takashima, Shuhei Tomita, Masahiko Ohsawa, Kosei Hirakawa, Masaichi Ohira

Abstract

"Avoiding immune destruction" has recently been established as one of the hallmarks of cancer. The programmed cell death (PD)-1/programmed cell death-ligand (PD-L) 1 pathway is an important immunosuppression mechanism that allows cancer cells to escape host immunity. The present study investigated how the expressions of these immune checkpoint proteins affected responses to neo-adjuvant chemotherapy (NAC) in breast cancer. A total of 177 patients with resectable early-stage breast cancer were treated with NAC. Estrogen receptor, progesteron receptor, human epidermal growth factor receptor 2, Ki67, PD-L1, PDL-2 and PD-1 status were assessed by immunohistochemistry. There were 37 (20.9%) patients with high PD-1 expression, 42 (23.7%) patients had high PD-L1 expression, and 52 (29.4%) patients had high PD-L2 expression. The patients with high PD-1 and PD-L1 expressions had a significantly higher rate of triple-negative breast cancer (TNBC) (p = 0.041) (p < 0.001). In TNBC, patients with high PD-1 and PD-L1 expressions had significantly higher rates of non-pCR (p = 0.003) (p < 0.001). Univariate analysis showed that PD-1 and PD-L1 expressions also significantly shortened disease free survival in TNBC (p = 0.048, HR = 3.318) (p = 0.007, HR = 8.375). However, multivariate analysis found that only PD-L1 expression was an independent prognostic factor (p = 0.041, HR = 9.479). PD-1 and PD-L1 expressions may be useful as biomarkers to predict treatment responses to NAC in breast cancer. Above all, PD-L1 expression may also be useful as biomarkers for more effective chemotherapy in TNBC.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 45 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 16%
Researcher 4 9%
Student > Ph. D. Student 4 9%
Student > Bachelor 3 7%
Student > Doctoral Student 3 7%
Other 9 20%
Unknown 15 33%
Readers by discipline Count As %
Medicine and Dentistry 15 33%
Biochemistry, Genetics and Molecular Biology 2 4%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Engineering 2 4%
Environmental Science 1 2%
Other 4 9%
Unknown 19 42%

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 06 April 2018.
All research outputs
#17,572,209
of 21,742,867 outputs
Outputs from Journal of Translational Medicine
#2,758
of 3,762 outputs
Outputs of similar age
#229,641
of 298,622 outputs
Outputs of similar age from Journal of Translational Medicine
#1
of 1 outputs
Altmetric has tracked 21,742,867 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,762 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one is in the 17th percentile – i.e., 17% of its peers scored the same or lower than it.
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We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them