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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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3 tweeters

Citations

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23 Dimensions

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39 Mendeley
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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 3 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 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 39 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 13%
Student > Ph. D. Student 4 10%
Student > Doctoral Student 3 8%
Researcher 3 8%
Student > Bachelor 2 5%
Other 8 21%
Unknown 14 36%
Readers by discipline Count As %
Medicine and Dentistry 11 28%
Pharmacology, Toxicology and Pharmaceutical Science 2 5%
Biochemistry, Genetics and Molecular Biology 2 5%
Engineering 2 5%
Nursing and Health Professions 1 3%
Other 3 8%
Unknown 18 46%

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
#10,635,043
of 16,620,251 outputs
Outputs from Journal of Translational Medicine
#1,754
of 3,119 outputs
Outputs of similar age
#170,998
of 283,165 outputs
Outputs of similar age from Journal of Translational Medicine
#1
of 1 outputs
Altmetric has tracked 16,620,251 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,119 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.5. This one is in the 24th percentile – i.e., 24% 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 283,165 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
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