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The additional facet of immunoscore: immunoprofiling as a possible predictive tool for cancer treatment

Overview of attention for article published in Journal of Translational Medicine, March 2013
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

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2 X users
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9 patents

Citations

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105 Dimensions

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174 Mendeley
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Title
The additional facet of immunoscore: immunoprofiling as a possible predictive tool for cancer treatment
Published in
Journal of Translational Medicine, March 2013
DOI 10.1186/1479-5876-11-54
Pubmed ID
Authors

Paolo A Ascierto, Mariaelena Capone, Walter J Urba, Carlo B Bifulco, Gerardo Botti, Alessandro Lugli, Francesco M Marincola, Gennaro Ciliberto, Jérôme Galon, Bernard A Fox

Abstract

Recent investigations of the tumor microenvironment have shown that many tumors are infiltrated by inflammatory and lymphocytic cells. Increasing evidence suggests that the number, type and location of these tumor-infiltrating lymphocytes in primary tumors has prognostic value, and this has led to the development of an 'immunoscore. As well as providing useful prognostic information, the immunoscore concept also has the potential to help predict response to treatment, thereby improving decision- making with regard to choice of therapy. This predictive aspect of the tumor microenvironment forms the basis for the concept of immunoprofiling, which can be described as 'using an individual's immune system signature (or profile) to predict that patient's response to therapy' The immunoprofile of an individual can be genetically determined or tumor-induced (and therefore dynamic). Ipilimumab is the first in a series of immunomodulating antibodies and has been shown to be associated with improved overall survival in patients with advanced melanoma. Other immunotherapies in development include anti-programmed death 1 protein (nivolumab), anti-PD-ligand 1, anti-CD137 (urelumab), and anti-OX40. Biomarkers that can be used as predictive factors for these treatments have not yet been clinically validated. However, there is already evidence that the tumor microenvironment can have a predictive role, with clinical activity of ipilimumab related to high baseline expression of the immune-related genes FoxP3 and indoleamine 2,3-dioxygenase and an increase in tumor-infiltrating lymphocytes. These biomarkers could represent the first potential proposal for an immunoprofiling panel in patients for whom anti-CTLA-4 therapy is being considered, although prospective data are required. In conclusion, the evaluation of systemic and local immunological biomarkers could offer useful prognostic information and facilitate clinical decision making. The challenge will be to identify the individual immunoprofile of each patient and the consequent choice of optimal therapy or combination of therapies to be used.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 174 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Spain 1 <1%
Puerto Rico 1 <1%
Brazil 1 <1%
Unknown 170 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 54 31%
Student > Ph. D. Student 32 18%
Other 16 9%
Student > Bachelor 11 6%
Student > Doctoral Student 10 6%
Other 31 18%
Unknown 20 11%
Readers by discipline Count As %
Medicine and Dentistry 64 37%
Agricultural and Biological Sciences 36 21%
Biochemistry, Genetics and Molecular Biology 18 10%
Immunology and Microbiology 16 9%
Pharmacology, Toxicology and Pharmaceutical Science 3 2%
Other 9 5%
Unknown 28 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 27 April 2022.
All research outputs
#4,155,390
of 22,711,645 outputs
Outputs from Journal of Translational Medicine
#669
of 3,972 outputs
Outputs of similar age
#35,108
of 194,504 outputs
Outputs of similar age from Journal of Translational Medicine
#12
of 61 outputs
Altmetric has tracked 22,711,645 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,972 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has done well, scoring higher than 82% 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 194,504 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.