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Mathematical modeling of tumor-associated macrophage interactions with the cancer microenvironment

Overview of attention for article published in Journal for Immunotherapy of Cancer, January 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (53rd percentile)

Mentioned by

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1 blog
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19 X users

Citations

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73 Dimensions

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70 Mendeley
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Title
Mathematical modeling of tumor-associated macrophage interactions with the cancer microenvironment
Published in
Journal for Immunotherapy of Cancer, January 2018
DOI 10.1186/s40425-017-0313-7
Pubmed ID
Authors

Grace Mahlbacher, Louis T. Curtis, John Lowengrub, Hermann B. Frieboes

Abstract

Immuno-oncotherapy has emerged as a promising means to target cancer. In particular, therapeutic manipulation of tumor-associated macrophages holds promise due to their various and sometimes opposing roles in tumor progression. It is established that M1-type macrophages suppress tumor progression while M2-types support it. Recently, Tie2-expressing macrophages (TEM) have been identified as a distinct sub-population influencing tumor angiogenesis and vascular remodeling as well as monocyte differentiation. This study develops a modeling framework to evaluate macrophage interactions with the tumor microenvironment, enabling assessment of how these interactions may affect tumor progression. M1, M2, and Tie2 expressing variants are integrated into a model of tumor growth representing a metastatic lesion in a highly vascularized organ, such as the liver. Behaviors simulated include M1 release of nitric oxide (NO), M2 release of growth-promoting factors, and TEM facilitation of angiogenesis via Angiopoietin-2 and promotion of monocyte differentiation into M2 via IL-10. The results show that M2 presence leads to larger tumor growth regardless of TEM effects, implying that immunotherapeutic strategies that lead to TEM ablation may fail to restrain growth when the M2 represents a sizeable population. As TEM pro-tumor effects are less pronounced and on a longer time scale than M1-driven tumor inhibition, a more nuanced approach to influence monocyte differentiation taking into account the tumor state (e.g., under chemotherapy) may be desirable. The results highlight the dynamic interaction of macrophages within a growing tumor, and, further, establish the initial feasibility of a mathematical framework that could longer term help to optimize cancer immunotherapy.

X Demographics

X Demographics

The data shown below were collected from the profiles of 19 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 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 70 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 16%
Researcher 10 14%
Student > Doctoral Student 7 10%
Student > Master 6 9%
Student > Bachelor 5 7%
Other 11 16%
Unknown 20 29%
Readers by discipline Count As %
Mathematics 11 16%
Engineering 9 13%
Biochemistry, Genetics and Molecular Biology 6 9%
Medicine and Dentistry 5 7%
Agricultural and Biological Sciences 4 6%
Other 10 14%
Unknown 25 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 29 January 2019.
All research outputs
#1,945,108
of 25,382,440 outputs
Outputs from Journal for Immunotherapy of Cancer
#514
of 3,422 outputs
Outputs of similar age
#44,621
of 449,219 outputs
Outputs of similar age from Journal for Immunotherapy of Cancer
#14
of 30 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,422 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.4. This one has done well, scoring higher than 85% 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 449,219 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.