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The Role of Tumor Tissue Architecture in Treatment Penetration and Efficacy: An Integrative Study

Overview of attention for article published in Frontiers in oncology, January 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 (88th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

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1 news outlet
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1 X user

Citations

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66 Dimensions

Readers on

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63 Mendeley
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Title
The Role of Tumor Tissue Architecture in Treatment Penetration and Efficacy: An Integrative Study
Published in
Frontiers in oncology, January 2013
DOI 10.3389/fonc.2013.00111
Pubmed ID
Authors

Katarzyna A. Rejniak, Veronica Estrella, Tingan Chen, Allison S. Cohen, Mark C. Lloyd, David L. Morse

Abstract

Despite the great progress that has been made in understanding cancer biology and the potential molecular targets for its treatment, the majority of drugs fail in the clinical trials. This may be attributed (at least in part) to the complexity of interstitial drug transport in the patient's body, which is hard to test experimentally. Similarly, recent advances in molecular imaging have led to the development of targeted biomarkers that can predict pharmacological responses to therapeutic interventions. However, both the drug and biomarker molecules need to access the tumor tissue and be taken up into individual cells in concentrations sufficient to exert the desired effect. To investigate the process of drug penetration at the mesoscopic level we developed a computational model of interstitial transport that incorporates the biophysical properties of the tumor tissue, including its architecture and interstitial fluid flow, as well as the properties of the agents. This model is based on the method of regularized Stokeslets to describe the fluid flow coupled with discrete diffusion-advection-reaction equations to model the dynamics of the drugs. Our results show that the tissue cellular porosity and density influence the depth of penetration in a non-linear way, with sparsely packed tissues being traveled through more slowly than the denser tissues. We demonstrate that irregularities in the cell spatial configurations result in the formation of interstitial corridors that are followed by agents leading to the emergence of tissue zones with less exposure to the drugs. We describe how the model can be integrated with in vivo experiments to test the extravasation and penetration of the targeted biomarkers through the tumor tissue. A better understanding of tissue- or compound-specific factors that limit the penetration through the tumors is important for non-invasive diagnoses, chemotherapy, the monitoring of treatment responses, and the detection of tumor recurrence.

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X Demographics

The data shown below were collected from the profile of 1 X user 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 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Unknown 62 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 29%
Student > Master 9 14%
Researcher 8 13%
Student > Bachelor 7 11%
Professor 5 8%
Other 5 8%
Unknown 11 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 17%
Engineering 8 13%
Medicine and Dentistry 7 11%
Biochemistry, Genetics and Molecular Biology 5 8%
Mathematics 4 6%
Other 14 22%
Unknown 14 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 18 July 2023.
All research outputs
#3,343,353
of 25,374,917 outputs
Outputs from Frontiers in oncology
#970
of 22,416 outputs
Outputs of similar age
#32,474
of 289,007 outputs
Outputs of similar age from Frontiers in oncology
#18
of 328 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 22,416 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done particularly well, scoring higher than 95% 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 289,007 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 88% of its contemporaries.
We're also able to compare this research output to 328 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.