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Three-Dimensional Patient-Derived In Vitro Sarcoma Models: Promising Tools for Improving Clinical Tumor Management

Overview of attention for article published in Frontiers in oncology, September 2017
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Title
Three-Dimensional Patient-Derived In Vitro Sarcoma Models: Promising Tools for Improving Clinical Tumor Management
Published in
Frontiers in oncology, September 2017
DOI 10.3389/fonc.2017.00203
Pubmed ID
Authors

Manuela Gaebler, Alessandra Silvestri, Johannes Haybaeck, Peter Reichardt, Caitlin D. Lowery, Louis F. Stancato, Gabriele Zybarth, Christian R. A. Regenbrecht

Abstract

Over the past decade, the development of new targeted therapeutics directed against specific molecular pathways involved in tumor cell proliferation and survival has allowed an essential improvement in carcinoma treatment. Unfortunately, the scenario is different for sarcomas, a group of malignant neoplasms originating from mesenchymal cells, for which the main therapeutic approach still consists in the combination of surgery, chemotherapy, and radiation therapy. The lack of innovative approaches in sarcoma treatment stems from the high degree of heterogeneity of this tumor type, with more that 70 different histopathological subtypes, and the limited knowledge of the molecular drivers of tumor development and progression. Currently, molecular therapies are available mainly for the treatment of gastrointestinal stromal tumor, a soft-tissue malignancy characterized by an activating mutation of the tyrosine kinase KIT. Since the first application of this approach, a strong effort has been made to understand sarcoma molecular alterations that can be potential targets for therapy. The low incidence combined with the high level of histopathological heterogeneity makes the development of clinical trials for sarcomas very challenging. For this reason, preclinical studies are needed to better understand tumor biology with the aim to develop new targeted therapeutics. Currently, these studies are mainly based on in vitro testing, since cell lines, and in particular patient-derived models, represent a reliable and easy to handle tool for investigation. In the present review, we summarize the most important models currently available in the field, focusing in particular on the three-dimensional spheroid/organoid model. This innovative approach for studying tumor biology better represents tissue architecture and cell-cell as well as cell-microenvironment crosstalk, which are fundamental steps for tumor cell proliferation and survival.

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

Geographical breakdown

Country Count As %
Unknown 142 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 25 18%
Researcher 20 14%
Student > Ph. D. Student 19 13%
Student > Bachelor 19 13%
Student > Doctoral Student 8 6%
Other 16 11%
Unknown 35 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 26 18%
Agricultural and Biological Sciences 19 13%
Medicine and Dentistry 18 13%
Engineering 11 8%
Immunology and Microbiology 7 5%
Other 24 17%
Unknown 37 26%
Attention Score in Context

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 11 September 2017.
All research outputs
#22,764,772
of 25,382,440 outputs
Outputs from Frontiers in oncology
#15,925
of 22,428 outputs
Outputs of similar age
#284,124
of 323,227 outputs
Outputs of similar age from Frontiers in oncology
#70
of 90 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,428 research outputs from this source. They receive a mean Attention Score of 3.0. This one is in the 1st percentile – i.e., 1% 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 323,227 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 90 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.