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B-Cell Lymphoma Patient-Derived Xenograft Models Enable Drug Discovery and Are a Platform for Personalized Therapy

Overview of attention for article published in Clinical Cancer Research, August 2017
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Title
B-Cell Lymphoma Patient-Derived Xenograft Models Enable Drug Discovery and Are a Platform for Personalized Therapy
Published in
Clinical Cancer Research, August 2017
DOI 10.1158/1078-0432.ccr-16-2703
Pubmed ID
Authors

Leo Zhang, Krystle Nomie, Hui Zhang, Taylor Bell, Lan Pham, Sabah Kadri, Jeremy Segal, Shaoying Li, Shouhao Zhou, David Santos, Shawana Richard, Shruti Sharma, Wendy Chen, Onyekachukwu Oriabure, Yang Liu, Shengjian Huang, Hui Guo, Zhihong Chen, Wenjing Tao, Carrie Li, Jack Wang, Bingliang Fang, Jacqueline Wang, Lei Li, Maria Badillo, Makhdum Ahmed, Selvi Thirumurthi, Steven Y. Huang, Yiping Shao, Laura Lam, Qing Yi, Y. Lynn Wang, Michael Wang

Abstract

Patients with B-cell lymphomas often relapse after frontline therapy, and novel therapies are urgently needed to provide long-term remission. We established B-cell lymphoma PDX (patient-derived xenograft) models to assess their ability to mimic tumor biology and to identify B-cell lymphoma patient treatment options. We established the PDX models from 16 patients with diffuse large B-cell lymphoma, mantle cell lymphoma, follicular lymphoma, marginal zone lymphoma, or Burkitt's lymphoma by inoculating the patient tumor cells into a human bone chip implanted into mice. We subjected the PDX models to histopathological and phenotypical examination, sequencing, and drug efficacy analysis. Primary and acquired resistance to ibrutinib, an oral covalent inhibitor of Bruton's tyrosine kinase, were investigated to elucidate the mechanisms underlying ibrutinib resistance and to identify drug treatments to overcome resistance. The PDXs maintained the same biological, histopathological, and immunophenotypical features, retained similar genetic mutations and produced comparable drug responses with the original patient tumors. In the acquired ibrutinib-resistant PDXs, PLC-γ2, p65, and Src were down-regulated; however, a PI3K signaling pathway member was up-regulated. Inactivation of the PI3K pathway with the inhibitor idelalisib in combination with ibrutinib significantly inhibited the growth of the ibrutinib-resistant tumors. Furthermore, we used a PDX model derived from a clinically ibrutinib-relapsed patient to evaluate various therapeutic choices, ultimately eliminating the tumor cells in the patient's peripheral blood. Our results demonstrate that the B-cell lymphoma PDX model is an effective system to predict and personalize therapies and address therapeutic resistance in B-cell lymphoma patients.

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The data shown below were collected from the profiles of 5 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 93 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 93 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 22 24%
Student > Ph. D. Student 13 14%
Student > Bachelor 7 8%
Student > Master 7 8%
Student > Doctoral Student 6 6%
Other 14 15%
Unknown 24 26%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 24 26%
Medicine and Dentistry 16 17%
Chemistry 5 5%
Immunology and Microbiology 5 5%
Agricultural and Biological Sciences 4 4%
Other 14 15%
Unknown 25 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 September 2021.
All research outputs
#14,475,316
of 24,415,997 outputs
Outputs from Clinical Cancer Research
#9,863
of 13,004 outputs
Outputs of similar age
#164,274
of 321,164 outputs
Outputs of similar age from Clinical Cancer Research
#169
of 254 outputs
Altmetric has tracked 24,415,997 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,004 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.5. This one is in the 23rd percentile – i.e., 23% 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 321,164 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 254 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.