↓ Skip to main content

Establishment and genomic characterizations of patient-derived esophageal squamous cell carcinoma xenograft models using biopsies for treatment optimization

Overview of attention for article published in Journal of Translational Medicine, January 2018
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
25 Dimensions

Readers on

mendeley
27 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Establishment and genomic characterizations of patient-derived esophageal squamous cell carcinoma xenograft models using biopsies for treatment optimization
Published in
Journal of Translational Medicine, January 2018
DOI 10.1186/s12967-018-1379-9
Pubmed ID
Authors

Jianling Zou, Ying Liu, Jingyuan Wang, Zhentao Liu, Zhihao Lu, Zuhua Chen, Zhongwu Li, Bin Dong, Wenwen Huang, Yanyan Li, Jing Gao, Lin Shen

Abstract

Squamous cell carcinoma is the dominant type of esophageal cancer in China with many patients initially diagnosed at advanced stage. Patient-derived xenografts (PDX) models have been developed to be an important platform for preclinical research. This study aims to establish and characterize PDX models using biopsy tissue from advanced esophageal cancer patients to lay the foundation of preclinical application. Fresh endoscopic biopsy tissues were harvested from patients with advanced esophageal cancer and implanted subcutaneously into NOD/SCID mice. Then, the PDXs were serially passaged for up to four generations. Transplantation was analyzed and genomic characteristics of xenografts were profiled using next-generation sequencing. Twenty-five PDX models were established (13.3%, 25/188). The latency period was 75.12 ± 19.87 days (50-120 days) for the first passage and it decreased with increasing passaging. Other than tumor stages, no differences were found between transplantations of xenografts and patient characteristics, irrespective of chemotherapy. Histopathological features and chemosensitivity of PDXs were in great accordance with primary patient tumors. Each PDX was assessed for molecular characteristics including copy number variations, somatic mutations, and signaling pathway abnormalities and these were similar to patient results. Our PDX models were established from real time biopsies and molecularly profiled. They might be promising for drug development and individualized therapy.

X Demographics

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

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 22%
Student > Master 5 19%
Other 3 11%
Student > Ph. D. Student 3 11%
Student > Doctoral Student 2 7%
Other 2 7%
Unknown 6 22%
Readers by discipline Count As %
Medicine and Dentistry 9 33%
Biochemistry, Genetics and Molecular Biology 3 11%
Nursing and Health Professions 2 7%
Agricultural and Biological Sciences 2 7%
Computer Science 2 7%
Other 3 11%
Unknown 6 22%
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 26 January 2018.
All research outputs
#15,489,831
of 23,018,998 outputs
Outputs from Journal of Translational Medicine
#2,258
of 4,027 outputs
Outputs of similar age
#269,977
of 441,125 outputs
Outputs of similar age from Journal of Translational Medicine
#53
of 82 outputs
Altmetric has tracked 23,018,998 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,027 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one is in the 31st percentile – i.e., 31% 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 441,125 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 82 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.